Use Case
Ways to improve performance
Through demand forecasting ?
AI at the Heart of Agri‑food
Background
Our client, an artisanal madeleine manufacturer renowned for its significant contribution to the local economy, is tackling supply chain challenges in the agri-food sector with a strong focus on sustainability.
Like all companies in the agri-food sector, our client faces numerous challenges dependent on the reliability of demand forecasts, such as :
- The need to ensure product availability
- The complexity of complying with the eco‑responsible approach defined by the company
- The need to have the right stock with the correct minimum durability dates (best-before dates)
- The consequences of inflation on its selling price
Step 1
Demand Forecasting
RENOVATIO is revolutionizing demand forecasting in the agri‑food industry through its systemic approach. By integrating a cutting‑edge AI engine, RENOVATIO leverages various algorithmic models, including Machine Learning and Deep Learning, to refine automated learning, shorten processing times, and increase forecast accuracy across product categories. Our advanced technology incorporates diverse data, both endogenous (promotions, special events, seasonality) and exogenous (weather conditions, impact of the COVID‑19 pandemic), thus providing our client with a 360° view of demand.
Top product: The Classic Madeleine – Refined forecasting
The Classic Madeleine stands out as our client’s flagship product, benefiting from a wealth of historical data that enables extremely precise forecasting. This timeless classic does not follow any specific seasonal trend, thereby simplifying its production cycle. But running out of stock would lead to a decline in customer satisfaction and a significant loss of revenue.
Trending product: The Organic Madeleine – Adapting to market evolutions
Faced with fluctuations in the popularity of organic products, the Organic Madeleine illustrates the importance of quickly adjusting production in response to consumer trends. Organic products, which enjoyed strong growth in past years, have seen their popularity decline significantly over the last 2–3 years. Our RENOVATIO solution enabled anticipation of a demand decrease, guiding our client toward optimized stock management and production adaptation.
L’offre promotionnelle : la Madeleine tout chocolat – Gérer les incertitudes
The All‑Chocolate Madeleine, designed for specific promotional periods (Easter, gift boxes, festive seasons), requires particular attention to fluctuations in raw materials such as cocoa. RENOVATIO provides predictive analysis that enables efficient navigation through supply chain challenges, ensuring continuity of supply without disrupting our client’s core business.
Step 2
Procurement Optimization with RENOVATIO’s Demand Forecasts
RENOVATIO plays a decisive role in this process. By providing our client with reliable data on future demand and suppliers, our solution enables informed discussions with cocoa suppliers, ensuring a judicious selection based on well‑defined criteria.
- Multi‑criteria evaluations including quantitative scoring (breakage rate, delivery times) and qualitative scoring (organic certifications, environmental commitment) of suppliers.
- Supplier Key Performance Indicators (KPIs): In‑depth analysis including turnover, BFA/RFA negotiation level, sales plan, purchase price, etc.
- Contract Negotiation Management: Monitoring ongoing WCR/YERagreements, including engagement levels and contractual clauses.
Often overlooked in other Demand Planning solutions, purchasing data — particularly those related to SRM
(Supplier Relationship Management) are crucial to enrich AI models
Step 3
Optimization of Procurement and Inventory for Efficient Production
“In our client’s case, the solution will alert them of the imminent stockout and recommend ordering 480 kg of cocoa no later than January 8 to secure the immediate stock requirement. This order recommendation can then be further optimized thanks to our AI engine.
To help them choose the most relevant supplier, our client will select and assign weight to different optimization criteria, namely: carbon impact, price, lead time, and free delivery terms.
For our 480 kg cocoa order, carbon impact was defined as the most important optimization criterion. The algorithm therefore recommends placing the order with Madagascar Cacao and adding an extra 20 kg of cocoa from this supplier to reduce the carbon impact associated with a future order.
Thanks to reliable forecasting and supplier data, RENOVATIO recommends the optimal order to answer the questions When and How Much. AI‑driven optimization goes further, as the choice of optimization criteria is aligned with corporate strategy: based on these criteria, the algorithm selects the most efficient supplier from the database while factoring in demand forecasting.
Step 4
Dynamic Management of Selling Price Based on Purchase Price
Aggressive Scenario
With the full pass‑through of the cocoa price increase to the selling price in order to gain margin, what is the impact on sales volumes?
Our client passes on supplier price increases one‑to‑one to the selling price. Thanks to price elasticity, we can observe that an increase in the selling price erodes revenue, with a very rapid decline in quantities sold.
Defensive scenario
No full pass‑through on price in order to remain competitive and potentially sell higher volumes — so what is the impact on revenue ?
In this case, our client accepts a slight margin loss by not passing 100% of the supplier’s price increase onto the selling price.” He thus maintains his revenue level and volumes at the expense of a slight margin decrease.
Often overlooked in other Demand Planning solutions, purchasing data — particularly those related to SRM (Supplier Relationship Management) — are crucial to enrich AI models.
Outcome
RENOVATIO turns challenges into opportunities for sustainable growth.
Deploying our RENOVATIO solution represented a strategic milestone for our client, the local madeleine producer.” By combining advanced AI technology with a sustainability-focused approach, RENOVATIO enabled the achievement of ambitious goals, transforming operational processes and significantly reducing the carbon footprint.
Concrete results
- Improved customer satisfaction: Thanks to an optimized product availability rate, our client experienced a significant increase in consumer satisfaction, thereby strengthening their market position.
- Inventory management optimization: RENOVATIO helped reduce overstock and prevent stockouts, minimizing losses and maximizing profits.
- Efficacité accrue des ressources : L’automatisation des tâches à faible valeur ajoutée a libéré des ressources humaines pour des activités plus stratégiques, tout en améliorant la gestion financière et minimisant l’impact environnemental.
Reliability of demand forecasts
Up to
%
Reduction of the carbon footprint
(gas, electricity, …)
Up to
%
Reduction of food losses
Up to
%