The Main Factors that Render a Cash Forecast Inaccurate


An introduction to how AI can help treasurers supersede challenges surrounding accounts payable unpredictabilityn

Contents

Chapter 01

The Main Factors that Render a Cash Forecast Inaccurate

Chapter 02

The Reasons Behind the Unpredictability of Accounts Payables

Chapter 03

Handling the A/P Unpredictability and the Way Forward
Chapter 01

The Main Factors that Render a Cash Forecast Inaccurate


The first step to designing a cash forecast is gathering data; and this data is related to payables, receivables, sales, and return on investments. And considering the scale at which organizations conduct their business, Treasurers are usually inundated with multiple spreadsheets containing this data, which is either extracted from CRMs, ERPs, Billing Management systems, or is received from the finance analysts. 
The treasurer then analyses the received data and then employs a spreadsheet-based forecast model that can factor in most of the data and extrapolate a cash position at a future point in time. 
However, this method of extrapolation future cash positions has its inherent challenges:
1. Possibilities of Negative Variance: Caused primarily due to the lack of granular visibility into inflows and outflows while using excel as a tool. As remediation, treasurers set up higher cash buffers (either by leveraging short-term debts or utilizing cash pools) to reduce the impact of the variance. 
2. Inability to  Factor in All the Data: A Spreadsheet is the most used tool to design a cash forecast. However, this tool comes with limitations such as the inability to factor in all the necessary forecast data, since spreadsheets are not designed to do so, which in turn reduces the accuracy of a Cash Forecast
3. The unpredictability of Cash Flow Categories: Along with the limitations created by spreadsheets, the unpredictability of cash flow categories such as accounts payable also adds to the inaccuracy of cash forecasts, since spreadsheet-based models seldom allow deep visibility into the payables data that can be leveraged to build an accurate cash forecast
Of the aforementioned factors that contribute to forecast inaccuracy, the unpredictability of the cash flow categories such as A/P contributes significantly. And this has been cited by 100+ treasurers from fortune 1000s in the 2019 Highradius Cash Forecasting Survey.  
It is also important to consider that, the unpredictability of this cash flow category also negatively impacts other factors such as working capital management which is crucial during times of crisis (Covid-19) and long term liquidity – which is an important element in the upkeep of an organization.

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HighRadius Integrated Receivables Software Platform is the world's only end-to-end accounts receivable software platform to lower DSO and bad-debt, automate cash posting, speed-up collections, and dispute resolution, and improve team productivity. It leverages RivanaTM Artificial Intelligence for Accounts Receivable to convert receivables faster and more effectively by using machine learning for accurate decision making across both credit and receivable processes and also enables suppliers to digitally connect with buyers via the radiusOneTM network, closing the loop from the supplier accounts receivable process to the buyer accounts payable process. Integrated Receivables have been divided into 6 distinct applications: Credit Software, EIPP Software, Cash Application Software, Deductions Software, Collections Software, and ERP Payment Gateway - covering the entire gamut of credit-to-cash.