Merchandising & Buying
Supplier spec sheet extraction
Extract structured product data from unstructured supplier spec sheets, PDFs, and email attachments. Outputs clean records ready for system upload.
70–85%
reduction in manual data entry time
Use case assessment
Negligible commercial impact. Saves time at the margins but won't move the needle on revenue or profit.
Relatively straightforward. Off-the-shelf tools handle the core task. Implementation is well-understood with good examples to follow.
Light data requirements. Uses straightforward inputs (documents, product descriptions, customer records) that are usually accessible with minimal prep.
Low risk. Limited external exposure. A human reviews output before it reaches anyone outside the team.
Light people impact. A new tool slots into an existing workflow. Minimal training needed. Most people will adapt quickly.
Tooling required
Things to consider
Supplier documents vary significantly in format. The extraction model needs exposure to the range of formats you receive before you can rely on it.
Build a validation step for anomalous outputs (blanks, implausible values) before records reach the system.
Map the target data schema first: knowing exactly what fields you need makes prompt design and validation much more precise.
Consider whether the root problem is the input format. A structured supplier portal or standardised template may solve the problem more cleanly than processing unstructured documents downstream.
Experiment starter: Collect 50 spec sheets from your top five suppliers. Define the target extraction schema. Run a prompted extraction and measure field-level accuracy. Aim for over 90% accuracy on mandatory fields before proceeding to automation.
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