Enterprise Intelligence Group
Micro and macro space planning: what to test in retail software
Evaluate micro and macro retail space planning software across planograms, category footprints, store clustering, data and execution. Includes a practical worksheet.
Retail space planning connects the range a business wants to sell with the physical capacity and execution of its stores. Software evaluation needs to examine both the plan and what is required to put it into practice.
This guide covers category-level footprints and planograms. It does not address architectural design, building compliance or office-space planning.
Micro planning and macro planning answer different questions
Micro space planning addresses product placement, facings and capacity within fixtures and planograms. Macro space planning addresses the allocation and arrangement of category space across the store, including category footprints and adjacencies.
The two need to inform each other. A category allocation may not fit the required range; a feasible planogram may still conflict with the wider store plan. Test how information passes between these levels rather than judging each screen separately.
Category footprints and adjacencies
Planograms, facings and shelf capacity
Store constraints • Assortment • Replenishment • Execution feedback
Start with one constrained store
Consider an illustrative range change that adds a private-label item to a category. The smaller store has less fixture capacity than the reference store, while replenishment arrives in fixed pack sizes. Ask how the software represents those constraints and what the planner must decide when the proposed range does not fit.
The useful demonstration makes the conflict visible. It should show the assumptions behind any revised allocation and who approves changes to range, space or replenishment parameters.
Establish which data the plan depends on
Review item dimensions, pack information, fixture dimensions, capacity, store layouts and the product/location hierarchy. Ask how measurements are validated and what happens when a store differs from its recorded configuration.
Data completeness alone is insufficient if dimensions use inconsistent units or a location’s fixture is no longer current. Assign owners and define how discrepancies are corrected before they become repeated planning exceptions.
Make store clustering operationally useful
Store groups can support differentiated assortments and space plans, but the grouping must help explain a decision. Ask which characteristics define the cluster, how exceptions are handled and when membership is reviewed.
Do not assume all stores in a cluster can execute an identical plan. Evaluate the balance between reusable templates and location-specific constraints, including how changes are communicated and maintained.
Space planning evaluation worksheet
For each row, record the current-state example, demonstrated capability, unresolved gap, owner and next test. Use consistent sample data across shortlisted options.
| Area | What to test |
|---|---|
| Macro allocation | Category footprints, adjacencies and the constraints behind a proposed change |
| Micro planograms | Item fit, facings, shelf capacity and permitted placement rules |
| Assortment connection | How additions and removals affect feasible space and range decisions |
| Store clusters | Grouping rationale, location exceptions and change maintenance |
| Data quality | Dimensions, units, fixture records and correction ownership |
| Replenishment connection | Capacity and pack-size conflicts, with clear ownership of resolution |
| Plan publication | Version, effective date, target stores and acknowledgment of the correct plan |
| Execution evidence | How planned versus implemented differences are recorded and reviewed |
| Workflow control | Approvals, overrides, audit history and access responsibilities |
| Benefits review | Baseline, execution status and measures relevant to the agreed objective |
Close the gap between planned and implemented
A published planogram is not proof that a store implemented it. Define how completion is reported, how exceptions are captured and who decides whether to correct the store execution or revise the plan.
If shelf-intelligence or image-based tools are involved, test the quality of their observations, location/item matching and exception review. Do not treat an automated detection as unquestionable evidence. EIG’s consulting role is to define requirements, workflows and acceptance; this guide does not offer a proprietary shelf-monitoring product.
Agree what improvement will mean
Choose measures that match the problem, such as implementation compliance, planning effort, capacity conflicts or availability. Commercial measures require an appropriate baseline and an explanation of other changes affecting the result. A software-generated optimum is a recommendation to evaluate, not a guaranteed store outcome.
The selection record should carry forward into implementation: approved constraints, data ownership, tests, operational responsibilities and review points.
Get support for the decision and delivery
EIG supports micro and macro space planning requirements, store clustering, data readiness and business-side implementation. A defined review can examine one planning workflow or software decision and establish the practical requirements and next actions.
Explore space planning and store clustering consulting
For a connected product-range question, explore merchandising and assortment. For an RFI, RFP or vendor evaluation, explore technology selection support.
Discuss your requirements or vendor selection
The EIG Library · Insights · AI Maturity Assessment · Contact