Overcome 3 Cash Forecasting Challenges

3 Key Cash Forecasting Performance Levers

There are three key performance levers of cash forecasting:

1. Visibility: Ability to view forecasts by categories, regions, and entities and track individual cash flows.

2. Accuracy: The efficacy of the forecasts required to make confident decisions.

3. Frequency: The forecasting cadence required to make timely decisions.

Challenges in Cash Forecasting Performance Levers

Visibility

Since the data is scattered across several entities such as TMS, ERPs, bank portals, sales order systems, etc, it hinders visibility. Low visibility may also stem from non-standard processes, currency fluctuations, which lead to inaccurate forecasts.

Accuracy

Accuracy is affected due to:

1. Process inefficiencies such as:

• Top-down forecasting approach
• Unpredictability in A/R and A/P
• Disparate data sources

2. Dynamic factors such as:

• Changing FX rates
• Seasonality/ business cycles
• Macroeconomic fluctuations

Frequency

Due to the high turnaround time for generating forecasts, the frequency of forecasting is not timely enough.

The vicious cycle of cash forecasting causes data overload with a scope of error. CFOs have to rely on static and outdated data for making decisions.

How to Overcome the 3 Cash Forecasting Challenges

Visibility

Apply Direct Forecasting: Building local forecasts from the ground up at individual entity, company code, and currency levels, that ultimately roll up to central treasury. This provides transaction-level granularity.

Accuracy

• Use right models: Utilizing suitable models for each cash flow category. For instance, using heuristic models for repetitive cash flows like payroll, taxes, etc, and using M/L algorithms/AI models for complex cash flows like Accounts Receivable and Accounts Payable.
• Make adjustments: Factoring for one-time events like M&A, shares repurchase programs, dividends, etc.
• Analyze variance: Tracking variance for multiple time horizons and adjusting the models.

Frequency

• Determine the right forecasting cadence: Since each company has different priorities, it is important to identify the frequency that meets their business needs.
• Automate data gathering: Leveraging technology such as RPA and API to gather data in real-time from banks, TMS, ERP, FP&A tools
• Incorporating time-series algorithms: Prioritizing recent trends to proactively detect changes in behavior.