Customer Story

Consumer Goods: Commercial Data Automation

For a multinational food company operating across 12 business units, finance automation wasn't a nice-to-have - it was survival.
Location
Sweden
Industry
Consumer goods
Website
European Consumer Goods Company   Transformance Case Study
120h
productivity gains per month gained

For a multinational food company operating across 12 business units, finance automation wasn’t a nice-to-have - it was survival. Commercial reporting had become a serious operational drag: each region produced its own data using local tools and formats, leadership couldn’t align on the numbers, and teams spent more time gathering data than using it. Commercial planning cycles were delayed, and performance reviews depended on Excel files that differed by business unit. This is what happens when data fragmentation goes unaddressed at scale.

The Challenge

Manual data aggregation and inconsistent KPIs were costing the company over 120 hours of productivity every month. But the real cost wasn’t just the hours - it was the erosion of trust in the numbers themselves.

When finance and sales leadership sit down for a performance review and can’t agree on which spreadsheet is correct, decision-making stalls. Agile steering becomes nearly impossible. Pricing decisions, trade spend reviews, and channel performance calls all depend on a shared view of commercial data - and that view simply didn’t exist.

Existing BI tools couldn’t solve the problem. The fragmentation was upstream: different definitions, different upload formats, different timelines across 12 business units. Until the data was harmonised at the source, any dashboard built on top of it would reflect the chaos beneath.

For enterprise finance teams in consumer goods, this is a familiar pattern. CPG data automation challenges aren’t just a technical inconvenience - they create real exposure. Inaccurate or incomplete commercial data doesn’t stay in a spreadsheet. It flows downstream into invoicing, deductions, and cash application, where errors become disputes, and disputes become write-offs.

The Solution

With Transformance, the company built a custom Commercial Hub that unified data across all 12 business units.

The app harmonises uploads and API connections from each unit, validates the data automatically, and connects directly to the company’s existing BI stack. Built-in logic enforces consistency of definitions - so a “sell-out unit” means the same thing in France as it does in Germany. KPI dashboards make comparisons between units fast and frictionless.

The first version was live in just four weeks, without requiring a central rebuild of the company’s BI model. That’s the practical advantage of modular commercial reporting automation: you can solve the upstream data problem without ripping out the downstream infrastructure that teams already depend on.

The solution scaled across all 12 units without requiring each region to change how they work - the Hub absorbs the variation and outputs consistency.

The Impact

The Commercial Hub eliminated 120+ hours of manual consolidation every month and gave leadership real-time visibility into sales, margin, and channel performance across the entire group.

Instead of debating Excel files, teams now focus on what matters: improving outcomes.

“Finally all commercial and financial KPIs in one place.”- SVP Sales Enablement

The team is already expanding the solution to include product-level margin analytics and monthly pricing impact reviews - all powered by the same modular Transformance framework.

What This Means for O2C and AR Teams

Commercial data doesn’t live in isolation. Sell-out figures, channel mix, and trade spend data are the upstream inputs that determine what gets invoiced, what deductions are valid, and ultimately what’s collected.

When that data is fragmented or untrustworthy, the problems compound quickly. Finance process automation at the commercial level creates a cleaner data foundation for everything that follows in the order-to-cash cycle:

  • Cash application depends on accurate invoice matching, which starts with accurate order and sell-out data.
  • Deductions management requires reliable trade spend and promotional data to validate or dispute claims. When commercial KPIs are inconsistent across regions, invalid deductions slip through - or valid ones get disputed unnecessarily.
  • AR aging and collections benefit from leadership having a single, trusted view of what’s owed and why.

For CPG companies specifically, this connection is critical. The volume of trade promotions, retailer deductions, and co-op agreements means that any ambiguity in the commercial data layer creates disproportionate downstream costs. Automating claims processing - as explored in our piece on AI claims automation for CPGs - is far more effective when the underlying commercial data is already clean and unified.

If your team is dealing with high deduction volumes or reconciliation delays, the root cause is often upstream. Understanding why claims reconciliation matters for CPGs starts with getting commercial data right.

Frequently Asked Questions

What is finance automation in the context of commercial reporting?Finance automation in commercial reporting means replacing manual data collection, consolidation, and validation with systems that do this automatically - giving finance and sales teams a single, consistent view of KPIs without the spreadsheet overhead.

How does commercial data quality affect accounts receivable?Poor commercial data quality creates downstream AR problems: invoicing errors, unresolved deductions, and slow cash application. When sell-out and trade spend data is fragmented, it’s harder to validate what’s owed and why - leading to disputes and delayed collections.

How long does it take to implement a commercial data automation solution?Implementation timelines vary, but modular solutions can go live quickly without requiring a full BI rebuild. In this case, the first working version was deployed in four weeks across 12 business units.

Is CPG data automation relevant for mid-sized companies, or only large enterprises?CPG data automation delivers value at any scale where multiple regions, channels, or business units are producing data independently. The fragmentation problem isn’t unique to large enterprises - it appears wherever data ownership is distributed.


Ready to automate your commercial reporting? Book a demo to see how Transformance can deliver similar results for your team.

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