A.I.-driven insight to have the right products in the right places.
Higher profits, fewer stock-outs and less excess inventory.
A.I.-powered demand forecasting is changing the paradigm.
Promoted. Unpromoted. Pricing. Halo sales. Forward-buying. Category cannibalization. There are many factors that have an impact on product demand. By using A.I., retailers can measure all the ripple effects, giving them a holistic view to optimize demand forecasting and better manage their physical inventory. The results are fewer stock-outs and less excess inventory, ultimately leading to maximized profitability.
Minimize stock-outs and safety stock for every SKU across the entire chain – right down to the store, intra-day level.
Forecast with greater accuracy.
A.I. enables forecasting that’s more than 50% more accurate than the standard developed two decades ago. For high-velocity products, A.I. can reduce the forecasting error rate to less than 5%.
GENERATE GRANULAR FORECASTS
Forecasting product demand is a complex mathematical exercise. Daisy’s A.I.-powered simulation and an understanding of the causal relationships across all products ensures profitability and an accurate inventory to meet customer demand.
- How much inventory should I purchase to support our product assortment plan?
- How do I carefully balance having enough inventory to support a promotion without the risk of being over stocked?
- How much inventory should I allocate to each of my stores to meet local demand?
IMPROVE FORECASTING ACCURACY
Predict demand with precision.
It takes simulation and a complex formula.
Demand forecasting has been limited until now by available technology and computing capacity. Traditional technologies typically analyze every product SKU and transaction as if it were an isolated incident. This is not how it works in the real world.
To achieve high levels of accuracy in forecasting, you need to get as granular as possible. Simply running sales numbers for individual product SKUs isn’t enough. It takes simulation and a much more complex formula. Purchasing behaviours such as product cannibalization, promotional cadence, seasonality and product affinities should also be considered holistically. Now factor in multiple price zones and ad zones, dozens of stores, and tens of thousands of products, and it becomes humanly impossible to execute an accurate decision.
Retailers implementing A.I. are seeing 10–15% improvement in their forecasting accuracies.
SEE HOW A.I. IS HELPING OUR CLIENTS
POWER THEIR PROFITS.
Learn more about the portal and how we deliver decisions.
How does A.I. work?
We were amazed. When we listened to Daisy’s recommendations, we had an 88% probability of having an above average flyer week.
MERCHANDISING MANAGER | GROCERY RETAILER
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