FINANCIAL ANALYSIS Public analysis engine
Profitability Driver Analysis
Understand profitability changes through price, volume and mix.
Cut through data overload to find the story behind profitability changes—and show management where to act.
Surfaces material drivers and opposing movements for finance review.
The business problem
Management needed to understand why profitability differed from expectations. A small net change could hide material pressures and offsetting improvements across countries and product segments. The analysis needed to distinguish calculated effects from commercial explanations that still required investigation.
My contribution
I developed a contribution-margin analysis and reporting workflow, evolving Power Query and Excel work into Python-based calculations, hierarchy-aware driver selection and reporting feeds. It supports actual-versus-expectation comparisons, country review and cross-country investigation of potential trends.
The result
The workflow makes recurring profitability analysis and its first draft repeatable, so finance can focus on commercial context and targeted follow-up. The current portfolio example also demonstrates the improvements made to driver selection and evidence traceability.
The original workflow used the internal label CM1 for contribution margin. The implementation calculates price and volume effects at its configured reporting leaf; “mix” is a residual and can include cost or reconciliation effects. It is not independent proof of a shift toward less profitable products.
SEE THE WORK
The idea in practice
Illustrative examples use fictional data.
What explains the shortfall?
Volume gains partly offset price pressure.
Fictional figures · mix includes residual effects
Expected contribution margin is 13 million euros; actual is 12.32 million, a shortfall of 680 thousand euros. The highlighted gap expands onto a separate change scale. Price contributes minus 1.58 million, volume plus 1 million, and mix and other effects minus 100 thousand. These reconcile to the shortfall. The analysis identifies drivers for investigation, not proven commercial causes.
The delivery approach
Calculate at the reporting leaf
Calculate effects at the lowest configured reporting elements—product families or subgroups in the saved workbook—and aggregate them through the hierarchy. Preserve explicit actual and comparison labels, and reconcile the bridge to the margin movement.
Find material movements and their offsets
Identify which countries, segments or reporting leaves contribute to each effect. Surface large opposing movements even when they cancel in the overall result.
Turn the analysis into a management discussion
Prepare charts and a first draft of commentary. Separate the arithmetic evidence from hypotheses about pricing, demand or portfolio changes, then identify the questions for local sales and finance teams.