Key Takeaways

Enhanced Automation: Transitioned from manual, Excel/sharepoint-based reporting to an automated system, reducing manual workload.

Improved Forecast Accuracy: Achieved greater precision in cash flow forecasts through a harmonized, data-driven process.

Increased Transparency: Gained real-time visibility into cash positions across all entities, facilitating better liquidity management.

Streamlined Intercompany Transitions: Enhanced insight into payment and intercompany management, enabling quick identification of payables, receivables, and deviations.

Comprehensive Data Access: Access to current and historical financial data per entity, supporting informed decision-making.

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BearingPoint is an independent, Europe-based management and technology consultancy firm that supports world-leading businesses and organizations in over 75 countries. With this global reach, the firm needs to have real-time visibility of cash in the business. After struggling through a manual forecasting process with limited reporting capabilities, BearingPoint now uses CashAnalytics to operate a data driven cash flow forecasting process—driving value far beyond the Treasury function, across the entire business.

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Challenges

For BearingPoint, the goals were more automation, greater forecast accuracy and better insight into cash flow. As a global company, BearingPoint faced a major challenge: improving the accuracy and transparency of its company wide cash forecasting model.

Before adopting CashAnalytics, BearingPoint followed a decentralized, bottom-up cash flow reporting and forecast process centrally and locally. The firm’s team manually created reports to cover actual cash flows and forecasts for the entire organization with an Excel/SharePoint-based forecast tool. This manual nature of this process made it difficult for BearingPoint’s entities and head office to gain tangible cash flow insights from their data and forecasts, so they were unable to accurately determine their firm’s optimal future liquidity needs.

“We had an unharmonized approach of sourcing data, a lot of manual work, little alignment of the entities with respect to intercompany trading and receivables,” said Fynn Krüger, Senior Business Consultant at BearingPoint.

The BearingPoint team knew they needed a more sophisticated way to retrieve and reconcile data from local teams to get a clear overview of not only the future but also of the current cash balance available per entity, as well as historical financial data for each of them.

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Key Requirements Overview

Automate the collection and processing of information from various data sources

Harmonize company-wide models for cash flow forecasting

Implement a structure for backtesting forecasting models

Ensure automated matching of past actual cash flows into the right categories

Gain drill-down capabilities into the entity levels of forecasted data for better context

Provide rationales for deviations from actuals to forecasts

Use cash as a source for strategic growth

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Solution

BearingPoint adopted CashAnalytics to automate the cash forecasting process and connect the data between their business entities. “It was crucial to look at what step each individual entity needs to take and think about how we can harmonize across all entities, how data is pulled from the respective sources and added to the forecast,” said Fynn.

Automatic Data Collection for Forecasting

With CashAnalytics, BearingPoint now has a centrally controlled forecasting model that automatically collects data from key systems. “I feel a lot lighter. There is a system in place that is doing things for me that I enjoy using,” said Eveline. “It’s also the beginning of collaborating differently with our controllers across the business.”

Intelligent Payment Collection Forecasting

Prior to using our platform, BearingPoint’s team struggled to accurately forecast payment collections. The firm now uses CashAnalytics’ machine learning SmartLedger feature to create data-driven payment collection forecasts with in-depth analysis of customer behavior.

Instead of forecasting using payment due dates or manually calculating the average day to pay, the SmartLedger feature uses historical customer data to understand their payment behavior. This user-based assessment goes a long way toward improving the accuracy of forecasts.

Instant Transaction Classification

With BearingPoint’s corporate payments platform connected with CashAnalytics, this enabled the firm to automatically classify actuals within the forecast model.

Clear Cash Visibility

With their corporate treasury platform account connected to CashAnalytics, BearingPoint has a consolidated view of all their cash balances. The firm can drill down to the transaction account level and view cash flows across various locations — filtering by region or business unit — to identify key entities that influence the inflow and outflow of cash within the business.

At the touch of CashAnalytics’ consolidation and reporting button, for instance, BearingPoint’s team can view forecasts by entity level. The firm’s team can then easily identify what cash is available across various parts of the business.

Real-Time Record Reconciliation

As a business operating in 40 different locations, it was key for BearingPoint’s head office team to have intercompany flows automatically reconcile within the forecasting model. With CashAnalytics, each entity can now create line items and instantly populate their counterparty’s input sheet with intercompany transactions for immediate reconciliation.

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Conclusion

Streamlining Cash Flow Forecasting

With CashAnalytics, BearingPoint is saving huge amounts of time. They are now focusing on carrying out comparative and variance analysis—such as Forecast vs. Actual—and putting together reports to share with BearingPoint management, investors, and the Board.

CashAnalytics also lets the Treasury team see actual and forecasted cash flows over a 12-month period across the entire business.

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“We should have done this earlier,” said Eveline.

“It’s been smarter. I can go in there (into CashAnalytics) and see the clients that are paying, and that’s really nice to have in one place.”

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