Skip to main content

Replenishment Intelligence: PO Recommendations

What is a PO Recommendation?​

A Purchase Order (PO) Recommendation is the actionable output of the module - the answer to "order this much of this product." It is where Demand Signals and Store Signals converge into a single, ready-to-act number.

Each recommendation tells the business user:

  • which product needs ordering,
  • how many units to order,
  • where it is needed (store and distribution center), and
  • how urgent it is.

What the business user sees​

  • Products needing a PO - the count of products that require action this week, filtered out of the full catalog so attention goes only where it is needed.
  • Total suggested PO units - the aggregate order quantity across the recommendation set.
  • Must-replenish list - the prioritized subset that cannot wait, ranked by urgency and business impact.
  • Per-store recommendations - order quantities resolved down to the individual store level.
  • DC cascade - store-level needs rolled up to the distribution centers that serve them.

A recommendation is not a raw forecast number. It is constructed in stages:

  1. Baseline need from the 26-week Demand Signal.
  2. Net of position - subtract what is already on hand and in transit.
  3. Risk adjustment from Store Signals - push up where stockout risk is high, pull down where overstock exists.
  4. Prioritization - rank by urgency and forecasted revenue so the must-replenish items surface first.

The result is a quantity that reflects both what will sell and what is actually happening in stores.

Distribution-center awareness and truck efficiency​

Replenishment does not stop at the store. Store-level needs cascade up to distribution centers, and the system looks at order consolidation:

  • DC rollup - aggregate the stores served by each DC into a single replenishment picture.
  • Full-truck-load (FTL) efficiency - highlight where consolidated orders align to efficient truckloads, reducing freight cost per unit.

This means a recommendation is not just "right for the shelf" but "efficient for the supply chain."

What the user can do with it​

  • Review the ranked PO list and the suggested units.
  • Drill into any product to see its per-store breakdown and the reasoning behind the quantity (see Agent2Agent).
  • Filter by segment, tier, severity, and channel to focus the plan.
  • Export the recommendations to act on them in the ordering workflow.

Why it matters for business​

  • Converts analysis into a concrete order quantity, not just a chart.
  • Reflects current inventory position, so the system does not over-order.
  • Is DC- and freight-aware, protecting margin as well as service level.
  • Surfaces the must-replenish few so nothing critical is missed.

See Agent2Agent for how each recommendation is produced on demand from a plain-language request and how its reasoning is made transparent.