Crossing the CASM: Why Complexity Matters in Risk Management

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.