DashboardWorx
Rebuilt Commercial Reporting Infrastructure, Cut Turnaround by 95%
0%
Forecast Accuracy
0%
Discretionary Spend Cut
0%
Reporting Effort Cut
0%
Turnaround Acceleration
Executive Summary
DashboardWorx, a boutique analytics consultancy serving 20+ clients across financial services and commercial sectors, brought me on as Financial Data Analyst Consultant to fix a forecasting process that was fragmented across business units, planned separately in spreadsheets with no shared assumptions or drivers. I traced the breakdown to its structural cause rather than assuming the model needed rebuilding, then designed an integrated revenue and expenditure model built in Excel for transparency and surfaced through Power BI so stakeholders could see the drivers behind the numbers, not just the outputs. I worked the assumptions through directly with finance and operational teams, connected the model to live Power BI dashboards, and produced monthly variance commentary that explained movements rather than reporting them after the fact. Forecast accuracy improved by 40%, and the cost-driver analysis that came out of the variance work identified where discretionary spend was concentrated, informing recommendations that cut it by 10% within four weeks.
Context
DashboardWorx is a boutique analytics consultancy serving 20+ clients across financial services and commercial sectors. As Financial Data Analyst Consultant from January 2026, I supported budget and forecasting cycles for client organisations where revenue and expenditure were planned separately across business units, in spreadsheets not linked to a common set of assumptions or drivers.
Challenge
Variances between budget and actuals were being explained after the fact rather than anticipated, management had limited visibility into which cost drivers were moving, and forecast accuracy was weak enough that the numbers weren't reliable inputs to decisions. The commercial impact was that discretionary spend decisions were being made without a clear view of what was actually driving cost.
Strategic Approach
Phase 1
Diagnosis
I traced where the forecast was breaking down by comparing prior forecasts against actuals, rather than assuming the model needed rebuilding, and found the error was structural: business units forecast independently against inconsistent drivers, so errors compounded rather than offsetting.
Phase 2
Integration
I designed an approach that modelled revenue and expenditure together against shared drivers, built in Excel for transparency and surfaced through Power BI so stakeholders could see the drivers behind the numbers, working through the assumptions directly with finance and operational teams.
Phase 3
Embedding the Discipline
I connected the integrated models to live Power BI dashboards giving management real-time visibility of budget versus actuals, and produced monthly variance commentary that explained movements rather than just reporting them.
Quantifiable Outcomes
- Forecast accuracy improved by 40% across the business units in scope.
- Discretionary operating spend reduced by 10% within four weeks, following evidence-based cost-driver recommendations to management.
- Cost-driver analysis identified where discretionary spend was concentrated and which items weren't delivering proportionate value.
- Reporting effort cut by 60% and pricing/reporting turnaround accelerated by 95% through the SQL ETL pipelines and Power BI dashboards built across the same engagement.
Qualitative Achievements
- Shifted how finance engaged with the business, from reporting what had happened to identifying what to do about it.
- Gave buyers and the merchandise team direct visibility into expenditure control through variance commentary they could act on immediately.
- Supported evidence-based CapEx and operational expenditure decisions across financial services and commercial clients.
A forecast model is only as good as the business logic behind it. Integrating the numbers matters less than integrating the people who understand what's actually driving them.
This engagement is the clearest evidence of what I bring to a commercial finance function: the ability to diagnose why a forecasting process is breaking down structurally, then design and embed the fix, not just operate inside the existing process. It remains an active engagement at DashboardWorx.