Advisory & Consulting
Your team knows something isn't working. No one can quite say what.
Data, technology, and business model decisions fail when they're made apart.
20+ Years in Quantitative Risk Systems
BARCLAYS — DEUTSCHE BANK — BNP PARIBAS — CITIGROUP
Where This Gets Triggered
The work sits where business, data, and technology decisions start to collide.
- Leadership is split between technical and commercial perspectives, with no one reconciling the two.
- AI strategy is being discussed without a clear view of the operational foundations underneath it.
- Data exists across the business, but decisions are still being made with limited confidence in it.
- Product or technology choices are starting to affect revenue, cost structure, or market position.
- Systems, processes, and data aren't compounding into a clear operational advantage.
The Through-Line
Quantitative risk taught me to make high-stakes decisions from imperfect data. The same discipline applies now — the data is rarely clean; the question is what can be decided reliably on what already exists.
Published Thinking
What this is grounded in
- Africa's Trust Infrastructure SSRN white paper on identity, verification, and SME growth barriers in African markets.
- No One Cares About Dashboards On why reporting projects fail, and what businesses need before analytics is useful.
- Data Foundations — Ahjayee Learn Curriculum built on the BFA methodology. Live now, with further levels following.