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Copyright © 2015 Frost & Sullivan. All rights reserved.
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TABLE OF CONTENTS 1. OBJECTIVES
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2.
INTRODUCTION TO DIGITAL ERA – CONSUMER TECHNOLOGY TRENDS
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3.
INTRODUCTION TO DIGITAL ERA – FINANCIAL TECHNOLOGY TRENDS
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4.
INTERNET OF THINGS
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5. WEARABLES
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6.
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EMERGING SOCIAL MEDIA
7. ECOMMERCE
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8. EPAYMENT
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9. CROWDFUNDING
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10.
BIG DATA & PREDICTIVE ANALYTICS
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11.
CYBER SECURITY
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12.
DATA CENTRE & CLOUD SERVICES
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13. BLOCKCHAIN
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OBJECTIVES
Technology today is radically transforming our lives in a way we have not envisioned before. Smartphones, Internet of Things (IoT), Bitcoin, ecommerce, and smartwatches, among others, are changing the way we live. At the same time, technologies like Big Data and cyber security are transforming the way businesses are run. The promise of new technologies is capturing tremendous investor interest. In fact, it is estimated that approximately US$120 billion will be invested by Venture Capital firms (VCs)1 in 2015, with the bulk of funding going into technology companies. Private companies with more than US$1 billion in valuation, termed unicorns, are increasingly common today. There are more than 140 technology unicorns globally as of September 20152. It is expected that many of these companies will go for public listing in the near future, drawing significant interest from retail investors.
Investors in these companies have so far been venture capital firms that understand technology trends and valuation parameters well. While most of these technologies have an exciting future, there are significant risks involved as well. Hence, it is desirable for retail investors to understand the technologies, trends, and potential risks before investing in these companies. This research paper aims to provide retail investors with valuable information on 10 key technology areas, including the major trends, business models, risks, and valuation drivers. The overall goal is to equip prospective investors with basic knowledge on the potential of emerging technologies to enable them to make well-informed investment decisions about these technology companies. The technology areas covered in this research paper include:
Figure 1: Technology Coverage3 CONSUMER TECHNOLOGIES
FINANCIAL TECHNOLOGIES
INTERNET OF THINGS
EPAYMENT
WEARABLES
CROWDFUNDING
SOCIAL MEDIA
BIG DATA & PREDICTIVE MODELING
ECOMMERCE
CYBER SECURITY
CLOUD & DATA CENTRE
Source: cbinsights, 2015 Source: cbinsights, 2015 3 Some technologies may have a broader set of applications but only the financial or consumer aspects are covered in this research paper. 1
BLOCKCHAIN
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INTRODUCTION TO THE DIGITAL ERA – CONSUMER TECHNOLOGY TRENDS
The past 20 years have been a remarkable era of rapid improvements in digital consumer technology. Digital technology, once limited to the confines of enterprise and big business, has now reached consumers worldwide at an unprecedented pace. Even poor people in emerging markets who may not even have access to electricity, may own mobile phones that have more processing power and memory than the supercomputers of the 1990s (the Deep Blue supercomputer that defeated Garry Kasparov in a
chess match in 1997, had a performance figure of 11.38 GFLOPS or Giga Floating Point Operations Per Second versus the 69 GFLOPS of a Xiaomi Mi4i). While the smartphone and PC markets are considered relatively mature, the rapid pace of technological advancements remains unabated and set to reinvent the way we work. These technologies and their enabling drivers are described below.
TRENDS SUPPORTING THE GROWTH OF CONSUMER TECHNOLOGIES Figure 2: Key Trends in Consumer Technologies
ENABLING DRIVERS
FALLING PRICE OF COMPUTATION & STORAGE
MINIATURISATION OF COMPONENTS
CONNECTED SENSORS
INTERNET OF THINGS
MINIATURISATION OF PERSONAL DEVICES
WEARABLES
SOCIAL INTERACTIONS USING MULTIPLE DEVICES
RADICAL IMPROVEMENTS IN LASTMILE CONNECTIVITY
FALLING PRICE OF COMPUTATION AND STORAGE The popular Moore’s Law observes that processors and memory chip performance will keep doubling every 18 months. This indicates that performance increases by 16 times every 6 years. As a result, the price of a processor or memory with the same performance keeps reducing. For example, a US$125 smartphone today has double the processing speed of the iPhone 3G that sold at US$600 without a contract at the time of its launch in 2009. 4
SOCIAL NETWORKS
SALES & PURCHASE FROM COMPUTERS &
ECOMMERCE
SMARTPHONES
Declining prices is a major catalyst spurring the growth of consumer technology applications. More consumers across the globe can now afford to own a smartphone or PC. What’s more a larger number of smaller devices can be given the same computing power of smartphones from previous generations, leading to the proliferation of smart sensors and wearables into our everyday lives.
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Figure 3: Average Price in US$ of 1 Megabyte Memory, 2008-2015
Source: jcmit.com, Frost & Sullivan Analysis MINIATURISATION OF COMPONENTS A direct consequence of improving chip performance is that similar computing power can now be compressed in a smaller chip, which in turn, can be fitted into a smaller device. A smartwatch today has the same memory and processing speed of a smartphone 3 years ago and of a PC from 6 years ago. In future, even smaller components used in our clothing or smart glasses can have similar processing power, making these devices more useful to us.
RADICAL IMPROVEMENTS IN LAST-MILE CONNECTIVITY Consumer devices do not only require processing power and memory; they also need fast connectivity to be truly useful. With the rapid development of wireless broadband technology in the form of ubiquitous and more efficient networks such as 3G, 4G, WiFi and Bluetooth, it is easier for new-generation consumer devices to be connected to a network and other devices. For example, modern cars use concierge and map services using 3G connectivity. Such solutions would not be possible without nearubiquitous 3G connectivity. Similarly, Samsung Gear and Apple Watch connect with the smartphone using Bluetooth 4.0 that consumes only a fraction of power compared to previous standards. With this connectivity, consumers can now shop from their mobile phones, track their fitness levels using fitness bands, check the security of their homes using connected IP cameras, and even remotely control the thermostats of their homes. The combination of smaller, cheaper and more powerful devices with ubiquitous connectivity are key drivers behind the rapid progress in consumer technologies.
Figure 4: First Devices with 1 GHz processor and Their Launch Year
COMPAQ DESKPRO EN Year: 2000
TOSHIBA TG01 SAMSUNG Year: 2009 GALAXY GEAR Year: 2013
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INTRODUCTION TO THE DIGITAL ERA – FINANCIAL TECHNOLOGY TRENDS
Financial technology (Fintech) refers to a business that provides financial services using software or the Internet. Essentially, it brings many innovations in consumer technology such as web portals and smartphones to the financial world. Smartphones are being used to enable payments (epayments), the web is being deployed to raise funds for ideas and companies (crowdfunding) while big data technology is helping to facilitate credit scoring and fraud detection. These advancements are being
enabled by improvements in the cloud and cyber security technologies. Leveraging these technologies, innovative fintech start-ups are revolutionising the once stagnant financial services industry by enabling payments, loans and other financial services, which so far has been monopolised by banks and other major financial institutions.
TRENDS SUPPORTING THE GROWTH OF FINANCIAL TECHNOLOGIES
ENABLING DRIVERS
Figure 5: Key Trends in Financial Technologies
INCREASING INTERNET & SMARTPHONE PENETRATION
EPAYMENT
CROWDFUNDING
IMPROVING CYBER SECURITY
BIG DATA & PREDICTIVE ANALYTICS
CYBER SECURITY
ADOPTION OF CLOUD AND BIG DATA
INCREASING INTERNET AND SMARTPHONE PENETRATION The Internet and smartphone are key enablers of fintech. As the medium for crowdfunding websites, the Internet enables companies to raise funds without going to VCs or banks. Similarly, the smartphone facilitates innovative payment options like Apple Pay and smartphone-based card readers like Square. Naturally, the larger the user base for Internet and smartphone, the faster the growth for fintech companies. IMPROVING CYBER SECURITY Security is the number one concern associated with performing online transactions, without which most 6
INFRASTRUCTURE TECHNOLOGY
BLOCKCHAIN
fintech areas would not have grown. Without strict security measures, we would not be able to make payments with our phones. Thus, improvements in cyber security play a huge role in the uptake of financial technology. ADOPTION OF CLOUD AND BIG DATA Cloud and Big Data are the other two enabling technologies powering fintech. On the one hand, cloud technologies allow fintech start-ups to quickly scale up their infrastructure according to their business growth. On the other hand, start-ups use Big Data and Analytics for fraud detection and credit scoring.
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INTERNET OF THINGS
The Internet of Things (IoT) refers to the connectivity of physical objects (as opposed to devices like the smartphone that are directly used by people), that are able to collect and exchange data. Physical devices can be sensors, electronics and other objects such as thermostats and IP cameras. In contrast to how the Internet is a way to connect people via personal devices like PCs and smartphones, IoT aims to interconnect devices, machines, services, including people, allowing for virtually endless connections and opportunities to take place. IoT is expected to accelerate automation of a large array of domestic and industrial areas such as home appliances, electric grids, agriculture, traffic management and automobiles. For example, home appliances can be switched off automatically when sensors at the gate detect that users have left the home. US households are reaping significant cost savings in utility bills with the installation of home motion sensors. While consumers in the AsiaPacific region are becoming increasingly aware of the benefits IoT can bring to their lives, with similar adoption trends expected as the technology matures. Frost & Sullivan predicts that by 2020, there will be almost 50 billion connected devices globally, averaging to approximately 10 connected devices per person. Although smartphones and laptops form the bulk of connected devices today, they are likely
to make up less than 10% of total connected devices by 2020. The market size of IoT spending in the Asia-Pacific region is estimated at US$24.2 billion in 2015. Growth is expected to be rapid at a compounded annual growth rate of 26.8% to reach US$79.3 billion in 5 years’ time. China is projected to be the largest IoT market in the region at US$36.8 billion in 2020 due to numerous smart city developments undertaken by the government. Japan is likely to follow with a market size of US$16.1 billion where automation is increasingly being adopted to address the challenges of an ageing population and rising wage costs. Emerging countries in Southeast Asia such as Indonesia, the Philippines, and Malaysia are poised to experience the fastest growth due to their relatively lower starting base in IoT spending. IoT applications are influencing a significant number of areas such as home appliances, agriculture, automotive, transportation, building management, factory management, industrial automation, healthcare, energy, and power systems. The technology is enabling banks to monitor and manage their ATM kiosks. However, the biggest impact of IoT is being seen in the transportation, energy, and home appliance segments.
Figure 6: Industries Adopting IoT Technology
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KEY DRIVERS & RESTRAINTS Figure 7: Drivers & Restraints of IoT Industry Growth GROWTH DRIVERS
GROWTH RESTRAINTS
IMPROVEMENTS IN THE COST & FUNCTIONALITY OF SENSORS
SECURITY, DATA PRIVACY AND SOVEREIGNTY CONCERNS
GOVERNMENT SMART CITY DEVELOPMENTS DRIVING RAPID IOT PROLIFERATION
CHALLENGES IN JUSTIFYING THE RETURN ON INVESTMENT
MAJOR IMPACT ON EFFICIENCY & CUSTOMER RESPONSIVENESS OF INDUSTRIES
COMPETING STANDARDS AND WALLED GARDEN APPROACH
UBIQUITOUS CONNECTIVITY AND THE PROLIFERATION OF SMART DEVICES
KEY DRIVERS 1. IMPROVEMENTS IN THE COST AND FUNCTIONALITY OF SENSORS IoT involves the use of sensors to capture useful data about its environment. Sensors have been around for some years; a common example is the use of motion sensors in public toilets to activate the automatic flush, electronic soap dispenser and sensor tap. In short, IoT and sensing technologies go hand in hand as it aims to connect these sensors. The declining cost of sensors and increasing miniaturisation are key drivers in the uptake of IoT. Sensors have evolved to become economical and small enough to be embedded in a range of ubiquitous objects. For example, the accelerometer (sensor to measure acceleration or movement of a device) can be easily fitted in a smartphone and costs around US$1. The cost of sensors is expected to further decline between 25% and 40% over the next 3 years. 2. GOVERNMENT SMART CITY DEVELOPMENTS SPURRING RAPID IOT PROLIFERATION In many countries, the public sector is leading the way in IoT proliferation with various smart city initiatives both at the national and regional levels. 8
While IoT and smart city are different concepts, IoT provides the necessary technological tools for policy makers to capture data and arrive at better policies and decisions to improve people’s lives. As part of its ambition to become the world’s first smart nation, the Singapore government is undertaking various smart city initiatives including installing sensors and cameras in various public infrastructures to collect data on urban density, pollution, and traffic conditions. Likewise in countries such as Australia, government subsidies are helping to stimulate the adoption of Automated Meter Readers (AMRs) for the utilities sector. To fund the various measures, government agencies are striking up partnerships between public and private sectors. Government initiatives and consortiums are key drivers in accelerating the development of IoT to reap the critical mass. 3. MAJOR IMPACT ON EFFICIENCY AND CUSTOMER RESPONSIVENESS OF INDUSTRIES IoT is pivotal in enhancing the competitiveness of industries through the use of enabling technologies. Enterprises have found that IoT brings about better utilisation of costly assets such as transportation fleets. With IoT, modern transportation companies can pinpoint the exact location of their vehicles, the
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time taken to travel between locations, resting times, and even factors such as fuel efficiency, all thanks to GPS vehicle tracking systems. As an another example, in early 2014, the US National Highways published two automotive recall announcements – one from Tesla Motors and the other from General Motors – due to fire risks. As the Tesla cars came equipped with 3G connectivity, 29,000 cars in people’s garages were fixed overnight simultaneously via a software upgrade performed remotely. IoT technology enabled Tesla to incur minimal costs in rectifying the issue. On the other hand, General Motors’ cars did not come with high-speed connectivity at that time. Consequently, 380,000 vehicles had to be manually taken to the dealers, incurring a much higher cost. The case highlights the tangible benefits of IoT that enterprises cannot afford to ignore. 4. UBIQUITOUS CONNECTIVITY AND PROLIFERATION OF SMART DEVICES The use of Machine-to-machine (M2M) is evolving and converging from a closed network using diverse technologies such as Ethernet to an all-IP network. The use of wireless networks and migration to the IPv64 provide reliable data connection to support the exchange of data across ubiquitous things without direct human intervention. The 3G and 4G mobile networks enable cost effective and robust wireless data connections to end user devices. The pervasiveness of cellular technology coupled with the increasing use of WiFi in places with lower coverage also provides seamless connection for realtime exchange of mission-critical applications. At the same time, the proliferation of smartphones will be instrumental as gateways to access and control other connected devices such as connected home appliances.
KEY RESTRAINTS 1. SECURITY AND DATA PRIVACY CONCERNS Security remains a key concern among people, policymakers, and industries in adopting IoT. One of the risks in connecting equipment, public infrastructure, and various objects is that data from those devices can be vulnerable to theft, damage and malicious attacks. From an enterprise perspective, IoT has the potential to cripple a manufacturing
plant or hack into a medical device. For example, the Stuxnet virus attack in 2013 that brought down Iran’s entire nuclear plant via a cyber worm highlights the vulnerability of critical infrastructure and importance of security sometimes taken for granted in an Internet-driven era. These threats are expected to slow down IoT deployment until the concept evolves to become more technologically mature and reliable. 2. JUSTIFYING THE RETURN ON INVESTMENT Despite the potential advantages IoT can bring to industries, some enterprises struggle to quantify the return on the investment needed to realise the value of the technology. While in sectors like transportation, the virtues of IoT are clear, however, there is a lack of quantifiable benefits and cost savings of IoT implementation in other use cases. For example, smart meters or AMRs were one of the most talked about IoT implementations with governments in the UK and Australia investing billions of dollars in the endeavour. However, an audit of smart meter investments by the State of Victoria in Australia concluded that any cost saving by smart meters was compensated by the higher cost of the meters. Due to cases like this, there is little willingness to embark on costly investments by enterprises in certain industries. Moreover, the relatively low cost of manpower in emerging Asia-Pacific nations signal that enterprises are not prepared to replace manpower with autonomous machines. 3. COMPETING STANDARDS AND WALLED GARDEN APPROACH The growth potential offered by IoT is attracting the attention of numerous vendors offering proprietary systems around platforms and applications to enterprises. In doing so, competing standards are being established to determine the requirements around power, hardware devices, capabilities and types of use. At present, enterprises find the multiple standards confusing, and are concerned about the lack of interoperability among competing standards. Given the uncertainty of the standards that are likely to lead the industry in time to come, enterprises are adopting a wait-and-see approach for standards to mature. The hesitation is likely to delay implementation plans over the short-term. In addition to the confusion, most vendors adopt a walled garden approach to protecting their territories by selling hardware devices that come with a software
IPv6 refers to the latest version of internet protocols which makes it possible to assign IP addresses to a much larger set of devices compared to the previous versions.
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lock-in. Enterprises that deploy their systems are effectively prevented from procuring solutions from competing vendors. The lack of interoperability is
making system integration a challenge, inevitably delaying decisions in implementing IoT solutions.
VALUE CHAIN AND KEY BUSINESS MODELS VALUE CHAIN The basic IoT value chain comprises five key components as illustrated in Figure 8. Figure 8: The Internet of Things Value Chain
OBJECTS
TRANSLATION
CONNECTIVITY
As described above, the IoT value chain has five components: 1. Objects refer to ubiquitous things that can be connected to the Internet, encompassing consumer electronics, sensing devices, embedded systems, controllers, and virtual objects. Examples include smart thermostats, IP cameras, and smart meters. Leading players in this segment are Cisco, Nest (Google subsidiary offering smart home solutions), Samsung (smart refrigerators), Itron (smart 10
PLATFORM
APPLICATION
meters), GE (smart meters and industrial sensors), Cooper Industries (electric grid sensors) and STMicroelectronics (motion sensors). 2. Translation refers to the capturing, storing and sharing of data across devices using a local network. The key components of translation are short range wireless sensor networks and wireless transmitting modules. Examples include NFC, Bluetooth, wireless sensor networks and RFID networks.
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3. Connectivity refers to the connection of sensors in the field, factory or home to the Internet or private networks. They include wired and wireless networks, enterprise and service provider gateways and network management. Broadband and 3G/4G networks are some options. Major connectivity providers are telcos such as SingTel, AT&T, and Celcom. Since most IoT applications require wireless connectivity, wireless operators are trying to adopt a central position in the value chain. They typically
host the IoT platform (e.g., Telstra hosts Jasper’s IoT platform) to make it easier for IoT device and application providers to use their network and manage their apps. AT&T goes one step further by offering a built-in wireless home networking platform covering electrical appliances, security and digital media entertainment as a single subscription package (with upfront payment for devices). AT&T has achieved a one-stop shop approach by entering into partnerships with vendors that are leading players in their area of expertise.
Figure 9: AT&T Digital Life Platform
SECURITY SYSTEM E.g., Honeywell
CONTROL PANELS E.g., Cisco
WIRELESS SENSORS E.g., Aeon Labs
ANALYTICS E.g., Aeon Labs
AGGREGATED BY TELECOM OPERATORS
AT&T’S DIGITAL LIFE PLATFORM A
B
RETAIL STORES
DIRECT SELLING
DIY package sold at retail stores
Professional installation at home
AGGREGATOR
OPERATION AND MAINTENANCE
Telecom vendors
Telecom vendors and ecosystem of partners
INSTALLATION
ANALYTICS AND MONITORING
Telecom vendors (or DIY)
Third-party analytics and monitoring stations/telecom vendor monitoring station
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4. Platform refers to an infrastructure layer for applications to be built on top of it. They include performance management, device management, identity management, payment platform and application platform. It is the software that connects the sensors together, automating them and enabling easy monitoring. Vendors of IoT platforms include Telenor (Telenor Objects), Jasper Wireless, Ericsson, and Tridium. 5. Applications refer to programs designed to solve a particular problem, carry out a function or provide a service. They include enterprise applications (e.g., ERP, CRM and SCM), analytics applications, and industry-specific applications like fleet management solutions, smart car applications, building automation solutions, and grid management applications. Industry players across the value chain are fairly specialised in their offerings. At present, industry players do not have all the capabilities of the value chain to offer an integrated end-to-end IoT solution, be it for the consumer or enterprise sector. For example, a telecommunications operator focusing on providing broadband connectivity is not well placed to manufacture chipset modules. Companies are highly receptive towards greater collaboration within the industry to supplement their lack of internal expertise in certain areas. While partnerships are the most common and fastest way in bringing expertise together, companies have limited control over their partners. On the other hand, acquisitions offer greater control in acquiring capabilities. However, the risk and uncertainty are also the highest in such an arrangement.
up selling a remote baby monitoring device, follows this business model as well. Sometimes customers have to pay an additional one-time fee to get advanced features. For example, Fitbit’s (the health band) premium service comes with a 12-week training programme as well as benchmarking and data export capabilities. DEVICE PLUS SUBSCRIPTION MODEL In this model, there is an upfront fee for the hardware plus a monthly subscription that covers wireless connectivity and other costs for the vendors. These models are popular for fleet tracking solutions, where customers pay upfront for the GPS tracker and other sensors, and a monthly fee per vehicle to the solution provider. Examples include fleet management companies such as CarTrack and iTrack. SUBSCRIPTION MODEL Software only solutions may be sold on a monthly subscription. For example, VersaFleet is a fleet tracking software that uses third-party GPS. Since there is no device sold, the pricing is on a monthly subscription basis.
KEY BUSINESS MODELS Business models employed by the connected industry fall into 3 broad categories: Device-centric Business Model; Device plus Subscription Model; and Subscription Model. DEVICE-CENTRIC BUSINESS MODEL In this model, the prime focus is on selling devices upfront. Services provided after the sale of the devices are either free or make up a minimal part of the overall revenue. A key example is Nest that sells smart thermostats and surveillance cameras for the home. Tesla Motors, which sells the IoT-powered connected car, can also be considered a devicecentric vendor. MNH Labs, a Singapore-based start-
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VALUE DRIVERS & KEY RISKS Figure 10: Value Drivers & Key Risks for IoT Companies
KEY RISKS
KEY VALUE DRIVERS • Partnerships & Collaboration • Ease of Use & Design • Installed Base
KEY VALUE DRIVERS
• Eventual Business Case • Competition & Commoditisation • Lack of Economies of Scale
Figure 11: Nest Thermostat
The key value drivers of an IoT company are as follows: 1. PARTNERSHIPS AND COLLABORATIONS IoT requires smooth interworking of multiple sensors, devices, connectivity networks and software. IoT applications may also need to work with legacy enterprise applications and networks. In most cases, a single company may not offer the entire range of devices and applications. Therefore it is important to have a wide range of partners that provide complementary services to seamlessly implement the company’s solution. However, partnerships alone may not be sufficient. The application must also be easy to integrate with the sensors, wireless sensor networks, cellular networks or the IoT platforms of the partners. For example, AT&T created and opened its IoT platform to its partners so they could develop innovative applications for its consumers, and be assured of seamless integration with the IoT platform and cellular network. This has resulted in AT&T becoming a leading participant in the IoT segment. 2. EASE OF USE AND DESIGN Companies offering consumer-focused IoT solutions need to be easy to use and have excellent aesthetic design. For example Nest, a smart thermostat and surveillance camera company, is a successful IoT player thanks to its simple to use device and awardwinning design. In fact, it became the third most sold thermostat in the US, 3 years after its launch. 13
3. INSTALLED BASE Like most enterprise applications, the number of IoT application deployments or installed base of the product signifies the efficacy and reliability of the solution to potential customers. The larger the installed base, the higher the chances of finding new customers.
KEY RISKS The key risks for a company in the IoT sector include the following: 1. EVENTUAL BUSINESS CASE RISK ASSESSMENT: HIGH (FOR EARLY AND GROWTH STAGE COMPANIES) IoT applications have the power to revolutionise the world. However, they require a substantial number of
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disparate hardware and software components to work together smoothly; that may not always be possible. Cost is another constraint potentially hindering the eventual adoption of the technology. Many IoT startups with promising solutions fail to gain sufficient momentum in the marketplace. For example, the concept of a connected home was introduced more than 10 years ago by broadband providers. However, several early start-ups aiming to provide intelligent switching to lights and other home appliances failed because of the high costs, integration challenges and low eventual benefits to consumers. Similarly, smart meters were a big thing a few years ago due to heavy investments by governments in the UK and Australia. However, the return on these investments has raised doubts, tapering industry growth. 2. COMPETITION AND COMMODITISATION RISK ASSESSMENT: HIGH Many IoT devices like smart meters and fleet management solutions have proliferated with the
influx of manufacturers from low-cost regions producing similar products at lower prices with entrylevel features. This is resulting in hardware devices becoming increasingly commoditised – a serious concern for hardware-centric IoT applications. 3. LACK OF ECONOMIES OF SCALE RISK ASSESSMENT: HIGH (FOR EARLY AND GROWTH STAGE COMPANIES) Start-ups and companies in the early growth stages face the risk of poor operating and financial performance due to the lack of scale. This is prevalent in the initial stages when the penetration rate of IoT solutions and devices is low. Early adoption by niche segments is not sufficient to elevate the business substantially even with a premium placed on the pricing of the solutions. Companies in the software aspect have a lower operating cost in the early stages. However, businesses offering devices incur a much higher cost that translates to higher prices. Although growth in adoption could result in greater economies of scale, the risk of failure in hardware start-ups is higher.
RELEVANT VALUATION METRICS IoT vendors have a simple business model of either outright sales or a subscription model. The valuation can be done based on the revenue (valuation/revenue) of EBITDA (enterprise value/EBITDA) multiple. However, before investing in an IoT company, it is vital to assess the company based on the key value drivers and evaluate risks to judge the future prospects of the company. Table 1: Valuation Metrics for IoT Companies in Various Stages S. NO.
EARLY STAGE
GROWTH STAGE
LATE STAGE
1.
Revenue & revenue growth
Revenue & revenue growth
Revenue & revenue growth
2.
Growth in monthly active users
EBITDA margin
EBITDA margin
3.
-
Profit margin
Profit margin
OVERALL FOCUS
CUSTOMER TRACTION
TOPLINE & BOTTOMLINE GROWTH
TOPLINE & BOTTOMLINE GROWTH
EARLY STAGE: Usually first 2 to 3 years of operations. GROWTH STAGE: Approximately 3 to 5 years of operations. LATE STAGE: More than 5 years of operations. 14
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WEARABLES
The terms “wearable technology”, “wearable devices”, and “wearables” refer to electronic technologies or computers incorporated into items of clothing and accessories that can be comfortably worn on the body. The wearable devices can perform many of the same computing tasks as mobile phones and laptop computers, but in a much smaller form factor. Wearable technology tends to be more sophisticated than handheld technology because it can provide sensory and scanning features not typically seen in mobile and laptop devices, such as biofeedback and tracking of physiological functions.
Wearable technology has some form of communications capability enabling the wearer to access or send information in real-time from the wearable device. Data input capabilities are also a feature of such devices, as is local storage. Examples of wearable devices include watches, glasses, contact lenses, e-textiles and smart fabrics, headbands, beanies and caps, jewellery such as rings, bracelets, and hearing aid-like devices designed to look like earrings. The figure below provides a classification of wearable technology based on the various types in the market.
Figure 12: Wearable Technology Taxonomy by Product Type
WEARABLE TECHNOLOGIES
ACTIVITY TRACKERS Traditionally coming in the form of smart bands, which track biometric data upon a designated activity
SMART WATCHES
SMART GLASSES
SMART CLOTHING
OTHERS
A wristwearable device which offers a wide variety of functions, on top of timetelling, and is often synced to smartphones
A wearable device resembling glasses which collects data and augments a user’s sight through an inbuilt display
All smart clothing and accessories including shoes and jewelry like rings
Any other wearable technology which does not fall into the four previous categories
Source: Frost & Sullivan
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The implications and uses of wearable technology are far reaching and anticipated to influence the fields of health and medicine, fitness, ageing, disabilities, education, transportation, enterprise, finance, gaming and music. The goal of wearable technologies across these fields is to smoothly incorporate functional, portable electronics and computers into individuals’ daily lives.
that superimposes a computer-generated image on a user’s view of the real world, and wearable technology can combine to create a more realistic and immersive environment in real-time. The concept is not necessarily new, as augmented reality through the use of wearable devices has been discussed since the late 1990s. However, the prototypes are moving away from bulky technology such as large goggles and backpacks, to smaller, lightweight and more mobile systems. If the more sophisticated designs of mobile phones and digital cameras currently on the market are any indication of the future of wearable devices, then fashion, practicality, function and design will be taken into account as these products advance. This consideration for both technology and aesthetics is already evident in devices such as Google Glass that has a sleek, lightweight, and unobtrusive design.
Although wearables could potentially have the biggest impact in the fields of health and fitness, the technology also promises great influence in gaming and entertainment. Augmented reality, a technology
CURRENT STATUS The following table summarises the current state of market development for various device categories and the most likely scenarios in the future.
While wearable technology tends to refer to items that can be put on and taken off with ease, there are more invasive versions such as implanted devices including micro-chips and smart tattoos. Ultimately, whether a device is worn or incorporated into the body, the purpose of wearable technology is to create constant, convenient, seamless, portable, and mostly hands-free access to information and insights.
Table 2: Types of Wearable Devices
CATEGORY
CURRENT MARKET STATE
DEFINITION
REASONS
ACTIVITY TRACKERS
Wearable bands and other devices that can track athletic activities like running, cycling and walking along with measuring heart rate.
Fast growing segment
Activity trackers use minimal computational power and require a smaller display. They are compatible with the current battery and display technology, lowering prices. There are multiple options available for consumers to choose.
SMART WATCHES
Watches that can connect to the smartphone and run thirdparty applications to take calls, check messages, find restaurants.
Emerging; set to grow in a big way
Smart watches consume more battery life compared to activity trackers, making long battery life a challenge. In addition, most applications require the use of touchscreen; hence, the small touchscreen size becomes a constraint. However, aggressive moves by major players like Apple have made it an interesting category to watch.
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CATEGORY
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CURRENT MARKET STATE
DEFINITION
REASONS
SMART GLASSES
Wearable glasses that can show content in front of the eye and guide users based on their locations.
Nascent; yet to take off in a big way
The challenges in providing an unobtrusive display right in front of the eye with miniaturised battery and processing are even more than the watch. Privacy of non-users is a major concern revolving around the usage of smart glasses. Google Glass, for example, was a clear failure with most early adopters giving it a “thumbs down”.
SMART CLOTHING
Clothes that can track body temperature, heart rate, intensity of workout, sporting actions.
Nascent; just beginning to grow
Doubts hover over the durability of smart clothing when it comes to long-term usage. Having shrunk sensors into thin, flexible, and comfortable-to-wear forms, producers also need to ensure the clothing can withstand daily wear and tear as well as vigorous washing machine cycles.
OTHERS
Niche applications like the medical alert system for the elderly, sporting action monitoring, gait detection for Parkinson’s patients, vital statistics measurement for workers in hazardous conditions.
Nascent; just beginning to grow
Most wearable devices in this category target the healthcare and sports industries. Due to high price and/or limited customer base that can benefit from the products, the market for the devices has been slow to develop.
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Figure 13: Wearable Technology Vendors by Product Type
SMART GLASSES
ACTIVITY TRACKERS
SMART WATCHES
SMART CLOTHING
OTHERS
To date, only smart watches and activity trackers have gained momentum in the consumer space. However, with continuing improvements in battery life, display and processor technologies, the future of wearable technology is bright. Frost & Sullivan estimates that wearable devices shipments will grow to 210 million units by 2020 compared to approximately 38 million in 2014. While activity trackers or smart bands
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constituted around 61% of wearable shipments in 2014, in 2020 smart watches are anticipated to be the largest segment constituting around 54% of the market. The following figure highlights the companies specialising in various categories of wearables.
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KEY DRIVERS & RESTRAINTS Figure 14: Drivers & Restraints of Wearables Industry Growth GROWTH DRIVERS
GROWTH RESTRAINTS
GROWING HEALTH CONSCIOUSNESS
BATTERY LIFE & PROCESSING POWER
MINIATURISATION OF SENSORS, MEMORY AND PROCESSOR
USER INTERFACE CONSTRAINTS
EASIER ACCESS TO THE DEVICE
SENSORS
EASY ACCESS TO FUNDING
APPS
APPLICATION IN A WIDE RANGE OF INDUSTRIES
COSTS
KEY DRIVERS The figure below provides a snapshot of the key factors driving the wearables market and challenges impeding growth. 1. GROWING HEALTH CONSCIOUSNESS Growing health awareness is resulting in more people being interested in tracking their physical activities like walking, cycling and running and comparing against their peers. Activity trackers provide an ideal solution for such health-conscious individuals. 2. MINIATURISATION OF SENSORS, MEMORY AND PROCESSORS Sensors, memory and processors are becoming more efficient and smaller, enabling their use in activity trackers and smart watches. For example, Samsung Gear, the first-generation smart watch from Samsung uses a 800 MHz processor with 512 MB memory – equivalent to the specification of a high-end laptop 10 years ago. 19
Similarly, a decade ago it was difficult to imagine that motion sensors could be fitted into mini devices like activity trackers. 3. EASIER ACCESS TO THE DEVICE Smartphones are a revolutionary technology, bringing almost the entire information of the world in the palm of our hands. However, smartphones have an inherent limitation that they need to be pulled out of the pocket or bag each time somebody wants to use them. Smart watches and smart glasses do away with this limitation, bringing the information to the user in a more convenient fashion. 4. EASY ACCESS TO FUNDING Start-ups mostly dominate the wearable technologies industry. The growing prominence of crowdfunding sites such as Kickstarter and Indiegogo have driven the growth of wearable technologies, enabling startups to pitch for required funding and seek market validation. For example, Pebble Watch was funded by a campaign on Kickstarter. Also, rising interest
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in wearables from the VC community is providing impetus to the growth of wearable technologies. 5. APPLICATION IN A WIDE RANGE OF INDUSTRIES Portable, compact, and with a broad array of functionalities, the non-intrusive characteristics
of wearables provide disruptive potential in many industries ranging from healthcare to engineering, and in several application areas. The figure below illustrates key applications in several industries.
Figure 15: Application of Wearables in Various Industries
CUSTOMER SERVICE
REHABILITATION & RECOVERY
PAYMENT
UMPIRING
PERFORMANCE MONITORING
ADVERTISING
RETAIL
SPORTS
EMPLOYEE SAFETY
STOCK MANAGEMENT
ENGINEERING
REPAIR & MAINTENANCE
LOGISTICS
WAREHOUSING HEALTHCARE
TRAINING
HOMELAND SECURITY
REMOTE PATIENT CARE
USER AUTHENTICATION
DISEASE MANAGEMENT
FITNESS
HAZMAT DETECTION
IDENTITY RECOGNITION
Source: Frost & Sullivan
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KEY RESTRAINTS 1. BATTERY LIFE AND PROCESSING POWER Wearables have significantly smaller space than other smart devices to house batteries, presenting serious constraints to the size of the battery. To make matters worse, the energy density of the batteries have not shown significant improvements over the years. Also, many do not allow for battery maintenance or repair due to their inherent design. Battery limitations also pose restrictions on processing speed since faster processors consume more battery life. 2. USER INTERFACE AND SENSOR CONSTRAINTS The small size poses a problem in the interaction of the user with the device. It is much harder to use the touch interface on a smart watch compared to the touch interface on a phone. Similarly, smart glasses face significant challenges in displaying content in an extremely small area so that the normal vision of the user is not restricted.
Likewise, due to the need to sense a multitude of signals, several sensors have to be miniaturised and embedded in wearables. However, miniaturisation and the inability to embed sufficient sensors could affect data accuracy. For example, accurate movement sensors from companies like APDM may cost thousands of dollars, and are not small enough to be fitted into popular wearable devices. 3. APPS Wearables have a highly fragmented ecosystem resulting in the proliferation of distinctly different sets of Software Defined Kits (SDKs) and Application Programming Interfaces (APIs) for each device. This acts as an obstacle to the growth of the number of apps available for any particular device. 4. COSTS The cost of wearables for more advanced applications like healthcare and sports remains prohibitively high. For example, a gait detection system for use in sports or certain diseases can cost thousands of dollars. Similarly, smart watches such as Apple Watch are facing lower than expected demand both due to pricing and functionality.
VALUE CHAIN AND KEY BUSINESS MODELS VALUE CHAIN The figure below provides the value chain of the wearable technology industry: Figure 16: Value Chain of the Wearables Industry
CHIP/SENSOR DEVELOPERS
OEMS/ODMS
OS VENDORS
APP DEVELOPERS
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DEVICE VENDORS
CONNECTIVITY PROVIDERS
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CHIP/SENSOR DEVELOPERS Companies that design the chips and components that form the nuts and bolts of wearable devices include: OEMS/ODMS Participants that create the original device or equipment and integrate all the components, so they function as one cohesive unit. OS VENDORS Participants that develop the operating system to power the wearable devices. APP DEVELOPERS They develop applications for wearable devices like smart watches. DEVICE VENDORS Participants that design and sell the devices under their own brand name. CONNECTIVITY PROVIDERS Telecommunications operators that provide wireless connectivity for smart wearables.
seniors, is available for purchase upfront, and can be worn around the neck or attached to the wrist. The device enables the elderly to contact a 24-hour call centre by pressing a button in case of an emergency and the call centre will dispatch an ambulance if required. The call centre service is on a monthly subscription basis. SUBSCRIPTION MODEL A variant of the Device + Subscription business model, the subscription model is based solely on subscription and restricted to enterprises. For instance, Catapult Sports from Australia, a manufacturer of sports wearables provides a subscription service to its clients. Similarly, HealthSTATS, a Singapore-based medical wearables company, sells BPro® wearable devices to monitor heart rate, blood pressure and other vital information of remote patients on subscription. Figure 17: Business Models for Smart Wearables
WEARABLE TECHNOLOGY BUSINESS MODELS
BUSINESS MODELS There are 3 business models in wearable technology: device sales, device + subscription sales, and subscription-only model.
DEVICE SALES
DEVICE + SUBSCRIPTION
DEVICE SALES In this model, the device is sold upfront along with the associated software. The accessories, replacement parts, and extended warranty may be sold separately or along with the device. DEVICE + SUBSCRIPTION Fitbit has an interesting model where customers can purchase the device and basic features for a set price. Users then have the option to subscribe to a premium annual subscription that creates a 12-week training programme based on the users’ activity level, provides in-depth data analysis, and ranks the users against their peers. This model is also used in medical alert systems like eAlert! in Singapore. The portable device targeted at 22
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VALUE DRIVERS & KEY RISKS Figure 18: Value Drivers & Key Risks for Wearable Technology Companies
KEY VALUE DRIVERS • Device Appeal • Cost of Device • Customer Traction • Application & Device Ecosystem • IPRs & R&D Capability
KEY VALUE DRIVERS 1. DEVICE APPEAL Primarily consumer devices, wearables focus on ease-of-use and design. It is important to find out if the product appeals to consumers in terms of design, functionality, practicality and ease-of-use. For example, Google Glass failed spectacularly due to bugs in the device and the perceived impracticality of walking around while looking at a screen. On the other hand, Fitbit, which is the most successful wearable device to date, ticks almost all the boxes for a successful consumer device. 2. COST OF DEVICE While expensive smartphones have achieved astonishing success, primarily because of their array of functions and subsidisation by mobile operators, it is highly unlikely to be the case with costly wearables. These devices are not subsidised by operators, and typically perform a limited set of functions due to their inherent size restrictions. Thus it is improbable that most customers would choose to pay the premium price. An example of cost appeal is the hugely successful Mi Band, a fitness tracker from Xiaomi priced at only US$13. According to the company, 6 million units were sold within 6 months of the launch. 23
KEY RISKS • Device Acceptance • Technology Obsolescence and Changing Market Preferences • Competition
3. CUSTOMER TRACTION While device appeal and cost are important, the best method to judge the success of these criteria is to look at customer traction. If the adoption of the device is growing, it is the best indication that the product has hit the sweet spot. Customer traction is also important since it creates a buzz around the product, attracting more partners and future customers. As a benchmark, Fitbit was selling close to 5 million devices a year within 5 years of launching its first device. Apple Watch was expected to sell between 2.5 million and 5 million units within one quarter of its launch. Both devices are considered to have good customer traction, although the sales of Apple Watch have been lower than original expectations. 4. APPLICATION AND DEVICE ECOSYSTEM Most wearables have limited functionality owing to their small size. However, they can become extremely powerful when paired with a smartphone and other accessories. For example, Apple Watch can be linked to an iPhone to receive calls, messages and calendar alerts on the watch. Likewise, although many activity trackers are standalone devices currently, the number of devices and accessories that work seamlessly with the wearables will be an important success factor in future.
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In addition, smart watches are expected to run a number of different applications. The larger the app ecosystem, the more useful the device will be. 5. INTELLECTUAL PROPERTY RIGHTS (IPRs) AND R&D CAPABILITIES The greatest competitive advantage of wearable technology lies in the strength of its R&D. The capability of the existing R&D team is a strong value driver for the company. The amount of money invested in R&D directly impacts the patent portfolio and trademarks, allowing the company to achieve or retain a dominant position in the market. Between 2010 and 2015, there were a number of patent battles between Apple and other smartphone vendors with most Android vendors paying out hefty royalties or penalties to Apple. In such a situation, the existing set of IPRs is extremely important to determine global success.
of smart watches, there is a high risk that the activity tracker market may stagnate after 2 to 3 years. 3. COMPETITION RISK ASSESSMENT: HIGH As new wearable devices inundate the marketplace, the risk of a company losing its market share to a competitor with a more compelling value proposition is high. For instance, Xiaomi introduced Mi Band in Q3 of 2014 and quickly garnered 25% market share by Q1 of 2015, capturing the market share of other vendors.
KEY RISKS 1. DEVICE ACCEPTANCE RISK ASSESSMENT: HIGH (FOR EARLY STAGE DEVICES) In its early stages, there is a risk whether the device will be accepted by the market. First-generation devices of major companies like Google Glass, Sony Smartwatch, and Samsung Gear were unequivocal failures due to challenges in providing attractive functionality in a small package. Even an established wearables company like Fitbit experienced issues when many users reported skin rashes after wearing its Fitbit Force fitness band. 2. TECHNOLOGICAL OBSOLESCENCE AND CHANGING MARKET PREFERENCES RISK ASSESSMENT: HIGH Wearable technology is an emerging field witnessing rapid growth and tremendous interest from both tech enthusiasts and VCs. As more capital is pumped into new start-ups, there is a genuine risk of a new emerging technology completely disrupting an existing product or device. Such disruptions may be technology-centric (e.g., a new form factor) or customer-centric (e.g., a new business model). For example, activity trackers form the largest wearables product segment today. But with improving appeal 24
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RELEVANT VALUATION METRICS Wearable technology companies have a relatively simple business model where they aim to sell as many devices as possible and achieve profitability when they reach a particular scale. Therefore, once the product is out of R&D, the company should be tracked on unit sales and revenue in the growth stage and revenue and profitability towards the later stage. Table 3: Valuation Metrics for Wearable Technology Companies in Various Stages S. NO.
EARLY STAGE
GROWTH STAGE
LATE STAGE
1.
Paid-up Capital5
Unit sales & growth
Revenue & revenue growth
2.
Potential Market Size
Revenue & revenue growth
EBITDA Margin
3.
-
-
Profit Margin
OVERALL FOCUS
RESEARCH & DEVELOPMENT
CUSTOMER TRACTION
TOPLINE & BOTTOMLINE GROWTH
EARLY STAGE: Usually first 2 to 3 years of operations. GROWTH STAGE: Approximately 3 to 7 years of operations. LATE STAGE: More than 7 years of operations.
These are the best available metrics at this stage. However, the valuation may change drastically based on the expected competitiveness of the solutions. 5
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EMERGING SOCIAL MEDIA
6.
Social media is a platform to share messages, videos, pictures and other multimedia with the general public or a network of the user’s contacts. The best examples of social media are Facebook, Twitter and LinkedIn. Together, the three social networks connect nearly 20% of humanity. Facebook has 1.2 billion monthly active users (users who use the website at least once a month); Twitter has 300 million monthly active users; while LinkedIn has 364 million monthly active users. Combined, the three companies are valued at US$318 billion in 2015. However, for this research paper, we focus solely on social media platforms that have emerged after the above 3 platforms. The new apps exploit the niche areas not addressed by the abovementioned major platforms.
3. MULTIMEDIA SHARING Several social media apps focus on sharing photographs, video clips and special multimedia formats. These include Pinterest, Tumblr, Instagram and Vine. 4. FOCUS ON MOBILE With mobile becoming the primary means of accessing the Internet in emerging markets, several mobile-focused social media platforms have sprung up recently. Examples include WhatsApp and Foursquare. These examples signify the fast-evolving social media landscape. It will be interesting to find out the growth drivers of these apps and platforms, and to assess their potential.
Among the emerging platforms, Instagram and WhatsApp gained the most limelight as both were acquired by Facebook for US$1 billion and US$19 billion respectively. Pinterest, Tumblr, Yik Yak and Quora are other prime examples of emerging social media platforms. Principal characteristics of the new-age social media platforms include: 1. INCREASED FOCUS ON PRIVACY AND ANONYMITY Many emerging social media companies concentrate on enhanced privacy requirements by featuring messages that expire after a set time to ensure privacy and security. Some of these platforms also feature messages that self-destruct after reading and anonymous postings. Examples include Snapchat, Burn Note, and Whisper. 2. LOCALISED SOCIAL MEDIA Many apps are focusing on localisation by providing access to anonymous messages in the local area of the user. These include Yik Yak, Nearby, and Skout. Apps like Foursquare help users to find places of interest in their locality.
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KEY DRIVERS & RESTRAINTS Figure 19: Drivers and Restraints of Social Media Industry Growth
GROWTH DRIVERS
GROWTH RESTRAINTS
INCREASING INTERNET AND MOBILE DATA PENETRATION
“WINNER TAKES ALL” DYNAMICS
GROWING NUMBER OF BUSINESS MODELS
LACK OF A WELL-DEFINED BUSINESS MODEL
FUNDING AVAILABILITY
KEY DRIVERS 1. INCREASING INTERNET AND MOBILE DATA PENETRATION The growing Internet and mobile data penetration are the biggest growth drivers for the social media industry. More people online mean more people who can be connected via social media platforms. Social media has a big network effect, which essentially means that as more people join in, the utility of the social media increases for each member on the platform. As an example, if there were just one telephone in the world, it would be of no use. However, as the number of telephone subscribers increased, the usefulness of the telephone would increase for every subscriber. In these cases, an escalation in the number of users leads to an accelerated growth of the platform. 2. GROWING NUMBER OF BUSINESS MODELS As discussed in the introductory section, there is an increasing number of new business models serving the unmet needs of privacy, localisation, dating, and multimedia sharing. This has led to the growth of social media platforms and users. 3. FUNDING AVAILABILITY The success of social media platforms like Facebook, LinkedIn, Twitter and WhatsApp are attracting keen 27
interest from VCs and motivating entrepreneurs to invent new social media offerings, leading to the faster expansion of social media.
KEY RESTRAINTS 1. “WINNER TAKES ALL” DYNAMICS As stated earlier, social media platforms have a strong network effect. Social media with a larger number of users and interactivity provides greater value than a smaller, less interactive platform. Users gravitate towards the largest platform in the category leading to the gradual demise of smaller ones. Orkut, Myspace, Digg, Friendster and Bebo are examples of social media platforms that were once popular but faded away as users gravitated towards Facebook. Even Google+ is facing significant hurdles despite Google using all its competencies and assets to popularise the platform. 2. LACK OF A WELL-DEFINED BUSINESS MODEL Most social media platforms are designed to attract users onboard. However, some platforms such as WhatsApp, Snapchat and Pinterest do not seem to have a clear monetisation model. Although this does not appear to be a key obstacle for social media platforms so far, it may lead to the demise of some apps as investors eventually lose patience and pull out.
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TYPES AND REVENUE MODELS OF SOCIAL MEDIA PLATFORMS TYPES MICROBLOGGING PLATFORMS Microblogging websites allow you to share short text, photographs and multimedia posts with a large audience or list of selected friends. Twitter is the classic microblogging website; however, post-Twitter, there are a growing number of websites focusing on multimedia content. For example, Pinterest allows people to post interesting pictures and videos that can be viewed by others. The pictures can be their own or discovered by them on the Internet. Similarly, Tumblr allows you to post a mix of pictures, text and videos. Instagram and Vine can also be classified as microblogging platforms. In such platforms, content is created or posted by all members but it is the content from a few influential content authors that is consumed by a very large number of members. Thus, the key success factor for such platforms is having a substantial number of influential content authors who post attractive content at regular intervals. TEXTING PLATFORMS Texting apps allow users to text with friends or group of friends. The most famous example is WhatsApp and WeChat. In these platforms, the ease of connecting to friends and texting or calling friends are the most critical success factors.
key success factors for such platforms. OTHERS Other types of social media platforms include location-based social apps, social news and social queries. Location-based social apps enable you to find locations of interest based on recommendations from friends. Foursquare and HungryGoWhere are examples of location-based social apps. In social news platforms, people post news items, and other people vote up or down their posts. The news items are then shown to users based on the votes. One example is Reddit. In the social queries platform, users can pose a question to a large pool of users. Users are then rated based on the quality of their answers. An example is Quora. Figure 20: Emerging Social Media Platforms by Category
MICROBLOGGING
TEXTING
There is a variation of texting platforms that focus on sending self-destructing messages . An example is Snapchat that lets users send messages to one other which self-destructs after a certain time. CHATTING AND DATING There are several social media apps that allow people to chat with strangers mostly with the intent of ultimately meeting up. Key examples include Tinder that enables people to view pictures of other users and chat if they are mutually interested. Skout and MeetMe are similar platforms.
CHATTING AND DATING OTHERS
The number of users, ease of meeting new people, and mechanisms to ensure privacy and secrecy are 28
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REVENUE MODELS The 3 most common revenue models used by social media platforms include:
advertisement models. Even Snapchat is starting to use this model by allowing advertisers to offer their content to Snapchat users.
1. ADVERTISING Advertisements are the most dominant revenue model for social media platforms. Due to their ability to draw visitors, advertisements are inherently attractive to advertisers keen on showcasing their brand to draw traffic to their websites or apps.
2. FREEMIUM In the Freemium model, the basic membership on the platform is free. However, members may need to pay for an enhanced membership or certain digital goods. Key examples are Premium Themes available for purchase at Tumblr, Tinder Plus subscription that offers additional services to subscribers and LinkedIn Premium.
Businesses wanting to advertise their brands opt for a CPM (Cost per thousand impressions) model where they pay based on the number of times their ad was served in front of a viewer. The best examples are suggested or sponsored posts on Facebook or Twitter. Advertisers aiming to generate traffic choose the CPC (Cost per Click) model where they pay based on the number of times their ad was clicked. Most social media platforms typically display CPM advertisements. Facebook (suggested posts), Twitter (suggested tweets), Tumblr (sponsored posts) and Pinterest (promoted pins) rely heavily on
Most social networks utilise this model as an add-on revenue stream with the major revenue coming from advertisements. 3. SUBSCRIPTION In the subscription model, each member has to pay an annual fee. Though no social media platform has started using this model, WhatsApp has switched to a subscription model in the US and several developed countries.
VALUE DRIVERS & KEY RISKS Figure 21: Value Drivers & Key Risks for Social Media Companies
KEY VALUE DRIVERS • Number of Active Users • Frequency of Interaction • Growth • Funding • Proven Revenue Model
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KEY RISKS • Lack of Availability of Funds • Viability of Business Model • Competition • Changing Market Preference
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KEY VALUE DRIVERS The key value drivers of a social media company are as follows: 1. NUMBER OF ACTIVE USERS As noted previously, social media platforms have a huge network effect, i.e., the utility of the platform grows for everyone as the number of active users increase. For example, Facebook is far more useful if most of the friends, family and acquaintances are actively using the platform compared to when only a few are on the platform. Therefore, the number of active users on the platform (instead of competition) directly translates into the probability of the platform’s success. 2. FREQUENCY OF INTERACTION Using only the number of active users as a metric for predicting the success of a social media platform has obvious pitfalls. In many cases, the platforms can get the user, but they cannot get them to interact with the platform. For example, while platforms like Google+ have been able to attract a large number of users with many visiting the platform actively; however, most don’t share anything through it. Thus, the number of users who share content on a daily basis (app or website) are the other two metrics that predict the success of the platform over the long term. 3. GROWTH The third value driver is the level of growth the platform is experiencing in terms of number of users and frequency of content sharing. Fast expansion of the platform means it has a significant influence on users and can expand quickly over the entire addressable market even in the presence of formidable competition. 4. FUNDING Most social media platforms are not able to build a revenue model in their early stages and need to burn a large amount of cash for R&D and marketing activities. A better-funded company with greater interest from investors is more likely to survive the initial phase of generating little or no revenue.
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5. PROVEN REVENUE MODEL Although most social media platforms do not focus on a revenue model in the early growth stage, it is an important consideration for late growth stage companies. When user growth starts reducing, investors start worrying about whether the platform can be monetized. If a successful monetisation model cannot be evolved, investors may lose interest.
KEY RISKS The primary risks for an ecommerce company include the following: 1. LACK OF AVAILABILITY OF FUNDS RISK ASSESSMENT: HIGH (FOR EARLY AND GROWTH STAGE COMPANIES) Social media platforms usually have negligible revenue in the early stage, and hence, are dependent almost exclusively on external funding for their viability. Any disruption in funding either in the form of waning interest or lack of funding from VCs can have an adverse impact on such companies. Pownce is an example of a microblogging website that had to shut down due to insufficient funding. 2. VIABILITY OF BUSINESS MODEL RISK ASSESSMENT: HIGH (FOR GROWTH AND LATE STAGE COMPANIES) At some point, social media platforms need to develop a revenue model and earn a steady income. There is always a risk they may not be able to create a model that keeps the business profitable. Even companies such as Facebook faced difficulties in posting its IPO due to doubts over its advertisement-based business model. One reason Twitter has seen a continuous decline in its stock prices is the company’s inability to sufficiently monetise its platform to be able to generate profits. 3. COMPETITION RISK ASSESSMENT: HIGH How Facebook made vast social networks such as Bebo, Orkut and MySpace defunct is an example of what competition can do in the social media space. Competitors with new and improved offerings can take away existing users and jeopardise the future of existing ecommerce enterprises. Typically, the larger
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the social network and higher the interaction of users, the better protected it is from new competitors. 4. CHANGING MARKET PREFERENCE RISK ASSESSMENT: HIGH Twitter was once the second-largest social media platform and touted as the second Facebook. It was difficult to enter a large amount of text in earlier smartphones; Twitter’s 180-character microblogging soon became immensely popular with people accessing the Internet via their mobile
phones. However, as the capability of smartphones increased, users did not mind sharing longer posts on Facebook and other social media platforms from their mobiles. Frost & Sullivan suspects this as one of the reasons behind the stalled user growth of Twitter. The company’s user base has now been eclipsed by platforms such as Instagram, WhatsApp and Facebook Messenger, indicating the effects of changing market preferences on the future of social media platforms.
Figure 22: Number of Active Monthly Users on Leading Social Media Platforms Facebook WhatsApp Twitter MILLIONS
Instagram
Source: Company Press Releases, Frost & Sullivan Estimates
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RELEVANT VALUATION METRICS Social media platforms focus first on getting the users (or eyeballs) and then try to monetise them. The metrics for early stage firms is usually non-financials. As they develop a revenue model, the focus shifts on revenue, and finally on profitability. 1. EARLY STAGE
The key focus at this stage is getting users on the platform to prove its attractiveness and creating a competitive advantage. The key valuation multiples include valuation/number of monthly active users. Such ratios may vary drastically based on factors such as uniqueness of the platform, frequency of interaction, and growth. For example, as of Q3 2015, Facebook’s valuation was around US$200/monthly active user; Snapchat was US$150/monthly active user; and Twitter was around US$60/monthly active user6.
2. GROWTH STAGE
A revenue model is usually developed in the growth stage and the focus shifts on revenue multiples. However, in some cases like Snapchat, social media companies wait longer before monetising the platform, and monthly active users remain an important metric. The key valuation multiples include valuation/revenue as well as valuation/monthly active users.
3. LATE STAGE
In late stage social media companies, the aim is to monetise the platform and maximise profitability and cash flow while maintaining growth. The key metrics are revenue and revenue growth, EBITDA margins and profit margins. The key valuation multiples include valuation/revenue, valuation/EBITDA (EV/ EBITDA) and valuation/earning (Price earning ratio).
Table 4: Valuation Metrics for Social Media Platforms in Various Stages S. NO.
EARLY STAGE
GROWTH STAGE
LATE STAGE
1.
Number of monthly active users
Revenue & revenue growth
Revenue & revenue growth
2.
Growth in monthly active users
Monthly active users & growth
EBITDA Margin
3.
-
-
Profit Margin
OVERALL FOCUS
CUSTOMER TRACTION
TOPLINE GROWTH & CUSTOMER TRACTION
TOPLINE & BOTTOMLINE GROWTH, CASH FLOWS
EARLY STAGE: Usually first 2-3 years of operations. GROWTH STAGE: 3-7 years of operations. LATE STAGE: More than 6-7 years of operations 6
Source: Company press releases and Bloomberg. 32
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ECOMMERCE
Electronic commerce or ecommerce is simply defined as websites or apps that facilitate the buying and selling of goods and services online. There are multiple variations of the ecommerce business model. The differences can be classified based on a number of characteristics including the type of sellers and buyers (consumers, businesses or government), the kind of goods and services being sold (digital or physical), and many other such parameters. We examine the multiple ecommerce models in a later section. Attracting nearly US$112 billion in investments globally in 2014, the ecommerce sector is undergoing explosive growth with portals such as Flipkart raising more than US$1 billion of funding in one single deal. New companies and business models enter the fray every day, striving to make online transactions more reliable and convenient for both buyers and sellers (merchants or individuals) alike. South East Asia has its fair share of thriving ecommerce start-ups
including firms such as Lazada, Shopee, Reebonz, Qoo10, RedMart, Rakuten and Wego. Despite the astounding growth of ecommerce, profitability remains a critical concern in the sector. Even mature firms like Amazon are still unprofitable and have focused on cashflow instead of profitability as the relevant financial metrics. Against this backdrop, cash flow instead of profitability is being proposed as the more relevant valuation parameter. Valuation becomes even more tricky for companies in the growth phase that are not only unprofitable but have significant negative cash flows. Despite the lack of profitability, investors are willing to pour billions of dollars into these firms. In this section, we explore the dynamics driving these valuations. Note: For the purpose of this research paper we will focus exclusively on consumer ecommerce – primarily the Business to Consumer (B2C) and Consumer to Consumer (C2C) segments.
KEY DRIVERS & RESTRAINTS Figure 23: Drivers and Restraints of Ecommerce Industry Growth
GROWTH DRIVERS
GROWTH RESTRAINTS
RAPID PROLIFERATION OF INTERNET & MOBILE DATA IN EMERGING MARKETS
LARGE INVESTMENT REQUIREMENTS & LONG GESTATION PERIOD
BETTER PAYMENT METHOD
UNTESTED BUSINESS MODELS
INVESTMENT IN LOGISTICS
SHIPPING COSTS
NEW BUSINESS MODELS
GOVERMENT REGULATIONS
FUNDING AVAILABILITY
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KEY DRIVERS 1. RAPID PROLIFERATION OF INTERNET AND MOBILE DATA IN EMERGING MARKETS Internet penetration in emerging markets is growing at a fast pace. For example, Indonesia’s Internet penetration increased from 17.5% in 2011 to 33% in 2014. More people online mean a greater addressable market for ecommerce – a compelling reason for the rapid growth of ecommerce in emerging markets. Mobile data penetration plays a pivotal role in spurring ecommerce activities. Given the challenges in increasing fixed broadband penetration, most new Internet users in these countries are getting online using a mobile phone. For example, portals like Flipkart receive 20% of their orders via mobile phones.
Internet Penetration (%)
Online Retail sales (US$ Billion)
Figure 24: Correlation between Online Sales and Internet Penetration in Indonesia
Retail
2. BETTER PAYMENT METHODS In the past, identity theft and credit card fraud have been among the most critical factors forming a significant barrier to ecommerce growth. However, advances in technology, increasing security measures and new payment systems are not only boosting the growth of credit card usage, but encouraging users to store their details at ecommerce websites. Several ecommerce portals also provide Cash on Delivery (CoD) terms, further enhancing the ease of payment. The emergence of online wallet services, e.g., PayPal, MatchMove Pay and TCash, in emerging markets is another feature fuelling the growth of ecommerce 34
3. INVESTMENT IN LOGISTICS A successful ecommerce model requires swift fulfilment of orders, which in turn, calls for efficient logistics. While large ecommerce companies like eBay, Rakuten and Rocket Internet are making substantial investments in warehousing and advanced logistics solutions, traditional logistics players are also taking steps to tap into the burgeoning ecommerce market. For example, DHL has a dedicated ecommerce logistics facility and aspires to become an endto-end ecommerce enabler. Similarly new startups such as Anchanto are providing a logistics fulfilment technology platform exclusively targeting ecommerce companies. 4. NEW BUSINESS MODELS The conventional consumer ecommerce model follows either a Consumer-to-Consumer (C2C) approach where consumers sell small items to other consumers or an integrated Business-to-Consumer (B2C) approach where participants such as Amazon keep the inventory and service consumers who require those goods. With the growing demand of ecommerce, numerous innovative business models are emerging. The predominant approach today is the marketplace model where multiple sellers (businesses or consumers) list their products, and the ecommerce portal supports the delivery and payment of goods once an order is placed. Other new models include the online mall model where the buyer creates a virtual storefront or mini portal within the larger ecommerce portal like in the case of Rakuten; the subscription model where consumers can subscribe to a beauty product, and the product is delivered to them at regular intervals, (e.g., Bellabox); the curated ecommerce model where sites feature expert curated products to target the particular needs of customers (e.g., Luxola); and social ecommerce where buyers share photographs of items they have purchased, and visitors are directed to ecommerce sites selling similar items in case they like it (e.g., Clozette). Apart from the new models, the types of goods and services available on ecommerce portals are increasing as well. In addition to the conventional items such as digital goods (music/movies), groceries, home furnishings, services, and beauty products are now available on ecommerce websites.
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Myriad options are available to users today depending on their needs. Virtually everything you need to buy is available on an ecommerce portal, increasing the overall popularity of ecommerce. 5. FUNDING AVAILABILITY The success of emerging market ecommerce portals such as Alibaba and Flipkart are attracting the interest of global venture capital (VC) firms in the ecommerce space. Singapore-based VC firms such as Golden Gate Ventures are taking advantage of the flourishing market as well. The flexible monetary policy in the US enables VC firms to raise massive amounts of capital. Since ecommerce portals need substantial cash investments in their initial years, funding from VCs are spawning a vast number of ecommerce portals worldwide.
KEY RESTRAINTS 1. LARGE INVESTMENT REQUIREMENTS AND LONG GESTATION PERIOD Ecommerce companies require tremendous investments over an extended period. It takes at least five years of operations for ecommerce companies to become cash positive. Substantial investments go into setting up an ecommerce portal, from logistics, technology to subsidising the purchase of goods to spur adoption. Since not many companies have the investment appetite to go through such a lengthy gestation period, this acts as a significant barrier to the growth of ecommerce. 2. UNTESTED BUSINESS MODELS While many new business models emerge each
year (e.g., subscription and mobile-only models), it is not certain which of these will eventually work. A model that works in one geographical region may not necessarily work in another. For example, Bellabox, a successful subscription portal for curated beauty products in Australia, attempted to expand into Singapore. However, the company soon realised that the Singapore market was too small to gain a significant number of subscription customers required to keep the business running. The company closed its subscription services within a few years of operation in Singapore. Similarly, Lykestore, a curated ecommerce portal owned by SingTel ceased operations due to intense competition and lack of demand for niche brands on the portal. These cases indicate the extremely high failure rates of ecommerce start-ups. 3. SHIPPING COSTS Shipping costs sometimes result in products ending up being more expensive than in the physical market. Therefore, smaller yet relatively high-value products, for which the shipping cost is usually a fraction of the cost of the items, are preferred over low-value items. 4. GOVERNMENT REGULATIONS Many governments in emerging markets have yet to introduce market-friendly regulations on investment, taxation, consumer protection and data protection for ecommerce websites resulting in the postponement of investments in some countries. For example, Indonesia has blocked foreign investors from investing in ecommerce portals – a move that is expected to severely erode the competitiveness of the ecommerce market in the country.
VALUE CHAIN AND KEY BUSINESS MODELS VALUE CHAIN Since ecommerce typically involves aggregating buyers and sellers, it has a relatively simple value chain. Figure 25: Ecommerce Value Chain
ECOMMERCE PLATFORM
SELLERS
LOGISTICS
PAYMENT
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Ecommerce platforms may have external sellers, logistics and payment systems or they may do everything inhouse. As an example, the players selling on Amazon & eBay are sellers (Amazon is a seller as well). Vendors may use Amazon logistics (Amazon-fulfilled) or other logistics companies. Amazon enables payment with the help of PayPal and credit card companies.
BUSINESS MODELS The business models of ecommerce companies can be differentiated based on their value creation, charging model (the way customers are charged)
and types of goods and services offered. There can also be a distinction in the priority of channels (mobile or web) as well.
Figure 26: Dimensions of Ecommerce Business Models
VALUE CREATION
How is value being created for buyers and/or sellers?
CHARGING MODEL
How are buyers being charged for the products & services?
TYPES OF GOODS
What types of goods & services are being sold through the portal?
CHANNELS
What is the primary channel to reach customers (web/mobile)?
1. VALUE CREATION Value creation refers to the way value is created for the clients. The table below describes the most common models and their significance.
Basis of Value Creation: Ease of purchase compared to physical stores. MULTI-BRAND RETAIL MODEL Figure 28: Representation of Multi-Brand Model
SINGLE BRAND RETAIL MODEL Figure 27: Representation of Single Brand Model 1
2 3
1
4
OWN BRAND
ECOMMERCE PORTAL
BUYERS
Description: The simplest ecommerce model where the portal sells a single brand usually owned by the portal or its parent company. Examples: Apple Web Store, Ikea, HipVan. 36
BRANDS
ECOMMERCE PORTAL
BUYERS
Description: Portal sells goods from multiple brands, as in the case of fashion, groceries, travel and digital goods. Examples: Zalora, RedMart
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Basis of Value Creation: Ease of purchase compared to physical stores, discounts (in some cases), and product reviews.
Basis of Value Creation: Connecting different buyers and sellers that may otherwise fail to reach each other, product reviews, and ease of purchase.
MARKETPLACE MODEL (STOREFRONT MODEL) Figure 29: Representation of Marketplace Model
DEAL MODEL Description: Portal sells discount coupons from physical retailers. It is a niche model where even pioneers such as Groupon struggle to achieve profitability. Example: Groupon
1 1
Basis of Value Creation: Allows retailers to run effective promotion campaigns.
2 3
4
BRANDS
2
3
ECOMMERCE PORTAL
BUYERS
SELLERS
Description: A platform that brings together multiple buyers and sellers. There can be different vendors in addition to the portal’s brand. It is the most dominant model and considered the most proven. Sometimes, sellers can have mini websites within the overall portal like in the case of Rakuten. Examples: Amazon, Lazada, Rakuten
OTHER NICHE MODELS Description: Business directories or social media sites that allow consumers to post their preferred products. These sites sometimes connect to other ecommerce portals to facilitate actual purchasing. Examples: TripAdvisor, Clozette, SGrooms Basis of Value Creation: Facilitates easier search functionality and features user reviews.
Basis of Value Creation: Connects various buyers and sellers that may otherwise fail to reach each other, product reviews, and ease of purchase. CONSUMER TO CONSUMER MODEL (C2C) MODEL Figure 30: Representation of C2C Model
1 1 2 3
4
BRANDS
2
3
ECOMMERCE PORTAL
BUYERS
SELLERS
Description: Similar to the marketplace model, however, the sellers are mostly individuals or small companies. The ease of selling is higher, and the mechanism to increase the trustworthiness of sellers is stronger than in the marketplace model. Examples: eBay, Tokopedia, Qoo10
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Table 5: Key Business Models based on Value Creation
SINGLE BRAND MODEL
Sales of goods & services
MULTI-BRAND RETAIL
Sales of goods & services
MARKETPLACE MODEL (STOREFRONT MODEL)
Commission from sales Sometimes a quarterly membership fee is charged to sellers Portal may sell its own goods to contribute to the revenue
C2C MODEL
Commission from sales
DEAL MODELS
Commission on discount coupons sold
OTHER NICHE MODELS
Listing fee Advertisements Referral fee from the portals to which they lead
CHARGING MODEL Charging model refers to the way consumers are charged. Key models are: Transaction-based: In this model, consumers are charged separately for each purchase. Most ecommerce portals follow this model. Subscription-based: In this model, consumers are delivered a set or variable number of goods for a fixed monthly fee. These can range from beauty products (e.g., Bellabox, Dollar Shave Club), to shoes (e.g., shoedazzle), movies (e.g., Netflix), news (e.g., FT.com) and music (e.g., Spotify). While the subscription model has the advantage of greater predictability of revenue, it may be harder to attract customers. Since this model has a low customer conversion rate, it typically requires countries with a broad consumer base. Subscription websites such as Bellabox have failed to make inroads in small countries with limited customer base like Singapore. 38
Listing/Freemium-based: In this model, anyone can list products or services they are offering. Sellers can list their products for a fee, or for free with a sum charged only if the seller wants a preferential listing. Purchases are usually not controlled by the portal in this model. Delivery charges and payments are settled between the buyers and sellers independently. TripAdvisor, SGroom, OLX, and HungryGoWhere are prime examples of this model. Monetisation is riskiest in this model; with even established players such as Zomato struggling to generate revenue.
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Figure 31: Examples of Key Ecommerce Business Models
VALUE CREATION MARKETPLACE REVENUE MODEL
MULTIBRAND RETAIL
CONSUMER TO CONSUMER
SINGLE BRAND/ NICHE /DEAL
TRANSACTION BASED
SUBSCRIPTION BASED
No examples
LISTING/ PREMIUM BASED
No examples
No examples
No examples
2. TYPES OF GOODS AND SERVICES In addition to the charging and value creation models, ecommerce companies can also be classified according to the type of goods and services they sell. Most ecommerce portals fall under one of the following categories: Integrated Portals: Sell a wide range of products including books, music, toys, white goods, clothing, jewellery and other items. Amazon is an example of an integrated portal. Niche Goods Portals: These include groceries (e.g., RedMart), fashion (e.g., Zalora), hotels (e.g., Agoda), airlines (e.g., Expedia), luxury goods (e.g., Reebonz), furniture (e.g., HipVan) and beauty and cosmetics (e.g., Bellabox).
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Services Portals: Markets skilled services ranging from language translators, handymen, tutors and others. Fiverr, which markets digital skills, is a key example of such portals. Digital Goods Portals: Sites and apps to purchase or subscribe digital goods. Examples include Apple’s AppStore (games and apps), Spotify (music), and Netflix (movies). 3. CHANNEL Considered the fourth dimension, Channel can refer to the traditional Internet where the ecommerce portal is available on the web or as a mobile app. In most cases, both channels are used, though mobileonly portals are gaining momentum. A key example of a mobile-only portal is Myntra.com in India.
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VALUE DRIVERS & KEY RISKS Figure 32: Value Drivers & Key Risks for Ecommerce Companies
KEY VALUE DRIVERS • Scale • Funding • Customer Stickiness & Growth • Potential Market • EBITDA Margin & Working Capital
KEY VALUE DRIVERS The key value drivers of an ecommerce company are as follows: 1. SCALE Scale is the biggest value driver for most ecommerce business models. An ecommerce company with more buyers is going to attract more sellers. It is also going to provide larger economies of scale in terms of marketing and brand reach as well as securing better deals from merchants and controlling overheads. More sellers and better economies of scales attract a greater number of buyers, becoming a virtuous cycle. In general, only one or two companies survive within a particular ecommerce category in a given geography. Businesses that cannot achieve significant scale are not able to attract enough buyers and hence are unable to compete with larger competitors. This is why most ecommerce companies spend tremendous amounts of cash upfront to achieve greater scale. In the early and growth stages, ecommerce enterprises strive to achieve scale and survive longer than competitors. Once the competition subsides, it is easier to get more cash and profitability for investors. 40
KEY RISKS • Viability of Business Model • Lack of Availability of Funds • Competition • Not Reaching Eventual Profitability or Cash Flow Goals • New Competitors & Business Models • Technological & Market Obsolescence
Investors use metrics such as Gross Merchandise Value (GMV) or the value of total goods or services sold on the portal to assess the scale of the company in relation to the competition. For example, eBay’s valuation is .36 times its annual GMV whereas for fast-growing Flipkart, the ratio is 3.5. Figure 33: Virtuous Cycle of Ecommerce Business Models
MORE BUYERS
GREATER ECONOMIES OF SCALE
MORE SELLERS
Note: In most models, more sellers may not be relevant. However, the overall virtuous cycle remains relevant.
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2. FUNDING The company with more cash to spend is likely to end up a winner. In short, better-funded companies are more likely to succeed than lesser funded ones. Therefore, it is advisable to look at the cash position and likelihood of subsequent funding for ecommerce companies. 3. CUSTOMER STICKINESS AND GROWTH While growth can be achieved through aggressive marketing and expansion to new geographies, what ultimately ascertains growth sustainability is whether buyers keep coming back to the site. The repeat purchase rate (percentage of buyers who return to the portal for another purchase) is a vital indicator of the long-term success of the company. A successful ecommerce portal will have higher customer stickiness than its competitors. For a successful portal, typically 25% to 40% of its customers are more likely to purchase again within a month. In addition, a portal’s fast growth often reflects that existing customers are referring friends to the site. While mature portals like Amazon grow at around 20%, growth stage portals such as Flipkart are growing at more than 100% per annum. Customer stickiness and growth indicate the presence of multiple attributes. These include the relevance of available products and services to customers, appropriate pricing, simple-to-use interface, convenient payment methods, and efficient delivery and product return process. 4. POTENTIAL MARKET A primary value driver of an ecommerce portal is the ultimate potential market. Can the model be extended to new products and service categories? How easy would it be for the portal to go into new geographies or countries? How many additional users are likely to start using the offerings of the portal in the future (due to reasons such as higher income, access to credit cards and the Internet). The larger the potential market size, the higher the value of the portal in the long-term. 5. EBITDA MARGINS AND WORKING CAPITAL These key value drivers are more relevant to late stage ecommerce portals where investors are looking to get returns from their investments instead of 41
injecting more funds into the company. The EBITDA margins indicate whether the company is able to make an operating profit, i.e., the cost of the goods and services it sells and its operating expenditure is less than the revenue. However, ecommerce companies employ a unique method where they can get excess cash for investors without necessarily being profitable. Most ecommerce companies have negative working capital. They pay their suppliers after consumers pay them. Consequently, till their growth is intact, they always end up generating more cash from customers than what they have to pay to suppliers. Hence, it is argued that the appropriate valuation measure for ecommerce companies is not profitability, but free cash flows (FCF) since only FCF includes the effect of working capital as well.
KEY RISKS The crucial risks for an ecommerce company include the following: 1. VIABILITY OF BUSINESS MODEL RISK ASSESSMENT: HIGH (FOR EARLY STAGE COMPANIES) Early stage ecommerce companies often do not have a revenue model or proven revenue models. For example, many advertisement- or referralbased firms face monetisation issues. Similarly, niche start-ups like LykeStore focusing on selling curated fashion products have had to cease operations. Even relatively older business models selling discount coupons online, e.g., Groupon, still face questions about their survivability. Investors should look for past successes of companies with similar business models, and assess whether the business model can work in the focus geography of the company (e.g., curated commerce is moderately successful elsewhere, but mostly failed in Singapore due to its low population). 2. LACK OF FUNDING AVAILABILITY RISK ASSESSMENT: HIGH (FOR EARLY AND GROWTH STAGE COMPANIES) Since ecommerce companies need to utilise a large amount of cash in the initial and growth stages to stay competitive, the biggest risk is that they will run out of cash before the competition. The current
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cash reserves, current cash burn rate (cash used per month), possibility of raising subsequent funding and financial capabilities of the investors are some of the key parameters to look at before evaluating the risk of running out of cash. 3. COMPETITION RISK ASSESSMENT: HIGH (FOR EARLY AND GROWTH STAGE COMPANIES) Most ecommerce business models have significant economies of scale, which means only one to two players eventually survive in a given business model. There is always a risk that larger competitors will attract more buyers and sellers, driving the smaller players out of business. Thus, the relative size of the player compared to key competitors should be an important criterion for investment. 4. NOT REACHING EVENTUAL PROFITABILITY OR CASH FLOW TARGETS RISK ASSESSMENT: HIGH Companies invest a lot of cash in the eventual hope of having a less competitive market and achieving higher profitability and positive cash flows. However, there is always a risk that the target profitability may not be achievable. Perhaps the portal will not be able to reach the kind of scale it requires for the target profitability, or buyers and sellers move away from the portal when the commission is increased, or the competition never reduces to the desired level. Another key risk is that negative working capital adds to the cash flow only until growth occurs. Once growth slows down, the negative working capital stops contributing significantly to the cash flow. Thus, the overall cash returns to investors reduce.
In fact, companies like Amazon are currently facing this very risk. Hence, we perceive this as a high risk for ecommerce portals. 5. NEW COMPETITORS AND BUSINESS MODELS RISK ASSESSMENT: MODERATE Another key risk is the emergence of new competitors into the market, notably larger international competitors. The competitors may be using the same business model as the portal in question or a superior business model that may be hard to emulate. An example is housing websites that used to connect consumers to brokers are now facing competition from new websites that directly connect consumers to consumers. However, historically these risks have been moderate since there are not many examples of new players that have been able to displace an existing market leader in the ecommerce space. 6. TECHNOLOGICAL AND MARKET OBSOLESCENCE RISK ASSESSMENT: MODERATE Ecommerce websites also face risks from new competitors coming in with a better technology platform. However, most large websites have been able to innovate or copy better platforms of new entrants. In some cases, the market for the key goods may come down sharply. For example, CDs and DVDs sold by ecommerce websites are being replaced by online downloads, while ebooks are fast replacing books. In these cases, most websites have been able to innovate to match the changing market preferences. Hence, we perceive these risks to be moderate.
RELEVANT VALUATION METRICS Since the focus of ecommerce firms is first to acquire sufficient scale by investing large amounts of cash upfront and then reaping the rewards, different metrics should be used for ecommerce companies in various stages. The following table shows the relevant metrics for ecommerce companies in different stages. 1. EARLY STAGE
The focus at this stage is scaling up by attracting more buyers and visitors to the site to prove the business model. Thus the key valuation multiples include valuation/visitors, valuation/GMV.
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2. GROWTH STAGE
In the growth stage, the primary aim is to establish a revenue model and scale up as rapidly as possible to pre-empt competitive action. Valuation metrics include overall GMV and growth in GMV, revenue and revenue growth, the number of buyers and growth as well as repeat purchase rates. Consequently, the key valuation multiples include valuation/visitors, valuation/ GMV and valuation/revenue.
3. LATE STAGE
For late stage ecommerce companies, the aim is to maximise profitability and cash flow while maintaining growth. Therefore, the critical metrics are revenue and revenue growth, GMV & GMV growth, EBITDA margins and free cash flow. Key valuation multiples include valuation/revenue, valuation/EBITDA (EV/EBITDA) and valuation/free cash flow.
Table 6: Valuation Metrics for Ecommerce Portals at Various Stages S. NO.
EARLY STAGE
GROWTH STAGE
LATE STAGE
1
Number of buyers & buyer growth
Revenue & revenue growth
Revenue & revenue growth
2
GMV & GMV growth
GMV & GMV growth
GMV & GMV growth
3
Repeat Purchase Rate
Number of buyer & growth
EBITDA Margin
4
-
Repeat Purchase Rate
Free Cash Flow
OVERALL FOCUS
CUSTOMER TRACTION
TOPLINE GROWTH & CUSTOMER TRACTION
TOPLINE & BOTTOMLINE GROWTH, CASH FLOW
EARLY STAGE: Usually first 2 to 3 years of operations of an ecommerce company. GROWTH STAGE: Approximately 3 to 6 years of operations. LATE STAGE: More than 6 years of operations.
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EPAYMENT
Epayment system is defined as a method of making payments for products or services over an electronic platform such as the Internet or mobile phone instead of using cash, cheque, in person or via mail. Consumers use epayments because of its convenience. For example, when you make a purchase online, and have a PayPal account, making a payment is as simple as clicking your mouse. On the other hand, merchants and ecommerce websites accept payments using epayment channels since it helps them attract more customers. Customers prefer to purchase from ecommerce websites that provide a greater variety of convenient payment options compared to ones that offer limited options. Epayments are growing fast driven by the growth
in the emerging markets. According to The Nilson Report, card payment transactions in the APAC grew 27.4% from US$7,362 billion in 2013 to US$9,382 billion in 2014. Epayment transactions were said to have grown to a total of 34.8 billion transactions globally in 2014. (Source: Capgemini) The epayment market, primarily in South East Asia, is drawing keen interest from leading international players such as PayPal, Alipay and Payment Asia. As per the graph below, the emerging Asian markets have the highest growth potential in epayments, as evident from the current low penetration levels. For the scope of this paper, we focus on the payments that support business to consumer ecommerce transactions or payments and transactions enabled by mobile phone (mpayment).
%, TRANSACTIONAL PER CAPITA 2011
Figure 34: Payment Preferences in Various Regions
Emerging Asia*
Latin America**
USA & Canada
CASH
98%
91%
48%
CHECK
0.6%
1%
9%
CARD
1%
4%
34%
0.4%
4%
9%
ELECTRONIC
* China, India, Indonesia, Malaysia and Thailand ** Argentina, Brazil, Chile, Colombia, Mexico and Peru 44
Source: McKinsey Global Institute
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KEY DRIVERS & RESTRAINTS Figure 35: Drivers & Restraints of Epayment Industry Growth GROWTH DRIVERS
GROWTH RESTRAINTS
INCREASING INTERNET PENETRATION
SECURITY CONCERNS
GROWTH IN ECOMMERCE
RESTRICTIVE REGULATIONS
HIGHER ADOPTION, REDUCING PRICES OF SMARTPHONE DEVICES
INDUSTRY FRAGMENTATION
Daily ePayment Transaction (US$ Mn)
Daily ePayment Transaction (US$ Mn)
Figure 36: Correlation between Internet Penetration and Epayment Transactions in Indonesia
ePayment volume Internet penetration
7
Figure 37: Correlation between Ecommerce Sales and Epayment Transactions in Indonesia
Daily ePayment Transaction (US$ Mn)
1. INCREASING INTERNET PENETRATION With electronic payments, it is hard to conduct transactions without the Internet. Hence, the increasing level of Internet penetration globally presents a conducive environment to facilitate the growth of epayment systems. The number of people using the Internet is expected to rapidly escalate to 3.6 billion by 2018, representing about 48% of the global population.
2. GROWTH IN ECOMMERCE Ecommerce is projected to expand at a fast pace, especially from emerging markets. The Asia-Pacific ecommerce volume is estimated to hit US$524 billion in 2016 (with a CAGR of 17% from 2012 to 2016)7 as shown in the graph below. More ecommerce volume means higher usage of epayments regardless of the methods or gateways. In South East Asia, Indonesia is forecasted to be the biggest ecommerce market, while the most sophisticated market is Singapore.
Online Retail Sales (US$ Billion)
KEY DRIVERS
Online retail sales
ePayment volume
Source: Frost & Sullivan, Bank Indonesia, eMarketeer
Source: Deloitte 45
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3. HIGHER ADOPTION, REDUCING PRICES OF SMARTPHONE DEVICES Advanced features in smartphones allow users to execute easily electronic transactions (epayment) from their devices. Smartphones are also increasingly serving as retail credit card readers (Point of Sales) for SMB companies through products such as Square and mPOS Plus. The declining prices of smartphones heighten the affordability for most people. In fact, the penetration rate of smartphones rose to 24.6% of the global population8 in 2014 and is poised to become a key driver for mobile payments. Figure 38: Indicative Prices of Smartphones
THEN
NOW
Xiaomi
Elephone
iPhone
Doogee $75 $200
>$500
KEY RESTRAINTS 1. SECURITY CONCERNS Ecommerce offers the electronic payment industry immense opportunities and potentially new security risks and vulnerabilities. Information security, therefore, is a critical management and technical prerequisite for any efficient epayment transaction activities over the Internet.
The increase in online credit card theft, extensive media coverage of such incidents, and heightened awareness among consumers about the threats of performing transactions online offer significant resistance to epayment growth. For example, the shopping cart of Sourcebooks, an online bookstore, was compromised between April and June of 2014. Hackers were able to steal the names, addresses, credit card numbers, expiration dates, card security codes and email addresses of users. 2. RESTRICTIVE REGULATIONS Since epayment is a fast-evolving industry, governments have not been able to keep up with the rapid pace of innovation in the industry. For example, in Indonesia, mobile wallet companies have had to face several licencing issues. Customers were even required by law to keep a minimum balance in their emoney accounts. These issues pose serious hurdles in the adoption of epayment in the country, although Indonesia’s central bank has been trying to relax the rules in recent years. 3. INDUSTRY FRAGMENTATION For any payment platform to become valuable, a sizable number of merchants and consumers should agree to use the same platform. As an example, PayPal is extremely popular with merchants because of the high number of consumers with a PayPal account. At the same time, it is popular among consumers since many ecommerce websites accept payments via PayPal. However, if too many people try to push their own epayment platform, none will have a critical mass of merchants or consumers. This is happening with the advent of near field communication (NFC)enabled payments (a technology allowing two devices placed near each other to exchange data), with Apple, Google, and credit card companies like Visa and MasterCard promoting their own platforms. In the end, none of the companies have been able to acquire enough merchants or consumers, hampering the growth of the industry.
VALUE CHAIN AND BUSINESS MODELS VALUE CHAIN Epayment refers to payments made online on an
Source: eMarketeer, United Nations, Frost & Sullivan
8
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ecommerce website. An offline payment made using a mobile phone is defined as mpayment, and increasingly treated as a subset of the epayment
universe. The value chains in the two cases are described below:
Figure 39: Online Epayment Value Chain
CUSTOMER
ONLINE/ MOBILE WALLET
ECOMMERCE WEBSITE
PAYMENT GATEWAY
ONLINE EPAYMENT VALUE CHAIN CUSTOMER The customer makes the payment on an ecommerce website. ONLINE WALLET Sometimes the consumer may use an online or mobile wallet to make payment on the website to avoid the hassle of filling out credit card details. PayPal, Lemon Wallet and Google Wallet are examples of online wallet services. Consumers can use these wallets independently, or link them to their bank account and credit card to avoid the risk of account balance running out. When used independently, it disrupts the traditional credit card value chain since it directly transfers money from the buyer’s account to the merchant’s without utilising the credit card network. ECOMMERCE WEBSITE A website that collects payment from customers in return for purchases, or in some cases, on behalf of a third-party.
MERCHANT ACQUIRER
PAYMENT NETWORK
data transmission, and data security of the credit card payment. MERCHANT ACQUIRER The bank that agrees to collect payment from the merchant (ecommerce website, in this case). The merchant acquirer takes on the financial risk in accepting the merchant’s payment card transactions and pays the merchant an equivalent amount after deducting the processing fee. PAYMENT NETWORK The network allows for transactions between the acquiring bank and card issuing bank. Visa, MasterCard and NETS are major payment networks. In cases when a consumer pays through PayPal account without linking to a credit card, PayPal may also serve as a payment network. ISSUING BANK The bank that issues the credit card or debit card to the consumer. It is the bank that pays for the transactions and payments made are ultimately reflected in the credit card account of the customer.
PAYMENT GATEWAY An application that allows the website authorisation, 47
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Figure 40: Offline Epayment Value Chain
CUSTOMER
MOBILE APPLICATION
OFFLINE MERCHANT
POS SOLUTION
MPAYMENT VALUE CHAIN CUSTOMER The customer makes payment to a physical merchant by swiping or tapping the card at a POS terminal. MOBILE APPLICATIONS Encompasses NFC-enabled and other mobile applications that facilitate transactions. The consumer may be using a conventional credit card or mobile phone to make payment. An NFC-based app allows the customer to pay by just tapping on the payment terminal while other apps require online verification. This distinction is explained in greater detail in the business model section. The apps may or may not be linked to a credit card.
MERCHANT ACQUIRER
PAYMENT NETWORK
POS SOLUTIONS These players provide Point of Sale (POS) terminals to merchants to accept payments from a mobile phone or credit card. The solutions may be smartphonebased as in the case of mPOS Plus and Square POS or swiping/contact-based like First Data. When the consumer exclusively uses a mobile application, or the merchant uses a smartphonebased POS (mPOS), the transaction falls under the definition of mobile payment, which is treated as a subset of epayment in this paper. The remaining three players (acquirer bank, payment network and issuer) have identical functions as in the case of online epayments.
Sometimes funds transfer or payments can be made via SMS, without the use of a mobile application. Such transfers are popular in countries like Kenya and the Philippines and examined in detail later in this section. Again, such mobile cash transfers may or may not be linked to a credit card. OFFLINE MERCHANTS These are physical merchants accepting payments.
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BUSINESS MODELS
execution of online payments as well as money transfers.
The idea behind epayments is simple; it involves payments made electronically. However, models may vary depending on the functions, device or purpose they serve. For this paper, we focus exclusively on the most popular product categories and their models. This includes payment gateway, mobile or online wallets, mobile cash, NFC-based payments, and smartphone-based credit card transactions. 1. PAYMENT GATEWAY A payment gateway allows you to make payment through a website or mobile app using a credit card or debit card. Traditionally, such gateways were only used by ecommerce websites. However, these days payments ranging from utility bills, school fees, to mobile bills can be settled via online gateways. Examples include eNETS, PayDollar, and GTPay. Basis of Value Creation: Enabling secure credit card and debit card transactions online. Charging Model: Merchants are charged a set-up fee, annual fees and transaction fee (minor fee per transaction and a percentage of payment value). The bulk of the fees charged as a percentage of payment value is passed onto the merchant acquirer, payment network, and issuer. 2. ONLINE OR MOBILE WALLET An online wallet is like an online account where you can transfer money and keep a balance. The balance can then be used to pay for online purchases or transfer funds to online accounts of other users. You can even store the details of your physical credit cards and use them to pay through your online wallet. Modern wallets also allow storing of debit cards and reward cards among others. The advantage is that the user need not fill out the details of these cards each time a payment is made. Examples include PayPal, Google Wallet, Lemon Wallet, and Paytm. Online wallet companies now have a mobile version, making it simpler to make payments and purchases through mobile app stores. These are referred to as mobile wallets. Basis of Value Creation: Convenient and secure 49
Charging Model: Transactional-based model (generally charged to the merchant; buyer is charged when a credit card is used). 3. MOBILE CASH Mobile cash is similar to the concept of a mobile wallet, but comes with a crucial difference – there is no credit card or debit card linked to a mobile cash account. This disrupts the traditional credit card value chain since the transaction occurs directly between the consumer’s mobile cash account and the merchant’s account. There are two variations to mobile cash: (i) SMS-based mobile cash: The account is linked to a mobile number where money can be transferred to other mobile cash accounts only. The model is popular in emerging markets with low mobile broadband penetration. Examples include T-Cash in Indonesia, M-PESA in Kenya, and Smart Money in the Philippines. (ii) App-based mobile cash: Payment is made using an app to other app users or business. Examples include Dash Pay and DBS PayLah! in Singapore. Basis of Value Creation: Convenient and secure transfers via mobile without credit cards or debit cards. Charging Model: Transactional-based models. Some services like DBS PayLah! are free. 4. NFC-BASED PAYMENTS NFC technology allows two devices placed within a few centimetres of each other to exchange data. For this to work, both devices must be equipped with an NFC chip. After launching the application on your phone, the phone is tapped on the credit card terminal to make payment. At this point, you may be asked to scan your finger or enter a passcode to approve the transaction. The transaction is then validated with a separate chip called the secure element (SE), which relays the authorisation back to the NFC modem. The payment
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completes processing similar to a traditional credit card swipe transaction. The NFC-based payment app can be linked to your mobile wallet. Examples include Apple Pay, Android Pay, Samsung Pay, Visa Paywave, and MasterCard PayPass. Basis of Value Creation: Faster payment in a secure manner.
using a smartphone or tablet and is especially beneficial for small-scale merchants that are unable to afford expensive POS solutions with high set-up and annual fees to accept credit card payments. This mode also keeps track of payments, inventory, realtime data, and invoices for the merchant. Examples include Square POS, mPOS Plus, and ROAMpay.
Charging model: Transactional-based model.
Basis of Value Creation: Lower cost of operation for merchants, and ease of payment.
5. SMARTPHONE-BASED CARD TRANSACTION The technology allows credit cards to be swiped
Charging Model: Device cost plus transactionalbased model.
VALUE DRIVERS & KEY RISKS Figure 41: Value Drivers & Key Risks for Epayment Companies
KEY VALUE DRIVERS • Scale • Funding • Customer Growth • Ease & Security
KEY RISKS • Validation of Technology Benefits • Failure to Scale Up • New Competition & Business Model
Frost & Sullivan
KEY VALUE DRIVERS 1. SCALE Any payment platform requires a critical mass of merchants and users. If there are not enough merchants accepting payments from the platform, users will not find it useful. Likewise, an insufficient number of users may not encourage merchants to invest in the platform. The number of merchants and consumers using a particular payment platform is a good predictor of how successful it will be in the future. This why the epayment industry is dominated by leading companies like PayPal since smaller players may find it difficult to survive beyond a point. 2. FUNDING Since scale is critical, epayment companies must heavily invest in initiatives to attract merchants 50
and consumers. Large investments are required to subsidise payment terminals at merchants, provide them with better transaction fees compared to competitors, and publicise features among consumers, such as cash back promotions. The amount of funding is important for the long-term prospects of an epayment company. For example, eBay paid US$800 million for Braintree, a global payment platform that facilitates mobile and ecommerce payments. Square POS received US$590 million after 9 rounds of investments. Card payment giant, Visa, invested in epayment solutions company Stripe, with total funding to date amounting to about US$200 million. 3. CUSTOMER GROWTH Customer growth indicates the attractiveness of a
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platform. A company with higher customer growth rate will have a better chance of achieving greater scale than its competitors and steady state revenue in the future. 4. EASE AND SECURITY These are key value drivers for epayment companies. Providers that can simplify payment and make it more secure will gain higher adoption by both merchants and customers, leading to a winning position among other providers. PayPal is a major success due to its payment ease and customer protection policy; Alipay from Alibaba adopts similar features and is poised for early success in China.
KEY RISKS 1. VALIDATION OF TECHNOLOGY BENEFITS RISK ASSESSMENT: HIGH (FOR EARLY STAGE COMPANIES) Epayment is a fast evolving field with promising technologies. However, not all make payments faster, more convenient or secure. For example, non-SMS based mobile cash platforms like Dash are struggling to grow since it does not simplify payments compared to credit cards. NFC-based mobile payment technology has been touted as the next big thing for several years with many pilot projects being executed by banks and telco operators. However, the pilot projects reaped limited success until recently because it was difficult to facilitate fast payment while ensuring security. A combination of convenience and security have been made possible only recently with solutions like Apple Pay.
2. FAILURE TO SCALE UP RISK ASSESSMENT: HIGH (FOR EARLY AND GROWTH STAGE COMPANIES) Since scale is of utmost importance in the epayment business, failure to scale up is the biggest risk in the business. Epayment companies may fail to scale up when they are not able to acquire enough merchants and consumers on their platform. This can happen due to inferior technology, ineffective marketing strategies or lack of funding. Companies that do not have sufficient funds to spend on merchant and consumer acquisitions are likely to lose the battle to better-funded companies. Investors interested in pouring funds into an epayment company should consider the company’s ability to raise successful funding, as well as its ability to attract enough merchants and users in the future. 3. NEW COMPETITION OR BUSINESS MODELS RISK ASSESSMENT: LOW There is always a possibility of larger global participants entering a regional market, driving out regional enterprises, or a newer, more efficient technology replacing an older one. However, once a payment platform gathers enough merchants and consumers, it is difficult to displace it. Hence, epayment companies like PayPal continue to maintain its popularity for the past 15 years. So apart from being daunting to set up and expand an epayment business, there are significant barriers to entry for new companies to challenge an already scaled up payment platform.
RELEVANT VALUATION METRICS Similar to ecommerce companies, epayment companies also need to obtain sufficient cash funding initially to spend on operations and infrastructure, and achieve the rewards later. As a result, epayment companies can be evaluated with various metrics at different stages. 1. EARLY STAGE
The key focus in this stage is attracting enough number of merchants and consumers and making them transact on the platform. This is also a stage where the company needs to prove that its technology indeed makes payment smoother and secure. The key valuation multiples include the number of merchants, number of users and monthly transaction volume (total dollar value of transactions on the platform) and growth.
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2. GROWTH STAGE
In the growth stage, revenue becomes important in addition to the transaction volume. Hence, the revenue and revenue growth, as well as transaction and transaction growth, become key parameters for valuation.
3. LATER STAGE
During this stage, the company’s main focus is to maximise profits and cash flow while keeping growth stable. The metrics we use for evaluation are revenue and revenue growth, EBITDA margins and profit margins.
Table 7: Valuation Metrics for Epayment Companies in Various Stages S. NO.
EARLY STAGE
GROWTH STAGE
LATE STAGE
1.
Merchants & merchant growth
Merchant & merchant growth
Revenue & revenue growth
2.
Users & user growth
Users & user growth
EBITDA Margin
3.
Transaction volume & growth
Transaction volume & growth
Profit Margin
4.
-
Revenue & revenue growth
-
OVERALL FOCUS
CUSTOMER TRACTION
INCREASE GROWTH & CUSTOMER TRACTION
TOPLINE & BOTTOMLINE GROWTH
EARLY STAGE: Usually first 1 to 2 years of operations. GROWTH STAGE: Approximately 2 to 5 years of operations. LATE STAGE: More than 5 years of operations
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CROWDFUNDING
Crowdfunding refers to the use of online platforms by project initiators to access a network of prospective funders/investors beyond the traditional circle of owners, friends and relatives, business angels and venture capitalists (VCs) to fund a campaign project or venture. It is an important source of financing for projects or ventures by start-up or early stage companies that would otherwise not get the necessary funds or access to lending. The primary reasons why campaigns turn to crowdfunding include little room for negotiations with banks on interest rates despite having a lucrative product, inflexible terms from banks, lack of track record/securities with banks, and the risks associated with their business. These factors limit them to a small pool of VCs that require high returns, and as such, are highly selective in who they fund. Globally, the crowdfunding industry raised US$16.2 billion (SGD22.6 billion based on exchange rate of USD/SGD = 1.398 on November 5, 20159) in funding volume in 2014. This is expected to grow to US$34.4 billion by the end of 201510 and up to US$96 billion by 202511. It is estimated that US$87,000 is raised on an hourly basis12. Based on 2014 statistics, North America continues to lead in the crowdfunding market at 58% contribution to the global funding volume with Asia recording exponential growth in funding volume. While the trend looks set to continue, Europe’s contribution is expected to decrease in 2015 from 20.1% to 18.8%10 due to its fragmented regulatory and Intellectual Property Rights (IPRs) regimes.
Reward- Equitybased based 10% 7%
Lending/Debt based 68%
Donation- Royaltybased based 10% 2% Hybrid-based 3% Source: 2015 Massolution Global Industry Report, Frost & Sullivan Analysis
To date, there are over 1,250+ crowdfunding sites listed on the Internet. The number continues to grow yearly as acceptance of the concept increases amongst traditional funding markets. Key subcategories are listed in Figure 43 below. Moving forward, the focus is expected to be on campaigns that involve investments (equity or revenue/profit sharing), localisation (limited locality), mobile solutions and group-based approaches.
Figure 42: Split of Funding Volume Raised through Crowdfunding by Geography and Type North America 58%
Europe 20%
Asia 21%
South America, Oceania & Africa 1% 9
Oanda.com Source: 2015 Massolution Global Industry Report. March 2015
10
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11 12
Source: Info Dev, World Bank. October 2013 Source: Entrepreneur, Entrepreneur Media Inc. October 2014
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Figure 43: Examples of Crowdfunding Sites
DEBT-BASED (Contributors receive interest payments in exchange for contributions)
EQUITY-BASED (Contributors receive shares in exchange for contributions)
REWARDSBASED (Contributors receive goods/ services in exchange for contributions)
DONATIONBASED (Contributions are tax deductible depending on nature of campaign)
HYBRID
Source: Frost & Sullivan
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Of all categories, equity crowdfunding is typically subject to stringent regulations. New regulations have been adopted in a handful of countries including the United States (US), Canada, United Kingdom (UK), Italy, France, Germany, Spain, New Zealand and Australia. However, the lack of regulation has not precluded the emergence of equity crowdfunding in a market. Despite equity crowdfunding being a global activity, legislation is different in most countries with varied regulations and guidelines on investment limits, the exercise of shareholder voting rights, threshold for prospectus requirements, rules on transparency, investment suitability tests, client money protection, investment advice as well as tax treatment for crowdfunding based on their readiness to embrace crowdfunding. This has implications on cross-border crowdfunding and may lead prospective investors to focus on unregulated jurisdictions.
In the US, Title III of the JOBS Act 201213 is anticipated to legally open up equity crowdfunding in a big way to the unaccredited/unprofessional investor by putting in place appropriate safeguards to mitigate investment risks. The recent Regulation A+ that came into force in June 2015 takes a step towards this by targeting only later stage companies. Title III targets the much larger number of start-up or early stage companies (e.g., seed and Series A types) with lower regulatory compliance costs. Title III is projected to give the US a head start of more than 2 years should Singapore start limiting equity crowdfunding to accredited and institutional investors as proposed in the February 2015 consultation paper issued by the Monetary Authority of Singapore (MAS). The JOBS Act 2012 promotes crowdfunding as a complement to traditional funding while the MAS paper views crowdfunding as a substitute for seed funding.
KEY DRIVERS & RESTRAINTS Figure 44: Drivers & Restraints of Crowdfunding Industry Growth GROWTH DRIVERS
GROWTH RESTRAINTS
UNMET NEEDS WITHIN TRADITIONAL FUNDING SECTOR
FAILURE TO RAISE FUNDS
GROWTH IN COLLABORATION ON THE INTERNET
POOR INVESTOR REACH AND EXHAUSTION
GROWTH OF SOCIAL MEDIA
INVESTMENT RISK
CENTRALISED REACH TO AND INTERACTIVITY WITH FUNDERS/ INVESTORS
LACK OF REGULATORY FRAMEWORK
GROWTH OF CROWDFUNDING SUCCESS STORIES
JURISDICTION ISSUES
INEFFICIENT SECONDARY MARKETS
13
Source: Jumpstart Our Business Startups (JOBS) Act of 2012, Title III-Crowdfunding. Scheduled implementation in October 2015. 55
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KEY DRIVERS
due to access to a much wider network.
1. UNMET NEEDS IN THE TRADITIONAL FUNDING SECTOR Banks and major investors are increasingly facing challenges in meeting society’s funding needs. Community-based projects, as well as less favourable and risky segments, require alternative funding channels. Examples of these segments include start-up and early stage companies, social/nonprofit enterprises, innovative entrepreneurs as well as organisations in the arts and scientific research sectors. Crowdfunding, due to its ability to spread fund acquisition and its associated risks across a large number of investors, is the ideal solution for these segments.
3. GROWTH OF SOCIAL MEDIA Social media with its current global penetration of 30%15 and growing, offers the crowdfunding community a ready source of prospects among interest-based communities. Social media also has the influence to build trust between stakeholders and accelerate adoption of crowdfunding and innovation.
2. GROWTH IN COLLABORATION ON THE INTERNET With global Internet penetration now at 40%14, the potential to tap into connections and resources available worldwide is set for exponential growth. The Alibaba Group’s recent success in ecommerce, i.e., surpassing Amazon.com sales in 2012, and continuous high growth rate is a testament to this fact. Crowdfunding is a prime growth area in today’s collaborative economy. Unlike the traditional VC model with limited funds spread across highly selective projects, equity crowdfunding has the potential to scale depending on the model employed
4. CENTRALISED REACH TO AND INTERACTIVITY WITH FUNDERS/INVESTORS Crowdfunding platforms facilitate quick, instant access to and interactivity with thousands of accredited prospective investors globally. This supports growth in entrepreneurship as well as in the quality and viability of products developed through valuable feedback and access to skill sets of accredited prospective investors via public forums. Without these platforms, project initiators may not have the contacts or the time to interact oneon-one with each potential investor. For SMEs and other incorporated businesses, crowdfunding offers the option of funding without the hassle of a public listing. 5. GROWTH OF CROWDFUNDING SUCCESS STORIES Crowdfunding success stories build confidence among investors. Below are some examples:
Table 8: Crowdfunding Success Stories COUNTRY OF ORIGIN CAMPAIGN
US
US
ROLE OF CROWDFUNDING IN CAMPAIGN SUCCESS
Pebble Time
Scanadu Scout
FUNDING TARGET VERSUS ACHIEVED
Raised funds for a wristband that works with iPhone and Android apps to provide instant, easy notifications of important calls, emails or other app alerts via the display on the watch’s digital face.
Target US$500,000
1. Raised funds for a scanner that reads and sends vital signs to the user’s smartphone.
Target US$100,000
2. Sped up the FDA approval process.
PLATFORM (TYPE)
Kickstarter (Reward)
Achieved US$20,338,986
Indiegogo (Reward)
Achieved US$1,664,574
3. The exposure gained attracted US$14 million in VC funds post-campaign. 14
Source: www.wearesocial.net. Retrieved in August 2015 56
Source: www.internetlivestats.com/internet-users/. Retrieved in November 2015 Investing in Financial Technology & Consumer Digital Technology Companies 15
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COUNTRY OF ORIGIN CAMPAIGN
UK
ROLE OF CROWDFUNDING IN CAMPAIGN SUCCESS
Seedrs
Raised funds for “aggressive” expansion in exchange for combined equity share of 33% in the business.
FUNDING TARGET VERSUS ACHIEVED
Target £750,000
PLATFORM (TYPE)
Seedrs (Equity)
(Target reached within a few hours!)
Achieved £2,583,420 Singapore
Djenee
Taiwan
Appendectomy Project
Raised funds to build a digital concierge business in Singapore.
Raised funds to build a platform to increase transparency in politics by ranking legislators.
KEY RESTRAINTS 1. FAILURE TO RAISE FUNDS Having a brilliant entrepreneurial idea and being able to patent it may not translate into the necessary funds to develop it. Due to the lack of experience, project initiators often struggle to send the right signals to investors and to find the right price points for their products, giving the impression of incompetence. There have been several massive crowdfunding failures such as the campaign by Canonical Ltd on Indiegogo to raise US$32 million for the Ubuntu Edge smartphone and the Wikipedia Books Project campaign that had planned to print the entire English Wikipedia in book form. 2. POOR INVESTOR REACH AND EXHAUSTION The success of crowdfunding platforms depends significantly on their ability to reach accredited investors globally without having to disclose highlyguarded intellectual property (IP) information. Should platforms fail to achieve the right mix (of social networks, philanthropic organisations and large companies) or diverse platforms reach the same network of investors multiple times, its effectiveness is diminished. 3. INVESTMENT RISK As the concept is relatively new, there is a considerable need to educate the market on the pros 57
Achieved SG$500,000
Target $11,984,994 NT
FundedByMe
FlyingV (Reward)
(Approx US$400,000)
and cons of crowdfunding as well as what to look out for in a crowdfunded investment. In particular, new investors need to be aware of the risks of equity-based crowdfunded campaigns and carry out detailed due diligence prior to investing. The alternative is to concentrate on investor-led models on equity crowdfunding platforms such as Syndicate Room and AngelList, where the crowds invest with professionals. Not conducting the proper due diligence carries the risk of investment failure. 4. LACK OF REGULATORY FRAMEWORK As the crowdfunding concept is still new, many countries have yet to adopt formal regulations for the investment model. Without clear and succinct regulations in place, there is a high likelihood of scams and potential for abuse of funds. Also, there is a risk of investors facing losses if there is no proper segregation of customer monies in the event of platform closure or failure. The absence of a regulatory framework poses a substantial barrier to attracting prospective funders/investors and to the campaign’s success. 5. JURISDICTION ISSUES Due to the nature of crowdfunding platforms sourcing funds via the Internet, it is expected that in countries where crowdfunding is legal may face uphill challenges in controlling and regulating crowdfunding activities that happen outside their
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country. Case in point: the potential regulatory arbitrage in Europe where one member state may invest in another member state. While harmonisation may be the answer, this may take time. 6. INEFFICIENT SECONDARY MARKETS The availability of an established secondary market for debt- and equity-based crowdfunding is
somewhat limited. For example, FOLIOfn Investment that offers investors an exit strategy for a fee prior to loan/note maturity currently only operates in the US, Canada and Japan. Other countries have yet to be addressed. The absence of an efficient secondary market means that investors might have to sell at a significant discount to exit, potentially deterring prospective funders/investors.
VALUE CHAIN AND KEY BUSINESS MODELS Figure 45: Crowdfunding Value Chain
PROJECT INITIATORS
CROWDFUNDING PLATFORM
INVESTORS
FUNDING
VALUE CHAIN The value chain for crowdfunding is relatively simple and straightforward. Crowdfunding platform companies assist project initiators in leveraging the crowd by connecting project initiators and investors via an online crowdfunding platform. Once key stakeholders connect and the necessary dialogue or exchange of pertinent information (e.g., on product features/ functionalities and funding goals/objectives) has taken place, project initiators then secure funding from investors via the crowdfunding platform with the help of payment partners, e.g., FirstGiving, Stripe, WePay, Amazon and PayPal. While project initiators are usually external, crowdfunding platform companies may also use their own platform to secure funds to cover operations costs as well as for expansion, e.g., Seedrs (see Table 8).
BUSINESS MODELS The business model for crowdfunding platforms is based on 3 parameters. First, is the type of fundraising (debt-, equity-, reward-, or donation-based); second, involves restrictions based on funding targets (all-ornothing; keep what you raise, and others); and third, refers to the revenue model for the platform.
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1. TYPE OF PLATFORM In general, there are 4 types of crowdfunding platforms: I. Debt-based Fund Raising This platform focuses on personal financing and later stage businesses. In this case, the fund is raised as a debt, i.e., the project initiator pays interest on the funds raised, and the debt is usually secured by business assets. It is the only sub-category that carries outbidding via auctions and requires a business continuity plan due to its role in debt recovery. The interest paid by the project initiator to investors is determined after the required loan/note amount is accumulated based on the lowest bidders’ offered loan/note amount and corresponding interest rate. The loan/note agreement is between the project initiator and selected investors. Examples include Lending Club, Prosper and Kabbage in the US, and MoolahSense in Singapore. II. Equity-based Fund Raising Unlike debt-based crowdfunding, this sub-category concentrates on early stage and growth stage financing. As the name signifies, investors get equity in the project in return for funds invested. Project initiators decide on their valuation target and if “overfunding” is allowed. Each investor’s equity interest will be proportionate to the investment made in the project initiator’s business. Platform
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revenues can be earned either from project initiators or investors. Examples include AngelList, Seedrs and CircleUp, all based in the US. III. Reward-based Fund Raising In the reward-based funding platform, project initiators offer rewards, for instance, a fixed quantity of the product, to be shipped to the investor once the project goes live or discount on purchase from the project initiator. Typically reward-based platforms target a much larger set of investors compared to equity-based platforms. Examples include Kickstarter and RocketHub in the US and Ulule in France. IV. Donation-based Fund Raising As the name suggests, funding is strictly donationbased and generally for social projects. Examples include Patreon in the US, YouCaring in the US, and Friendfund in Germany. 2. RESTRICTION BASED ON FUNDING TARGET There can be 2 restriction categories if the project initiators do not meet their funding targets: I. All or Nothing In this model, the project initiator is allowed to collect funds only if the funding target is met. If the funding target is not achieved, there is a high probability the project will not be financially viable. Hence, investors may end up losing money. The All or Nothing restriction aims to protect investors from financial viability risk. While this model is most prevalent in equity-based crowdfunding, it also applies to debtand reward-based crowdfunding as well. II. Keep What You Raise Many reward- and donation-based platforms allow project initiators to collect whatever money they obtain irrespective of the funds raised. Higher fees may be charged on the Keep What you Raise campaigns that do not meet their funding goals.
The project initiator is usually charged a fee. However, some crowdfunding platform companies offer the option of charging investors related fees, e.g., on charity campaigns, making it free for the project initiators. II. Listing or Due Diligence Fees Many platforms charge a flat fee for listing. The fee is charged for due diligence of the company or idea. For example, the legal team at Bolstr reviews each campaign before it is launched to protect potential investors. The company charges a legal fee of US$500 to US$1,000. Similarly, SeedInvest, a US-based equity crowdfunding website charges between US$3,000 and US$5,000 for due diligence and legal expense reimbursements. Due diligence typically involves confirming the current revenue, customers, profitability, financing, market potential, and other financial and commercial parameters critical for valuation and prospects of the company. Several crowdfunding websites do not enable transactions between the investors and fundraisers. In such cases, they act merely as a listing website and the listing fee is their sole revenue source. Investors go through the listed ideas on the website, identify potential investment opportunities, contact the fundraisers independently and finance ventures of their choice. The listing fee for such platforms is typically a few hundred dollars. III. Fees for Ancillary Services Many platforms provide multiple ancillary services such as legal support, advice on campaign management, video creation services, and community organising software. Separate fees are charged for such services. IV. Servicing Fees Investors are charged servicing fees of between 0.5% and 1% of the total value of their investment. This is most popular in debt-based funding.
3. REVENUE MODEL Refers to the method project initiators are charged and how revenue is earned for the platforms. Typical revenue streams for crowdfunding platforms consist of the following:
V. Carry Fees The fee is charged to the investor on capital gains made by them upon successful exit. The fee is usually 5% to 7.5% of capital gains and is the primary model for several equity-based crowdfunding platforms.
I. Commission on Funds Collected Nearly all crowdfunding platforms charge a commission on the funds collected by the project initiator (called origination fee in debt-based platforms). The standard commission is between 2% and 5% of funds raised – a primary revenue model for all platforms.
Investors and project initiators may also incur payment processing, late payment, and early exit fees. Such costs are transparent for the platform.
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In addition to the fees charged to the project initiators and investors, crowdfunding platforms also have the following revenue sources:
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I. Investing in successfully funded businesses As part of the agreement to list campaigns on their platform, crowdfunding platform companies can reserve their right to invest in successfully funded businesses. As an example, Let’sVenture has the option to invest half of its 2% syndicate fee as equity in a start-up or early stage company. II. Investing in downstream markets Relationships with successfully funded businesses can be tapped to offer clients an initial marketplace for successful products. 4. LEVEL OF CURATION Crowdfunding websites range from completely open platforms to highly curated platforms. In an open platform, anybody can start a funding campaign. The disadvantage of an open platform is there is no guarantee on the quality of the project. Due to the inherent risks to investors, funding targets are usually lower for the open platform.
On the other hand, curated platforms vet the business model and perform due diligence on the company or idea before listing on their platform. The due diligence involves examining the current revenue, customers, profitability, financing, market potential, and other financial and commercial parameters critical for valuation and prospects of the company. Curated platforms such as Funding Club claim that less than 5% of ideas pitched to them are eventually listed on the platform. As a result, investors are assured of the quality of the idea and able to invest larger sums. Curated crowdfunding platforms earn revenue through carry fees, direct investment in the idea or success-based commissions rather than through listing fees or ancillary services. Curated platforms are popular for equity-based crowdfunding. Most platforms lie somewhere between completely open platforms and highly curated platforms.
Table 9: Revenue Models of Various Crowdfunding Platforms TYPE OF FUNDRAISING
TARGET-BASED RESTRICTIONS
REVENUE MODEL
Debt-based
1. All or Nothing 2. At least 70% of funds
• Origination Fee • Listing or Due Diligence Fee • Annual Servicing Fee • Early Exit Fee • Ancillary Services
Equity-based
All or Nothing
• Commission on funds collected • Listing Fee (Optional) • Carry Fee (For some curated platforms) • Ancillary Services
Rewards-based
• All or Nothing • Keep What you Raise
• Commission on funds collected • Listing Fee (Optional) • Ancillary Services
Donation-based
• All or Nothing • Keep What you Raise
• Commission on funds collected (by project initiator or by investors) • Ancillary Services
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VALUE DRIVERS & KEY RISKS Figure 46: Value Drivers & Key Risks for Crowdfunding Platform Companies
KEY VALUE DRIVERS • Scale • Funding Volume on Platform • Monetisation Model • Funding Success Rate
KEY VALUE DRIVERS The key value drivers of a crowdfunding platform company include the following: 1. SCALE As with most online businesses, achieving scale early on offers crowdfunding platform companies several benefits. Economies of scale, in this context, means the crowdfunding platform company has accessed a large enough network of investors able to offer the funds required by the range of project initiators they work with. The more project initiators and investors a crowdfunding platform company attracts to its platform, the higher the likelihood of campaign success resulting in higher funding volume. Higher funding volume enables crowdfunding platform companies to lower commission rates both to stay competitive and capture more project initiators. This becomes a virtuous cycle. Even for curated crowdfunding platforms, the relative scale compared to similar competitors is important.
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KEY RISKS • Competition Risk • Intellectual Property Rights (IPRs) • Platform Security Risk • Reputational Risk • Business Model Viability • Funding Environment
2. FUNDING VALUE OF EACH CAMPAIGN To be self-sustaining and cover individual cost structures, crowdfunding platform companies need to raise a minimum funding volume on their platforms. Apart from increasing the number of successfully funded campaigns, the size of the campaign is also a key driver of funding volume. A few prominent, high-value campaigns could raise the same amount in funding volume as a large number of small, lowvalue campaigns. 3. MONETISATION MODEL While there is a host of crowdfunding platforms available worldwide, not all end up making money. Revenue earned from commissions and other ancillary services is an indication of whether the platform is going to survive in the long-term. Platforms like FundersClub rely only on fees on capital gains (carry fee) that are inherently riskier. On the other hand, platforms with a higher number of investors and project initiators, as well as multiple revenue streams offer lower long-term risks.
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4. FUNDING SUCCESS RATE The funding success rate is a long-term value driver for crowdfunding websites. A low funding success rate, compared to other platforms with a similar model, may result in project initiators losing interest and shifting to competitors. Low success rate may also signify the absence of serious investors on the platform or issues with project discovery on the platform. In general, success rates vary based on the model and can be as low as 9.8% .
KEY RISKS The main risks for a crowdfunding platform company include: 1. COMPETITION RISK ASSESSMENT: HIGH When a crowdfunding platform is successful, competition begins to increase rapidly. With competition, commissions start to spread over a larger number of platforms and may decrease over time. It may become increasingly more difficult to raise the minimum funding volume required to be self-sustaining if a platform is not able to achieve economies of scale. Therefore, competition is a significant failure risk for early stage platforms. 2. INTELLECTUAL PROPERTY RIGHTS RISK ASSESSMENT: HIGH Intellectual property rights (IPRs) vary from country to country and is a major concern with cross-border crowdfunding. For example, Europe’s fragmented IPRs regime means that copyright management across the region would be a challenge since there is no single EU patent that provides project initiators Europe-wide protection. 3. PLATFORM SECURITY RISK ASSESSMENT: MODERATE Without the necessary network security measures in
place to protect the platform from security breaches, a company may put at risk its highly sensitive donation records, user information and passwords. While this may not be detrimental, it still represents a violation of the Personal Data Protection Act (PDPA). 4. REPUTATION RISK ASSESSMENT: MODERATE Without proper policies in place, a company may face reputational risk when its crowdfunding platform is used to raise funds that are not used for its intended purpose resulting in fraud/misrepresentation or involvement in illegal activities, e.g., production/ distribution of adult content. 5. BUSINESS MODEL VIABILITY RISK ASSESSMENT: HIGH (FOR EARLY STAGE) Crowdfunding websites have to either ensure a significant number of listings with easy search functionality to lure small investments or greater funding and high success rates through curation of ideas. If it is not able to achieve either, the long-term viability of the platform is uncertain. Thus, unless a platform has already built a large community with reasonable success rate, it potentially faces significant risks. 6. FUNDING ENVIRONMENT RISK ASSESSMENT: HIGH (FOR EQUITY-BASED PLATFORM) Equity-based platforms rely on investors being able to earn handsome profits on their investments when the company undertakes an IPO, or its stakes are sold to another investor or company. Ultimately, prospects for such liquidity events or subsequent stake sales are driven by the overall funding environment. This in turn, depends on the overall liquidity in the market and interest in the particular industry. If the funding environment deteriorates, it poses tremendous risks for equity investors and the business model of equitybased crowdfunding platforms.
RELEVANT VALUATION METRICS Crowdfunding platform companies have to invest heavily in building their platforms before being able to bring in project initiators. As this means investing large amounts of cash upfront and slowly building up the scale to recoup their initial investment, various metrics should be used at different stages. The following table shows the relevant metrics for a crowdfunding platform company at each stage of its development.
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1. EARLY STAGE
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In the early stages of growth, the focus should be on establishing credibility and trust with stakeholders on the crowdfunding platform. The company should adopt measures to build a secure platform and conduct due diligence on projects and project initiators. A key parameter to consider is whether momentum is building among project initiators and investors. The key valuation multiples include valuation/number of campaigns, valuation/ successful campaigns, and valuation/fund raised.
2. GROWTH STAGE
In the growth stage, the aim is to prove the revenue model and to scale up as rapidly as possible to pre-empt the competition. The key valuation multiples include valuation/funding value and valuation/revenue.
3. LATE STAGE
In the late stage, the aim is to maximise profitability and cash flow while maintaining growth. The key valuation multiples include valuation/revenue, valuation/EBITDA (EV/ EBITDA) and valuation/earnings (P/E ratio).
Table 10: Valuation Metrics for Crowdfunding Platforms in Various Stages S. NO.
EARLY STAGE
GROWTH STAGE
LATE STAGE
1.
Number of campaigns & growth
Revenue & revenue growth
Revenue & revenue growth
2
Number of successful campaigns & growth
Funding value & growth
Funding value & growth
3
Funding value & growth
Number of successful campaigns & growth
EBITDA margin
4
-
-
Profit Margin
OVERALL FOCUS
CUSTOMER TRACTION
TOPLINE GROWTH & CUSTOMER TRACTION
TOPLINE & BOTTOMLINE GROWTH
EARLY STAGE: Usually first 2-3 years of operations. GROWTH STAGE: 3-5 years of operations. LATE STAGE: More than 5 years of operations.
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10.
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BIG DATA AND PREDICTIVE ANALYTICS
Big Data has been attracting much interest and publicity over the past few years as companies and solution providers highlight the tremendous potential benefits of the technology. Many organisations believe that data is the new “oil” and will give them a competitive advantage over their competitors. However, it is still a poorly defined term and needs to be understood properly. Big Data is a phenomenon that describes the exponential growth of data, from every imaginable digital source, including machine data, social media data, pictures, audio and video collected by commercial and government organisations. Traditionally, much of these different data sources were not stored and analysed in a meaningful way due to the size, speed at which they were generated. What’s more, the data was not organised into fields to be stored in Relational Database Management System (RDBMS), the de-facto standard for databases in the past. The amount of data generated each day has surpassed the capturing and processing capabilities of traditional database management
tools and enterprise systems. Big Data refers to a new set of technologies that enable companies to store, manage and analyse large volumes of data being generated at a high velocity from varied sources in different formats. This capability is a game changer for multiple industries including the financial sector that extensively uses Big Data technologies for multiple use cases including fraud detection (primarily fraudulent credit card transactions), credit scoring and risk analysis of customers and identifying cross-selling and upselling opportunities based on past activities of their clients. The global Big Data market is experiencing exponential growth, expecting to reach US$78 billion by 2020, and grow at a CAGR of 18.7% for the period of 2014 to 2020. The initial growth of the market is being driven by the need to manage the cost of storage and adoption of new visualisation tools that simplify data integration and analysis, but will give way to a more advanced analytical need as organisations increasingly compete on information.
KEY DRIVERS & RESTRAINTS Figure 47: Drivers & Restraints of Big Data and Analytics Industry Growth GROWTH DRIVERS
GROWTH RESTRAINTS
NEED FOR REAL-TIME DATA-DRIVEN INSIGHTS
SHORTAGE OF TALENT
“CONSUMERISATION” OF SOLUTIONS
SIGNIFICANT INVESTMENT
GROWTH OF DATA FROM IOT, SOCIAL MEDIA AND CONNECTED INDUSTRIES
LEGACY INFRASTRUCTURE
AVAILABILITY AND AFFORDABILITY OF SOLUTIONS
BUSINESS & USE CASES
DIGITAL TRANSFORMATION AND NEW BUSINESS MODELS
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KEY DRIVERS 1. NEED FOR REAL-TIME DATA-DRIVEN INSIGHTS Organisations have long recognised the importance of information to help guide decision-making. In the early 80s and 90s, this was termed as executive support and decision support systems to guide decision-making by senior executives. Although the terminology and technology have evolved from online analytical processing to business intelligence to analytics to Big Data, the main objective of these systems have not changed dramatically, that is to support decision-making. The difference is the exponential growth of data, the speed at which data is being generated, and the variety of data formats that is challenging the ability of existing systems to provide insights on a timely basis. As organisations’ operations become increasingly complex and time-sensitive, it is critical that these systems support the need for timely insights to provide organisations with a competitive advantage and to optimise their operations. Big Data solutions provide a new paradigm for storing and computing data and enable organisations to extract near realtime insights from the large volume of data they are accumulating. For example Marketstudy, an insurance company in the UK, implemented a Hadoop and Spark solution, enabling them to analyse hundreds of millions of quotes a second compared to the 400 thousand quotes in seven hours previously. This has led to savings of US$7.5 million from the reduction of fraud and decreasing customer cancellation rates by 50%. 2. “CONSUMERISATION” OF SOLUTIONS As companies increasingly compete on information and recognise the value of Big Data, they strive to improve the efficiency of their internal analysis across the entire organisation and demand tools that enable their employees to study the growing volume of data being generated. Big Data solutions providers are meeting this demand by making analytics and Big Data more user-friendly and easily consumed for a wider audience beyond the data analyst and data scientist. For example, solutions providers like Tableau and Qlik have made analysis of data easy by simplifying data access and providing intuitive visualisations to enable data discovery and exploration. 65
3. GROWTH OF DATA FROM IOT, SOCIAL MEDIA AND CONNECTED INDUSTRIES By 2020, it is estimated that most individuals on the planet will have an average of 5 to 10 connected devices associated with them. This means that there will be between 50 to 80 billion connected devices generating data and information by 2020.
CONNECTED DEVICES By
2020 there will be around
80 BILLION CONNECTED devices and sensors That’s about
CONNECTED DEVICES
for every human on the planet
There are about
50-100 sensors in a car
2X The number of sensors in the car are expected to double and this information analysed in the cloud.
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The data is expected to exceed that of social media networking in the next two years. The Internet of Things phenomenon is expected to fuel the need for Big Data solutions as companies struggle to optimise the insights gleaned from collecting information from billions of low-cost sensors. 4. AVAILABILITY AND AFFORDABILITY OF SOLUTIONS One of the main drivers of Big Data technology is its ability to provide resilient and cost-effective compute and storage using commodity (off-theshelf) hardware, and open source driven software. Inspired by Google File System, the Hadoop and MapReduce framework enable organisations to store and compute data over multiple hardware as a potential alternative to the more costly Enterprise Data Warehouse currently used. This has enabled businesses to lower their cost of storage, accommodate more unstructured data, and in some cases, increase the amount of data storage by 100 to 150 times. 5. DIGITAL TRANSFORMATION AND NEW BUSINESS MODELS There is an increasing awareness to leverage data to not only optimise internal efficiencies and increase sales, but also to use it to create value in the form of new data products and business models. One example of leveraging information to create new business is Uber’s use of data to transform the taxi industry. Uber has more in common with a Big Data company than a taxi company. The company is highly valued not because of its fleets of taxis, but rather for how it uses the information to connect drivers and passengers, to automate and optimise the taxi industry. These companies recognise the potential of data to create innovative data products and new business models. The trend towards using data to create value is expected to grow with the IoT phenomenon, as organisations move from transactional product sales to having ongoing relationships with their clients by providing them with managed services.
KEY RESTRAINTS 1. SHORTAGE OF TALENT The acute shortage of experienced individuals who 16
have the necessary skill sets in Big Data and deep analytics is significantly impeding the adoption of Big Data effectively across industries. Even in the US, the largest market for Big Data and Analytics, it is estimated that by 2018, there will be a shortage of 140,000 to 190,000 people with deep analytics skills and 1.5 million managers and analysts with the ability to leverage Big Data16. The resultant effect is the need for organisations to rely on Big Data Analytics solutions providers to provide technical and business consulting services to help them achieve their business objectives. Big Data Analytics solutions providers are rising to the challenge by adding easy-to-use analytics capabilities into their solutions, democratising Big Data and Analytics for a much wider audience. An excellent example is Microsoft’s Machine Learning that is providing easyto-consume data science capabilities over its Azure cloud platform. 2. SIGNIFICANT INVESTMENT Big Data Analytics is on the radar of many C-suites and identified as a strategic imperative by most companies. However, most Big Data Analytics deployments are not cheap, costing approximately hundreds of thousand dollars, and as much as a few million dollars. Due to the high cost of such implementations, organisations are justifiably cautious about their investments on Big Data Analytics and the need to align them with their overall business objectives and strategy. 3. LEGACY INFRASTRUCTURE Traditional database infrastructure was designed for efficiency; not volume, speed and the varied nature of Big Data. Databases were predominantly designed for data mining and reporting purposes for specific applications, resulting in a proliferation of databases and data stores. A big challenge in introducing Big Data is integrating legacy data sources and dealing with the data governance and architecture needs of the expanding use of existing data and new types of data. 4. BUSINESS AND USE CASES Many companies struggle with identifying appropriate business cases and use cases for deploying Big Data solutions. Although many Big Data deployments
Source McKinsey Global Institute: Big data (The next frontier for innovation, competition, and productivity) 66
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have been successful at integrating multiple sources of data, organisations strive to extract insights across functional silos. Currently, outside of the well-publicised successful use of Big Data to create new services and products by Facebook, LinkedIn, Amazon, Google and Uber, the most common utilisation of Big Data by many organisations has been to reduce the cost of storage. However, to realise the full potential of Big Data, use cases have to evolve from improving costs and internal efficiencies
to the creation of new services and business models from data.
KEY BUSINESS MODELS The business models of Big Data companies are varied, but can be broadly categorised based on the target customer segment, revenue model (way customers are charged), distribution channel, and types of goods and services being offered.
Figure 48: Dimensions of Big Data Business Models
TARGET SEGMENT
Is it targeted towards B2B, B2C or B2B2C?
REVENUE MODEL
How are buyers being charged for the products & services?
DISTRIBUTION CHANNEL
How is the solution being offered into the market?
TYPE OF GOODS & SERVICES OFFERED
What is being offered: product, software, data, knowledge, and services?
1. TARGET SEGMENT Defines the consumer of the Big Data services and products being offered. Target customers can be individuals, in the case of Business-to-Consumers (B2C), or business-to-business (B2B). An example of Big Data use in B2C includes Amazon’s recommendation engine to suggest relevant products buyers might be interested in, where the solution leverages their past transactions to create upsell and cross-sell opportunities. Big Data Analytics vendors and solutions providers contribute to the bulk of the B2B segment, with supply-side organisations offering their products and services directly or via channel partners to clients. These include companies such as IBM, Greenplum, Cloudera, SAP and SAS selling and deploying analytics hardware, software and services for clients or offering cloud infrastructure and analytics services like Microsoft. 67
2. REVENUE MODEL Refers to how consumers are charged. Key models include: Transaction model: In this model customers are charged based on the contractual delivery and deployment of hardware, software, and services. Licence model: Software pricing models based on Software-as-a-Service using subscription or usagebased deployment architecture. Solutions can be deployed on-premise or in the cloud. The most common factors used to determine pricing include: Volume: The volume of data to be analysed would determine pricing. Number of concurrent users: Could range from a few to tens of thousands of users. Processing capacity: The total capacity required to process a given volume of data. Complexity of query: The complexity of queries
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to be run on a data set also affects the processing capacity a company needs. The software term can be perpetual or annual depending on the vendor. For large analytical providers like SAS or IBM, the contract may be more complex based on the combination of purchased products. For example, Splunk offers perpetual or term licencing purchase options. Pricing is based on the amount of data being indexed, with discounts given for larger data volume. Alternatively, AlchemyAPI, recently acquired by IBM, charges based on the number of Application Programming Interface (API) events, which refers to the number of times an external software utilises the Big Data software capabilities. Freemium Model: Several Big Data Analytics start-ups adopt similar models as Internet-based start-ups by providing Freemium-like services where the solution is offered free up to a capacity or data volume being processed. For example BigML, a machine learning and data visualisation company, allows its software to be used for free up to a task size of less than 16MB. Several Big Data Analytics companies contribute to open source development and make their solutions open to the public while providing paid enterprise support and services. PredictionIO, an open source machine learning server, offers an enterprise edition that has additional advanced features for its enterprise clients while providing support, training and other consulting services. 3. DISTRIBUTION CHANNELS Big Data Analytics solutions providers offer a directselling model, and in many cases, have established networks of end users through indirect channels.
Technology/Application/OEM Partners: Big Data analytics solutions providers form partnerships with software solution providers based on the sophistication of the solution. For example, Alteryx partners with Cloudera and Hortonworks, the leading Hadoop distributors in the market, making its software more readily integrated with other Big Data solutions providers. Consulting Service Partners/System Integrators: Vendors establish partnerships with system integrators or service providers to complement their solutions with the services required by the customer. IBM has in-house consultants trained with the necessary skills required for initial set-up and training. Resellers: Certified to sell software through their own direct channels. These partnerships are usually commission based. 4. TYPES OF GOODS AND SERVICES OFFERED Big Data Analytics solutions providers offer a myriad products and services, including physical hardware, software, and services required to support the data storage, compute and analytics infrastructure. Wellestablished solutions providers include Cloudera, IBM, SAS, MapR, Couchbase, Teradata, Microsoft, Google, EMC and HP. Big Data Analytics solutions providers also offer data and insights as a service. These providers can be categorised based on the nature of the data on offer and the key activities performed on the data, as illustrated in the following diagram.
Figure 49: Channels for Big Data Sales Direct Sales
VARs
OEM Partners
System Integrators
Application Partners
Service Partners
Technology Partners
End User
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Figure 50: Types of Big Data Offerings
KEY ACTIVITY AGGREGATION
ANALYTICS
DATA GENERATION
DATA SOURCES DATA GENERATION AND ANALYSIS Companies in this category track & generate data and analyse this data. Companies are segregated by data generated from crowdsourcing, web analytics companies, connected devices.
TRACKED AND GENERATED
PRIVATE DATA
PUBLIC DATA
DATA AGGREGATION AS A SERVICE Companies collect & aggregate information from multiple internal sources for their customers.
ANALYTICS AS A SERVICE Companies provide analytics and insights based on data provided by the customers.
FREE DATA AGGREGATOR Companies collect & aggregate information from available sources, usually free, and provide data distribution/ dissemination.
FREE DATA KNOWLEDGE DISCOVERY Companies help analyse freely available data, which might be in a non-standard format.
MASH UP AND ANALYSIS Companies that aggregate data as well as track data by themselves and perform analytics on the combined data set.
Source: University of Cambridge
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VALUE DRIVERS & KEY RISKS Figure 51: Value Drivers & Key Risks for Big Data Companies
KEY VALUE DRIVERS • Data Availability & Access • Funding & Support • Talent • Potential Market • Embedded User Base and Interoperability
KEY VALUE DRIVERS The key value drivers of a Big Data company are as follows: 1. DATA AVAILABILITY AND ACCESS Access to public and private data, especially unique data sources, is a big value driver for companies that build their successes around data products. Datadriven insights and predictions tend to become more accurate with larger amounts of data. The economics of data is apparent with Amazon’s use of its vast personal catalogue browsing and purchasing history to make relevant recommendations or Google’s use of personal searches to provide highly targeted advertising. Similarly, companies like Next Big Sound, FarmLogs and Welovroi leverage private and public data to provide data/insights as a service. 2. FUNDING AND SUPPORT Big Data Analytics start-ups, like most Internet startup companies, need to operate in the initial phase. Several start-ups operate in stealth mode in their initial phase and rely heavily on funding to get the operations off the ground. It is advisable to look at initial backers of the start-ups and their track record in the relevant domains to understand how they could help these businesses grow in their targeted areas. 70
KEY RISKS • Viability of Business Model • Lack of Availability of Funds • Regulation and Governance • Technological & Market Obsolescence
3. TALENT There are many new start-ups appearing on the Big Data Analytics scene. While the large analytics companies like IBM, HP, Google, Facebook, EMC, Baidu and SAS have long history and experience in the relevant markets, and extensive capabilities to match, many new Big Data Analytics companies are relatively small, and hence, unproven. Many of these companies operate with few employees and deliver solutions with relatively low capital by leveraging the cloud. As deep Big Data Analytics talent is in short supply, it is vital to understand the expertise and experience of individuals that form the company and its technical team. This is one of the most critical value drivers for evaluating Big Data Analytics startup companies. In fact, many large Big Data Analytics companies have been going on a shopping spree, purchasing companies with an intention to acquire talents in the respective fields of expertise. For example, Google acquired DeepMind Technologies, a start-up based in London, with the intention of adding experts in deep learning rather than specific products to the company. 4. POTENTIAL MARKET A key value driver for Big Data Analytics firms is identifying the relevant potential addressable market for the solution. Big Data Analytics solutions are custom built for a variety of purposes, from business intelligence, human capital analytics, network
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performance analytics to social media analytics, and reducing the cost of data storage. Understanding the potential market requires the current segments and geographies the company plays, in how they might grow in future, and which other segments and geographies may find use of the company’s solutions. For example, companies like Tableau operates in the data discovery and analytics segment. Currently, it has around 35,000 customers in the form of large and medium-sized organisations in the world. However, its products can potentially be adopted by a number of small companies, individuals, research scientists, and students in future. 5. EMBEDDED USER BASE AND INTEROPERABILITY Other key value drivers are the size of the solution provider’s embedded base of users and interoperability of its solutions into existing systems. The number of active users and licences are important to sustain the development of features and asset utilisation for solutions providers offering pay-asyou-use services. Similarly, interoperability is essential as organisations invest significantly in their existing information infrastructure and require Big Data Analytics vendors to support integration for new solutions into existing systems. The current interest in visualisation tools such as Tableau and Qlik are due to their increasing support for data integration into existing systems, making it easier for solutions to be deployed and consumed.
KEY RISKS The key risks for Big Data Analytics companies include the following: 1. VIABILITY OF BUSINESS MODEL RISK ASSESSMENT: HIGH (FOR EARLY STAGE COMPANIES) While many large Big Data Analytics vendors have revenue models based on product, professional and consulting services, and software licence sale, many early stage Data/Insight-as-a-Service companies do not have a clear revenue model nor proven revenue models. Many of these companies are advertisementand referral-based or B2B2C making it difficult to evaluate the revenues and profitability of the service. For example, OpTier, a major Big Data Analytics company raised more than US$100 million in funding 71
and still closed its doors in 2014 since it was unable to get enough customers for its SaaS model to recoup its large investments. 2. LACK OF AVAILABILITY OF FUNDS RISK ASSESSMENT: MODERATE (FOR EARLY & GROWTH STAGE COMPANIES) Like most other Internet start-up companies, Big Data Analytics enterprises need a moderate amount of cash in the initial and growth stages to stay competitive. This is necessary to fund the development of technology, keep the company operating while it acquires a sustainable user base, and retain the necessary talents before it sees a reliable cash flow or is acquired by others. The current cash reserves, operating costs, possibility of raising subsequent funding and experience, and investor capabilities are some of the main parameters to evaluate. 3. REGULATION AND GOVERNANCE RISK ASSESSMENT: HIGH Data-as-a-service and other business models leveraging the use of personal data are highly affected by the diverse data laws and regulations in different countries. Personal data regulations, for the most part, have not caught up with the speed of innovation in the use of information. As there is increasing interest in privacy and the rules governing the use of personal data, there is significant risk associated with how different countries would implement personal data use guidelines and rules. The EU has agreed to implement new European data protection laws that potentially pose serious implications for companies such as Facebook and Google. 4. TECHNOLOGICAL AND MARKET OBSOLESCENCE RISK ASSESSMENT: HIGH The Big Data Analytics landscape is one of the most vibrant, rapidly evolving technologies with many new companies appearing. Agile new companies are continuously innovating, bringing advanced technologies and new ways of doing business. For example, Tableau’s visualisation tool is changing the expectations of business intelligence and analytics tools, leading BI vendors to evolve and enhance their existing portfolio or risk losing market share. Similarly, mature Big Data Analytics companies continue to incorporate changes in the landscape, for instance, Microsoft working with Hortonworks to introduce Hadoop to Azure, and more recently, Spark.
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RELEVANT VALUATION METRICS Valuation metrics for Big Data Analytics companies remain varied depending on the nature of their Big Data Analytics solution. The following table shows the relevant metrics for Big Data Analytics companies in different stages. 1. EARLY STAGE
The primary focus in this stage is scaling up by getting more users to try the solution and estimating the potential addressable market. The key valuation includes the number of software downloads and active users, as well as the potential addressable market and growth of the market. For example, although the analytics application segment contributes to only 12.2% of the US$32.12 billion Big Data Analytics market, it is growing at a much higher CAGR of 28.1% compared to 18.7% for the general Big Data Analytics Market growth.
2. GROWTH STAGE
In the growth stage, the primary aim is to establish a sustainable revenue model and to scale up rapidly. The valuation metrics revolve around the usage of the solution and software captured by measuring the number of licences and the consumption/ utilisation of solution. Valuation multiples include the number of licences, revenue and revenue growth, and consumption/utilisation of solution.
3. LATE STAGE
In late stage ecommerce companies, the aim is to maximise the profitability and cash flow while maintaining growth. The key metrics are revenue and revenue growth, EBITDA margins and cash flow.
Table 11: Valuation Metrics for Big Data Companies in Various Stages S. NO.
EARLY STAGE
GROWTH STAGE
LATE STAGE
1.
Number of downloads & growth
Revenue & revenue growth
Revenue & revenue growth
2.
Active users & growth
Number of licences & growth
EBITDA Margin
OVERALL FOCUS
CUSTOMER TRACTION
TOPLINE GROWTH & CUSTOMER TRACTION
TOPLINE & BOTTOMLINE GROWTH, CASH FLOW
EARLY STAGE: Usually first 2 to 3 years of operations. GROWTH STAGE: Approximately 3 to 5 years of operations. LATE STAGE: More than 5 years of operations.
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11.
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CYBER SECURITY
Cyber security is the sum total of technologies, methods, procedures and practices employed in cyberspace to protect systems, networks, programs and data from unauthorised access, attacks, damage and other malicious intrusions. Cyber security is a critical requirement for institutions today. For financial organisations, however, cyber security is vital to survival as it determines how they evolve without compromising brand reputation, customer loyalty, and existence. Cyber security is extensively accepted as a challenge for governments and businesses alike. Once considered the realm of IT departments and security professionals, companies now recognise that a wider response is required. Cyber risks are business risks and must be dealt within an overall information and risk management framework. Cyber security is poised to gain prominence as more devices, the Internet of Things, become connected to the Internet. The importance of cyber security is also evident from the large-scale breaches in the past, with 2014 being the year of cyber security breaches. The trend in frequency, magnitude and complexity continue to escalate with time.
The financial services sector is the mainstay of today’s globalised monetary and economic setting. Large financial transactions and broad industry scope have resulted in the financial services sector becoming a prime target for cyber crimes – such as financial fraud, identity theft, unauthorised access, or loss of data and denial of service attacks. There are three times as many security incidents among banks, credit unions and insurance companies than any other sector. For example, computer systems were hacked at JP Morgan Chase & Co where the names, addresses, phone numbers and email addresses of approximately 76 million households and 7 million small businesses were compromised. The company only became aware of the cyber attack in August 2014. As a result of the growing security threats and awareness, the banking and finance industry is continuously increasing its spending on security products. The overall market is forecasted to rise from US$16.3 billion in 2015 to US$36.9 billion by 2024.
Figure 52: Notable Security Breaches in Past Years 152
Adobe, 2013
145
eBay, 2014
130
Heartland, 2013 56
Home Depot, 2014 JP Morgan Chase, 2014
76
Sony PSN, 2011
77 110
Target, 2013 50
Evernote, 2013
37
Ashley Madison, 2015
No. of Compromised Records, Millions Source: Business Insider 73
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Figure 53: Banking & Finance Security Market Forecast Total Banking and Finance Security Technology Market Revenue Forecast, Global 2015-2024 Revenue CAGR 9.5%
2015 16.27
SECURITY ESSENTIALS FOR FINTECH SECTOR From a fintech perspective, the essential cyber security technologies are cloud security, POS encryption, mobile security, advanced endpoint (mobiles, PCs, laptops) protection, web application firewalls, anti-DDoS (software to protect websites against distributed denial of service attacks, the most common cyber attack crippling websites) solutions, and integrated security appliances.
PRODUCTS AND SERVICES
2016 17.53
Since financial companies have to focus on multiple aspects of cyber security, there are a variety of products and services available in the cyber security domain.
2017 18.94
CLOUD SECURITY A rising trend in the fintech sector is the use of the cloud platform to host applications. There are specialised software available to secure the cloud platform to protect the applications hosted on it. Cloud security refers to an exhaustive set of technologies and controls installed to protect data and applications associated with the cloud infrastructure.
2018 20.62 2019 22.53 2020 24.74 2021 27.15 2022 29.93 2023 33.15 2024 36.88 Source: Frost & Sullivan
Revenue
Cloud technology or “shared” computing services enable organisations or individuals to store and access data and programs over the Internet. Despite their advantages, cloud platforms present unique cyber risks. These include compromising an organisation’s control over its data and systems; especially so with a third-party provider or one that operates offshore. This becomes hypercritical for fintech enterprises. With the banking and finance industry extensively adopting cloud application services such as migrating their Customer Relationship Management (CRM) resources to public cloud applications such as Salesforce.com, the need for cloud security is more important than ever. Most services in the cloud security market are achieving robust growth, primarily because of the flexible capacity, cost efficacy and technical competence of cloud security providers.
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Figure 54: Key Security Products Used by Financial Organisations
ANTI DDOS CLOUD SECURITY
Website (ecommerce/ corporate)
Cloud Infrastructure
Financial Organisation Office
POS ENCRYPTION
WEB APPLICATION FIREWALL
INTEGRATED SECURITY APPLIANCES
ADVANCED ENDPOINT SECURITY AND FORENSICS
Retail Transactions
Office Worker/ Remote MOBILE Worker/ATM SECURITY
(enabled by the financial organisation)
POS ENCRYPTION Point of Sale (POS) describes the technology used by consumers to provide their payment information in exchange for goods or services. The most familiar example of a POS system is the check-out counter at a retail or grocery store.
aimed at gaining access without being detected to steal vital high-value data rather than causing damage) and Zero-Day attacks (exploit previously unknown vulnerabilities in computer applications) and enables protection of endpoints by blocking attacks before any malware is initiated.
A virus infecting the POS can compromise data stored in the system. Therefore, the best defense to a POS breach lies in effective encryption of critical customer data and efficient authentication techniques to ensure any data transfer with the system is completely secure.
There is a growing need for AESF judging from the increasing number of vulnerabilities and readily available exploit kits, programming tools that allow someone who does not have experience writing software code to create, customise and distribute malware. AESF is most practical to protect the weakest areas of endpoint security in fintech, which can be found in legacy systems such as Automated Teller Machine (ATM) systems that are still running on Windows XP.
ADVANCED ENDPOINT SECURITY AND FORENSICS (AESF) Advanced Endpoint Protection is a solution that prevents Advanced Persistent Threats (cyber-attacks 75
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MOBILE SECURITY As organisations and their employees become increasingly dependent on mobile devices, they need to allow these devices to access critical business information, requiring a certain level of security for these devices to be implemented. The trend of BYOD (Bring Your Own Device) is fast gaining popularity with employees using their personal laptops, tablets and smartphones for company-related work. There are grave concerns about how these devices that do not belong to the company can access critical data on the corporate network. Serious insider threats could occur, such as when an employee exits a company, with critical data stored in these devices, without having to turn them in before leaving. External hackers could also exploit the vulnerabilities in a mobile application when it connects directly to the corporate network. It is essential for organisations to look into managing their data securely with field devices, such as Mobile Device Management tools, with powerful authentication and secure built-in tunnel to access confidential corporate information. In case an employee leaves the company, there are remote wipe capabilities to erase the application and critical data from the mobile devices. Mobile payment security is also a rapidly growing area. Consumers now store their credit card and mobile wallet information on their smartphones, and pay via their mobiles using NFC technology such as Apple Pay. The security of this information is a huge concern for merchants, issuers, payment networks and new wallet providers. Given the positive growth projections for mobile payments, mobile payment data security is projected to be one of the fastestgrowing fields in cyber security. WEB APPLICATION FIREWALLS The Web Application Firewall (WAF) is a software or hardware solution plug-in, filter or appliance that protects web applications by subjecting network conversations to a set of protocols that enables it to monitor, control, and analyse network traffic on the application layer. More importantly, the ability to customise rules to specific applications also allows the WAF to enhance protection and guard against increasingly targeted attacks. 76
WAF is considered crucial for securing ecommerce transactions and to meet compliance standards such as the Payment Card Industry Data Security Standard (PCI-DSS). The PCI Standard is mandated by card brands and administered by the Payment Card Industry Security Standards Council They also perform the role of protecting websites from defacements to save companies from reputation loss. Frost & Sullivan expects the global WAF market to expand from US$494.1 million in 2014 to US$777.3 million by 2018, growing at a CAGR of 12%. ANTI-DDOS SOLUTIONS To maintain the availability of websites and allow consumers to perform online transactions, it is essential for retailers and banks to have the right detection and mitigation technologies against Distributed Denial of Service (DDoS) attacks. These attacks are usually volumetric in nature, targeting a website with several attempts of requests that could interrupt or suspend services. The Anti-DDoS market is one of the fastest-growing industries due to the escalating DDoS attacks in recent years. As per Frost & Sullivan, the global DDoS market is estimated to reach US$929.5 million by 2018 from US$418 million in 2014 with a CAGR of 22.1%. INTEGRATED SECURITY APPLIANCES The network firewall is considered to be one of the most widely adopted security tools in the industry. It basically filters the traffic permitted in the trusted network of the organisation. However, it is not sufficient to prevent injection attacks by hackers, requiring additional features, such as Intrusion Prevention Systems (IPS), Application Control, and Gateway Anti-Virus. The Integrated Security Appliance approach benefits enterprises by offering lower total cost of ownership, and a multilayered security approach at the perimeter. Integrated Security Appliance solutions companies are constantly being challenged to offer enhanced performance (additional servers tend to reduce traffic speeds), as well as improve the efficacy of detecting advanced threats that attempt to evade firewall technologies.
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Figure 55: Key Cyber Security Vendors
CLOUD ACCESS SECURITY BROKERS
ADVANCED ENDPOINT SECURITY
MOBILE SECURITY
WEB APPLICATION FIREWALLS
ANTI-DDOS
INTEGRATED SECURITY APPLIANCES
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KEY DRIVERS & RESTRAINTS Figure 56: Drivers & Restraints of Cyber Security Industry Growth
GROWTH DRIVERS INCREASING CYBER THREATS AND RISING AWARENESS INTERNET AND ECOMMERCE GROWTH
GROWTH RESTRAINTS
BUDGETARY CONSTRAINTS
INADEQUACY OF CURRENT SOLUTIONS IN MEETING CONTINUOUSLY EVOLVING THREATS
REGULATIONS AND COMPLIANCES TRUST DEFICIT RISE OF IOT AND DATA BOOM
KEY DRIVERS 1. INCREASING CYBER THREATS AND RISING AWARENESS The most ironical thing about the rise of cyber security is that its main driver is the increasing magnitude and frequency of threats leading to mass awareness about the possible catastrophic impact it can have on businesses. The intimidating threat landscape in terms of the magnitude of attacks, frequency, and potential damage, leaves stakeholders with little choice but to opt for cyber security services either by employing in-house experts or involving thirdparty solutions. The massive cost of data breaches – tangible and intangible – can take a toll on company profits and customer loyalty. A data breach cost companies an average of US$3.79 million, or US$154 for every lost or stolen record in 2015. The amounts represent an increase from the overall average cost of US$3.52 17
million in 2014 and a per-record cost of US$14517. Initially, financial firms used to address the information security risk in a reactive manner, as a response to security breaches. As such, risk management strategies have been based on what has occurred in the past instead of strengthening the system against all possible future threats. However, more and more financial institutions are gaining greater awareness about the serious consequences of a cyber attack. As such, the onus now is on creating a more secure environment in financial institutions by taking a comprehensive and holistic end-to-end view of the IT security scenario. 2. INTERNET AND ECOMMERCE GROWTH With growing Internet penetration and ecommerce explosion, voluminous amounts of critical data are being serviced and processed each second. The data may include credit card information for a direct access attack or seemingly insignificant
Source: IBM and Ponemon Research Institute 78
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personal information like addresses, phone numbers, preferences, and health parameters. Companies or conglomerates that service such data have to ensure its integrity and confidentiality as it may directly affect their reputation, business and revenue. This calls for cyber security facilities. 3. REGULATIONS AND COMPLIANCES It is the prerogative of every government to protect itself, the country and technological systems from domestic and foreign attacks and preventing monetary injuries to civilians and damage to infrastructure caused by cyber attacks. As such governments lay down strict guidelines to be rigorously followed by any firm dealing with significant amounts of data. The regulations and compliances demand well-structured, sophisticated and hard to infiltrate cyber security systems from these firms. This is particularly essential for financial and technological institutions as their data is considered to be the most critical of all. With mandatory data breach regulations in place, organisations should be able to identify and deal with breaches faster, resulting in increased spending on cyber security. 4. RISE OF IOT AND DATA BOOM With the explosion of Internet of Things where large numbers of devices are interconnected on a network and sharing real-time data, the devices being IPenabled having firmware, operating systems and thus having vulnerabilities and configuration issues are expected to increase IT workloads and transform the way cyber security operations are conducted. Quite simply, an abundance of online devices means more connections and data to scan for vulnerabilities, monitor for compromises, and protect from attacks – an unavoidable reality for cyber security. By 2020, it is predicted that the number of connected devices will soar up to 50 billion, more than 6 times the world population18.
18
KEY RESTRAINTS 1. BUDGETARY CONSTRAINTS Given the huge losses incurred by companies like Target, Sony, and other major institutions, it is evident that spending on cyber security developments is still relatively low compared to the risks. To date, the adoption of cyber security is largely determined by the size of the business and visibility of threats to it. Large banks and financial institutions stringently adhere to compliances, and it is well within their capacity to spend hefty amounts on securing their assets. However, the scenario is different for SMEs that do not come under the purview of regional regulations and compliances and lack funding. Even if they do implement cyber security solutions, the services are typically cheaper and most likely easier to breach such as legacy cyber security products. Budgetary restraints are also intertwined with the economic situation of a country where allocations influence the investments in security. Companies in a country with low GDP output and low per capita GDP are less likely to spend heavily on upgrading their security infrastructure at least not as a foremost priority. 2. INADEQUACY OF CURRENT SOLUTIONS IN MEETING CONTINUOUSLY EVOLVING THREATS The cyber security market is a highly dynamic market with emerging, advanced threats and new solutions being engendered every second. As such, there is no definite solution to the threat panorama; a fact that is well known to all potential adopters of cyber security. The most striking development in the first half of 2015 was the huge shift from URL-based cyber attacks to threats that rely on malicious document attachments. There has been an increase in the targeting of personally identifiable information (PII), use of malvertising (Internet advertisements linked to malicious software) and ransomware (software that prevents users from accessing their devices until a ransom is paid) in the first half of 2015. Such a dynamic swing of attack strategies makes it difficult to devise a viable and timely solution. A data breach becomes unavoidable under such conditions. Against this backdrop, most adopters acknowledge
Source: Frost & Sullivan 79
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that no matter how strong the security infrastructure, a zero-day attack or concealed vulnerability could potentially render their solutions ineffective.
handle their critical and sensitive data. However, lack of trust may be a significant barrier to fresh adopters outsourcing a critical part of their enterprise to a cyber security provider.
3. TRUST DEFICIT Enterprises considering cyber security have to either come up with in-house solutions or rely on a thirdparty that is competent in cyber security services to
VALUE CHAIN AND BUSINESS MODELS VALUE CHAIN Figure 57: Cyber Security Value Chain
SECURITY VENDORS
DISTRIBUTORS
MANAGED SECURITY SERVICE PROVIDERS
RESELLERS/ SYSTEM INTEGRATORS
ENTERPRISE
Security vendors provide the R&D and creation of appliance-, software-, or cloud-based solutions to be delivered through a 2-tier channel ecosystem. Distributors import the goods and facilitate the availability of products to in-country channels with the required support on fulfillment. Goods are sold through resellers that could be general retail businesses or system integrators that provide professional services such as installation for the end user. Managed security service providers facilitate the management of these solutions commonly delivered through telecommunications companies that can provide management services via their lines leased to enterprise clients.
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BUSINESS MODEL Cyber security covers various layers of threat detection, prevention, and mitigation before, during and after an attack. Enterprises looking for security solutions providers prioritise them based on how extensive and secure the solutions are against typical attacks. The services and solutions model for cyber security is extensive. The solutions are highly technical in nature and include Intrusion Detection System (IDS), Intrusion Prevention System (IPS), Unified Threat Management (UTM), Firewalls, antivirus, anti-malware, Security Information and Event Management (SIEM), web filtering, identity and access management, and may be provided either onpremise or on the cloud. ON-PREMISES MODEL An on-premise model ensures complete control of the systems and processes running on it. In this model, all corporate data is handled internally by dedicated IT staff meant for maintenance and support. The initial capital expenditure is high, and the firm may not be able to keep abreast of the rapidly changing threat landscape. Network security tools such as next-generation firewalls and IPS mostly remain on-premise because enterprises need to control the flow of data in and out of their networks. The latency, delays, and risks associated with running confidential data to/from a cloud provider are greater than organisations are willing to tolerate. The military is likely to opt for closed on-premise networks because they cannot risk sensitive data related to national security being intercepted and/or modified through a cloud-based solution. Likewise, financial institutions such as banks and credit card agencies will also choose closed onpremise networks because they cannot risk sensitive data related to financial records, accounting and money transfers being intercepted and/or modified in the cloud.
vendors is that their cash flow starts building immediately. However, in this model, revenues are harder to predict since new customers are required every year to keep revenues growing. CLOUD-BASED SOLUTION A cloud-based solution, on the other hand, requires no new infrastructure requirements and offers services at a lower cost. No software licencing costs are incurred by the enterprise either. Third-party technical professionals handle all the security-related tasks. Some applications are well-suited for hosting in the cloud such as CRM products, network monitoring, travel applications, systems back-up on-premise hardware/software solutions. On the other hand, applications such as accounting packages, data storage solutions for compliance purposes and most security products are best implemented on-premise. However, if the cloud service provider is of high market repute, even critical data is stored on the cloud. When factoring in the cost savings, the cloud often appears to be the best choice, but this does not mean that a solution’s implementation is justified in terms of the technology, organisation set-up and/or its requirements. Examples of technologies that live in the cloud include email security, hosted management, and various aspects of gateway anti-virus. Usually, SMEs prefer cloud-based solutions as they cannot afford the infrastructure and capital-intensive on-premise security solutions. Charging Model: Companies are charged monthly or annually for software they use. In this case, vendors or service providers need large investments upfront and revenue build-up at a relatively slower rate. However, once scale is achieved, revenues are highly predictable because of the high customer retention rates.
Charging Model: Companies are charged software and hardware costs upfront with additional Annual Maintenance Charges (AMC). The advantage for 81
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VALUE DRIVERS & KEY RISKS Figure 58: Value Drivers & Key Risks for Cyber Security Vendors
KEY VALUE DRIVERS • Existing Installed Base • Technological Edge and Efficacy • Completeness of Solution
KEY VALUE DRIVERS 1. EXISTING INSTALLED BASE A critical value driver for cyber security companies is the presence of an installed base in and around the region of operation and geographical region being served. Since cyber security is highly critical; customers need to know if the solutions are working well for other similar companies as well. An existing installed base is the most effective way to convince customers of the solutions’ efficacy. Since the requirements of cyber security may vary from one area to the next, a regional installed base is more important compared to a global one. 2. TECHNOLOGICAL EDGE AND EFFICACY The efficacy of the technology a particular company is using in comparison to the solutions of the competitors is a strong value driver. A company that has more secure solutions based on the latest technologies will find more customers compared to one based on older technology or a relatively less secure solution. As an example, the firewall industry faces constant challenges where cyber attackers could use several techniques to bypass firewall rules. For example, the use of unauthorised applications such as Zenmate, that can be installed in browsers to encrypt all traffic and bypass the policy rules being set in the organisation. Next-generation firewalls were developed to have visibility and granular 82
KEY RISKS • Technological Obsolescence • Competition • Security Breach Event
control over the applications in the network, gaining high adoption in recent years for their efficacy in not only mitigating the circumventing of policies, but also increasing work productivity. 3. COMPLETENESS OF SOLUTION Cyber security addresses a varied set of risks and threats that are so diverse that each type of threat has a custom-generated remediation or mitigation strategy. A cyber security provider with an extensive platform of solutions catering to most or virtually all threats in the market is most likely to emerge a winner. This is due to customers’ preference for working with fewer vendors compared to adopting multiple solutions from different vendors that may be difficult to integrate. A company having a vast array of solutions is more likely to succeed compared to a company providing a point solution. This could explain the spate of mergers and acquisitions happening as cyber security vendors strive to increase the coverage of their solutions. For example, Trend Micro recently signed a definitive agreement to acquire HP TippingPoint, a provider of next-generation intrusion prevention systems (NGIPS) and related network security solutions. The almost US$300 million agreement encompasses security technology, intellectual property, industry expertise, as well as an extensive, loyal enterprise customer base. The acquisition positions Trend Micro
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as the go-to enterprise security provider of dynamic threat defense solutions spanning endpoints, network, data centres and the cloud. Trend Micro will also combine current and acquired capabilities to create a Network Defense business unit, serving more than 3,500 enterprise customers.
KEY RISKS 1. TECHNOLOGICAL OBSOLESCENCE RISK ASSESSMENT: HIGH The ramifications of an ever-changing technological setting on the performance and growth of a cyber security service provider can hardly be ignored. Hardware (equipment required to maintain and use digital objects) and software (off-the-shelf and inhouse software programs and packages required to maintain and use digital objects) are fast becoming obsolete. Furthermore, solutions that are cutting edge today are likely to become commonly available at low prices in the future. For example, anti-virus technology was the biggest cyber security segment a decade ago. However, today anti-virus comes embedded in both Windows and Apple platforms. Consequently, anti-virus is the only major cyber security segment declining year on year.
For example, Target, a popular US-based retailer, was hit by a massive security breach where cyber attackers accessed the personal information of almost 110 million of its customers. It was disclosed that Target was using security tools from a major security solutions vendor that detected the attack. However, the security analysts at Target were not able to decide on how to react. It was also observed that key competitors tried to leverage the situation. The overall impact on the reputation of the solutions vendor for Target was severe after the incident. There have been instances where malware was discovered in cyber security firms, and in some cases, acts of insider threats performing a level of espionage on the security technologies used to mitigate malware so as to develop exploit codes that could circumvent them.
2. COMPETITION RISK ASSESSMENT: HIGH Since cyber security is an evolving technology, cyber security companies constantly face the risk of new competition coming in with better products. With the growing list of cyber security vendors entering each security sector, it is essential for decision-makers to use third-party vendor assessments to provide an impartial view when shortlisting potential service providers. 3. SECURITY BREACH EVENT RISK ASSESSMENT: HIGH A cyber security provider can face major risk to its business if one of its customers faces a serious security breach. Data breaches are a significant business risk. Companies hold large amounts of personal information, including financial information on individuals, customers, suppliers or staff.
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RELEVANT VALUATION METRICS Cyber security vendors have a simpler business model of either outright sales or a monthly payment based cloud business model. Hence, the valuation can be done simply on the basis of revenue (valuation/revenue) of EBITDA (enterprise value/EBITDA) multiple. However, before investing in a cyber security company, it is vital to assess the company on the key value drivers and assess the key risks to judge the future prospects of the company. Table 12: Valuation Metrics for Cyber Security Companies in Various Stages S. NO.
EARLY STAGE
GROWTH STAGE
LATE STAGE
1.
Paid-up capital19
Revenue & revenue growth
Revenue & revenue growth
2.
Addressable market size
Growth in monthly active users
EBITDA margin
3.
-
-
Profit margin
OVERALL FOCUS
RESEARCH & DEVELOPMENT
TOPLINE & BOTTOMLINE GROWTH
TOPLINE & BOTTOMLINE GROWTH
EARLY STAGE: Usually first 1 to 3 years of operations. GROWTH STAGE: Approximately 3 to 5 years of operations. LATE STAGE: More than 5 years of operations.
19 These are the best available metrics at this stage. But the valuation may change drastically based on the expected competitiveness of the solutions.
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12.
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DATA CENTRE AND CLOUD SERVICES
DATA CENTRE SERVICES A data centre is a facility used to house computer systems and associated components, such as telecommunications and storage systems. It generally includes a raised floor, redundant or backup power supplies, redundant data communications connections, environmental controls (e.g., air conditioning, fire suppression) and security devices. There are 2 main data centre operating models. One is where an organisation builds, operates and manages its own data centre for internal purposes, known as a captive data centre. The other is an outsourced model, where organisations lease space and hosting services from external data centre providers. In the outsourced model, the data centre provider furnishes the security, power and cooling needs for the data centre, and customers can use the space to deploy their servers and other equipment. This is commonly referred to as data centre services. Traditional data centre services primarily involve the co-location of servers and managed hosting. Colocation refers to the provisioning of racks within the data centre. Along with the racks, the power, cooling, connectivity and security features are supplied by the data centre service providers. Managed hosting refers to the hosting of applications like website within a server. Frost & Sullivan estimates the global data centre services market to be valued at more than US$42
billion in 2014, a growth of 17.0% over 2013. The market is mostly driven by an explosion in demand for data centre capacity, increasing complexities in managing data centres, and the burgeoning cloud computing services market. Current data centres aim at packing more powerful servers in increasingly smaller spaces, which mean higher power requirements for servers and better cooling technologies to siphon the heat generated from them. As a result, power and cooling technologies are fast becoming critical for new data centres. In fact, companies like Google are attempting to build data centres in cold-weather areas like Ireland and using seawater to reduce temperatures to save on the immense cooling costs for modern data centres. Another growing trend is the Data Centre Infrastructure Management (DCIM) solutions. DCIM solutions refer to complex software that collect, filter and analyse data from sensors in a data centre and proactively raise alarms, model potential workload placement and make recommendations about prospective changes. This ensures that server workloads, cooling in different areas and other critical parameters are optimised for efficiency and greater reliability. DCIM is critical to manage highlycomplex modern data centres and ensure reliability. In fact, the rising popularity of Big Data and Analytics is impacting DCIM solutions as well, as they are now being used to undertake what-if analysis to improve power usage efficiency (PUE).
Figure 59: Data Centre Investment Plans in Singapore DATA CENTRE OPERATOR
INVESTMENT PLANS
• Building its largest facility in Asia - SG3 • Phase 1 - 1,000 cabinets; Finished - 5,000 cabinets
• Building its second DC in Singapore • At an investment of US$380 million, the bigger multi-level facility will be ready in 2017
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INVESTMENT PLANS
• Building its second facility with 200,000 sq. ft. of space with an investment of about US$130 million • Facility opened in 2015 and serves ASEAN
• At an investment of US$200 million, the 2nd facility will have about 177,000 sq. ft. of rentable space • With over 13 MW of power it will connect 50 cloud providers
• Building its second facility in the IDA DC park with 200,000 sq. ft. of total space • Its largest investment outside Indonesia to support the communications hub for the region
CLOUD SERVICES Cloud services refer to computing and storage services or applications delivered as a service over a network with seemingly infinite scalability. With the cloud, the customer can use computing resources or applications as much as they want (scaling up or down as required) and pay only for what they use. Cloud technology is radically changing the way organisations work. In the old model, enterprises had to purchase the entire hardware and software upfront and keep a large IT department to maintain them. If there was a fresh requirement to add more hardware or scale up software, the process could take months. However, in the cloud paradigm, enterprises pay for the hardware and software on a pay-per-use basis, doing away with upfront expenses. Any new demand for hardware and software is met almost instantaneously by ordering extra capacity or licences from the cloud service provider. Also, the infrastructure or software is maintained by the cloud service provider, not the internal IT department. Finally, any upgrade cycle is managed by the cloud service provider. With the benefits of agility and flexibility, it is no wonder cloud services have become one of the fastest growing business segments currently. We estimate cloud services to be worth more than US$50 billion globally in 2014, having grown by 38.4% over 2013. 86
Overall, the cloud services market is largely being driven by advancements in cloud infrastructure offered by the vendors. Key technologies include virtualisation and next-generation computing and storage servers. Virtualisation refers to creating virtual versions of computing and storage servers; meaning the same physical server can act as multiple virtual servers. This technology lies at the core of cloud computing since it enables service providers to swiftly ramp up capacity for clients without having to add new physical servers. Any new requirement can be quickly served by creating a virtual server within an existing physical server. Next-generation computing and storage servers aim to pack higher computing (or storage) capacity in a smaller space while utilising lower power. They also have management features to make them easier to use for cloud applications. In addition to the two technologies, cloud services are also being enabled by modern DCIM solutions that allow easy management of multiple servers.
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KEY CHARACTERISTICS OF CLOUD COMPUTING
ON DEMAND, SELF-SERVICE
RAPID ELASTICITY, SCALE UP/DOWN
PAY AS YOU USE, METERED CONSUMPTION
SHARED POOLS, ILLUSION OF INFINITE RESOURCES
BROAD NETWORK ACCESS USING STANDARD INTERNET PROTOCOLS
TYPES OF CLOUD SERVICES Cloud services can be grouped into 3 categories: Infrastructure-as-a-Service (IaaS), Software-as-aService (SaaS) and Platform-as-a-Services (PaaS). INFRASTRUCTURE-AS-A-SERVICE (IAAS) The IaaS model involves an organisation outsourcing the hardware (computing or data storage resources) to support business operations. The service provider owns the equipment and is responsible for housing, running and maintaining it with the client typically paying on a per-use basis. Key examples include Amazon Web Services (AWS) and Rackspace. This is the second largest cloud service segment after SaaS. Frost & Sullivan estimates the global spending on IaaS at US$12 billion in 2014, a growth of 47.9% over 2013. Growth rate in APAC from 2014 to 2019 is projected at 42.4%. SOFTWARE-AS-A-SERVICE (SAAS) SaaS is a software distribution model where an
application is hosted by a service provider and made available to customers over a public or private network. In the SaaS model, software or application is provided over the cloud instead of computing or storage infrastructure. Key examples include Salesforce.com, Microsoft 360 and Gmail. This is the largest cloud segment with an estimated global market size of around US$37.4 billion in 2014 as per Frost & Sullivan. Growth rate in APAC from 2014 to 2019 is projected at 29.5%. PLATFORM-AS-A-SERVICE (PAAS) PaaS is a key component of the new cloud computing environment, in which developers use templates provided by the platform vendor to build their software applications to be delivered over the cloud. Examples include Google AppEngine and Microsoft Azure. PaaS makes up a minor portion of the overall cloud revenue; however, it is also growing the fastest. Frost & Sullivan predicts growth from 2014 to 2019 in APAC to be around 54.3% from a market size of US$1.05 billion in 2014.
Figure 60: Types & Enablers of Cloud Services CLOUD ENABLERS
VIRTUALIZATION
SAAS
NEXT GENERATION SERVERS
PAAS
DCIM
87
TYPES OF CLOUD SERVICES
IAAS
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KEY DRIVERS & RESTRAINTS Figure 61: Drivers & Restraints of Data Centre and Cloud Services Industry Growth GROWTH DRIVERS
GROWTH RESTRAINTS
EXPLOSION OF CONTENT
SECURITY
REDUCING COST OF CLOUD TECHNOLOGIES
CONCERNS OVER LOSS OF CONTROL
TREND TOWARDS OPEX DRIVEN MODEL
UNRELIABLE NETWORK CONNECTIONS
INCREASING CONNECTIVITY AND ADOPTION BY SMBs
REGULATORY ISSUES
KEY DRIVERS 1. EXPLOSION OF CONTENT The explosive growth of ecommerce, social media, content streaming sites like Netflix and other websites is contributing to the influx of content. Trends like Big Data and Internet of Things (IoT) are also contributing to the data explosion. The data needs to be stored and “mirrored” across the globe for faster access to consumers worldwide, resulting in the tremendous demand for Internet data centres.
Traffic (Zettabyte)
Spending (US$ Bn)
Figure 62: Content vs Data Centre Growth
Global Data Center Services Spending ($ Bn) Global Data Center Traffic (Zettabytes)
Source: Cisco GCI, Frost & Sullivan 88
2. REDUCING COST OF CLOUD TECHNOLOGIES Cloud technologies, including the next-generation servers, are becoming increasingly efficient. Frost & Sullivan estimates that server prices have declined by 3% to 5% annually over the 2012 to 2015 period, assuming compute and storage capacities and performances remain constant. In addition, cloud offerings available in the market are becoming more affordable by the day. For example, Amazon’s new on-demand pricing for certain Linux/ Unix instances on EC2 fell between 10% and 40% in early 2014, with a similar price reduction in Q3 2015 as well. 3. OPEX DRIVEN MODEL Enterprises are increasingly looking to reduce huge upfront investments in IT for models where users only need to pay a small monthly fee. An attractive feature about the cloud is that enterprises need to pay for only what they use. Many companies involved in product development, rent capacity from AWS only when they require it for product testing. Similarly, ecommerce companies are able to scale up easily in line with customer growth. The diversity of flexible financing models continue to drive the expansion of cloud computing.
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4. INCREASING CONNECTIVITY AND IT ADOPTION BY SMBs Traditionally, SMBs have not been extremely IT savvy, with most using basic connectivity and a handful of critical applications like email. These days, however, there is a growing number of SMBs adopting applications such as CRM, ERP and other productivity-enhancing solutions. Since SMBs cannot afford huge upfront investments to purchase the applications and associated hardware, they prefer to use cloud-based applications.
KEY RESTRAINTS 1. SECURITY According to Frost & Sullivan’s 2014 Cloud User Survey, the largest number of respondents (63%) identified security as a major roadblock towards cloud adoption. The primary concern about the cloud is that data resides outside of the enterprise IT network and may be vulnerable to greater security risks. While models like private cloud (private cloud infrastructure of an enterprise) help reduce the security threats, they fail to offer the economies-ofscale cloud solutions offered by AWS. With the growing interest in cloud security, models like the hybrid cloud (part private to ensure security and part public to reap cost advantages) are able to effectively tackle these issues. That stated, skepticism among a large number of companies remains.
without access to applications hosted in the cloud. In Frost & Sullivan’s 2014 Cloud User Survey, almost 54% of respondents mentioned unreliable networks as a deterrent to cloud adoption. However, cloud service providers are quick to address this hurdle by offering customers the choice to connect over private networks (e.g., MPLS or Carrier Ethernet) that offer better availability and reliability in comparison to the Internet. In the past few years, almost every leading cloud provider has entered into partnerships with leading network providers to enable private connectivity to their cloud services. For example, AWS has partnered with network service providers such as Level 3, TW telecom, and Zayo. 4. REGULATORY ISSUES The cloud model faces a number of regulatory challenges. For example, regulations in Indonesia mandate that local businesses maintain data of all Indonesian customers in the country. Therefore, Indonesian companies may not be able to use cloud services at data centres outside Indonesia. Similarly in highly-regulated industries, such as healthcare and financial services, cloud service providers must be compliant with a number of standards. These issues are motivating cloud providers to develop hosted private cloud services that may become certified as compliant with specific standards or regulations. However, such community clouds or industry-specific private hosted clouds are typically priced higher than public IaaS.
2. CONCERNS OVER LOSS OF CONTROL Loss of control is the second biggest issue in cloud IaaS adoption, with 55% of survey respondents citing it as a top concern. IT leaders are not confident that a multi-tenant environment is well-suited to keep their apps running in the face of equipment or network failures. In the traditional IT model, when a hard drive or network failed, the IT department was responsible for fixing the problem or reaching out to a service provider. With the cloud model, the enterprise IT does not own the hardware; hence, they have little to no control over addressing the system failure. However, as the cloud market continues to evolve, this restraint is expected to be mitigated with providers consistently building up trust of customers. 3. UNRELIABLE NETWORK CONNECTIVITY A majority of users connect to the cloud over the public Internet that offers best-effort connectivity. Any disruption to the access network can leave users 89
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VALUE CHAIN Figure 63: Value Chain of Data Centre & Cloud Services
HARDWARE VENDORS
CLOUD & DCIM SOFTWARE PROVIDERS
CONSULTING DATA CENTRE SERVICE & SYSTEM PROVIDERS INTEGRATION
HARDWARE VENDORS Provide the storage and computing servers as well as networking gear for data centres and cloud infrastructure. Key examples include Cisco, IBM, HP, Dell, EMC, and Oracle. CLOUD AND DCIM SOFTWARE PROVIDERS Provide the necessary software for enabling and managing cloud technologies. Key virtualisation technology vendors include VMware, Citrix, Oracle and Microsoft. Key DCIM vendors are Emerson Network Power, ABB, Schneider Electric, and Nlyte Software. CONSULTING AND SYSTEM INTEGRATION Assists enterprises and data centres adopt cloud technologies. Primary services include data centre implementation, application migration (to the cloud), and private cloud consultation. Key players in this market include IBM, EMC, NTT Data, TCS, Unisys, HP, and Accenture. DATA CENTRE SERVICE PROVIDERS Provide the data centre space required for server colocation or managed server offerings. Several companies require a basic data centre shell with cloud service providers while other larger participants can rent and fit out according to their needs, closely resembling a real-estate model. Key players in this space include Digital Realty. Other participants may provide a completely built-out data centre with connectivity to multiple networks and racks in place. These encompass enterprise data centres that host a server for the enterprise and Internet data centres (IDCs) that primarily store content to be delivered to the enterprise and consumers by carriers, ecommerce companies and content players. Completely built out data centres are typically connected to multiple highspeed networks and to other similar IDCs worldwide. Key enterprise data centre players include Equinix, Cyrus One, and Global Switch. Larger enterprise data centre participants in the region include NTT Communications, SingTel, Telkomsigma, and CSF. 90
CLOUD SERVICE PROVIDERS
CONNECTIVITY SERVICE PROVIDERS
ENTERPRISE & CONTENT PLAYERS
CLOUD SERVICE PROVIDERS As discussed earlier, cloud services can be classified as IaaS, SaaS or PaaS providers. IAAS: These providers use third-party data centres or build their own data centres to host IaaS capabilities. Amazon Web Services (AWS) dominates this space with extremely cheap and flexible options, and is the top choice of leading companies like Netflix, Expedia, Adobe, Pfizer, and Airbnb. Other players in this space include AT&T, CenturyLink, Rackspace, NTT Data, and SingTel. These players charge customers on a per month basis according to capacity (storage or compute) and service levels. SAAS: A highly fragmented space with literally thousands of software players offering software through the cloud. The most well-known SaaS provider is SalesForce.com that offers CRM solutions over the cloud. For the financial industry, key SaaS vendors include Oracle, SAP, and Temenos. These players charge customers on a per month basis according to the number of user licences and features of the software subscribed by the enterprise. PAAS: A smaller yet fast-growing field; key players include Microsoft and Google. CONNECTIVITY SERVICE PROVIDERS These encompass local, regional of global telecom operators providing connectivity to data centres. Examples include SingTel, AT&T, Telekom Malaysia, Telkom Indonesia, and NTT Communications. They charge customers per month on the basis of capacity and other value-added services. ENTERPRISE AND CONTENT PLAYERS Content players deliver multimedia content to consumers worldwide and are emerging as major
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demand drivers for data centre services. There are a massive number of participants in this space including Netflix, Spotify, and ecommerce companies. Enterprise data centre services can also belong to
verticals such as banking and finance, manufacturing, and retail. The banking and finance sector is one of the largest verticals for enterprise data centre services
VALUE DRIVERS & KEY RISKS Figure 64: Value Drivers & Key Risks for Data Centre & Cloud Services Providers
KEY VALUE DRIVERS • Scale & Investment Capacity • Capacity Utilisation • Operational Efficiency • Geographical Reach • Alliances & Partnerships • Customer Traction & Growth
KEY VALUE DRIVERS 1. SCALE AND INVESTMENT CAPACITY Cloud services have significant economies of scale. A service provider with a larger infrastructure base will be able to serve additional customers at lower additional cost (since spare capacity of existing servers can be used to serve extra customers). This is a major reason why AWS is priced more competitively than IaaS offered by telecoms operators in smaller markets. Investment capacity is another significant driver. A company that can invest in bigger data centres globally will be more successful compared to a company that does not have similar investment capacity. The current cash position and capacity to raise additional funding (internally or externally) are important. This is why cloud services such as IaaS, are dominated by giants like Amazon. 2. CAPACITY UTILISATION Data centres and cloud services require large upfront investments to acquire infrastructure and then utilise 91
KEY RISKS • Failure to fill Capacity • Delay in achieving Profitability • Customer Risk • Competition and Overinvestment
the infrastructure to earn revenue. Since this involves substantial fixed costs, it is essential to have high capacity utilisation to reach profitability. Companies with higher capacity utilisation are more likely to succeed in the future. However, this may not be true for SaaS players that only have the opportunity to increase investments as demand grows. Many SaaS providers use IaaS services like AWS and expand capacity only when required. 3. OPERATIONAL EFFICIENCY Due to the significant investments, data centres and cloud services providers need to have low operating cost to recoup their upfront investments as fast as possible. A high operating margin is a good indicator of the eventual success of a data centre and cloud services company. 4. GEOGRAPHICAL REACH Major investors in IT include MNCs with a global footprint. A single service provider that can serve all markets where the company is present has a
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competitive advantage over a local provider. Similarly, content providers (video, social media) that need to deliver content worldwide look for data centres or cloud players that have a global footprint. Companies like Equinix, NTT Communications and Amazon tout their geographic coverage as a compelling advantage over competitors. 5. ALLIANCES AND PARTNERSHIPS Internet data centres that are well linked to large data centres have a clear advantage over ones that are not connected. This appeals to customers that have servers at different data centres and want to connect to them immediately. Likewise, the large capacity may require sales partners that can reach out to end customers and fill this capacity. Hence, connectivity to other data centres and network of resellers are critical indicators of success for these players. 6. CUSTOMER TRACTION & GROWTH Customer traction and growth are important indicators of how optimised SaaS or IaaS offerings are for the customers. Providers that experience rapid growth in their customers are more likely to succeed in the long-term.
KEY RISKS 1. FAILURE TO FILL CAPACITY Cloud and data centre service providers need to invest in sizable infrastructure to be competitive. However, this capacity becomes profitable only after reaching a particular utilisation level. If the capacity is not fully utilised fast enough, it may lead to heavy losses for the company. For example, CSF, a major Malaysian data centre provider invested huge capacities in Indonesia and Malaysia through equity funding. However, it failed to fill the capacity, making significant losses. The company’s stock price crashed from GBP77 in January 2011 to less than GBP1.5 in 2015.
capacity or competitive price pressures may prevent these companies from becoming profitable even after a long period. Equinix, one of the largest Internet data centre companies in the world, was unprofitable until 2014 even after 16 years of operations. It achieved single-digit profitability only in 2015. 3. CUSTOMER RISK A crucial uncertainty data centres and cloud services providers face is customer risk. Ecommerce and content companies are key customers of many of these providers and inherently volatile businesses. For example, the dot-com collapse of 2000 significantly affected the data centre business in the US. A similar crash today can have serious implications for data centre participants worldwide. 4. COMPETITION AND OVERINVESTMENT The data centre industry is cyclical in nature where large investments are made when customer demand rises. New entrants set up huge capacities and go after the same customers. However, once demand slows, the industry players may realise they have overinvested in capacity, and not reach target capacity utilisation. A similar scenario occurred when the dot-com bubble burst in 2000; many data centres had invested heavily in substantial modern capacity in the hope of huge demand from dot-com companies. However, when the tech boom ended, demand swiftly declined and the industry was saddled with significant spare capacity for a long period. Competition also plays a significant role from a pricing perspective. For example, a number of local telecoms operators have made huge investments to offer IaaS services. However, Amazon offers its AWS services at a fraction of the cost giving telecoms operators stiff competition.
The company was most likely unable to fill capacity due to a number of factors including lower than expected demand, growing competition, and uncompetitive offerings. 2. DELAY IN ACHIEVING PROFITABILITY Data centre and cloud businesses require massive upfront investments that can result in losses in the initial years. In return for these high investments and heavy losses, investors hope to make a profit in the later years. However, the imperative to keep adding 92
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RELEVANT VALUATION METRICS For the purpose of valuation, data centres and IaaS need to be viewed separately from SaaS. Data centre and IaaS businesses require much higher upfront investments, while SaaS is mostly about customer traction and competitiveness of the offering. Data centres and IaaS enterprises are also concerned about achieving a big enough scale in addition to customer traction. DATA CENTRES & IAAS The focus of early and growth stage companies is to achieve significant scale in infrastructure and customers before achieving profitability when they become mature companies. The key valuation metrics for companies in different stages are:
1. EARLY STAGE COMPANIES
For these companies, the focus is on building capacity and getting customers. Therefore, the key valuation multiples should be capacity and revenue.
2. GROWTH STAGE COMPANIES
At this stage, monetisation of infrastructure becomes important. Companies should have high EBITDA margins since it is required to compensate for the high initial investments. Since growth is imperative, the cash flows may still be negative. Key metrics include capacity, revenue and EBITDA margin.
3. LATE STAGE COMPANIES
At this stage, it is crucial for data centres and IaaS companies to be profitable and cash positive. Hence, revenue, EBITDA and profit margins, become important valuation metrics.
Table 13: Valuation Metrics for Data Centre and IaaS Companies in Various Stages S. NO.
EARLY STAGE
GROWTH STAGE
LATE STAGE
1.
Revenue & revenue growth
Revenue & revenue growth
Revenue & revenue growth
2.
Capacity & capacity growth
Capacity & capacity growth
EBITDA margin
3.
-
EBITDA margin
Profit Margin
OVERALL FOCUS
CAPACITY CREATION & CUSTOMER TRACTION
TOPLINE GROWTH & CAPACITY CREATION
TOPLINE & BOTTOMLINE GROWTH
EARLY STAGE: Usually first 2 to 3 years of operations. GROWTH STAGE: Approximately 3 to 6 years of operations. LATE STAGE: More than 6 years of operations.
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SAAS For SaaS companies, the upfront investment is lower compared to IaaS or data centre companies. As a result, they usually reach overall profitability faster. In addition, instead of capacity, they should be valued based on the number of customers during their early stages. 1. EARLY STAGE COMPANIES
For these companies, the focus is on achieving significant customer traction typically through competitive pricing. The key valuation multiples should be the number of customers as well as revenue.
2. GROWTH STAGE COMPANIES
At this stage, revenues become important while EBITDA margins may or may not be positive. Therefore, the right metrics are still revenue and revenue growth.
3. LATE STAGE COMPANIES
At this stage, profitability becomes crucial. Hence, revenue as well as EBITDA and profit margins become important valuation metrics.
Table 14: Valuation Metrics for SaaS Companies in Various Stages S. NO.
EARLY STAGE
GROWTH STAGE
LATE STAGE
1.
Revenue & revenue growth
Revenue & revenue growth
Revenue & revenue growth
2.
Number of customers & growth
Number of customers & growth
EBITDA margin
3.
-
-
Profit Margin
OVERALL FOCUS
CUSTOMER TRACTION
TOPLINE GROWTH
TOPLINE & BOTTOMLINE GROWTH
EARLY STAGE: Usually first 2 to 3 years of operations. GROWTH STAGE: Approximately 3 to 5 years of operations. LATE STAGE: More than 5 years of operations.
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BLOCKCHAIN
Blockchain is the little-known enabling technology behind Bitcoin, the mysterious digital currency that has featured prominently in the news for the past 4 to 5 years. Bitcoin is a digital currency that can be transacted across the globe in relatively anonymous fashion without any regulatory oversight with low transaction fees and a tamper-proof record system where transactions can be quickly verified. Bitcoin has grown in popularity with daily transactions increasing from around 2,000 transactions per day in 2012 to almost 204,000 as of July 12, 201520. The value of the Bitcoin has also leaped from US$10 in 2012 to more than US$220 in 2015. However, the success and hype surrounding Bitcoins may soon be eclipsed by the blockchain technology.
transaction is kept by a central intermediary. In case of any future conflict (e.g., disputes arising from the transaction), the central intermediary verifies its records to prove the legitimacy of the transaction. For example, in credit card transactions, companies like Visa or MasterCard are the central intermediary. In civil contracts of property deals, the relevant government agency acts as the central intermediary.
Blockchain is a distributed database technology; and the primary reason behind the popularity of Bitcoin. Facilitating the most attractive attributes of Bitcoin, blockchain enables low transaction fees, tamper-proof transaction records, easy verification of previous transactions, and relative anonymity of transacting parties. Blockchain offers numerous potential applications that Marc Andreessen, owner of Andreessen Horowitz, one of the most influential Venture Capital (VC) firms in the Silicon Valley, has likened it to the invention of the PC and Internet.
TRANSACTION RECORDS
Potential uses include renting or selling assets protected by digital locks, transacting real currencies, building crowdfunding platforms with low transactions fees, facilitating anonymous and secure contract management, and enabling the transaction of financial shares and other fiscal instruments. To see how blockchain can add value to the abovementioned scenarios, we first need to understand the difference between blockchain and traditional transactions.
TRADITIONAL TRANSACTIONS In most traditional transactions such as credit card transactions or land purchases, the record of the 20
Source: coindesk.com
Figure 65: Traditional Transaction Record Management
CENTRAL INTERMEDIARY
BUYERS
While this method works well in most cases, there are certain issues with traditional transaction record management: 1. HIGHER COST The central intermediary needs to invest significantly to record every transaction and ensure it is tamperproof to preserve the integrity of its records. Hence, it needs to charge a transaction fee from the buyers and sellers. Central intermediaries, such as credit card networks (Visa, MasterCard) charge 3% fee for each credit card transaction. On the other hand, the transaction fee for Bitcoins is usually less than 40 cents and can even be 021.
21
95
SELLERS
Source: Bitcoinfees
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2. LACK OF ANONYMITY The identity of the buyers and sellers is known to the central intermediary. While the central intermediary keeps the identity of buyers and sellers confidential, it may share the information for legal or other purposes. 3. POSSIBILITY OF CORRUPTION OR DESTRUCTION OF RECORDS While it is rare, there is always a possibility of corruption within the central intermediary that may lead to tampering of records or leakage of personal information. Records could also be destroyed due to a natural calamity or hacker attack if the level of technological sophistication of the central intermediary is low.
BLOCKCHAIN TRANSACTIONS Figure 66: Record Management in Blockchain-enabled Transactions
IDENTICAL COPIES OF TRANSACTION RECORDS
NODES
NODES
NODES
TRANSACTION RECORDS
BUYERS
SELLERS
Blocks are simply a record of a certain number of transactions and form the basis of blockchain transactions. The blocks are immediately shared 96
among a large number of nodes, or record-keeping systems, operated by independent node operators worldwide. All nodes have an identical copy of the blocks. Together, these nodes form a network. New blocks, which keep a record of the most recent transactions on the network as well as information on older blocks, are created continuously and shared with all the nodes. As a result, a chain of blocks is formed (hence, the term “blockchain”). When a new block is created, every node can verify if the block is genuine by checking whether it provides accurate information about the older blocks. The probability of manipulation is low. The new block created then starts recording the new transactions happening across the blockchain network. This method ensures that transactions are tamperproof through two ways. First, since the copies of transactions are kept in multiple blocks, tampering a transaction will require tampering multiple blocks, which is more difficult than tampering one block. Second, multiple nodes have the same copy of these blocks. So tampering a transaction will require tampering the blocks in a large number of nodes, which is even more problematic. Furthermore, the chain of blocks (and record of all transactions) stored in the nodes are completely public. Anyone can go through the blockchain to verify whether a particular transaction has taken place. The key advantage of blockchain is that it offers high integrity and verifiability of the transaction record without the need for an expensive central intermediary. As a result, the transaction cost reduces significantly, as in the case of the Bitcoin. Second, the blockchain only records the blockchain addresses of buyers and sellers and not their real identity. Therefore, it is hard for an entity to determine the real identity of the buyer or seller (though not impossible). Consequently, in certain scenarios blockchain offers greater anonymity. Finally, there is no possibility of corruption within a central intermediary since such an intermediary does not exist. Most nodes in the network need to be corrupted simultaneously for tampering of a transaction. Blockchain is an ideal instrument to perform digital transactions with high degree of trust, ease and at
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a low cost compared to traditional methods. Since even physical assets can be secured by digital locks
(e.g., keyless entry system for cars) blockchain applications can be extended to these assets as well.
KEY DRIVERS & RESTRAINTS Figure 67: Drivers & Restraints of Blockchain Adoption GROWTH DRIVERS PERVASIVE NEED FOR DISTRIBUTED TRANSACTION SETTLEMENT
LACK OF PROVEN BUSINESS MODELS
AGGRESSIVE FUNDING BY VCs
SLOW END USER ADOPTION
SUCCESS OF BITCOIN
LACK OF REGULATORY FRAMEWORK
KEY DRIVERS 1. PERVASIVE NEED FOR DISTRIBUTED TRANSACTION SETTLEMENT Current transaction settlements and contract management require a central intermediary, and most times, multiple intermediaries. As discussed earlier, this increases the transaction cost and may even make the process slower. There is a need to have a blockchain-type distributed transaction settlement to reduce cost and increase efficiency. While this is especially relevant for the trading of financial instruments, its need is felt in many other areas as well. 2. AGGRESSIVE FUNDING BY VCs Blockchain and Bitcoin are current favourites among VCs like Andreessen Horowitz that are big proponents of the technology. In 2015 alone, the total funding to Bitcoin and blockchain start-ups was estimated at US$380 million till July.22 Based on actual investments till July 2015 and current trends, we estimate that by between January 2012 and October 2015 close to a 22
GROWTH RESTRAINTS
US$1 billion may have been invested in these startups, stimulating the entry of various business models and new blockchain-based platforms for different industries. 3. SUCCESS OF BITCOIN The success of Bitcoin is a major catalyst for lucrative investments in the blockchain sector. The hype surrounding Bitcoins is generating the interest of VCs and entrepreneurs alike towards the potential of blockchain technology.
KEY RESTRAINTS 1. LACK OF PROVEN BUSINESS MODELS Despite numerous efforts, we have yet to see many successful implementation cases of blockchain beyond the realm of Bitcoins. Even for completed implementations, a successful revenue model is yet to be seen outside the Bitcoin ecosystem. Until the few success stories of Bitcoin gain popularity, largescale adoption of the technology may not happen.
Source: coindesk.com 97
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2. SLOW END USER ADOPTION Even in cases where implementation has been successful, the end user adoption has remained low. An example is Ripple, which enables cross-currency settlements between banks. Despite being a success in implementation, the actual adoption has been low. As of October 2015, Fidor Bank in Germany is said to be the only financial institution “using” Ripple. Key factors for the low adoption can be attributed to poor familiarity with the new technology and a higher comfort level with the existing interbank settlement system. 3. LACK OF REGULATORY FRAMEWORK The current legal framework in most countries is not ready for blockchain-based transactions. As a fairly recent trend, the blockchain regulatory framework is not explicit about the legal validity of its contracts and even more complex in crossborder transactions. Furthermore, countries like the US requires that transaction platforms based on the blockchain comply with same legal restrictions that exist for other platforms. This is often a problem for blockchain-based platforms. For example, in May 2015, US regulatory body FinCEN, fined Ripple Labs for violating several requirements of the Bank Secrecy Act (BSA) and failing to implement and maintain an adequate antimoney laundering (AML) program.
BUSINESS MODELS Major business models for blockchain relate to the Bitcoin ecosystem. These include: 1. BITCOIN EXCHANGES, TRANSACTION PROCESSORS AND WALLETS Bitcoin exchanges provide a platform for trading Bitcoin with other currencies. Key examples of Bitcoin exchanges include Coinbase, BTC China, Bitcoin Source, and Bitstamp. Companies like Blockchain offer digital wallets for Bitcoin; an equivalent of a bank account for Bitcoin. 2. BITCOIN MINING Bitcoin technology incentivises the creation of new blocks by rewarding people who generate blocks 98
with new Bitcoins. For Bitcoin technology to work, new blocks need to be continuously created. This requires processing or hashing of recent transactions as well as relevant information from previous blocks, requiring computing resources. Since there is no central intermediary, Bitcoin technology incentivises any entity in the world to contribute to the creation process of new blocks by allowing them to generate Bitcoins for every block created. By investing their computing resources and time, users can earn Bitcoins, a process called Bitcoin mining. While Bitcoin mining has been limited to companies like BitFury, firms like 21 Inc provide necessary processors and hardware to the general public for Bitcoin mining. 3. FINANCIAL SETTLEMENTS AND PAYMENTS These refer to the general application of blockchain that is not based on Bitcoin. Due to the high transaction fee and network of intermediaries, financial settlements are one of the early targets for blockchain-based platforms. Ripple Lab provides services related to money market settlements. Nasdaq also recently launched a new platform called Linq that manages the transfer of shares of private companies based on the blockchain ledger. In addition, several banks including RBS, Bank of New York Mellon, Barclays, are experimenting with blockchain applications to see how it can enable payments and other financial transactions for their customers. Companies like Circle also facilitate the transfer of US dollars using blockchain technology. 4. BLOCKCHAIN PLATFORMS Several companies offer a blockchain platform to enable multiple applications. For example, Chain Inc, one of the best-funded blockchain start-ups, offers a blockchain platform that enables Nasdaq’s Linq platform. The platform can also be used to enable settlement of minutes for mobile carriers and to transfer digital gift cards. Ethereum is another platform that facilitates blockchain-based applications.
OTHER APPLICATIONS Blockchain’s fundamental advantage is that a transaction recorded through blockchain cannot be tampered with and can be verified by anyone easily without the need for a high-cost intermediary.
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This opens up significant opportunities for other blockchain applications. These include determining the authenticity of rare art products (by tracing its ownership transfers based on blockchain transactions), low-cost digital escrow, intellectual property registration, transfer and management
of digital assets like digital tickets, coupons and copyrights. While there are several companies working in these domains, significant customer traction or lucrative revenue models have yet to emerge.
Figure 68: Blockchain Companies with Different Business Models
BITCOIN EXCHANGES, TRANSACTION & WALLETS
BITCOIN MINING
FINANCIAL SETTLEMENTS & PAYMENTS OTHERS
CONCLUSION Blockchain is an extremely promising technology since it creates an immutable record of any digital asset transfer at a much lower cost than traditional intermediaries. This has the potential to change the way we transfer any digital asset or an asset that can be digitised.
We believe one has to wait for the technology and business model to evolve, before we can develop a framework for evaluating these companies and business models. At this point, investment in blockchain start-ups by the VCs is a longer-term bet, and investors with a lower risk appetite may choose to wait for clarity to emerge.
At the same time, attempts to gain significant customer traction and create a viable business model are ongoing. Bitcoin is the only exception, where despite its volatility, the business models have stabilised and companies are making money by providing exchanges, payment processing and wallets. 99
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