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

What you’ll learn

There are two main methods when it comes to cash flow forecasting.
Learn about when to use direct vs. indirect cash flow forecasting for your business. 

What is 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 the finances of a company and predicts where a 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 shows cash positions at a specific time. It’s also called as receipts and disbursements method

Time period: The direct method of cash forecasting is useful for 3 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 when the invoices were sent. 

It is built bottom-up by rolling up regional forecasts into a global forecast. This provides cash flow visibility at a granular level. 

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 a high volume of transactions. It uses the balance sheet and profit and loss statements to predict cash flows including investments and loans. The gathered data from the balance sheet is converted to the cash flow by rearranging the net income to a cash basis. 

Benefits: It shows the amount of cash required for working capital 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 cash forecasting tools, you would need to analyze the size, mission, performance, and budget of your firm first. 

Big enterprises that have more transaction data will avoid the direct method as the volume of the data is too high to be gathered and incorporated in forecasts. They will most likely choose the indirect method for cash forecasting as their goals are to:

  • Quantify speculative profits through achieving interest gains. 
  • Make decisions on exchange rates and cash deployment.
  • Track variance by leveraging the best technologies.

On the contrary, a smaller firm lacks adequate baseline data, has unclear expectations, inconsistent tools for forecasting, and lacks technical expertise. So they would prefer the direct method due to the need to:

  • Forecast regularly with high accuracy to prevent falling short on cash during volatile times.
  • Work closely with banks to check current balance and make proper use of credit revolver. 
  • Stay debt-free by collecting due payments quicker from slow-paying customers.

It is necessary to understand what benefits are more favorable to your organization to decide between the two since both provide different advantages:

  • Direct cash forecasting provides granular analysis and better visibility.
  • Indirect cash forecasting is simpler to use by extracting data from existing reports.

How does AI make indirect and direct cash forecasting easy?

Artificial intelligence is widely known for improving business processes and operations.
These are the top 5 reasons how it makes indirect and direct cash forecasting easy:

  • Easy integration with various sources

AI integrates readily with ERP, TMS, banks, payroll and 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 for using idle cash and increasing ROI.

  • Continuous improvements to deliver more accurate forecasts

Machine learning keeps evolving to improve the accuracy of the cash flow forecasts by factoring in 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 failures from the treasury realms, and yields significant productivity gain to treasury leaders.

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HighRadius Cash Forecasting Cloud – an advanced forecasting system – leverages the proven RivanaTM Artificial Intelligence (AI) platform to provide the most accurate cash flow forecasts – right from a ledger account level and rolling up to the organizational level. Delivered as a Software as a Service (SaaS), the solution seamlessly integrates with your company’s ERPs, accounting systems, banks and order management systems. Multiple AI and Machine Learning algorithms process datasets including bank statement inflows/outflows, sales orders/customers invoices, purchase orders/vendor invoices and expense reimbursements for comprehensive as well as accurate cash flow forecasts. The closed-loop, machine learning feedback system ensures that the forecast models become more accurate with time.