Published in the Project Post-Gazette, January 2014
by Paul Lohnes, MBA, PMP
Many Project Managers (PM) are not seeing the value of risk management on their projects. What we have seen, if risk management is done, many times it stops at the collection of risks and a qualitative prioritization of these risks. The concern we are hearing is the prioritization is done by guess and “gut feeling” thus not supporting the challenge a PM may need to make in requesting the modification of a project’s primary constraints from senior management. The type of risk analysis or for that matter any type of analysis on most projects is easily placed in the qualitative arena where the results are from small sample sizes, observations of human reactions, and the type of reasoning referred to as inductive – the specific to the general. However, if the PM were well read in the art and science of business analysis, it would be very clear that most forms of project qualitative analysis does not have the quality of soundness or validity to support most inductively drawn conclusions.
The definition of qualitative analysis may help us to understand its place in project risk management as well as its limitations: “qualitative analysis is primarily the use of subjective judgment based on nonquantifiable data obtained from the observation of human interactions thus limiting the data set to small, specifically defined samples resulting in the use of inductive reasoning to draw conclusions or make decisions.” In other words, qualitative analysis does use small samples, subjective judgment, and inductive reasoning that attempts to draw conclusions about the general nature of the aspect under interest from the specific observations of its experiments. As we mentioned previously – gut feeling. Now the use of qualitative analysis for risk management is still useful if the PM and project team understand the above limitations and weaknesses. However, qualitative analysis is much easier to perform, can provide suitable answers when used by a knowledgeable expert, and is usually much less time consuming in its completion than other forms of analysis. The fixation on qualitative analysis for project risk management is what may be hampering the effective and efficacious application of risk management. The solution is to use other forms of analysis such as quantitative.
Quantitative analysis is quite a different beast and the mere mention of it tends to cause most PM to shudder and begin thinking of ways to dismiss its use not because of its value but more that they are not familiar with its principles and concepts. Quantitative analysis is simply the application of objective, statistically valid and verifiable methods that utilize the techniques of mathematical disciplines primarily in the statistical and probability sciences. Quantitative analysis, unlike qualitative analysis, operates more effectively when large datasets are available for analysis by the mathematical techniques; however, this is not always a hard requirement. The PPG has presented the use of quantitative analysis on small datasets in previous issues.
When analyzing project risk potentials, the PM will be best served if a combination of analysis techniques are utilized; if the application of quantitative analysis precedes the application of qualitative analysis – which is in opposition to the PMI’s PMBOK® Guide’s Chapter 11: Project Risk Management. The reason for this difference is that the PMI chose the order of qualitative before quantitative analysis when the advent and power of desktop computing had not yet been felt. Given today’s computing power and availability this restriction and order should now be remedied. We at the PPG highly suggest that PM and risk managers (RM) utilize the available techniques of quantitative analysis on ALL risk potentials before the use of qualitative analysis is applied to their prioritization. The results of the quantitative analysis can significantly improve the use of qualitative analysis and thereby increase the value of risk management to their projects.
The analysis of risk potentials regardless of the type of analysis must provide the answers to two primary questions:
- What is the probability of occurrence for this risk potential?
- What is cost of impact if this risk potential should trigger into reality?
The answers to these questions must be more than the current suggested qualitative type of cardinality of 1 to 5 where 1 is a low value and 5 is the highest so that a rank ordering can be performed. This simplistic assessment of a risk’s probability of occurrence and cost of impact is just too childish given our current level of technology and easily deployed sophistication of mathematical tooling.
Quantitative analysis methods are very easily understand, utilized, and deployed by most every PM that has at least the minimum of a copy of Microsoft’s Excel spreadsheet program. With this very easy to use application the following quantitative analysis methods and techniques can be used by most PM or business analysts (BA) to improve the quality and accuracy of estimates, predictions, and simulations:
- Linear regression analysis
- Multivariate regression analysis
- Linear programming
- Monte Carlo simulation
- Variance analysis
- Gap analysis, and
- Goodness-of-fit testing
There is no longer any need to be fearful of using such techniques as they are quite safe and easy to master. The PPG is and will continue to provide simple to follow ‘how to’ discussions on each of these techniques after which this column will illustrate how to apply them specifically to the improvement of your risk management program. The first technique, linear regression analysis, has already be discussed beginning in the October 2013 PPG.
Return to read how these quantitative analysis techniques can be directly applied to your current project’s risk management activities.