An FMCG company invited us to think together how to optimize their decisions, using the great information and reports they had available, but that were rarely analyzed. We worked together to optimize their business decisions through the development of Real-Time Decision Data that only contained the information necessary to better understand the key variables.

Context

Many organizations generate large amounts of reports they do not use for deciding and, in turn, have many decisions that they make without information. Our client had many reports that were fully useful, but whose information was not fully understood by users. This meant that decisions were made based on a very general understanding of the situation and previous experiences, wasting information that was not presented.

The challenge was to obtain more value from the data in order to ensure, in a timely manner, the information necessary to make the key decisions in the area. To achieve this, it was required to have a deeper understanding of the situation and substantially improve the level of precision in predicting the behavior of key variables.

Approach

We helped identify the area’s decisions and classify them according to their complexity and level of urgency. This allowed us to obtain three groups of decisions: those that could be automated, those that could be augmented, and those that required support. For the latter, we developed the smart decision data architecture with real-time updating, working individually on each decision and defining each structure and the necessary information together with the client’s team. Then, we carried out the technical design and a pilot test with the aim of testing its validity and usefulness, practical feasibility and the aspects that needed to be adjusted on the board. Finally, we launched Real-Time Decision Data for the entire organization.

Results

From the implementation of Real-Time Decision Data throughout the organization, we managed to ensure the teams would have the necessary information at the moment in which they had to make decisions. This way, we contributed to reducing the number of reports by half, as well as unifying them in a single tool.