Business Question:

Revenue was below budget. What is driving the variance – price, volume or product mix – and where should management focus?

Objective:

Analyse revenue performance against budget, identify the underlying price-volume-mix drivers and translate the findings into actionable commercial and finance recommendations.

This project uses SQL Server to prepare and structure Price-Volume-Mix revenue variance data, then connects the dataset to Power BI to build an interactive dashboard for Budget vs Actual analysis, KPI monitoring, monthly trends, and product-level insights.

SQL code can be found here

January revenue came in below budget, driven mainly by a volume shortfall. Pricing was slightly ahead of plan and helped offset part of the miss, while mix had only a limited overall impact. Overall, this suggests the gap is more demand / sales-execution related than a pricing issue at this point.

The near-term priority should be to recover volume rather than respond with pricing action. Current price realisation looks broadly healthy, so immediate discounting would likely address the wrong issue and could create unnecessary margin pressure. Focus should instead be on pipeline quality, conversion, deal timing, and any signs of competitive pressure.

Commercial

Review whether pipeline build is tracking below plan. Check if conversion rates are weaker than expected at any stage of the funnel. Assess whether competitors are taking share in key products or segments. Confirm whether deals have slipped into later months rather than being fully lost.

Finance

Re-forecast revenue and volume assumptions if the shortfall continues for three consecutive months. Investigate the root cause in more detail, including churn, run-rate, and order trends. Update Q1 and full-year assumptions based on latest trading evidence. Quantify the EBITDA impact of the volume shortfall. Track whether this is a one-off timing issue or the start of a broader trend.

From Analysis to Automated Reporting

The analysis can be developed into a repeatable management reporting solution using SQL and Power BI. The underlying SQL model provides a structured source for the reporting layer, while Power BI can provide automated refresh, interactive analysis and controlled distribution through Power BI Service.

Reporting Architecture

SQL Data → Financial Data Model → Power BI → Interactive Management Analysis

The solution can subsequently be extended into Power BI Service for scheduled refresh, controlled distribution and ongoing management reporting.