Risk evaluation

There is a risk that software might exceed the original specification and that a project will be completed early and under budget. That is not a risk that need concern us.

Every project involves risk of some form. When assessing and planning a project, we are concerned with the risk of the project's not meeting its objectives. In Chapter 8 we shall discuss ways of analysing and minimizing risk during the development of a software system. In this chapter, we are concerned with taking risk into account when deciding whether to proceed with a proposed project.

Risk identification and ranking

In any project evaluation we should attempt to identify the risks and quantify their potential effects. One common approach to risk analysis is to construct a project risk matrix utilizing a checklist of possible risks and to classify each risk according to its relative importance and likelihood. Note that the importance and likelihood need to be separately assessed - we might be less concerned with something that, although serious, is very unlikely to occur than with something less serious that is almost certain. Table 3.7 illustrates a basic project risk matrix listing some of the risks that might be considered for a project, with their importance and likelihood classified as high (H), medium (M), low (L) or exceedingly unlikely (—). So that projects may be compared the list of risks must be the same for each project being assessed. It is likely, in reality, that it would be somewhat longer than shown and more precisely defined.

The project risk matrix may be used as a way of evaluating projects (those with high risks being less favoured) or as a means of identifying and ranking the risks for a specific project. In Chapter 7 we shall consider a method for scoring the importance and likelihood of risks that may be used in conjunction with the project risk matrix to score and rank projects.

Risk and net present value

Where a project is relatively risky it is common practice to use a higher discount rate to calculate net present value. This addition or risk premium, might, for example, be an additional 2% for a reasonably safe project or 5% for a fairly risky one. Projects may be categorized as high, medium or low risk using a scoring method and risk premiums designated for each category. The premiums, even if arbitrary, provide a consistent method of taking risk into account.

Cost-benefit analysis

A rather more sophisticated approach to the evaluation of risk is to consider each possible outcome and estimate the probability of its occurring and the corresponding value of the outcome. Rather than a single cash flow forecast for a project, we will then have a set of cash flow forecasts, each with an associated probability of occurring. The value of the project is then obtained by summing the cost or benefit for each possible outcome weighted by its corresponding probability. Exercise 3.7 illustrates how this may be done.

Table 3.7 A fragment of a basic project risk matrix




Software never completed or delivered



Project cancelled after design stage



Software delivered late



Development budget exceeded < 20%



Development budget exceeded > 20%



Maintenance costs higher than estimated



Response time targets not met



BuyRight, a software house, is considering developing a payroll application for Exercise 3.7

use in academic institutions and is currently engaged in a cost-benefit analysis.

Study of the market has shown that, if they can target it efficiently and no competing products become available, they will obtain a high level of sales generating an annual income of £800,000. They estimate that there is a 1 in 10

chance of this happening. However, a competitor might launch a competing application before their own launch date and then sales might generate only

£ 100,000 per year. They estimate that there is a 30% chance of this happening. The most likely outcome, they believe, is somewhere in between these two extremes -

they will gain a market lead by launching before any competing product becomes available and achieve an annual income of £650,000. BuyRight have therefore calculated their expected sales income as in Table 3.8.

Total development costs are estimated at £750,000 and sales are expected to be maintained at a reasonably constant level for at least four years. Annual costs of marketing and product maintenance are estimated at £200,000, irrespective of the market share gained. Would you advise them to go ahead with the project?

This approach is frequently used in the evaluation of large projects such as the building of new motorways, where variables such as future traffic volumes, and hence the total benefit of shorter journey times, are subject to uncertainty. The technique does, of course, rely on our being able to assign probabilities of occurrence to each scenario and, without extensive study, this can be difficult.

When used to evaluate a single project, the cost-benefit approach, by 'averaging out' the effects of the different scenarios, does not take account an organization's reluctance to risk damaging outcomes. Because of this, where overall profitability is the primary concern, it is often considered more appropriate for the evaluation of a portfolio of projects.

Risk profile analysis

An approach which attempts to overcome some of the objections to cost-benefit averaging is the construction of risk profiles using sensitivity analysis.

Table 3.8 Buy Right \s income forecasts


Probability P

Expected Value (£) i xp













Expected Income


This involves varying each of the parameters that affect the project's cost or benefits to ascertain how sensitive the project's profitability is to each factor. We might, for example, vary one of our original estimates by plus or minus 5% and recalculate the expected costs and benefits for the project. By repeating this exercise for each of our estimates in turn we can evaluate the sensitivity of the project to each factor.

By studying the results of a sensitivity analysis we can identify those factors that are most important to the success of the project. We then need to decide whether we can exercise greater control over them or otherwise mitigate their effects. If neither is the case, then we must live with the risk or abandon the project. For an explanation of the Sensitivity analysis demands that we vary each factor one at a time. It does not Monte Carlo technique easily allow us to consider the effects of combinations of circumstances, neither see any textbook on does it evaluate the chances of a particular outcome occurring. In order to do this operational research. we need to use a more sophisticated tool such as Monte Carlo simulation. There are a number of risk analysis applications available (such as @Risk from Palisade) that use Monte Carlo simulation and produce risk profiles of the type shown in Figure 3.4.

Projects may be compared as in Figure 3.4, which compares three projects with the same expected profitability. Project A is unlikely to depart far from this expected value compared to project B, which exhibits a larger variance. Both of these have symmetric profiles, which contrast with project C. Project C has a skewed distribution, which indicates that although it is unlikely ever to be much more profitable than expected, it is quite likely to be far worse.

Using decision trees

The approaches to risk analysis discussed previously rather assume that we are passive bystanders allowing nature to take its own course - the best we can do is to reject over-risky projects or choose those with the best risk profile. There are many situations, however, where we can evaluate whether a risk is important and, if it is, indicate a suitable course of action.

Many such decisions will limit or affect future options and, at any point, it is important to be able to see into the future to assess how a decision will affect the future profitability of the project.

Prior to giving Amanda the job of extending their invoicing system, IOE must consider the alternative of completely replacing the existing system - which they

All three projects have the same expected profitability.

The profitability of project A is unlikely to depart greatly from its expected value (indicated by the vertical axis) compared to the likely variations for project B. Project A is therefore less risky than project B.

expected profitability profitability

Figure 3.4 A risk analysis profile.

will have to do at some point in the future. The decision largely rests upon the rate at which their equipment maintenance business expands - if their market share significantly increases (which they believe will happen if rumours of a competitor's imminent bankruptcy are fulfilled) the existing system might need to be replaced within 2 years. Not replacing the system in time could be an expensive option as it could lead to lost revenue if they cannot cope with the increase in invoicing demand. Replacing it immediately will, however, be expensive as it will mean deferring other projects that have already been scheduled.

They have calculated that extending the existing system will have an NPV of £57,000, although if the market expands significantly, this will be turned into a loss with an NPV of -£100,000 due to lost revenue. If the market does expand, replacing the system now has an NPV of £250,000 due to the benefits of being able to handle increased sales and other benefits such as improved management information. If sales do not increase, however, the benefits will be severely reduced and the project will suffer a loss with an NPV of -£50,000.

The company estimate the likelihood of the market increasing significantly at 20% - and, hence, the probability that it will not increase as 80%. This scenario can be represented as a tree structure as shown in Figure 3.5.

The analysis of a decision tree consists of evaluating the expected benefit of taking each path from a decision point (denoted by D in Figure 3.5). The expected value of each path is the sum of the value of each possible outcome multiplied by its probability of occurrence. The expected value of extending the system is therefore £40,000 (75,000 x 0.8 - 100,000 x 0.2) and the expected value of replacing the system £ 10,000 (250,000 x 0.2 - 50,000 x 0.8). IOE should therefore choose the option of extending the existing system.

This example illustrates the use of a decision tree to evaluate a simple decision at the start of a project. One of the great advantages of using decision trees to



Figure 3.5 A decision tree.

Expansion 0.2


Dog Bandana Pattern Template




No expansion




model and analyse problems is the ease with which they can be extended. Figure 3.6 illustrates an extended version of Amanda's decision tree, which includes the possibility of a later decision should they decide to extend the system and then find there is an early market expansion.

The net present values shown in italic are those identified in Amanda's original decision tree shown in Figure 3.5.

Pmp Decision Tree
Figure 3.6 An extension to Amanda's decision tree.

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Project Management Made Easy

Project Management Made Easy

What you need to know about… Project Management Made Easy! Project management consists of more than just a large building project and can encompass small projects as well. No matter what the size of your project, you need to have some sort of project management. How you manage your project has everything to do with its outcome.

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