Financial Data Integration Ahead of a Global Merger

The Situation

The client was in discussions with a competitor about a potential acquisition and merger. Ahead of the transaction, their financial data needed to be mapped to the acquiring company's metadata structure.

Each company's data structure had been designed independently, which made one-to-one mapping extremely complex and meant extensive data cleanup would be required first. The two forecasting models were also different, so a new 12-month forecast had to be developed to match the acquirer's. Finally, a new profitability cost management allocation process had to be established in a matter of months, replicating a process the acquiring company had taken five years to build.

The Challenge

The client considered a number of vendors, including two of the Big Four professional services firms. We were selected based on the quality of work delivered on prior projects and our familiarity with the client's data.

That familiarity mattered more than it might sound. In an M&A timeline, there is no room to spend the first month learning where the data lives.

Our Approach

We established a five-member team working alongside both companies' IT, finance, integration, and divestiture organizations. Over four months the teams worked together across every phase.

Financial data mapping. Understanding both companies' data structures was the foundation. Data had to be mapped to the acquirer's metadata structure using the client's data. Accounts including Company Code, Cost Center, Product Line, Function, and Entity, along with functional accounts, had to be matched. Selected accounts were redefined and logic was created to map like accounts accurately.

Forecast development. We recreated the logic for a process mirroring the acquirer's 12-month forecast, replacing the client's quarterly cycle. After meetings with FP&A stakeholders to complete data requirements and acceptance of the Business Requirement Document, a proof of concept was built in Hyperion Planning. The team created seven data forms across Excel and the online interface, through which end users prepared forecasts. Calculation logic ran automatically on save, eliminating additional steps. Maxl scripts extracted data from the planning team and loaded it into the reporting Essbase database, and 18 additional reports were updated for the acquiring company.

The Results

The integration was delivered across all phases within the merger timeline, giving both organizations a single mapped view of the client's financial data ahead of the transaction.

Why It Mattered

Merger timelines do not move. Financial data that cannot be mapped to the acquirer's structure on schedule becomes a due diligence problem, and due diligence problems change deal terms.