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Case study

Retail pricing governance with markup-based price calculation

Retail pricing

  • SAP EWM
  • Retail pricing

SAP Retail case study on using sales price calculation, planned markups and pricing levels to improve retail price governance at scale.

Problem
SAP Retail case study on using sales price calculation, planned markups and pricing levels to improve retail price governance at scale.
Solution
SAP EWM process design, RF execution and warehouse task control
Outcome
Clearer warehouse execution and more reliable stock movement

Project overview

Retail pricing becomes difficult when a company operates large article volumes, multiple organizational levels and different price strategies across the network. The retailer needed a more transparent pricing model in which SAP Retail can suggest retail prices based on purchase prices and planned markups, while still allowing controlled user intervention where business exceptions justify it.

Business challenges

  • Sales prices were difficult to maintain consistently across large assortments and multiple levels.
  • Users needed clarity on how site-level, price-list-level and distribution-chain-level prices interact.
  • Pricing teams wanted system support without losing the ability to handle commercial exceptions.
  • Screen layout and data visibility needed to work for different user groups and pricing scenarios.

SAP Retail solution design

  • Used markup-based sales price calculation as the standard pricing approach.
  • Defined pricing governance across distribution chain, price-list and site levels with the most detailed price taking priority.
  • Positioned planned markup conditions as the basis for systematic price suggestion.
  • Used pricing layouts, list groups and list variants to support efficient maintenance and review.

Expected business impact

  • Improved consistency and scalability in sales price maintenance.
  • Made pricing logic more transparent to business users.
  • Reduced the manual burden of maintaining large retail price volumes.
  • Created a stronger foundation for later expansion into advanced pricing functions.

Recommended next steps

The natural extension is competitor-pricing scenarios, automated monitoring through change pointers and stronger promotion-price coordination.

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