Minimum Viable Product Set
A data-driven analysis that reduced a complex catalogue of nearly 6,000 SKUs into a focused selection of 20 essential products — a strategic approach to launching lean, minimising risk and maximising recurring revenue potential.
- Year
- 2024
- Engagement
- Data analysis
- Focus
- Data Engineering, AI/ML
- Status
- Open source
01 — The problem
Launching with 6,000 SKUs means 6,000 ways to tie up capital. The commercial question — which handful of products actually carries the offering — is a data problem disguised as a merchandising one.
02 — Our solution
Analyse the catalogue on its own numbers: coverage, overlap and recurring-revenue potential, then narrow to the smallest set that still serves the demand. The output is a defensible shortlist, not an opinion.
How it works
The pipeline, step by step — from the first input to the final output.
- 01
Catalogue profiling
The full SKU set is profiled to understand structure, overlap and distribution.
- 02
Criteria definition
Selection criteria are defined around coverage and recurring revenue potential.
- 03
Reduction
The catalogue is narrowed iteratively against those criteria.
- 04
Validation
The resulting set is checked to confirm it still covers the intended demand.
What we built
The outcomes
01
A focused 20-product launch set from ~6,000 SKUs
02
A documented, repeatable selection method
03
Reduced launch risk and inventory exposure
Challenges we solved
Defining "essential"
The analysis is only as good as the criteria. Making them explicit is what turns a judgement call into a repeatable method.
Technology stack
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