Finance Data & Analytics · Case Study
How a Fortune 500 Auto Ancillary Manufacturer Cut Period-End Close from 10 to 3 Days
Finance Data & Analytics | Manufacturing. See how a Fortune 500 auto ancillary manufacturer standardized revenue, cost, and margin definitions across BUs and cut period-end reporting from 10 to 3 days.
Each business unit was reporting revenue, cost and margin, but Group Finance still had to make those numbers comparable before it could understand performance. Period-end close took 10 days.
d4 codified group definitions for revenue, cost, and margin and applied them consistently to BU-level financial data before consolidated reporting. The same governed logic fed cost variance analysis and natural-language queries on live financial data.
Period-end close dropped from 10 days to 3. Finance gained access to 65% of COGS information for daily analysis. One definition was applied consistently across BUs.
01 · The challenge
Making BU-level financials comparable before reporting could even begin.
For a Fortune 500 auto ancillary manufacturer, each business unit was reporting revenue, cost and margin. But Group Finance still had to make those numbers comparable before it could understand and explain performance across the business.
Definitions and calculations needed to be applied consistently across BUs before consolidated reporting and variance analysis could begin. This added time to the reporting process, with period-end close taking 10 days.
Once the period-end numbers were consolidated, Finance still had to understand what was driving changes in margin. That meant analyzing cost variances, tracing their impact on profitability, and explaining what had changed and why.
A working example
Period-end close took 10 days. The numbers were not yet comparable.
Each BU can report revenue, cost, and margin. Before Group Finance can explain performance - or act - it still has to determine whether those numbers were defined and calculated the same way. None of the questions below are answered by BU reports alone.
The corporate Finance team no longer had to spend the first part of every reporting cycle making BU numbers comparable. This gave Finance more time to understand what was changing across the business and why.
Manufacturing · Finance Data & Analytics
02 · The insight
Automating period-end reporting and margin analysis
Midoffice Data’s d4 codified group definitions for revenue, cost, and margin and applied them consistently to BU-level financial data before consolidated reporting. This gave Group Finance a common view of performance across the business.
The same governed logic fed cost variance analysis, allowing Finance to move from reported margins to the underlying cost drivers without rebuilding calculations outside the reporting process.
Natural-language queries on live financial data gave Finance teams another way to investigate changes and get to the drivers faster. These insights also fed into automated reporting, reducing the manual work involved in preparing and explaining the numbers.
03 · The framework
What the governed definitions made possible
Finance needed more than BU reports. It needed group definitions applied the same way every time, cost drivers that could be traced without rebuilding calculations, and earlier access to the numbers.
Group definitions, codified
d4 codified group definitions for revenue, cost, and margin so Finance was no longer reconciling different calculations across business units at period-end.
Applied before consolidation
Those definitions were applied consistently to BU-level financial data before consolidated reporting. That gave Group Finance a common view of performance across the business.
Cost variance from the same logic
The same governed logic fed cost variance analysis, so Finance could move from reported margins to the underlying cost drivers without rebuilding calculations outside the reporting process.
Live queries, automated reporting
Natural-language queries on live financial data helped Finance investigate changes faster. Those insights also fed into automated reporting, reducing the manual work of preparing and explaining the numbers.
04 · The approach
How d4 automated period-end reporting and margin analysis
The work was practical: make BU numbers comparable, keep the same logic in the reporting process, and give Finance a faster path from reported performance to the drivers behind it.
Codify group definitions for revenue, cost, and margin
Midoffice Data’s d4 captured the group definitions Finance needed so every business unit was measured the same way.
Apply those definitions to BU-level financial data
Definitions were applied consistently before consolidated reporting, giving Group Finance a common view of performance across the business.
Feed cost variance analysis from the same governed logic
Finance could move from reported margins to the underlying cost drivers without rebuilding calculations outside the reporting process.
Investigate on live data and automate the reporting pack
Natural-language queries on live financial data helped Finance get to the drivers faster. Those insights fed automated reporting and reduced the manual work of preparing and explaining the numbers.
05 · The impact
From a 10-day close to 3 days
With consolidated reporting automated and governed definitions applied consistently across BUs, period-end close dropped from 10 days to 3. This provided Finance with earlier access to the numbers needed for analysis.
Finance also gained access to 65% of COGS information for daily analysis, providing a more timely view of the costs influencing profitability. The same governed logic now supported both period-end reporting and ongoing performance analysis.
The corporate Finance team no longer had to spend the first part of every reporting cycle making BU numbers comparable. This gave Finance more time to understand what was changing across the business and why.
Next step
See how d4 can help your Finance team accelerate reporting and margin analysis.
Book a demo to see how governed group definitions, applied consistently across business units, can cut period-end close and give Finance earlier access to the numbers needed for analysis.