We connect data to decisions, and people to opportunities.
Sharper strategy. Better-managed data. More revenue. The right introductions.
Our clients share one thing: a significant decision that depends on data or technology, and not enough independent clarity to make it with confidence.
CDOs, CDAOs and Heads of Analytics who need a strategy the business will adopt, an operating model that scales, and an honest view on where AI fits.
VCs, private equity, angels and family offices who need to know whether a company's data and AI capability is real, defensible and worth the valuation.
Teams who need senior data leadership before they can justify a full-time hire, or a data story that stands up in the next raise.
Three practice areas. One way of working: we start with research, not assumptions, and finish with an outcome you can measure.
For enterprises and SMEs
Most organisations hold data that is worth more than they realise. We find where it can create value, through new revenue, lower costs or better decisions, then build the business case, model and products to capture it.
Typical work
For enterprise data and technology leaders
We diagnose how data is really used across your organisation, find what's actually blocking value, and design the strategy, operating model and data products to fix it. We then stay close enough to see it delivered.
Typical work
For VCs, private equity, angels and family offices
An independent, practitioner's view of a target's data, AI and technology. We separate genuine capability from the pitch, quantify the risks, and show where value can be created after the deal closes.
Typical work
Clear scope, clear outputs, and a format that suits the decision. Most clients start with a diagnostic and continue from there.
2 to 4 weeks
Interviews, data review and a written recommendation with a prioritised plan.
Deal timeline
A fixed-scope assessment of a target's data, AI and technology, reported to your investment committee.
Monthly
Ongoing senior counsel for leadership teams and boards as decisions come up.
1 to 3 days a week
Embedded data leadership until you're ready for a permanent hire.
Client details are withheld. Every engagement follows the same principles: research, insight, strategy, outcome.
Interviews across the client's three regions on their challenges, how they used data day to day, and what information they could actually access.
Local customisation in each region, not the underlying data, was the real cause of inconsistent reporting.
Changed the operating model to centralise data ownership, then designed and led the build of standard global data products to support it.
Daily dynamic reporting increased efficiency, and a single source of truth removed the risk of relying on inconsistent regional data.
A light audit of architecture and operations found product usage data siloed in an analytics tool, sales data fragmented in the CRM, and finance tracked in spreadsheets.
Duplicate customer identifiers hid the full customer journey. The board couldn't get reliable Net Revenue Retention or CAC payback by cohort, the figures that would justify the Series A valuation.
Designed a modern data stack to centralise the data, and established a single source of truth for customer IDs.
An automated, real-time board dashboard tracking unit economics, with NRR and CAC payback reported by cohort.
Strong transactional data collection, but no formal data governance or predictive modelling. Risk was assessed reactively through manual SQL queries.
Manual risk checks were slowing credit approvals and increasing fraud exposure. To secure institutional debt alongside the equity round, the board needed AML and KYC compliance reporting and a validated model for loan defaults.
Recruited and structured an agile data science squad, introduced data cataloguing for compliance, and deployed an automated risk-scoring model.
Default rates fell by 14%, and the board gained real-time visibility of portfolio risk.
Our thinking on data, AI and the decisions around them.
Bi-weekly briefing
AI and data developments translated into decisions for CDOs, CDAOs, Heads of Analytics and the investors who back data-driven businesses.
Subscribe to The AI StrategistOpinion writing for Computer Weekly on leadership and diversity in technology.
Read in Computer WeeklyTools and research where we test our methods in public, including football modelling and tournament analysis.
A short introductory call is the best place to start. It's free, and you'll leave with a clearer view of the problem whether or not we work together.
30 minutes with Diana to talk through your situation and whether we're the right fit.
Request a callOr email hello@insightsessions.co.uk
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