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

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.

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.

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.