Supply Chain & Logistics
Warehouse slotting and pick path optimisation
Optimise where products are stored and how picks are sequenced based on velocity, affinity between products, size, and pick equipment, reducing walking distance per order.
10–25%
reduction in pick travel time
Opportunity assessment
Moderate impact. Meaningful cost or revenue improvement, likely noticeable at function level but modest relative to total business scale.
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.
Low risk. Limited external exposure. A human reviews output before it reaches anyone outside the team.
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
Travel is typically the largest single component of pick time in a manual warehouse, which is why slotting has a bigger effect than most operational interventions of similar cost.
Reslotting has a real cost in labour and disruption. Optimise on a rolling basis — a percentage of locations each week — rather than as a single big-bang move.
Product affinity is the input people forget. Items frequently bought together should be slotted together, and that data lives in order history rather than in the warehouse system.
Experiment starter: Analyse a month of pick data and model the travel reduction from reslotting your top-moving 500 SKUs. Implement in one zone, measure actual picks per hour for four weeks, and compare against the unchanged zones.
Go deeper in the playbook
Section — Opportunity Identification, including the AI Opportunity Assessment ScorecardSection — RAG and Knowledge Systems: Unlocking Proprietary DataThis is an decision support opportunity — see the relevant playbook section for how to approach it.More in Supply Chain & Logistics
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Convert sales, stock, and forward-order data into plain-language summaries for planning meetings. Identifies trends, spikes, and cover risks.
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