Retail Supply Chain Planning
DemandLabs forecasts each item at each store from daily POS and plans DC and store stock against that number. Price and promotion moves are tested against the stock the network can deliver.
Solutions for Retail
The DemandLabs applications that fit retail planning, and how each one handles it.
Store-item forecasts refresh each day from POS and weather, so a heat wave or a competitor stockout reaches the plan the same day. Items that sell a few units a month use intermittent-demand methods.
Explore demand planningBuffers are set across DCs and stores for the service each segment needs. Stock close to its date is flagged while it can still sell, with a recovery play for each SKU.
Explore inventory optimizationOwn-price and cross-price elasticity are estimated by channel and pack from your own sales, and each price move is checked against DC supply.
Explore revenue growth managementThe unit plan reconciles to the finance view by period, so merchandise and finance teams review one set of numbers.
Explore IBPHow Retail Planning Connects
A store forecast drives the stock plan for each store and the DC orders behind it.
Store Forecast
- Daily POS
- Weather
- Local events
Price and Promotion
- Price changes
- Promotions
- Markdowns
Store Stock
- Service targets
- Shelf life
- Transfers
DC Plan
- Vendor orders
- Lead times
- Deployment
Category P&L
- Margin
- Markdown cost
- Stock value
Built for Retail
Retail planning works at the grain where the shopper buys: one item, in one store, on one day.
Forecasts at Store and Item
Each store-item pair gets its own forecast, refreshed each day from POS.
Lost Sales Put Back
Days with no stock are flagged and the demand you could not serve is estimated, so a stockout does not lower next season's forecast.
Fresh Stock Where It Sells
Remaining shelf life feeds the aging view, so stock close to its date moves while it can still sell.
Prices Checked Against Supply
A price or promotion move is tested against what the DCs can deliver before it reaches the stores.
Retail Segments
How retail planning differs by segment, with the applications that fit each one.
Planning Notes for Retail
See all notes
Your sales history is missing the demand you could not serve
Censored demand forecasting recovers the sales a stockout hid, why the loop keeps shrinking the buffer, four recovery methods, and the flags they need.
23 August 20267 min read
What a daily signal can fix, and what it cannot
Demand sensing is a latency upgrade rather than an accuracy one. The five mechanics, where the value lands, and the horizon at which the correction decays.
22 August 20269 min read
Half your catalogue does not sell often enough for a normal forecast
Intermittent demand forecasting for the part of a catalogue that sells rarely: classify first, Croston and its successors, and why the usual metrics fail.
23 August 20269 min readRetail Planning FAQs
Can DemandLabs forecast for each store?
Forecasts run per item and store, and items that sell a few units a month use intermittent-demand methods.
Does it use POS data?
Daily POS refreshes the near-term forecast. Weather and local events enter as drivers where you have them.
How does it treat stockouts in the sales history?
Days with no stock are flagged and the unserved demand is estimated, so a stockout does not teach the model that shoppers stopped buying.
How long does implementation take?
Eight weeks to the first live cycle for one planning area, with a value review with your CFO in week 10.
Other Industries
See Store-Level Forecasts on Your Own POS
A 45-minute walkthrough on your own data.