Analytics project / Decision support
Account Health Framework
A multi-factor scoring framework designed to evaluate customer value, risk, and commercial prioritization beyond revenue alone.
It gives teams a shared way to identify accounts worth a closer look, understand what drives their scores, and decide where to focus.
My role: Led the scoring methodology, framework design, Power BI development, stakeholder validation, and training for the broader team and leadership on evaluating accounts with the framework.
How the framework works
Four dimensions. One adaptable health score.
We identified contribution, growth, cash flow, and cost-to-serve as four dimensions of account health. Each has its own scoring logic, with configurable weights combining them into an assessment that reflects business priorities.
- DimensionContributionProfitability
- DimensionGrowthChange over time
- DimensionCash FlowPayment behavior
- DimensionCost-to-ServeService efficiency
HealthCombined assessment
Configurable weighting across dimensions
From assessment to account prioritization.
The combined assessment informs an account health group and helps focus commercial review, retention, growth or deeper investigation.
Conceptual framework illustration. It does not show fixed weights, individual account scores or simulated financial outcomes.
Try the framework
How would changing priorities affect your accounts?
Business priorities can change. A company may prioritize cash flow over growth at certain times, for example. Adjust the weights to see how account scores, rankings, and classifications respond.
Changing one weight redistributes the rest. These are example settings, not the live report's weights.
Northstar Coffee
| Account | Default | Scenario | Group | Rank |
|---|---|---|---|---|
| 9.5 | 9.5 | Strong | — | |
| 8.1 | 8.1 | Stable | — | |
| 7.8 | 7.8 | Stable | — | |
| 7.5 | 7.5 | Stable | — | |
| 7.0 | 7.0 | Stable | — | |
| 6.7 | 6.7 | Weak | — | |
| 6.6 | 6.6 | Weak | — | |
| 3.9 | 3.9 | Weak | — | |
| 3.0 | 3.0 | Weak | — | |
| 2.0 | 2.0 | Critical | — |
No accounts changed health groups. Rank movement is compared with default weighting.
This is a fictional what-if exercise, not the production scoring model. Account names, component scores, default weights, and scenarios are invented. Scores use illustrative 0–10 bands (Strong 9–10, Stable 7–8.9, Weak 3–6.9, Critical below 3). Higher component scores always indicate more favorable performance.
01
Why Revenue Wasn't Enough
Revenue shows account size, but not necessarily profitability, growth, payment performance, or service efficiency.
02
Explore the report
Report Walkthrough
Four ways to investigate account health
Choose a view to see how the report supports account diagnosis, revenue comparisons, trend monitoring, and portfolio review.
Move from portfolio signal to account-level drivers
Understand the factors behind an account's health score and investigate areas of concern.
Demo data note: Customer names, account attributes, classifications, and financial values shown in this case study have been fictionalized or transformed for public presentation.
03
Technical Implementation
Built in Power BI using SQL Server, Analysis Services, and shared semantic models. Custom DAX measures supported dimension-level scoring and weighting, while automated refresh and stakeholder-tested definitions enabled repeatable account reviews.
I'm also exploring whether predictive modeling and machine learning could complement the framework in future iterations. These ideas are exploratory and are not part of the current scoring model.
Decision Studio / Continue exploring
