Commodity & Gas Index Mapping

2023 · Python, NLP, Snowflake, Public Gas & Commodities APIs

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Problem

During the Ukraine war, gas prices surged and suppliers started citing increased production costs as justification for price increases. The problem: there was no way to verify these claims independently, and no systematic tracking of the input costs that actually drive supplier pricing — gas indices, flour, sugar, cocoa, wheat.

If suppliers claim their costs went up, you need the data to check.

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Solution

Pulled public gas and commodity price indices via APIs and mapped them to the relevant supplier cost structures using NLP. The mapping identifies which commodities are inputs to which product categories, tracks index movements over time, and surfaces the correlation between commodity prices and supplier price change requests.

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Architecture

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Status

This was a proof-of-concept used manually. It was useful for specific negotiation moments — checking whether a supplier's claimed cost increase matched what the indices showed — but wasn't productionized into an automated workflow.