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Economic decision data model

Economic planning does not start with a P&L report. It starts with physical decisions—what was sold, produced, purchased, transferred, held, served, or lost—and connects them to the prices, costs, taxes, and policy assumptions that give those decisions economic meaning.

This page is a relationship map. It connects the main data families used by Inventory Optimization and Cost-to-Serve; it is not the upload contract for a single data set.

Where the data appears

  • Data → Data Operations contains the master, transactional, configuration, and planning records that feed the calculations.
  • Visibility → Inventory Optimization compares candidate inventory policies through service and economic impact.
  • Visibility → P&L / Cost-to-Serve reads a saved Supply Plan through revenue, cost, tax, and contribution.
Dark Inventory Optimization workspace for selecting a model and comparison policy

Policy economics

Inventory Optimization changes protection and measures service, stock, stockout, write-off, and economic impact.

Dark Cost-to-Serve workspace for selecting Supply Plans and an aggregation scope

Plan economics

Cost-to-Serve preserves the physical plan and explains how its flows produce revenue, cost, and contribution.

Five connected layers

Layer Main data Role in the decision
Physical requirement and response Demand Plan, Supply Plan, planned vehicle trips, served demand, production, purchase, transfer, and inventory Establishes what the scenario physically required and executed
Commercial value Sell-in, prices, discounts, taxes, and COGS Values demand and sales at the relevant product, customer or channel, location, and period
Operating cost Material purchase, production costs, and logistics and location costs Assigns cost to the objects and events that consume resources
Policy and uncertainty Inventory positions, inventory policies, lead time, replenishment reliability, shelf life, and demand variation Defines the protection candidates and risk simulated by Inventory Optimization
Economic evidence Inventory-policy simulation results, P&L facts, transmitted balances, consolidated lines, and plan comparison Explains why a policy or physical scenario creates a different economic outcome

Grains must remain explicit

Decision object Logical grain Why it cannot be flattened early
Price or COGS material, optionally customer/channel and location, validity or period, and version The same material can have different commercial value by market and time
Operating cost cost object, location, resource, routing, lane, vehicle or order, and period A total cost cannot explain which physical choice generated it
Inventory-policy parameter model, material, location, and applicable validity or scenario Protection is chosen for an item-location under one loaded set of assumptions
Inventory simulation model, material, location, candidate policy, sample, and period Average impact depends on the simulated curve and its stochastic samples
P&L fact Supply Plan, economic line type, period, material and location; optionally origin, destination, resource, or bill of material The economic event must remain traceable to its physical origin
Transmitted balance original economic fact plus the reference material-location-period and propagation direction Cost-to-Serve must preserve how value moved through transfers, production, inventory, and sales

Main relationships

Origin Relationship Destination
Demand Plan creates the future requirement evaluated by the Supply Plan and policy simulations
Supply Plan persists physical facts consumed by Cost-to-Serve and scenario comparison
Consolidated planned loading orders multiply cost per trip by planned trips and allocate it to distributed materials on the same lane and period
Sell-in, prices, and COGS value served demand and customer-product-market outcomes
Production costs and logistics and location costs value the resource, route, inventory, or node that generated the expense
Inventory positions and inventory policies initialize and constrain candidate-policy simulation
Inventory Optimization produces service, stock, stockout, write-off, and economic impact by candidate
A physical or commercial event creates an original P&L fact
Transfers, production, inventory, and sales propagate or allocate the economic fact through the operating network
Detailed economic facts consolidate into P&L, contribution, Cost-to-Serve, and plan-comparison views

Two analyses, one economic vocabulary

Inventory Optimization and Cost-to-Serve use related concepts but answer different questions:

  • Inventory Optimization changes a candidate policy and simulates its consequences. Its comparison needs explicit capital, write-off, and shortage economics for the loaded model.
  • Cost-to-Serve keeps the saved physical plan and traces economic facts through the network. It explains where revenue, COGS, production, logistics, storage, and other costs were generated or transmitted.

Do not assume that one calculation automatically supplied every economic input to the other. Confirm the economic source and version loaded for each run.

Data-quality checklist

  1. Confirm the Demand Plan and Supply Plan versions and their common horizon.
  2. Confirm the default planning UOM and every required conversion.
  3. Verify price, COGS, tax, and cost validity for the scenario period.
  4. Separate missing data from a true zero value.
  5. Check that lanes, resources, routings, vehicles, and locations referenced by a cost are part of the selected scenario.
  6. Verify whether stockout becomes lost sales, backlog, substitution, or another economic consequence.
  7. Confirm shelf life, aging, and write-off behavior before comparing coverage.
  8. Trace a surprising consolidated number back to its physical event and original economic fact.

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Interpretation boundary

A zero line is not proof of zero cost, and a recommended policy is not an unconditional optimum. Both results depend on the physical plan, loaded versions, units, filters, and economic assumptions.