Identifying and visualizing a diverse set of plausible scenarios for strategic planning

When making long-term strategic decisions, organizations may benefit from characterizing their future operational environment with a set of scenarios. These scenarios can be built based on combinations of levels of uncertainty factors describing, e.g., alternative political or technological developments. However, the number of such combinations grows exponentially in the number of the uncertainty factors, whereby the selection of a few combinations to work as a basis for scenario development can be difficult. In this paper, we develop a method for identifying a small but diverse set of plausible combinations of uncertainty factor levels. The method filters an exponentially large set of possible combinations to a smaller set of most plausible combinations, as assessed by the consistencies of the pairs of uncertainty factor levels in the combinations. To support the selection of the final set of combinations from the most consistent ones, we formulate a weighted set cover problem, the solution to which gives the smallest number of maximally consistent combinations that together cover all uncertainty factor levels. Moreover, we develop an interactive software tool utilizing Multiple Correspondence Analysis to visualize the consistency and diversity of the combinations, thus improving the transparency and communicability of the methods. This paper also presents a real case in which our method was used to identify a set of plausible scenarios for the Finnish National Emergency Supply Organization to support their strategic decision making.