The Premise / Practice / Data Analysis
iv. Data Analysis
Most operating questions are data questions in disguise. The practice exists to ask them in the right form.
Capabilities
The work
A summary number compresses information. That is its job. The cost is that the interesting findings, the ones that change a decision, almost always live one layer below the rollup. The first question of any data engagement is whether the data is being cut at a fine enough grain to support the question being asked.
Common engagements include pricing and fee structure analysis on multi-year transaction histories, revenue impact modeling for a policy or operational change, and scenario work that compares two or three viable paths against each other on consistent assumptions.
Deliverables tend to include a working model the client can run after the engagement closes, a memo with the recommended path and the analytical basis for it, and a short briefing for the leadership team that will make the decision. A dashboard is sometimes the right output. More often it is not.
The Premise at Scale.
Related practices
The system the data describes. Analysis without an operating context is academic.
The infrastructure that makes high-quality analysis possible at speed. Most analytical bottlenecks are platform problems.
What the analysis is for. A clean number with no decision attached is a slide.