Supply Chain & Logistics
Packaging optimisation using AI
Analyse product dimensions and fragility to recommend optimal packaging size and material. Reduce void fill, packaging waste, and shipping costs by right-sizing every order.
10–25%
reduction in packaging material cost
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.
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
Dimensional weight pricing by carriers means oversized packaging is doubly expensive — you pay for the space and the waste. Right-sizing packaging directly reduces shipping costs.
Accurate product dimension data is the prerequisite. If your product master data has approximate or missing dimensions, start by measuring your top 100 shipped products.
The sustainability angle is commercially valuable — demonstrating reduced packaging waste resonates with environmentally conscious customers and supports ESG reporting.
Experiment starter: Measure the void space in your last 50 shipped orders. If average void exceeds 30%, there's meaningful packaging optimisation opportunity. Trial right-sized packaging for your top 10 shipped products and measure material cost and damage rate changes.
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 Supply Chain & Logistics
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