A Fortune 500 financial services institution had modern analytics available to a handful of technical users and spreadsheets everywhere else. We built a 14-week enablement framework that took Finance from three platform users to more than a hundred, and 85 automation use cases into production.
85 automation use cases in production and 3,721 annual hours saved, with adoption across more than 100 active participants.
Finance ran on spreadsheets. Advanced automation sat with three technical users, and earlier training rollouts had produced attendance but no lasting change.
One designated analytics platform, a 14-week enablement framework with 48 hours of instructor-led training, and a tiered no-code to pro-code capability model.
85 automation use cases in production and 3,721 annual hours saved, with adoption across more than 100 active participants.
Finance designated a single modern analytics platform as a core productivity tool, ending tool sprawl. Business users, analysts, and advanced practitioners came under one operating model with shared governance and consistent data definitions.
A 14-week innovation framework with 48 hours of instructor-led training, built on applied business problems rather than product features. The rollout was accountability-driven, with a visible link between what someone learned and what it saved.
Structured ideation cycles and gamified hackathons kept the candidate pipeline full. A tiered no-code to pro-code model let business users start simple and analysts go deeper, without forcing anyone to become an engineer.
Across controllership, tax, planning, and commercial finance, data volumes and regulatory demands had outgrown manual processes and disconnected tools. The gaps showed up as operational risk rather than inconvenience.
Analytics capability varied widely between functions. Some teams generated insight quickly, others waited. Advanced automation sat with a small subset of technical users, which capped how far any single improvement could travel — a reconciliation automated in one group stayed in that group.
The organization had tried to close the gap before. Traditional training and ad hoc tool rollouts produced attendance, then no sustained change in how the work got done. Three people were using the analytics platform the company already owned.
We started by settling the tool question, then let enablement carry the rest. People learned the platform by automating work they already owned, which is why the capability held after we left. The tiered model mattered as much as the training: business users stayed useful at the no-code end, and the people who wanted depth were not held back by the entry point.
Finance delivered 85 cross-functional automation use cases — automated reconciliations and reporting workflows, forecasting and predictive modeling, and enterprise data integration built without creating a new skill silo. Adoption went from 3 initial users to more than 100 active participants in four months. 84% of them had never used the platform before.
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