Holistic by Design
Contribution, growth, cash flow, and cost to serve provide a broader view of customer value than any single metric.
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Case Study
Account Health Framework
A standardized decision-support framework for evaluating customer value beyond revenue.
Contribution
Growth
Cash Flow
Cost to Serve
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Account Health Score
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Commercial Decision Support
Overview
Executive Summary
The Account Health Framework established a standardized way to evaluate customer accounts across a large commercial portfolio using a weighted evaluation framework based on contribution, growth, cash flow, and cost to serve. These dimensions were identified as the key factors that best represent long-term account health, moving the business beyond evaluating customers primarily through revenue.
I led the initiative from concept through implementation, designing the evaluation methodology, developing the scoring model, building the Power BI solution, and collaborating with operations, finance, and executive leadership to validate and adopt the framework. Today, it supports monthly portfolio reviews and helps leadership make more informed commercial decisions.
01
Why Revenue Wasn't Enough
Customer accounts were primarily evaluated through revenue and a handful of financial metrics. While useful individually, no single measure could adequately represent overall account health or long-term customer value. A more holistic and standardized approach was needed.
02
The Solution
I built the Account Health Score around four dimensions: Contribution, Growth, Cash Flow, and Cost to Serve. Each dimension captures a different characteristic of customer value and contributes to the overall score through a configurable weighting model.
The framework was intentionally designed to remain flexible. By adjusting the weighting of each dimension, the evaluation model can evolve alongside changing business priorities without requiring structural changes to the solution. This allows leadership to emphasize the metrics that matter most at different stages of the business.
Demo data note: All customer names, account attributes, classifications, and financial values shown in this case study have been sanitized or transformed for public presentation. The demo uses a reduced sample of 100 fictionalized accounts and does not represent actual customers or business activity.
03
Design Principles
Built to Adapt
Configurable weighting allows business priorities to change without rebuilding the evaluation model.
Grounded in Business Reality
The scoring methodology was iteratively validated against known account performance and stakeholder expectations.
04
Business Impact
The framework supports monthly executive portfolio reviews through a daily refreshed Power BI solution.
By shifting the focus from revenue alone to long-term customer value, it helps identify underperforming partnerships, prioritize healthier customer relationships, and establish a shared language for evaluating account health across the business.
From Portfolio Signal to Driver Analysis
Move from a portfolio-level signal to the drivers behind it.
The drill-through workflow allows users to move from a portfolio-level signal into the underlying drivers of an account's score. In the sanitized demo below, a fictional account with meaningful revenue scores poorly overall because weak contribution and cost-to-serve performance outweigh stronger cash-flow performance.
05
Implementation
The framework was implemented in Power BI using enterprise data from SQL Server, Analysis Services, and existing semantic models. Custom DAX measures, automated refresh processes, and ongoing data governance ensure the solution remains reliable, performant, and trusted for executive decision-making.
SQL ServerAnalysis ServicesSemantic ModelsPower BIExecutive Decision Support
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What the Framework Enables
Beyond current portfolio evaluation, the Account Health Score creates a consistent foundation for deeper analysis. Historical scores can be used to study which customer characteristics are most associated with long-term account health and, over time, support predictive analysis earlier in the commercial process.
Continue Exploring
More work is on the way.
Additional case studies focused on sourcing optimization, profitability, and enterprise sales reporting are currently being prepared.
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