4 Key Pillars of Cash Flow Forecasts | HighRadius (2024)

Autonomous Treasury Cash Forecasting

What you’ll learn

  • Learn the 4 pillars of cash forecasts and the 4 stages of the cash forecasting maturity model.
  • Learn the ways to become best-in-class in cash forecasting.

Treasury priorities

Cash forecasting has been the topmost priority for treasury for managing liquidity by implementing quicker and better decisions.

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There are two types of cash forecasting:

1. Short-term cash flow forecasting: It ranges from periods of 4 weeks to 6 months. It requires high accuracy and frequency. Short-term forecasting is useful to identify potential cash crunches and surpluses.

2. Long-term cash flow forecasting: It ranges from periods of 6 months to 5 years. It allows some leeway for accuracy and frequency and is useful to guide FP&A decisions.

The questionable period ranges from 6 months to 12 months, where both forecasts are applicable. So companies analyze their data and purposes to make a choice between both.

There are 4 stages to segregate firms based on their cash forecasting practices.

Understanding the maturity model

There are 4 stages in the cash forecasting maturity model:

  • Laggard: Use the same/inadequate model for many years for cash forecasting.
  • Proactive: Try to improve cash forecasting by using better models, but lag during challenging times.
  • Strategic: Use proper models and tools to improve forecasts and decision-making agility.
  • Best-in-class: Use automation and AI to achieve high-level forecast accuracy.

Most companies want to improve their processes, but they don’t know how to significantly climb up the ladder to become best-in-class.

4 pillars of the cash forecasting process

The 4 pillars of the cash flow forecasting process are:

1. Approach: The approach is either artistic or scientific(subjective or objective).

2. Data gathering: Data is extracted from a variety of sources and teams.

3. Modeling: Various models can be used for forecasting different cash flow categories.

4. Variance analysis: It is performed by using appropriate tools to measure accuracy across various areas and time horizons.

Approach

  • Laggards: Perform cash forecasting based on judgments, opinions, past experiences and take last year’s data along with metrics for recent year’s forecast.
  • Proactive: Build forecasts through effective collaboration between managers, controllers, etc.
  • Strategic: Build top-down forecasts from FP&A forecasts and set some distribution rules.
  • Best-in-class: Build forecast bottom-up from granular level and build them up to global forecasts.

Data gathering

  • Laggards: Have a manual process, use previous years’ data as a basis for the current year.
  • Proactive: Have a manual process, but utilize the previous years’ data and add some forward-looking adjustments by including current data.
  • Strategic: Automate their data gathering process and utilize both previous and current data for cash forecasting.
  • Best-in-class: Use APIs for connectivity between various systems to ensure real-time information access, and gather information from FP&A, sales forecasts, ERPs, A/P, and A/R data.

Modeling

  • Laggards: Use Excel for forecasting all cash flow categories. Complex categories like A/P and A/R are unpredictable. Thus adding more variables can give a realistic forecast. However, Excel limits adding multiple variables, causing forecast inaccuracies.
  • Proactive: Use the average-based approach, which is useful for categories like payroll, taxes but doesn’t give high accuracy for A/R and A/P.
  • Strategic: Use data from open ERP and banks, and adjust due dates to generate A/R and A/P forecasts.
  • Best-in-class: Use current and historical data and leverage AI to use sophisticated AI models for A/R and A/P and heuristic models for simple cash flow categories.

Variance analysis

  • Laggards: Unable to perform variance analysis due to lack of data or tools.
  • Proactive: Perform variance analysis at the global level and for a single duration.
  • Strategic: Perform variance analysis at entity and cash flow category level with proper tools.
  • Best-in-class: Use better tools and models to perform variance analysis at the entity, region, cash flow category level over multiple durations.

4 ways to generate accurate forecasts

The way to become best-in-class is to refine the 4 pillars of cash forecasting through the following ways:

Approach: Build bottom-up forecasts by rolling up local forecasts to global forecasts.

Data gathering: Use API to extract historical and current data seamlessly.

Modeling: Use heuristic models and AI models for suitable cash flow categories.

Variance analysis: Analyze variances over multiple time horizons and entities.

Take this quiz to evaluate the stage of your company (Laggards, Proactive, Strategic, Best-in-class) in the cash forecasting maturity model.

Dive deeper into the 4 pillars of cash forecasts and how to optimize the current processes.

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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.

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4 Key Pillars of Cash Flow Forecasts | HighRadius (2024)
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