My blog discusses how portfolio owners can use simple risk information to gain crucial insight into portfolio health, forecast future performance with greater certainty and maximise the value delivered from the portfolio.

Why Risk Management

The Association for Project Management (APM) in its Project Risk Analysis and Management (PRAM) guide articulates several 'hard' and 'soft' benefits of risk management:

According to ISO 31000, risk management process is a "systematic application of management policies, procedures and practices to the tasks of communication, consultation, establishing the context, identifying, analysing, evaluating, treating, monitoring and reviewing risk".

ISO 31000 consists of 11 key principles which view risk management as an elementary process of generating success of the organization. These eleven principles can be regarded as the "essential qualities" required for risk management.

• Principle 1: Risk management creates and protects value
• Principle 2: Risk management is an integral part of the organizational procedure
• Principle 3: Risk management is part of decision making
• Principle 4: Risk management explicitly addresses uncertainty
• Principle 5: Risk management is systematic, structured and timely
• Principle 6: Risk management is based on the best available information
• Principle7: Risk management is tailored
• Principle 8: Risk management takes human and cultural factors into account
• Principle 9: Risk management is transparent and inclusive
• Principle 10: Risk management is dynamic, iterative and responsive to change
• Principle 11: Risk management facilitates continual improvement and enhancement of the organization.

Many excellent definitions for 'risk' and 'risk management' exist and I do not seek to analyse each definition in this blog. In embarking on a structured approach to risk management, each organisation should determine the benefits that they aspire to realise from management of risk and should monitor the degree to which their chosen approach is delivering these benefits.

My blog will examine the benefits of risk management from the point of view of managing a portfolio of capital projects, both in delivering the projects themselves and in controlling the portfolio as a whole.

The eventual completion date and cost at completion of capital projects is inherently uncertain whether the project is yet to be sanctioned or is underway. The same can be said for the timescale and costs of delivering milestones within each project. Decisions made not only within the project (how to allocate resources, how to schedule tasks etc.) but also externally to projects (which projects to authorise and fund, when to speed up or slow down projects, which projects to terminate or replace) are affected by this uncertainty. Taking account of the uncertainty facing projects and portfolios in a structured and preferably quantified way presents decision makers with more information to support their decisions and with which to achieve strategic objectives (and objectives of stakeholders).

Particularly from a portfolio point of view (that is, externally to project delivery), decision makers have relatively few 'levers' with which they can influence their portfolio. They can approve and fund new projects, change the sanction parameters of existing projects (cost limit, required completion date), change the output required from a project (i.e. change the deliverables), terminate a project or replace one project with another (which is essentially an extreme sanction envelope and output change). Each of these decisions or interventions should be made with as much information as possible on how the decision will affect the portfolio not just according to plan but also taking into account the possible upside or downside that could be realised. A view of risks facing each project, and how those risks might impact cost and delivery schedule of the project are essential to understanding the status of the portfolio as a whole. This project-by-project view of risks must be gathered systematically and in such a way as to limit bias in any risk based forecasts that are made. Identifying common risks and linkages between risks across projects is increasingly being embraced as a value adding function of portfolio management.

Structured risk management processes can be an extremely effective tool, not only for uniting diverse groups within project teams or businesses but also for bringing together stakeholder groups both within and outside the portfolio owning organisation. Such stakeholders may include customers, users, suppliers, regulators, investors and affected third parties. A transparent and widely publicised risk management process and high quality risk information allows all stakeholders to understand the uncertainties to which project outcomes and portfolio delivery are subject. It also allows discussions to take place on the basis of shared information and provides a much greater chance of mitigating risks by tackling them at source.

A culture of open disclosure of risk information increases the amount of information available to all those making decisions about the progression of a project or a portfolio of projects, whether within the project team itself, the portfolio owning organisation or the stakeholder community.

NOTE: There is an interesting side discussion to be had on what constitutes a 'portfolio owning organisation'. An initial definition could be those organisations funding the delivery of projects. A revision to this could include those with some form of formally recognised claim on the benefits arising from completion of the project. A further revision could include those stakeholders that will realise any sort of benefit from the delivery of a project, including unintended or unplanned benefits or benefits that are not material to those funding the project. This may have implications on the composition and terms of reference of portfolio boards, particularly where establishing or strengthening risk culture is an objective of the portfolio board.

Financial Management and Risk Based Forecasting for Portfolios

It is common to use Monte Carlo analysis and other techniques to produce quantitative forecasts of how much a project will cost at completion and when the project will reach completion. Regardless of the technique chosen the quality of the outputs of any such analysis rests on the quality of the data on which the analysis is based. In Monte Carlo analysis of project cost and schedule commonly considered factors include:

• A project schedule articulating the sequences of activities to be undertaken and how these activities logically relate to each other. It is worth noting that the sequence of activities is itself an important assumption on which any quantitative analysis is based. If the activity sequence changes significantly (as project schedules often do during delivery!) any previous quantitative analysis may lose validity. It is worth considering, therefore, the appropriate level of detail to use when carrying out such an analysis
• A cost information forecast, for example, against the project's Work Breakdown Structure (WBS). The same argument about project schedule changes also applies to WBS changes
• A risk register which articulates risk events or other uncertainties that may affect delivery time or cost.

Assumptions on how uncertain factors are related to each other. For example, if a risk exists that 'Supplier A' may take longer than expected to dig 'trench A' it would be reasonable to assume that the risk of 'Supplier A' taking longer than expected to dig 'trench B' is related. Where schedule activities, WBS elements or risks have common uncertainties there are grounds for looking at the degree to which the outcome of one element may affect another (or the degree to which two elements are mutually affected by some other factor). This correlation of uncertainty is extremely important when carrying out quantitative analysis of any sort. Failure to model relationships between uncertain elements (which is equivalent to making a fallacious assumption that elements are completely independent) may result in forecasts that dramatically underplay both upside and downside cost and schedule; this could therefore result in portfolio owners taking much more risk than they realise.

A quantitative analysis will produce confidence figures for the timescale and cost to which the project (and possible individual milestones) might be delivered. The information is often presented textually (e.g. there is a 10% chance that the project will be delivered for less than £16M and a 90% chance that the project will be delivered for no more than £25M) or graphically:

In addition, high quality quantitative forecasts provide additional information on which project factors have the greatest influence on total cost and schedule duration. The analysis would highlight those risks, tasks or WBS elements that are the main drivers of increased cost or time.

This information provides project managers, project directors and other senior management with forecasts of the likely level of expenditure required to take a project through to completion and the timescale over which this expenditure will be required. Project managers and project staff can use these forecasts to better prioritise effort and attention on those areas that might have the greatest beneficial impact on the project.

Forecasting Portfolio Costs

Adopting a consistent methodology for generating quantitative risk based forecasts of project cost and schedule will provide portfolio owners with more information to support decision making on portfolio interventions. Consistent forecasts across a portfolio will assist in determining whether a project's original sanction parameters remain valid, in particular whether the value proposition on which the project was authorised for funding is in jeopardy. This may support decisions on accelerating or delaying projects, or indeed on project cancellation or change of sanction envelope.

A portfolio of projects is rarely static. Businesses that are able to authorise new projects (in response to portfolio developments, changes in customer need or identification of opportunities for value creation) will be able to maximise the value of their investment in project delivery; this is achieved through changing the allocation of their capital according to where the balance of risk and return are optimised in line with the risk appetite and tolerance of the business. Portfolio owners should, therefore, apply the same quantitative risk based forecast of cost and schedule to projects yet to be sanctioned.

Consistent quantitative risk based forecasts across a portfolio of ongoing and candidate new projects provides portfolio owners with rich information with which to make decisions. The ability to model 'what if' scenarios using this information is a powerful tool for putting together an optimal project portfolio. This forecast information can be used to model different scenarios and observe the likely effect on portfolio level metrics such as:

• • Annual spend
• • Likelihood of exceeding annual budget in future years
• • Year on year likely spend over a period of time
• • Expected annual underspend
• • Excessive risk of overspend in a given year or accounting period.

The model should also illustrate the effect on portfolio level forecasts of making various decisions:

• • Moving projects in time (delaying or bringing forward start date)
• • Speeding up or delaying the rate of project execution (also known as crashing and relaxing projects)
• • Cancelling projects
• • Authorising new projects.

Initial Portfolio Forecast In this scenario we have an initial portfolio of current (Projects A, B, C) and planned projects each of which has its own quantitative cost and schedule forecast. From these we can generate a portfolio view of completion dates for all projects and likely annual spend. In this example, expenditure will finish in 2018, and there is approximately a 75% likelihood that the portfolio will require more than £20M of expenditure in 2013.

We might imagine the scenario where the portfolio owner has an annual budget of £20M up to the end of 2017 when all project should be complete and any cash not spent in a given year is not rolled over to the next year. In this case, authorising additional projects looks like a good use of the budget (providing those projects will provide a suitable return on investment).

Portfolio Forecast With New Project Introduced In the second scenario, we look at the impact on the portfolio of authorising a new project, 'Project K', scheduled to start in September 2014 and costing £20M. However, rather than use up the underspend efficiently, there are now two years (2013 and 2016) where the £20M budget is more than 75% likely to be exceeded and in 2014 and 2017 a significant underspend still exists. The portfolio will be complete in 2018, but having spent hardly any of that year's budget.

Balanced Portfolio In this scenario changes have been made to project start dates, and in some cases project execution rates, in order to balance the annual append of the portfolio. There is approximately a 50% chance in each year that the £20M budget will be used and a 75% chance that all projects will have been completed by the end of 2017. As well as providing a more balanced portfolio of projects, this approach provides valuable decision making information to management.

Decision Supporting Not Decision Making

It is imperative to remember that optimising delivery timescales and annual spend is only one aspect of good portfolio management. Any decision to bring forward, delay, accelerate or slow down projects to control spend must be done in the context of overall project and portfolio value, regulatory constraints, contract terms and resource availability. Meeting budget expectations on a portfolio that cannot accomplish delivery of value to stakeholders should not be an objective!

However, portfolio based forecasting provides rich but simple information by which the health of the portfolio can be monitored as part of robust portfolio management and through which clear information can be communicated to senior management. Information such as "over the next 5 years we have less than a 5% chance of exceeding budget in any year and a 90% chance that all projects will be delivered by end Dec 2016" provides simple, meaningful insight that a project by project analysis of individual projects would not provide.

The first step for any enterprise looking for greater insight into the future performance of their projects and portfolios is to establish a strong risk culture in their teams. On the foundation of strong culture, good quality information and simple analysis will provide rich insight into future performance that is easy to understand and therefore capable of driving better decision making.

To discuss these and related issues that affect your business, contact Jim Morrison