4 Key Pillars of Cash Flow Forecasts

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.

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.

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.