Decision-makers often report that models that are presented to them are sub-optimal, often because:
- The decisionmakers require specific functionality within the model, or to be able to address issues that may have been excluded or overlooked in existing approaches. Typically, this may involve improving the alignment of the model with a decisionmaker’s thought processes, the need for additional functionality and flexibility, whilst controlling complexity. Further, there may be a need to use risk modelling techniques, the ability to rapidly bring in new data sets, run optimisation algorithms, time-shifting cash flows or production volumes, or the ability to easily update a forecasting model as actual reported figures arrive.
- The models are excessively complex or large, lack transparency and are not user-friendly. This may arise when models have developed over time, by several people, and without there having been any real serious efforts to adapt the model during these stages. Indeed, even models built by people with extremely good knowledge of Excel functionality are often built in ways that are too complex and do not sufficiently follow best practice principles. Thus, the re-building of (complex) models often involves make them “as simple as possible, but no simpler”.
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