Unilever uses Palisade’s DecisionTools Suite software to inform decisions on innovation
In recognition that the decisions it needs to make around business-critical innovation are highly complex, global fast moving consumer goods supplier Unilever developed its Decision Making Under Uncertainty (DMUU) approach. Combining a structured method with Palisade’s DecisionTools Suite software ensures that project teams fully understand the scope of their decisions, and have the tools and the knowledge to make informed and high-quality choices. This prevents opportunities and threats being overlooked, and increases Unilever’s agility in the market place.
However, like any large, dynamic organisation, complexity has a large impact on Unilever’s decision-making process. Many parties are involved in the process, often with conflicting values, motivations, perspectives, personalities and power bases. These organisational complexities are reinforced with analytical complexities such as the large number of interrelated inputs that must be factored in to the decision, the high level of uncertainty inherent in early-stage developments and potentially conflicting decision criteria.
A structured approach to decision-making
The Unilever response was to develop a unique approach known as Decision Making Under Uncertainty (DMUU). This is a disciplined, methodical and structured approach to decision-making, with probabilistic analysis at the heart of its logical reasoning. It combines framing and structuring tools with leading-edge analytical software - Palisade’s DecisionTools Suite. The DecisionTools Suite is an integrated package of seven risk, decision, and data analysis tools that run in Microsoft Excel. This approach ensures that project teams fully understand the scope of the decision, that they have the tools and the knowledge to make high-quality decisions, and the insight to understand the consequences of taking one course of action over another.
Overall, DMUU helps to provide the required clarity, insights and commitment to action.
DMUU and the use of the DecisionTools Suite is now a standard part of Unilever’s innovation process and probabilistic business cases are required for all big and complex projects. For example, a typical use for @RISK, the risk analysis element of the suite, is in evaluating alternative strategies for a new product launch or a major capital investment.
Unilever teams also use PrecisionTree, the decision analysis tool, to evaluate early stage projects where decisions and uncertainties will occur at various times in the future. This approach, using decision trees in PrecisionTree, is used to evaluate the current value of a project and also to understand the risks and benefits of internal versus external development routes.
In recognition of the importance of the DMUU, Unilever has an internal consultancy function to provide decision support and software expertise when required.
In addition, Palisade’s software is used to support other business areas including supply chain, safety, regulatory, as well as additional complex one-off decisions. All of these have the common features of multiple compelling alternatives, significant contradictions on how to proceed and high stakes should the ‘wrong’ decision be made.
“Strategic decisions require a process that addresses all the elements of decision quality,” explains Andrew Evans, decision analyst at Unilever. “However, an integral part of that process is powerful and flexible software that informs the debate on which direction should be taken. We evaluated various options and Palisade’s DecisionTools Suite was the tool that best met our business requirements. As a result it has played a key role in increasing the quality of decision-making and helping project teams to think clearly, act decisively and feel confident.”
@RISK is the most commonly used application of the tools available in the DecisionTools Suite. Decision-makers at Unilever are now used to seeing insights from business cases described using histograms and advanced sensitivity tornados. Box-and-whisker diagrams (box plots) are also very useful when alternatives or projects need to be compared. Sensitivity and scenario analysis are used to understand the key drivers of uncertainty. In addition, analysts help to draw insights from the models using summary graphs and scenario analyses.