A consumer goods company operated in a highly volatile market due to unstable consumption patterns and tax laws. This variability made product pricing one of the core drivers of consumer choice and therefore a key strategic lever to define brand placement and impact overall market share.
The company was then aiming at improving its strategic price and distribution planning process by using analytic methods to best leverage the available consumer and market data.
An optimization model was developed, along with the required market forecast models, to support strategic planning by providing senior stakeholders with the top alternative scenarios to reach certain P&L targets of volume, gross margin and bottom-line profitability, using forecasting models to predict retail prices, sell-in and sell-out volumes and game theory mechanisms to explore different brand marketing strategies across regions and market competitors.
The optimization model allowed the planning team to indirectly explore millions of alternative scenarios, with automatic identification of a vast set of most relevant alternatives for further validation and analysis.
This enabled the strategic planning team to reduce the average lead time of market planning from one week to a matter of hours, while also improving the quality of the explored scenarios.
The developed strategic optimization solution was incorporated within the existing planning system and a scenario exploration dashboard was developed to share scenarios and P&L projections for each competitor with key stakeholders.