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 decentralised, 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 organisation 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 unharmonised 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.

1. Automate the collection and processing of information from various data sources
2. Harmonise company-wide models for cash flow forecasting
3. Implement a structure for backtesting forecasting models
4. Ensure automated matching of past actual cash flows into the right categories
5. Gain drill-down capabilities into the entity levels of forecasted data for better context
6. Provide rationales for deviations from actuals to forecasts
7. Use cash as a source for strategic growth

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.

“The system can learn how your clients are paying and look at historic[al] patterns,” said Eveline. “You can understand how our customers pay, something that adds value not only from a forecasting perspective but broader cash management and working capital processes.”

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.

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.

“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.”