Stephen Cresswell: Director, Into Risk
From: The Terry Bishop Award's 2011
14 November 2011 Management channel
A number of my assignments have been to conduct regular updates on forecasts for projects. During these I saw that the updates would frequently see the probabilities and impacts of the identified risks creeping up over time. The reasons for this were that the inputs were driven by the same events and risks were impacting each other. Often newly identified items would be spin offs or secondary risks from other impacts. There seemed to be a cascading or chain like effect that is very hard to stop or reverse once the project is running at full steam. The development process was basically a creative problem solving exercise: why is this happening and what can be done to improve the situation?
The Terry Bishop Award has been launched in 2011 to commemorate the contribution Terry Bishop made to the Project Controls profession. Terry, a former President of ACostE instigated the collaborative partnership between the Association of Cost Engineers and The IET.
Corporate processes and Enterprise Risk Management (ERM) systems generally ignore complexity when forecasting. This means that highly optimistic forecasts are produced routinely and as a matter of course; with serious financial, reputation and governance consequences. This also means that opportunities to reduce exposure are persistently missed, and competitive advantage lost. Common practice methodology for forecasting involves summing the values for individual inputs using a 'Simple Addition' approach. Simple Addition assumes component items are unconnected. Such forecasts do not recognise that inputs may have root causes in common ('Cause Association') and that the scenario or project being forecast is an interlinked system with behaviours that may not be linear or straightforward ('Systemic Mechanisms'). Where complexity in the form of Cause Association and Systemic Mechanisms (CASM) is present, but the Simple Addition approach is used, a highly significant optimistic bias is introduced. Experience shows that low levels of CASM can lead to 10-50% cost overruns, high levels can lead to 100-500% overruns and, anecdotally, 1,000% and more. Conceptually, the error rises disproportionately with the presence and strength of both.