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REFLECTIVE PRACTICE

Performance measurement system for healthcare processes Shankar Purbey, Kampan Mukherjee and Chandan Bhar Indian School of Mines, Dhanbad, Jharkhand, India

Performance measurement for healthcare 241 Received November 2006 Accepted November 2006

Abstract Purpose – The purpose of this article is to provide an overview and evaluation of performance measurement systems and also present a framework for the selection of an appropriate performance measurement system for healthcare processes. Design/methodology/approach – The paper provides a brief review of the existing performance measurement frameworks. On the basis of review, performance measurement system criteria are identified and accordingly a framework has been proposed for measuring performance in healthcare processes. Findings – The measurement of performance of a healthcare organization is still an unresolved issue. A performance measurement system should be sensitive to changes in the external and internal environment of an organization. The proposed framework measures performance from a multi and interrelated perspective, namely efficiency, effectiveness and flexibility. Practical implications – The study will help the healthcare organization to know how they are performing; it will also help in benchmarking the organization so that customers know the value of the money they pay for the service. Originality/value – The framework presented provides a performance measurement system for healthcare processes that is sensitive to change in the external and internal environment of an organization. Keywords Performance measures, National health services, Strategic planning Paper type Research paper

Background The design of an effective performance measurement system, that includes the selection of appropriate measures and approaches for analyzing results, is central to aligning an organization’s operations with its strategic direction. Despite its importance, this is one area that many organizations fail to address effectively. Performance measurement is an established concept that has taken a renewed importance in varieties of organizations (Camarata and Camarata, 2000). Historically, performance measurement systems were developed as a means of monitoring and maintaining organizational control, which ensures that an organization pursues strategies that lead to the achievement of overall goals and objectives of the organization (Nani et al., 1990). The development of performance measurement system in management has followed a path that has been influenced by general push to improve quality of service while meeting cost parameters. Bititcti et al. (2000) identified that performance measurement system needs to have the following characteristics: . being sensitive to changes in the external and internal environment of an organization;

International Journal of Productivity and Performance Management Vol. 56 No. 3, 2007 pp. 241-251 q Emerald Group Publishing Limited 1741-0401 DOI 10.1108/17410400710731446

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reviewing and reprioritizing internal objectives when the changes in the external and internal environment are significant enough; deploying changes to internal objectives and priorities to critical parts of the organization, thus ensuring alignment at all times; and ensuring that gains achieved through improvement programs are maintained.

Performance measurement provides the basis for an organization to assess how well it is progressing towards its predetermined objectives, helps to identify areas of strengths and weaknesses, and decides on future initiatives, with the goal of improving organizational performance. Performance measurement is not an end in itself, but a tool for more effective management. Results of performance measurement indicate what happened, not why it happened, or what to do about it. In order to make an organization effective, the performance measurement outcomes must be able to make the transition from measurement to management. It must also be able to anticipate the changes needed in the strategic direction of the organization and have a methodology in place for effecting strategic change. This concept is identified as performance management in performance measurement literature. Organizations which do not integrate ongoing performance measurement and feedback into their management development programs tend to experience lower than expected performance improvements and higher dissatisfaction and turnover of employees (Longenecker and Fink, 2001). Healthcare sector: an overview The healthcare sector is one of the fastest growing areas of the economy of most developed countries. Governments (and taxpayers) invest larger amounts of money in it, either directly or indirectly, and expect a high quality services from this sector. In reality, the performance of this sector is quite different and is characterized by long waiting times, inefficiency, low productivity, stressed medical staff and dissatisfied patients. The healthcare system is composed of a complex set of entities, activities and processes – at the core of which inevitably are the clinical ones and involves a wide range of participants, each of them carrying to the system a different set of needs, priorities and evaluation criteria (Kanji Quality Culture). Like other business organizations, increasing levels of competition, patient service alternatives, joint ventures, quality initiatives and emphasis on continuous improvement evidences dramatic changes in the operation of healthcare organizations. One of the important changes in today’s healthcare industry, is an increasingly knowledgeable consumer with intensifying demands to have information available for helping them to make appropriate health care decisions. Good management requires reliable and timely information on facts for making decisions. In spite of the unquestionable truth of this statement, there is a prevalent tendency to rely on intuition and opinions and to assume that the organization is “doing the right things right” without any support from facts. Performance measurement provides hospital administrations with hard evidence about existing practices, values, beliefs, and assumptions and enables the administration to develop a systematic means of identifying shortfalls and improve its future performance. This paper starts with the review of some well-known literature

on performance measurement of service sector and a framework has been suggested for performance measurement of healthcare sector. Existing performance measurement frameworks Various authors have suggested different performance measurement frameworks for measuring performance of an organization. Some of the important performance measurement frameworks are discussed below. Balanced performance measurement matrix Keegan et al. (1989) presented a balanced performance measurement matrix. This matrix is simple and easy to use for performance measurement (Neely, 2002). This approach includes the measures like financial as well as non-financial indicators. However, the matrix could have been developed further to incorporate certain element of lead measures, refined, within their dimensions. Lead measures are those measures that focus on analyzing forward looking, predictive and future performance comparisons (Anderson and McAdam, 2004). Further, the matrix does not make explicit links between different dimensions of business performance, which makes the measurement of performance of a system complex. Performance measures for time-based competition Azzone et al. (1991) have attempted to be more prescriptive, by proposing a detailed and specific performance measurement framework based on time. These measures consider internal configuration and external configuration as dimensions of performance that reflect the efficiency and effectiveness of the organization. This framework has the potential to respond to diversity or change and takes into consideration the lead performance dimensions to enable a better competitive advantage. Performance pyramid system The performance pyramid system (PPS) was originally developed by Judson (1990) and later improved by Lynch and Cross (1991). This framework distinctly ties together the hierarchical view of business performance measurement with the business process view (Neely et al., 2001). It is also useful for describing how objectives are communicated down to the troops and how measures can be rolled up at various levels in the organization. This system monitors performance at different levels of organization. It makes clear-cut difference between measures that are of interest to external parties – customer satisfaction, quality and delivery, and measures that are primarily of interest within the business – products, cycle time and waste. Bond (1999) argues that direct personnel measures have not been considered in this approach as well as in balanced scorecard approach. Hudson et al. (2001) outlined the main problem with this approach. He identified that this approach fails to specify the detail relating to the form of measures of performance or the process for developing them, with no apparent scope for lead measures of performance. Balanced scorecard framework Kaplan and Norton (1992) presented balanced scorecard framework for measuring performance of an organization. The balanced scorecard approach allows the

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managers to look at a business from four important perspectives – financial perspective, internal perspective, customer perspective and learning and growth perspective. Neely et al. (2001) identified that the strength of this framework is the way in which it integrates different classes of organizational performance. The balanced scorecard shows a multi-facet view of an organization’s performance (Atkinson and Brown, 2001). This framework explicitly links different dimensions of business performance measurement to organizational strategy and integrates four ways of looking at performance of the organization (Neely, 2002). Anthony and Govindorajan (1998) comprehend that it is a tool for focusing an organization, improving communication, setting organizational objectives and providing feedback on strategy. It also measures how employees performed in relation to corporate strategy. The balanced scorecard is conceptually and intuitively appealing, however, the culture and needs of an organization needs to be considered before designing a balanced scorecard. Neely et al. (1995) states that there is a serious flaw is the absence of competitiveness dimension in this framework, which is also outlined by Fitzgerald et al. (1991). The balanced scorecard also shows a lack of consideration to the measurement of human resources, employee satisfaction, supplier performance, product/service quality, and environmental/community perspective (Brown, 1996; Lingle and Schiemann, 1996; Maisel, 1992). Failure of the scorecard to consider these dimensions limits its comprehensiveness (Neely, 2002). An additional deficiency outlined by Hudson et al. (2001) is the lack of integration between the top level, strategic scorecard and operational level measures, which makes the execution of strategy problematic. Furthermore, it fails to specify a user centered development process. It is evident from the balanced scorecard that some reference is made to lead performance measures within the non-financial dimensions like innovation, learning, and customers. Therefore, lead elements were present in this approach, but were not fully developed. Brown’s input, processes, outputs and outcomes framework This framework is conceptually appealing and useful, as it highlights the difference between input, process, output and outcome measures (Neely et al., 2001). Brown (1996) argues that each stage of this framework is the driver of performance for the next. The framework develops the concept of linking measures through cause and effect relationships. Lead benchmarking can be included within Brown’s input and processing dimensions in order to create better output and outcome goals and results for organizations. Performance prism Neely (2002), and Kennerley and Neely (2001) outlined that the performance prism is a multi-faceted framework, which attempts to address the shortcomings of the frameworks that are currently available. Neely (2002) argues that the performance prism can be considered as a second-generation performance management framework. The framework has been deliberately designed as a highly flexible so that it can provide a broad as well as narrow focus. The performance prism consists of five interrelated perspectives namely stakeholder satisfaction, strategies, processes, capabilities and stakeholder contributions. These five perspectives provide a comprehensive and an integrated framework for thinking about organizational performance. Neely (2002) and Wivel, Senior Partner in

the Danish Arm of Ernst and Young, argued that “It will not be possible to create shareholder value without creating stakeholder value”. The performance prism provides a broader view of stakeholders than the balanced scorecard, which makes reference only to customers and shareholders. In the tomorrow’s company report, the Royal Society of Arts, Manufacturer and Commerce (RSA) suggested that competitive success in future would depend on management taking an inclusive approach in meeting the needs and indeed, requirements of all stakeholders. The performance prism also considers both regulators and pressure groups that are stakeholders with growing significance and power in the current dynamic business environment. The performance prism enables to provide a balanced picture of the business, significantly highlighting external and internal measures, as well as enabling financial and non-financial measures and measures of efficiency and effectiveness (Neely et al., 2001). These could be easily developed into lead measures of organizational performance. Although such performance measurement frameworks are undoubtedly valuable, their adoption is often constrained by the fact that they are simply frameworks. They suggest some areas in which measures of performance might be useful, but provide little guidance on how the appropriate measures can be identified, introduced and ultimately used to manage the business (Medori and Steeple, 2000). Criteria for performance measurement system design The review of the recommendations made by various authors, already mentioned throughout this critique, has been used designing the performance measurement system for healthcare processes. In 1980s and 1990s, the process of deciding what to measure became topical – with several authors discussing it, sometimes in a quite frivolous manner. Keegan et al. (1989) outline three distinct steps for developing performance measurement system: (1) defining strategic objectives of the firm and deciding how they can be translated into divisional goals and individual management actions; (2) deciding what to measure; and (3) installing performance measurement system into management thinking, possibly through the budgeting process. Wisner and Fawcett (1991) suggested a nine-step process for performance measurement system design. This process is similar to that of the process suggested by Keegan et al. (1989), but it makes explicit that the system be regularly reviewed and updated. Kaplan and Norton (1992) paid no attention to the design of performance measurement system, but in 1993 they developed an eight-step process, which they believed that it enables management to design balanced measurement systems. A more dynamic approach to performance measurement design needs to be developed to withstand the evolving changes in organizational performance measures. Beamon (1999) presents a set of characteristics that are found in effective performance measurement systems, and can therefore be used in evaluation of the measurement systems. These characteristics include: inclusiveness (measurement of all pertinent aspects), universality (allow for comparison under various operating conditions), measurability (data required are measurable), and consistency (measures consistent with organization goals). However, the characteristics suggested by Beamon dose not consider applicability, i.e. the extent to which the measurement system is

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applicable. The following characteristics may be considered for the evaluation of the existing performance measurement systems: . inclusiveness; . universality; . measurability; . consistency; and . applicability. On the basis of the above characteristics a comparison may be made between the existing performance measurement frameworks. Proposed framework for performance measurement system Most of the existing performance measurement systems used in organizations lack the flexibility to change as they focus on the past as opposed to the future. In today’s highly dynamic environment, it is not appropriate to view the design and implementation of a performance measurement system as a sequential process. The design, implementation and use of measurements should be a simultaneous and continuously evolving process in which changes in the strategic direction and learning requirements of an organization are constantly accounted for. It ensures a speedy and effective implementation of the formulated strategy (Feurer and Chaharbaghi, 1995). A critical examination of above literatures suggest that a good system of performance measurement should exhibit the following characteristics: . measure performance from a multi and interrelated perspective; . be valid, reliable and easy to use; . be linked to the organization’s value and strategy; . being sensitive to changes in the external and internal environment of an organization i.e. contains lead measures of performance; . enable comparisons to be made and progress to be monitored; and . be based on the critical success factors or performance drivers. According to framework proposed by WHR2000 (WHO, 2000), performance is equivalent to the concept of efficiency. It is a function of the system’s contributions to intrinsic goals taking into account the inputs used to achieve them. The health system contributes towards many outcomes that are socially desirable, including improving health, educational attainment, and individual incomes. After reviewing different performance measurement models, it has been observed that the WHR performance measurement framework includes lead performance measure dimension as well as dimensions, which will show effectiveness parameters. The performance measurement parameters can be categorized into following three categories: (1) efficiency; (2) effectiveness; and (3) flexibility.

The first dimension i.e. efficiency is a parameter that is already included in WHR2000. This parameter measures the output obtained in relation to consumption of input (resources). This parameter also appears in Fitzgerald et al. (1991) model in determinants heading as resource utilization. Efficiency measure deals with the success with which hospital management uses its funds or resources to produce outputs or outcomes. This is measured, wherever possible, in terms of inputs by output. Efficiency may be measured in terms of quantity of output (highest level of output for a given set of inputs) or by cost (least cost or cost of inputs associated with producing a given level of output). The implicit assumption in any such comparison of efficiency is that the quality is comparable. So any assessments must simultaneously draw an analysis of the effectiveness indicators. Efficiency measurement consists of following sub-indicators: . Resource utilization: In case of a hospital where there is in- patient department, bed utilization rate is one such criterion; and . Cost reduction: Service rate can be one of the measures for the same. The second dimension of performance measurement is effectiveness. The review of literatures indicates that effectiveness will include dimensions like customer satisfaction, quality of service etc. In balanced scorecard approach Kaplan and Norton (1992) have also considered these dimensions under different perspective like customer perspective and internal perspective. Effectiveness of a service is indicated by its overall outcomes or impacts. In healthcare context, effectiveness indicates the extent to which an intervention achieves health improvements and can be measured in terms of various outcomes such as cases of disease prevented, years of life saved etc. effectiveness can be measured by measuring the following dimensions: . service quality; . customer satisfaction; . growth; and . safety. Further, these dimensions can be measured by expressing them into measurable units. Service quality of any hospital can be measured by quality of care, quality of clinical investigations, cleanliness of hospital environment etc. Waiting time may be one of the criteria for customer satisfaction measure. In the case of private hospitals (profit organizations) growth can be measured by financial indicator like income, profit of hospital. Safety may be measured by reduction in number of cases of bacterial infection in the hospital due to introduction of efficient infection control system. Different reviewers have suggested that flexibility can also be considered as lead performance measures (Anderson and McAdam, 2004). In manufacturing sector already this dimension has been considered in supply chain by different authors (Beamon, 1999; Chan, 2003). Kaplan and Norton (1992) took the innovation and learning perspective as lead measure in balance scorecard approach. Flexibility is a lead performance measure, which focuses on analyzing forward looking, predictive and future performance comparisons. This can measure a system’s ability or the adaptability to respond to diversity or change. There are very few literatures are available to measure flexibility in service sector, though many researchers have

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identified this dimension as lead performance measure in manufacturing sector. Slack (1991) identified two types of flexibility measures for manufacturing sector: range flexibility and response flexibility. Range flexibility is defined as to what extent the service can be changed. Response flexibility is defined as the ease (in terms of cost, time, or both) with which the service can be changed. On the same line the flexibility measures have been identified that should be included in the proposed framework for its potential to adapt changes: . professional flexibility; . instrument flexibility; . process flexibility; . volume flexibility; . mix flexibility; . expansion flexibility; and . new service flexibility. A performance system shall be so designed that the adaptability of performance measurement system in an organization should not incur high cost. In order to achieve that each dimensions of flexibility can be measured in two ways: one relating to range aspects and other relating to response aspects. Professional flexibility can be measured by type of different (department like orthopedic, pediatric etc.) cases treated by doctors and time or cost or both spent for consulting specialized doctors not available in the hospital. Instrument flexibility can be measured by time saved by particular instrument in conducting test as well as number of tests conducted by a particular instrument. The number of cases that has been transferred to other specialized hospitals and time taken to transfer those cases to other hospital can be used to measure process flexibility. Volume of demand (number of patients) may change and healthcare organization may have to respond quickly and efficiently to this change in (either increase or decrease) in aggregate demand levels. The extent of change and the degree of fluctuations in aggregate output level, which the system can accommodate without incurring high cost or large changes in performance outcomes, can be measured as the volume flexibility. This can be measured with the help of measuring maximum number of patients that can be treated in each department per day and average number of patients treated in each department per day. In a hospital, number of patients visiting different departments may not be same everyday. In a particular day patient workload may be high in a particular department than other departments. This fluctuation in workload may require more number of professionals in that particular department on that day. The additional requirement of professionals in that department may be fulfilled by drawing professionals from the department where the workload is low. The possibility of transferring professionals from one department to other at the time of need gives rise to mix flexibility. Further, it is important to expand the hospital with state of the art technology to sustain its competitive advantage. The hospital may consider number and variety of expansions that can be accommodated without incurring high cost or large changes in performance outcomes. Number of new services that can be launched by the hospital may be one indicator of new service flexibility.

Conclusion Performance measurement system comprise a set of coherent activities designed to enable management to determine, directly or indirectly, how an organizational system is performing – improving or deteriorating, in or out of control – whilst providing information in support of decisions and actions aimed at improving performance of the system. A performance measurement system embraces the things we do to find out how we are doing and decide how we can do better. This paper presents the development of a proposed performance measurement framework for healthcare sector by reviewing various well-known performance measurement frameworks available for service sector. The proposed framework broadly categorizes performance measurement parameters into three categories namely efficiency, effectiveness and flexibility. These parameters are further sub-divided to give a detailed description of these parameters. The first dimension efficiency measures the output obtained in relation to consumption of input (resources). Efficiency measure deals with the success with which hospital management uses its funds or resources to produce outputs or outcomes. Second dimension effectiveness of a service is indicated by its overall outcomes or impacts. In healthcare context, effectiveness indicates the extent to which an intervention achieves health improvements and can be measured in terms of various outcomes such as cases of disease prevented, years of life saved etc. Flexibility, the third dimension, is a lead performance measure, which focuses on analyzing forward looking, predictive and future performance comparisons. This can measure a system’s ability or the adaptability to respond to diversity or change. Further division of these parameters will help the healthcare units to directly use the framework for assessment of their performance. This framework will help the health care organizations to know their performance and also it will help in benchmarking the organization so that customers can know the worth of money they pay for the service. References Anderson, K. and McAdam, R. (2004), “A critique of benchmarking and performance measurement: lead or lag?”, Benchmarking: An International Journal, Vol. 11 No. 5, pp. 465-83. Anthony, R. and Govindorajan, V. (1998), Management Control Systems, McGraw-Hill, New York, NY. Atkinson, H. and Brown, J.B. (2001), “Rethinking performance measures: assessing progress in UK hotels”, International Journal of Contemporary Hospitality Management, Vol. 13 No. 3, pp. 128-35. Azzone, G., Masella, C. and Bertele, U. (1991), “Design of performance measures for time-based companies”, International Journal of Operations & Production Management, Vol. 11 No. 3, pp. 77-85. Beamon, B.M. (1999), “Measuring supply chain performance”, International Journal of Operations & Production Management, Vol. 19 No. 3, pp. 275-92. Bititcti, U.S., Turner, T. and Begemann, C. (2000), “Dynamics of performance measurement systems”, International Journal of Operations & Production Management, Vol. 20 No. 6, pp. 692-704. Bond, T.C. (1999), “The role of performance measurement in continuous improvement”, International Journal of Productions and Operations, Vol. 19 No. 12, pp. 1318-34.

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Brown, M.G. (1996), Keeping Score: Using the Right Metrics to Drive World-Class Performance, Quality Resources, New York, NY. Camarata, J.B. and Camarata, M.R. (2000), “Towards an integrative model: performance measurement in not-for-profit organizations”, in Neely, A. (Ed.), Performance Measurement – Past, Present and Future, Centre for Business Performance, Cranfield School of Management, Cranfield. Chan, F.T.S. (2003), “Performance measurement in a supply chain”, The International Journal of Advanced Manufacturing Technology, Vol. 21, pp. 534-48. Feurer, R. and Chaharbaghi, K. (1995), “Performance measurement in strategic change”, Benchmarking for Quality Management & Technology, Vol. 2 No. 2, pp. 68-83. Fitzgerald, L., Johnston, R., Brignall, T.J., Silvestro, R. and Voss, C. (1991), Performance Measurement in Service Businesses, The Chartered Institute of Management Accountants, London. Hudson, M., Smart, A. and Bourne, M. (2001), “Theory and practice in SME performance measurement systems”, International Journal of Operations & Productions Management, Vol. 21 No. 8, pp. 1096-115. Judson, A.S. (1990), Making Strategy Happen, Transforming Plans into Reality, Basil Blackwell, London. Kaplan, R.S. and Norton, D.P. (1992), “The balanced scorecard: measures that drive performance”, Harvard Business Review, January/February, pp. 71-9. Keegan, D.P., Eiler, R.G. and Jones, C.P. (1989), “Are your performance measures obsolete?”, Management Accounting, June, pp. 45-50. Kennerley, M. and Neely, A. (2001), “Enterprise resource planning: analyzing the impact”, Integrated Manufacturing Systems, Vol. 21 No. 2, pp. 103-18. Lingle, J.H. and Schiemann, W.A. (1996), “From balanced scorecard to strategy gauge: is measurement worth it?”, Management Review, March, pp. 56-62. Longenecker, C.O. and Fink, L.S. (2001), “Improving management performance in rapidly changing organizations”, Journal of Management Development, Vol. 20 No. 1, pp. 7-18. Lynch, R. and Cross, K. (1991), Measure Up! Yardsticks for Continuous Improvement, Blackwell, Oxford. Maisel, L.S. (1992), “Performance measurement: the balanced scorecard approach”, Journal of Cost Management, Vol. 5 No. 2, pp. 47-52. Medori, D. and Steeple, D. (2000), “A framework for auditing and enhancing performance measurement systems”, International Journal of Operations & Production Management, Vol. 20 No. 5, pp. 520-33. Nani, A.J., Dixon, J.R. and Vollmann, T.E. (1990), “Strategic control and performance measurement”, Journal of Cost Management, Summer, pp. 33-42. Neely, A. (2002), Business Performance Measurement, Theory and Practice, Cambridge University Press, Cambridge. Neely, A., Adams, C. and Crowe, P. (2001), “The performance prism in practice measuring excellence”, The Journal of Business Performance Management, Vol. 5 No. 2, pp. 6-12. Neely, A., Gregory, M. and Platts, K. (1995), “Performance measurement system design: a literature review and research agenda”, International Journal of Operations & Productions Management, Vol. 15 No. 4, pp. 80-116. Slack, N. (1991), The Manufacturing Advantage, Mercury Books, London. WHO (2000), WHR2000, World Health Organization, Geneva.

Wisner, J.D. and Fawcett, S.E. (1991), “Link firm strategy to operating decisions through performance measurement”, Production and Operations Management Journal, Vol. 32 No. 3, pp. 5-11. Further reading Allen, D. (1995), “Observable stances”, Management Accounting, Vol. 73, pp. 20-2. Ballantine, J. and Brignall, S.J. (1995), “A taxonomic framework for performance measurement”, paper presented to the 18th Annual Congress of the European Accounting Association, Birmingham, May. Brown, M.G. (1994), “Is your measurement system well-balanced?”, Journal for Quality and Participation, Vol. 17, pp. 6-11. Hazell, M. and Morrow, M. (1992), “Performance measurement and benchmarking”, Management Accounting, December 9, pp. 44-5. Laitinen, E.K. (2002), “A dynamic performance measurement system: evidence from small Finnish technology companies”, Scandinavian Journal of Management, Vol. 18, pp. 65-99. Letza, S.R. (1996), “The design and implementation of the balanced business scorecard: an analysis of three companies in practice”, Business Process Re-engineering & Management Journal, Vol. 2 No. 3, pp. 54-76. About the authors Shankar Purbey is pursuing his PhD from Department of Management Studies Indian School of Mines, Dhanbad. He is the recipient of a National Doctoral Fellowship Award during his research at the Indian School of Mines Dhanbad. Shankar Purbey is the corresponding author and can be contacted at: [email protected] Professor Kampan Mukherjee is Chair of Professor and he is the Founder Head of the Department of Management Studies. Dr Mukherjee was under visiting assignment at Paris as Senior Scientist Fellow of French Government in 1998 and at Curtin Business School, Australia in 2001. He taught in management programs as Visiting Professor at Germany in 2000-2001 and also in 2004. Dr Mukherjee delivered talks in various universities of Europe. His research papers have been published in Indian and International journals like, Omega, European Journal of Operations Research, International Journal of Production Economics, etc. He is reviewer for reputed journals like International Journal of Production Economics, International Transactions of Operations Research, Vision and IIMB Management Review. Dr Chandan Bhar has 20 years of teaching experience and actively engaged in consultancy and research in the areas of Long-Range Planning, System Dynamics and Productivity Management. Prior to joining this institute, he served Coal India Limited for approximately seven years. He has undertaken two research projects financed by AICTE, GOI and ISM, Dhanbad, India in the areas of productivity improvement in coal mining industry and development of computerized safety management system for collieries for. He has been guiding several research scholars in the areas of long-range planning for the coal industry, as well as for technical education sector, performance assessment of service sector industries, technology transfer in small-scale industries etc.

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