Palisade Risk Conference Introduction to Schedule Risk Analysis using a Risk Driver Approach

Sydney, 20 & 21 October 2009 Presenter: Michael Brink

TBH CAPITAL ADVISERS CAPITAL ADVISERS

CAPITAL ADVICE FOR THE LIFE OF THE PROJECT

Objectives and Purpose • Purpose of presentation is to provide an introduction to Schedule Risk Analysis as a tool to understand project schedule and completion risk and to introduce the risk driver approach to Schedule Risk Analysis • The Risk Driver approach to Schedule Risk Analysis in the presentation draws largely on approach outlined in the text “Practical Schedule Risk Analysis” by David Hulett.

Scope and Limitations of Presentation • Time allocated is about 45 minutes so presentation is necessarily high level • Assumption is attendees have some familiarity with Schedule Risk Analysis via tools such as @RISK for MS Project (ideally sat through Rishi’s MS Project @RISK presentation yesterday?) • Hopefully provides enough of the flavour of the risk driver approach • Anyone seeking a more detailed discussion I am in the process of developing a 2 day hands on workshop on this topic

Critical Path Method (CPM) raises a number of issues” • Experience indicates that CPM scheduling does not always reliably identify the path that ultimately determines project completion date • Possible drivers of this are: – – – –

Project Scheduling by is nature is a difficult discipline Rules of Scheduling complex Often owners/manager set unrealistic deadlines Historically schedules have used point estimates for duration i.e. deterministic approach

• Schedule Risk Analysis offers an approach that can address some of the inherent CPM weaknesses. • Risk Driver Approach is a further refinement to Schedule Risk Analysis that focuses on specific risks driving schedule risk

Questions that Schedule Risk Analysis seeks to answer • What is the likelihood of achieving target completion dates • What level of contingency time should be allowed to provide a level of completion certainty acceptable to the project owners • Where are the greatest risks in the project schedule

Dealing with Schedule Uncertainty “There are no facts about the future” • Uncertainty in project schedule duration arises primarily due to: – uncertainty due to estimation error; and – uncertainty due to risks and impact on schedule durations

• The Risk Driver Approach to Schedule Risk Analysis is focused on explicitly analysing schedule uncertainty arising from these two sources

Dealing with Schedule Uncertainty Uncertainty arising from Estimation Error

• Activity duration usually estimated based on: – Knowledge of work done – Resources available – Productivity of resources available – Reliance on other parties

• Expressed in terms of: – Percentage below and above – E.g. -10% +15%

Dealing with Schedule Uncertainty Uncertainty arising from Project Risks

• Project Risks leading to schedule uncertainty include: – Technology risk – Resource availability risk – Resource productivity risk – Supplier performance or delivery risk – Regulatory risk – Schedule Completion pressure

Applying Monte Carlo analysis to Schedule analysis • Activity duration best represented by probability distribution • Selecting best/most suitable probability distributions beyond scope of this presentation (triangular distribution is used in all following examples) but usual options are: – – – –

Triangular Beta distribution Normal Uniform

Visualising random sampling from a triangular distribution (Lotto model)

Best Case

Most Likely

Worst Case

Monte Carlo Random Sampling visualised For each input distribution each Monte Carlo iteration involves a single random draw from the bucket of balls

Applying Monte Carlo analysis

Typical Schedule Risk Analysis outputs Distribution for Complete/Finish 1 X