Food Industry X
Company name protected by contractual confidentiality clause.
With accurate forecasts, you know when to allocate inventory, adjust production, set goals, align teams, automate recommendations, and manage the supply chain all on a single platform.
Challenge
Planning was fragmented between the Sales (salespeople/representatives), Distribution (regional distributors) and PPC/Logistics areas, making it difficult to have an integrated view of the operation.
Decisions were based solely on history and local perception, without integrating critical external variables such as weather, promotional calendar, media, purchasing power by location, and events.
Side effect: mismatch between supply and demand, pressure on margins and low predictability of turnover at the POS.
Solution
The system uses predictive models and Artificial Intelligence (AI) powered by a combination of internal data and, crucially, multiple layers of external data.
How Sales Forecast Works
Climate: It incorporates local weather forecasts (temperature, rainfall) that affect consumption.
Calendar: It takes into account holidays, regional events, payment dates, and retail promotions.
Market: It analyzes consumer signals, such as economic indicators, online searches, and in-store traffic.
AI (Learning): It automatically calibrates forecasts by SKU and channel, learning from new data.
AI (Analytics): It explains the impact of each variable (climate, price) and simulates "what if?" scenarios.
Unified Data Lake: A framework that integrates and organizes all data (historical and external) to feed the AI.
Operational recommendations generated by the model: salesperson / representative:
Sell-out targets and forecast by portfolio.
Warnings of imminent rupture.
Mix suggested by POS.
By distributor:
Optimal allocation by distribution center/route.
Target coverage and replacement policy per window.
Possibility of VMI (Vendor-Managed Inventory) models with reliable sales and inventory data at the POS.
By channel:
Turnover forecast and purchase recommendation by period.
“What if?” scenario simulations.
Results obtained
Reduction in average inventory, freeing up capital and reducing maturity risk.
Reduction of stockouts in strategic SKUs, ensuring constant availability at the POS.
Increase in operating margin.
Synchronized planning by cluster, channel and portfolio, uniting sellers, representatives and distributors around realistic forecasts.
Differential perceived by the sales team and partners
Salesperson/Representative:
Agenda prioritized by potential and risk. Mix and volume per point of sale. Explainable sales argument ("increased due to heat + campaign").
Distributor:
Replenishment window and route allocation with realistic targets. Fewer "blind" trips.
Management:
Alignment between Trade, Sales and Logistics. Less reliance on gut feeling. A single plan from the industry to the point of sale, with clear drivers (climate, income, promotion, media and events).
