Retail supply chain planning is the set of decisions that puts the right stock in the right store or fulfillment node before the customer asks for it: demand forecasts, DC purchasing, store replenishment, allocation, transfers, promotions and markdowns. Each decision is small on its own. A retailer makes millions of them every week, and the quality of those decisions shows up in stock-outs, excess inventory and margin.
What Retail Supply Chain Planning Covers
Most retailers split the work into a handful of connected planning processes:
- Demand forecasting: a forecast for every product at every location, usually daily or weekly, that accounts for seasonality, price, promotions, weather and local events.
- DC purchasing: how much to order from each vendor into each distribution center, and when, given lead times, order minimums and DC capacity.
- Store replenishment: how much to ship from the DC (or direct from the vendor) to each store to cover forecast demand plus a safety buffer.
- Initial allocation: for new or seasonal products, how to split the first buy across stores and channels before any sales history exists.
- Store-to-store transfers: moving stock from locations where it is not selling to locations where it is.
- Promotion planning: forecasting the uplift of a campaign, including cannibalization and halo effects, and making sure the stock is there when the campaign starts.
- Markdown planning: deciding when and how deeply to discount slow sellers so end-of-season stock clears at the lowest margin cost.
These processes share the same inventory. A promotion changes the replenishment plan, a transfer changes what the markdown plan has to clear, and a DC purchase decides what every store can receive next week. Planning them in separate spreadsheets lets them drift apart.
Why Is Retail Supply Chain Planning Hard?
The difficulty is mostly scale and speed. A101, one of the world’s fastest-growing retailers, runs 12K+ stores, 56 DCs and 2K+ active SKUs, and it opens around 1,000 new stores a year. That is up to roughly 24 million store and item combinations, each needing a forecast and an order decision. No planning team reviews that by hand, so the choice is whether a system or a set of static rules makes those decisions.
Retail demand also moves fast. On the Croatian Adriatic coast, Studenac Market sees demand for everyday essentials rise three to five times when summer tourists arrive, and then reset when the season ends. Fashion retailers sell products with lifecycles of a few weeks, so a poor initial allocation cannot be fixed with next season’s data. Omnichannel adds another layer, because the same unit of stock can serve a store shelf, a click-and-collect order or a home delivery.
Forecasting and Replenishment: Where Most Decisions Sit
Replenishment is where most of the daily decisions are made and where manual processes break first. A typical starting point looks like the one A101 and Mopas described: replenishment orders built in response to store orders, DC purchase orders that depend on individual planners, and no shared view of supply chain KPIs.
Demand-driven replenishment replaces that with a forecast-based plan for each product and location. The forecast uses sales history plus the signals that move retail demand, such as promotions, price changes, weather and local events. Inventory targets are set per location rather than as one rule for every store, and the DC purchasing plan is built from the same store-level demand so the two do not drift apart.
For perishables, the plan also has to respect shelf life. A grocery store that orders to a generic service level will either run out of fresh products or throw them away. Shelf-life-aware replenishment balances availability against expected waste for each item.
A101 automated demand-driven replenishment and DC purchasing on one platform and reported 50% fewer stock-outs with 18% less inventory. Mopas, a grocery retailer with 121 stores, cut lost sales by 58% and inventory cost by 14% after automating store replenishment.
Allocation, Transfers and Markdowns in Fashion and Specialty Retail
Fashion and specialty retailers face a different version of the problem. Most products have no sales history when they launch, sizes split demand into smaller pieces, and the selling window is short. Planning runs as a lifecycle:
- Initial allocation sends the first buy to stores based on store clusters, similar products from past seasons and minimum presentation stock.
- Replenishment tops up the stores that sell faster than expected from DC stock.
- Store-to-store transfers move stock away from stores where it is not selling before it turns into markdown inventory.
- Markdown optimization sets discounts per product and market to clear end-of-season stock while protecting margin.
DeFacto, the Turkish fashion retailer operating in more than 50 countries, automated initial allocation, replenishment and store-to-store transfers with Solvoyo. The platform produces 150M+ recommendations a week, and planners accept 95% of the daily recommendations. DeFacto also standardized markdown management across 50 countries with local price lists in the same solution, and reports 80% no-touch planning for markdowns.
How Do You Measure Retail Plan Quality?
Retailers usually judge a planning system by forecast accuracy. Accuracy matters, but a precise forecast that planners override every morning changes nothing on the shelf. A more direct test is how often planners execute the recommended decision as it is.
Solvoyo tracks this as the User Acceptance Rate (UAR): the share of executed planning decisions with no planner intervention. A high UAR means the recommendations already account for the constraints planners know about, such as vendor minimums, truck sizes, shelf space and promotion calendars.
The published retail cases show what that looks like in practice:
- DeFacto: 95% acceptance of daily allocation and replenishment recommendations, with a 20% smaller allocation team while expanding to 50 countries.
- Mopas: 93% acceptance of store replenishment decisions, 58% fewer lost sales.
- Studenac Market: 81% acceptance across 1,000+ stores and 14,000+ active SKUs, 8x planner productivity and 55% fewer lost sales.
A useful question to ask of any planning tool is what share of its recommendations went out unchanged last week, and who measured it.
How Solvoyo Approaches Retail Supply Chain Planning
Solvoyo is a supply chain decision automation platform. It runs forecasting, replenishment, allocation, transfers, promotion and markdown decisions on one cloud-native platform with a unified data model, so each plan works from the same demand and the same inventory. Planners review exceptions instead of every line.
The platform is modular, so a retailer can start with one process, such as store replenishment or initial allocation, and add the next once the first one runs. You can see the retail modules on the Omnichannel Inventory & Replenishment and Pricing Optimization pages, read how A101 automated replenishment and DC purchasing, or see how allocation and replenishment work for fashion retailers.
To see the platform on your own data, request a demo.
Frequently Asked Questions
It includes demand forecasting, DC purchasing, store replenishment, initial allocation, store-to-store transfers, promotion planning and markdown planning. All of these decisions draw on the same inventory, so they work best when planned on one platform with one demand forecast.
RILA stands for the Retail Industry Leaders Association, the U.S. trade association for leading retailers. It runs LINK: The Retail Supply Chain Conference, an annual event for senior supply chain leaders from retailers and their partners.
They replace rule-based or manual replenishment and allocation with a system that forecasts demand per product and location and recommends each order, transfer or markdown. Planners review exceptions instead of every line. Solvoyo measures the result as the User Acceptance Rate, the share of decisions executed with no planner intervention; DeFacto’s planners accept 95% of daily allocation and replenishment recommendations.
