Client name withheld under a non-disclosure agreement.
The challenge
The group distributes industrial components through branches in several Central European countries. Its strategy team wanted a clear view of where to open next. Each candidate market meant weeks of desk research: trade statistics, customer density, competitor lists and regulatory notes, collected from different sources into separate spreadsheets.
The team could review only a few markets per quarter. By the time a shortlist reached the board, parts of the data were months old, and two analysts rarely scored the same market the same way.
What we delivered
- AI-Powered Opportunity Intelligence. A screening model that scores each candidate market against criteria the strategy team set: demand indicators, competitor density, logistics reach and regulatory effort. The model ranks the markets and shows which factors drive each score.
- Market & Business Intelligence. Automated collection of trade, industry and company data into one market dataset that refreshes monthly. Analysts can trace every figure back to its source.
We started from the evaluation checklist the analysts already used and turned it into weighted criteria with them. We then tested the rankings against expansion decisions the group had made in previous years before anyone relied on them.
Timeline
- Weeks 1 to 3: data audit and agreement on scoring criteria
- Weeks 4 to 9: data pipelines and the first version of the scoring model
- Weeks 10 to 14: validation against past decisions, analyst training and handover
Outcomes
- 30 to 40% less analyst time per market review
- Screening coverage grew from a few markets per quarter to the full regional shortlist
- The board now receives a ranking refreshed every month instead of once a year