Supply Chain Dataset
100 supply-chain records with product type, SKU, availability, lead times, order quantities, shipping carriers and costs, defect rates, and transportation modes. Classic operations set for lead-time vs revenue analysis.
Challenge brief
Supply Chain Dataset - Challenge Brief
Challenge period: November 2024 Dataset: Reconstructed brief based on the shipped data file for the November 2024 DataDNA challenge.
About the data
The primary data table for this challenge carries the following columns:
Product typeSKUPriceAvailabilityNumber of products soldRevenue generatedCustomer demographicsStock levelsLead timesOrder quantitiesShipping timesShipping carriersShipping costsSupplier nameLocationLatitideLongitudeLead timeProduction volumesManufacturing lead timeManufacturing costsInspection resultsDefect ratesTransportation modesRoutes- ...and 1 more columns
Suggested analytical angles
- Which product types have the tightest lead-time-to-revenue ratios?
- How do defect rates cluster across carriers and transportation modes?
- Which suppliers deliver the strongest margin after shipping cost?
- How do stock levels interact with lead time to predict availability?
What great submissions did
This brief was reconstructed from the dataset contents in 2026 as part of the Playground audit. The original November 2024 challenge brief was not preserved as a separate file in the source archive, so the analytical angles above are inferred from the column list. See the corresponding /challenges/ entry on datadna.onyxdata.co.uk for examples of how participants approached the data.
This dataset was the subject of the DataDNA November 2024 community challenge. The original scoring and leaderboard pre-date the current submission system and are not available for display.