Industries
Five industries. One pattern of work.
Different operating contexts, the same data problems — and the same playbook for solving them.
Restaurants & Multi-Unit Retail
Multi-unit QSR · Big-box retail · Department stores
Multi-unit operations analytics, single view of customer across channels, franchise data pipelines, store-level performance reporting.
Insurance & Reinsurance
Global reinsurance · Multi-line carriers
Underwriting, claims, program-manager and carrier integration, predictive analytics for specialty lines, actuarial-data platforms.
Financial Services & Mortgage
Mortgage finance enterprises
Loss-mitigation analytics, credit-data repositories, servicer scorecard programs, self-service analytics portals at scale.
Distribution & Supply Chain
Supermarket & food-service distribution
Inventory and service-level analytics, vendor and DC performance, on-hand and on-order analysis — the work that found $5M of avoided spend at one supermarket distributor.
Marketing & AdTech
Holding-company marketing agencies
Campaign analytics, CRM and customer-touchpoint integration, weekly client reporting at scale, agency delivery operations.
Cross-Cutting
What we see across all five.
Multi-unit / multi-channel operators all hit the same wall: their data scales linearly with units, but their analytics capability scales sublinearly with leadership.
The single biggest source of analytics dysfunction is not technology — it is the gap between what the business asks for and what the business actually needs to decide.
Self-service is rarely the answer on its own. Governed self-service is.
Cloud migrations rarely fail on the technology. They fail on the team operating model that should have changed alongside.
Recognize your industry?
Tell us where the analytics function is breaking down. We’ll tell you whether we’ve seen the same pattern before — and what worked.