SCHALK GROBBELAAR Projects fail when they don't meet expectations. Therefore, assigning confidence levels to expectations could assist us with reducing uncertainty and increasing transparency
Projects are inherently uncertain undertakings with numerous accounts of failed projects evidence of this, leading University of Pretoria senior lecturer Schalk Grobbelaar to pose the question of how it can be ensured that projects meet expectations.
“Historically, project risk management has focused on preventing ‘bad things’ from happening. The process would start with identifying everything that could go wrong and assigning a probability and consequence to each event. This would usually lead to a long list of potential hazards that need to be prioritised and actioned. Risk standards, however, have moved on,” he states.
As an example, he outlines that the Project Management Body of Knowledge book includes ‘The Standard for Risk Management in Portfolios, Programs, and Projects’.
The book describes risk as an “uncertain event or condition that, if it occurs, has a positive or negative effect on one or more objectives”.
Positive risks are considered opportunities, while negative risks are regarded as threats. The ISO 31 000 Risk Management — Guidelines define risk as “the effect of uncertainty on objectives”. The focus has changed from managing hazards to managing uncertainty, Grobbelaar explains.
He adds that a question regularly asked in project risk management is how much contingency should be added to a project management budget.
“Some project managers use a simple rule of thumb and advise 20%. However, does this consider the uncertainty associated with a specific project? A much better question would be how much confidence one has that the project will be completed within the expected budget, and at what is the acceptable level? As a project progresses, project managers are regularly questioned whether they will still meet the target. However, it would be better to assign a confidence level to this estimation.”
Grobbelaar states that one of the most significant risks commonly ignored during projects is team members’ lack of transparency owing to their instinctive desire not to disappoint their superiors.
To emphasise this point, Grobbelaar points out a quote by licensed psychotherapist Sharon Martin: “Our need to please is actually more of a need to belong, and our need to belong was probably written in our DNA millions of years ago”.
Grobbelaar states that, fortunately, risk managers have developed useful tools to assist with these challenges, with the first tool being the Monte Carlo method.
The Monte Carlo method uses random sampling to determine a distribution of expected values numerically. Typically, three input values (best case, expected case, and worst case) for every cost item are sufficient for the model. This approach motivates team members to provide pessimistic and optimistic expectations.
The model’s output can be used to ascertain the uncertainty associated with the project. If the project has a high level of uncertainty or the confidence level is not acceptable, then the team can focus their efforts on reducing the variability in the input values. This approach changes the team’s mindset from managing risks to managing expectations.
“Projects fail when they don’t meet expectations. Therefore, assigning confidence levels to expectations could assist us with reducing uncertainty and increasing transparency,” Grobbelaar concludes.