Afresh DC Buying: Frequently asked RFP questions

Afresh DC Buying gives distribution center buyers one AI workspace for all the items on their desk. It does more than just forecast store demand: It helps buyers prioritize their day by automating routine purchase orders, provides scenario analysis on forward buys and much more.

What Afresh DC Buying does

1. How does Afresh DC Buying build a recommended purchase order?

Afresh recommends an order quantity for every item a buyer manages, every order day. Each recommendation draws on four inputs:

• A forecast of store demand

• Projected DC inventory (incoming and on-hand)

• Vendor and truck settings

• An ordering policy, customized for each retailer, that balances service level, freshness, and freight cost

Afresh builds and submits each PO

Each recommended PO includes the vendor, loading and delivery dates, delivered or FOB terms, and items, quantities, and costs.

Routine POs are created automatically and submitted to the retailer's PO system. A targeted list of POs is added to the buyer’s prioritized tasks for review, with recommendations and tradeoffs.

When a buyer approves or edits a PO, Afresh creates it directly in the retailer's PO system. Buyers never rekey orders.

Afresh forecasts store demand for every item at every DC, by day, 35 days out

Afresh forecasts what stores will order from each DC, not what the DC shipped, so past shortages don't lower future forecasts.

The forecast is built from:

• historical store orders and sales

• pricing and promotions

• holidays

• seasonality

• day-of-week patterns

Forecasts are daily. For center store, weekly and monthly views are also available.

Each forecast is a probability distribution: the full range of likely outcomes and how likely each one is. Buyers see the most likely outcome and what's driving it, such as a promotion or holiday. They can compare it against past periods with similar conditions and adjust it when they know something the system doesn't.

Every adjustment is tracked, so retailers can see whether buyer overrides improve accuracy. And if a forecast, lead time, case size, or vendor minimum changes, Afresh recalculates the recommended PO automatically.

Inventory is projected forward, not just counted today

Afresh projects DC inventory into the future from on hand, on order, prebooks, and inbound POs. It also accounts for how perishable each item is and how reliably each vendor delivers on time and in full.

Safety stock is dynamic and determined for each item and season

Afresh doesn't apply a fixed safety stock, which ties up capital and often leads to shrink and pushes to stores. Instead, safety stock is determined for each item by looking at four factors:

• How reliably vendor(s) deliver on time and in full

• How many days until the next delivery

• How much shelf life the item has left

• How variable demand is

For example, an item with unpredictable demand and an unreliable vendor gets more buffer, but only as much as its shelf life can hold. A steady item on a frequent delivery schedule gets very little.

Each retailer sets how the cost of a stockout is weighed against the cost of carrying extra inventory. Afresh also sets item-level priorities, such as items that should never be out of stock, items to run long rather than short, and maximum days on hand.

Vendor and truck constraints are part of the order decision, not applied afterward

Afresh weighs vendor lead times, contracts, minimums, order schedules, and truck capacity when it chooses each quantity. When a full truck would lower freight cost but bring in more days of supply than a perishable item can hold, Afresh weighs the freight savings against the spoilage risk.

When several POs share a truck, Afresh totals weight and pallets across all of them, so buyers can see truck fullness before submitting.

2. How does Afresh account for promotions and deals?

Afresh forecasts promotions from historical ads, deal performance, and price elasticity modeling, combined with future ad dates and deal terms.

Historical promotion performance drives future forecasts

Past ad and deal results are core inputs to the forecast. Afresh measures forecast accuracy on promoted items as a separate category, because promotions are where errors cost the most.

Prebooks and committed inventory are part of the forecast

Historical prebooks and committed inventory feed the forecast. When building a vendor PO, buyers can see actual prebooks by ad group, not just total orders.

Buyers can add demand for specific ads and store groups

Buyers can enter additional demand with start and end dates, at the ad group, product group, or store group level. They can enter it manually or upload it as a CSV.

Afresh flags promotions that sell above plan and recommends a response

When an item sells faster than forecast during an event, Afresh alerts the buyer. It recommends a response, such as increasing an existing PO or issuing a new one.

3. How does Afresh handle seasonal, holiday, new, and irregular items?

Afresh's forecast adapts to each item's demand pattern automatically.

Seasonal items can be identified automatically

Afresh detects seasonal patterns from history. Buyers can also set a season's start and end dates. They can mark items as temporarily unavailable or out of season, with a next available date.

Holiday demand is built into the forecast

Holidays are forecast from past holiday performance. Buyers see when a holiday is driving the forecast.

New items borrow history from similar items

Afresh automatically matches new items to similar existing items and uses their demand patterns until the new item builds its own history.

Slow, lumpy, and fast-changing items don't need special setup

The same forecast handles items that move erratically, move slowly, or are trending up or down fast. There are no separate forecast types to assign or maintain.

Item history follows the item

When stores move to a different DC, or an item's sourcing changes, the item's full history stays with it. Discontinued, inactive, and out-of-season items are skipped automatically.

4. What data does Afresh need to begin?

Afresh needs historical store orders plus the day-to-day data a DC already produces:

• Historical store orders and sales by item and DC

• Item and vendor master data, including case sizes, pallet configurations, lead times, minimums, and order schedules

• Pricing, promotions, deals, and scheduled cost changes

• DC inventory, at the lot level where available

• Open purchase orders, receipts, and shipments

• Truck and delivery schedules

Afresh trains its forecasts on two to three years of history. More history improves accuracy on less frequent events, such as holidays, seasonal items, and some promotions.

Afresh works with your team on data quality during implementation

Afresh ensures incoming data is clean and normalized, working directly with your team to fix errors and data feed issues during implementation.

5. How does Afresh support forward buys and investment buys?

Afresh identifies items with deals ending or cost increases coming. It recommends the buy quantity with the best return, after accounting for inventory, carrying cost, and capital limits.

Afresh alerts buyers to forward-buy opportunities

When a vendor email announces a deal or cost increase, Afresh picks it up and alerts the buyer automatically. Afresh then evaluates the opportunity and recommends a buy quantity based on expected return, inventory, carrying costs, and capital limits.

Recommendations weigh return against cost

Each investment buy recommendation accounts for:

• Deal terms

• The forecast

• On hand and on order

• Pallet limits

• Capital limits

• Carrying cost

Afresh compares each buy's return to the category's ROI goal. Retailers can set these parameters at the DC and category level.

When deals overlap or run back to back, Afresh considers them together rather than one at a time.

Buyers stay in control

Forward buys are never automatically placed. Buyers can accept, adjust, or reject investment buy recommendations.

Fresh vs center store

Investment buys matter most in center store, where deal windows and cost increases are frequent and product can be held. In fresh, the same logic applies to seasonal and holiday buys, with shelf life limiting how far ahead a buyer can go.

6. How does Afresh support opportunity buys in fresh?

When a vendor offers promotional pricing, excess inventory, or a spot deal, Afresh shows whether the deal is worth taking. It then recommends how much to buy and how to sell it.

Afresh alerts buyers to opportunity buys

When a vendor offer arrives by email, Afresh picks it up and notifies the buyer. For each offer, Afresh shows:

• A recommended order quantity

• Forecasted demand at that price

• A suggested sale price

• The resulting margin

Afresh weighs the downstream impact before the buyer commits

The recommendation accounts for the effect on demand, inventory, carrying cost, shelf life, and margin. A low price only counts as a good deal if the product can sell before it spoils.

7. How does Afresh account for shelf life and aging product?

Afresh applies a shelf life to every item, from code dates or retailer-configured limits, tracks remaining shelf life across the supply chain, and acts on product at risk of spoiling before it’s lost.

Every item has a shelf life

Shelf life comes from code dates or retailer-configured limits and feeds projected inventory and every ordering decision.

Remaining shelf life is visible at every point in the supply chain

Afresh takes in inventory at the lot level. That lets it track each item's total shelf life, and how much remains, from vendor to DC to store.

Buyers can review expiration dates on existing inventory while they build POs. The buyer's dashboard shows time spent in the supply chain and average remaining shelf life for the items on their desk.

Aging product is flagged automatically

Afresh identifies DC inventory that needs to move and recommends how to resolve it:

• Store allocations, based on each store's inventory position and rate of sale

• Markdowns, with scenario planning across price points and projected margin

Resolutions follow the retailer's approval process

Price changes can be routed to a category manager for approval. Approved allocations and pricing are sent to the retailer's systems, and store teams are notified.

Allocations made to clear aging product are flagged, so they don't inflate future forecasts.

8. What does a buyer's day look like in Afresh?

Buyers start each day with one prioritized list of the decisions that need them. Each item comes with context and a recommended action.

• POs that need review

• Late trucks, shorts, and rejections, with recommended fixes

• Aging product actions

• Vendor offers

Review is exception-based at every level

Afresh surfaces only the POs and actions that need review and automates the rest. Within each PO, it highlights the specific items and quantities that need attention.

Items are flagged when forecast confidence is low, when data looks wrong, or when recent trends break from the norm.

Alerts cover what buyers would otherwise track by hand

Afresh alerts buyers to:

• Upcoming out-of-stocks

• Overdue shipments

• Short shipments

• Forecast deviations, with thresholds the buyer can set

• Items whose recent sales differ significantly from last year

• Promotions selling above plan

Buyers see the impact of a decision before they make it

While building a PO, buyers see days of supply, on hand, on order, and projected margin, both before and after the order. When they override a recommendation, they see the tradeoff.

9. How does Afresh handle late trucks, shorts, and rejections?

Afresh shows each disruption with its impact and a recommended fix, and it simulates the outcome of each option before the buyer acts.

For every late truck, short PO, or quality rejection, Afresh shows: what happened, which items and stores are affected, and the impact on service level and inventory.

Afresh then recommends a resolution, such as pulling a PO forward, transferring product between DCs, issuing an urgent PO.

Afresh simulates the impact of each option on fill rate, days on hand, and margin so buyers can make informed decisions.

Options can be configured per DC. For example, DC-to-DC transfers can be turned off where a retailer has only one warehouse for that category.

Demand shifts to substitutes when an item is unavailable

When an item is out, buyers set its availability dates. Afresh automatically moves that demand to substitute items, so the substitutes are ordered to cover it.

10. Can buyers adjust forecasts and recommendations?

Yes. Buyers can adjust any forecast or recommendation, and every adjustment is tracked, so retailers can see whether overrides help or hurt, and Afresh’s models learn from them.

Additional demand at group levels

Buyers can add demand at the product group, ad group, or store group level, with start and end dates.

When an input affects a whole category, Afresh adjusts every related item's forecast automatically. Buyers don't have to override items one by one.

Order and buy recommendations

Buyers can edit quantities on any recommended PO. They can accept, adjust, or reject investment buy and opportunity buy recommendations, with a reason for any rejection. Recommendations recalculate immediately when an input changes.

Override performance is measured

Afresh compares system forecasts, buyer overrides, and actual sales. That shows whether overrides are improving results, and where.

11. How does Afresh choose between vendors?

Afresh compares vendors that supply the same item on cost, lead time, service, quality, and past performance. It then recommends how to allocate volume across them.

Vendor reliability shapes every order

Afresh tracks how reliably each vendor delivers on time and in full. It orders more conservatively from less reliable vendors.

Vendor performance is reported

Vendor fill rate and other vendor performance metrics are available at any level of the product hierarchy.

12. How does Afresh measure performance?

Afresh reports on buyer overrides and business results such as service level, fill rate, and days of supply, at any level of the business.

In-product reporting covers:

• Service level

• Fill rate

• Inventory turns

• Days of supply

• Vendor fill rate

• DC transfers

• Order time

Each is available at any level of the product hierarchy. For wholesalers, reporting goes down to the member or banner level.

Overrides and adoption

Afresh reports how many forecasts buyers overrode and whether those overrides improved accuracy.

13. What systems does Afresh integrate with?

Afresh connects to a retailer's existing ERP, purchasing, warehouse, and pricing systems. It creates POs directly in the retailer's PO system.

Integration methods

• API-based and event-driven integration for real-time and asynchronous data exchange

• Batch file transfer over SFTP

• Private connections to cloud infrastructure where preferred

Purchase orders go straight into the retailer's system

Afresh creates and edits POs directly in the retailer's purchasing system. PO output can be customized to the retailer's format.

14. What does implementation look like?

Afresh integrates with the retailer’s data, works with your team on data readiness, then rolls out desk by desk.

Integration and data readiness

Afresh sets up data feeds, loads history, and works directly with your team to clean and normalize data before buyers rely on Afresh for daily buying.

Rollout, training, and support

Buyers move to Afresh gradually, desk by desk, so each team can switch from its old tools without disrupting daily ordering.

Afresh program managers provide training materials, and solutions engineers provide technical integration documentation.

Security

• SOC 2 compliant

• SSO and SCIM authentication

• Role-based and rules-based access control

• Data encryption in transit and at rest

• Client data destroyed at the end of the agreement

• Web application, with no installation required

15. How do I submit an RFP?

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