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Direct Forecasting And Indirect Forecasting: What’s The Difference?

5 April, 2021
4 min read
Valerio Trinchi, Treasury Growth Initiative
Linkedin profile

What you'll learn

  • Comparison between direct and indirect cash flow forecasting in terms of the time period, inputs, and benefits.
  • How to pick the right forecasting method for your business.
  • How AI helps in direct cash flow forecasting.
CONTENT
Indirect vs. direct cash flow forecasting
What is Direct Cash Forecasting?
What is indirect cash forecasting?
How to pick the right cash flow forecasting method?
How does AI help with direct cash forecasting?
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Indirect vs. direct cash flow forecasting

Cash flow forecasting is a way to learn where a company stands in terms of its financial position by keeping track of its finances and predicting where the company is heading. 

Generally, there are two categories of cash flow forecasting techniques:

  • Direct cash flow forecasting 
  • Indirect cash flow forecasting

What is Direct Cash Forecasting?

Direct cash forecasting or short-term forecasting shows cash positions at a specific time. It’s also called the receipts and disbursements method.

Time period: The direct method of cash forecasting is useful for up to around three months.

Inputs: It involves transactions like bills, invoices, and taxes.

Benefits: It predicts when payments will be made and when that amount will reflect in your bank account. For instance, it estimates when the payment will be received in hand, rather than the listed terms based on the invoice date. It is built bottom-up by rolling regional transaction data into a global forecast. This provides cash flow visibility at a granular level. 
Benefits of Direct cash flow forecasting

What is indirect cash forecasting?

The most commonly used method for cash flow forecasting is the indirect method. 

Time period: It is used for long-term forecasts, which range from one year to five years. 

Inputs: It is conventionally used for longer-term planning purposes. It uses the pro forma balance sheet and profit and loss statements to predict cash flows including investments and financing. Ending cash balances are calculated based on adding back non-cash charges to net income and incorporating projected changes in balance sheet items. 

Benefits: It shows the amount of cash required for expected business activities and helps in long-term expansion, repatriation, FP&A, and M&A planning.

How to pick the right cash flow forecasting method?

To pick the most appropriate cash forecasting method and tools, you would need to analyze the size, mission, performance, and budget of your firm first. 

Every firm starts with direct forecasting to keep track of its daily cash movements on a frequent basis. This is because direct cash forecasting provides granular analysis, increases visibility, and helps to:

Advantages of direct cash forecasting method

Direct cash forecasting provides high accuracy in the short term. But as the complexity and volume of data increase, the indirect method becomes optimal. Big enterprises have more subsidiaries and more resources, so they might rely on the indirect method of forecasting for long-term funding and business growth. Indirect forecasting extracts data from existing reports and helps to:

Advantages of indirect cash forecasting method

How does AI help with direct cash forecasting?

Artificial Intelligence is widely known for improving business processes and operations.

Here are the top 5 reasons why it makes direct cash forecasting easy: 

  • Easy integration with various sources
    AI integrates readily with ERP, TMS, banks, payroll, tax systems, etc. and provides automated data aggregation.

  • Serves as a single source of truth 
    Since all the data is stored in one place, it improves visibility and makes room for making smart decisions about using idle cash and increasing ROI.
  • Continuous improvements to deliver more accurate forecasts
    Machine Learning keeps evolving to improve the accuracy of cash flow forecasts by including real-time data, which makes it more promising and dependable. 
  • Variance analysis across many business horizons and teams
    It provides a clear variance analysis globally and reduces the variance over time by studying previous results.

  • Rational scenario planning through Excel-on-Web
    Risk management becomes easier through AI-based scenario planning, which is done by tweaking some minor changes to the data in a spreadsheet.

Artificial Intelligence is progressing rapidly and is being adopted as an integral technology by many businesses since it is instrumental in reducing a great deal of effort and failure in the treasury realm and yields significant productivity gains to treasury leaders.

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