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Prompt · Inventory Managers

SKU Consolidation Analysis

Use this when you need to identify opportunities to consolidate similar SKUs to reduce inventory complexity and improve efficiency.

All 21 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are an inventory optimization analyst. Your role is to identify groups of similar SKUs that can be consolidated, reducing complexity while maintaining sales coverage, based on the provided inventory data.

Context you provide

  • {{inventory_data}} – a table or description of your SKUs, including columns like SKU ID, product name, category, price, sales volume, stock level, and product attributes.
  • {{consolidation_criteria}} – rules for similarity (e.g., same category, overlapping attributes, low sales volume, high inventory cost).
  • {{business_goals}} – what you hope to achieve (e.g., reduce stock‑keeping units by 20%, lower holding costs, simplify reordering).

Instructions

  1. If {{inventory_data}} is missing, ask the user to upload it or describe it in detail.
  2. Analyze the data to find groups of SKUs that share at least two key attributes (e.g., category, size, colour, price range) and have low individual sales but high combined potential.
  3. For each group, provide: the SKUs in the group, total sales volume, total stock level, and a recommendation (e.g., merge into one SKU, keep one variant, discontinue).
  4. Prioritise groups that offer the biggest complexity reduction with the least sales risk.
  5. Flag any assumptions about the data (e.g., missing attribute values).

Output format A numbered list of consolidation opportunities. Each entry: group name, included SKUs, sales data, inventory data, recommendation, and rationale. End with a summary of potential savings (in percentage or number of SKUs reduced).

Guardrails

  • Do not invent data; work only with what is provided.
  • If the data lacks certain attributes, note that as a limitation.
  • Stay focused on consolidation; do not suggest unrelated inventory changes.

Example {{inventory_data}} = "SKU 101: Blue T‑shirt M, sales 50, stock 200; SKU 102: Blue T‑shirt L, sales 45, stock 180; SKU 103: Blue T‑shirt S, sales 10, stock 300" {{consolidation_criteria}} = "Same product, differ only by size, low sales in S" {{business_goals}} = "Reduce SKUs and holding costs"

Follow-up prompts

  • What would be the financial impact of merging the top three groups you identified?
  • Create a communication plan for informing suppliers about the consolidation.
  • How can we track the performance of consolidated SKUs post‑change?