Merchandising & Buying
Automated purchase order generation
Generate purchase orders from agreed range plans, supplier terms, and stock requirements. Reduce manual PO creation to exception-only review.
60–80%
reduction in purchase order creation time
Opportunity assessment
Minor improvement. Small efficiency gain with limited effect on overall turnover or bottom line.
Moderate effort. Requires configuration, prompt engineering, and testing. A capable team can get there but expect several months.
Moderate data needs. Works with data most businesses hold, but will likely need consolidation, cleaning, or reformatting before use.
Moderate risk. Some customer or external exposure. Errors create rework or reputational impact but are recoverable.
Moderate people impact. Part of someone's working day changes. Requires training and some adjustment time, but roles remain broadly the same.
Tooling required
Things to consider
This only works if your range plans, supplier terms, and stock parameters are already digitised and accurate. If buyers are working from spreadsheets with manual overrides, you need to formalise the inputs first.
Build clear exception rules — which POs require human review (new suppliers, above-threshold values, unusual quantities) and which can flow straight through.
The time saving is significant per PO but the total business impact depends on volume. A business raising 50 POs a week sees less total value than one raising 500.
Experiment starter: For one supplier with stable terms and predictable ordering patterns, automate PO generation for one month. Compare the automated POs against what the buyer would have raised manually. Track exceptions and errors.
Go deeper in the playbook
Section — Opportunity Identification, including the AI Opportunity Assessment ScorecardSection — The Tooling LandscapeThis is an automation opportunity — see the relevant playbook section for how to approach it.More in Merchandising & Buying
Product description writing
Generate first-draft product descriptions from attributes, imagery, and brand guidelines. Buying team reviews, edits, and approves before publish.
Supplier spec sheet extraction
Extract structured product data from unstructured supplier spec sheets, PDFs, and email attachments. Outputs clean records ready for system upload.
Range review analysis
Summarise sales performance, markdown rates, and return data by category to surface underperformers and inform ranging decisions.
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