Honest to Goodness operates a highly diverse business with supply across various channels. As a result, demand for individual SKUs can vary widely, making accurate forecasting and inventory management essential for sustaining business growth.

The existing tools within the company lacked flexibility, making it both challenging and time-consuming to identify and respond to external factors affecting demand fluctuations.

Following the project to restructure the data architecture and governance, the business was well-positioned to segment data and identify deviations and trends effectively.

Given the high cost of integrating business data with off-the-shelf planning tools, we opted to develop our own planning and forecasting solutions in-house.

We created statistical models using Python and developed visualizations with Power BI. This internal development allowed us to produce customized reports that addressed the specific needs of the business more effectively.

The complexity of Honest to Goodness' channels and product range requires ongoing refinement of our forecasting and demand planning tools.

Following the completion of the framework and statistical models, the business achieved a 50% reduction in out-of-stock rates and established more stable purchasing planning. These enhancements improved inventory management and cash flow.

The tools now provide long-term visibility into potential stockouts and overstock situations, allowing the business to manage each product and category proactively and strategically. This capability includes the identification of demand peaks and troughs driven by specific customer behaviors.