Securing Organizational Buy-In for Effective Forecasting: A Strategic Guide

Introduction

They rely on static, once-a-year budgets that quickly become obsolete, unable to adapt to the ever-changing market conditions. Enter rolling forecasts—a dynamic approach to financial planning that keeps you agile and ready to navigate the choppy seas of business.

In this blog post, we'll explore how rolling forecasts can revolutionize your business planning. We'll delve into the tools and techniques—such as regressions, ARIMA, SARIMA, SARIMAX, Prophet, MLForecast, and NeuralProphet—that can make your forecasts more accurate and actionable. So, buckle up, and let’s set sail towards better forecasting!

What is Rolling Forecasting?

Rolling forecasting is an ongoing process that regularly updates forecasts based on the latest actuals. Unlike traditional annual budgets, rolling forecasts provide a continuous planning horizon, typically updated quarterly or monthly. This approach enables businesses to stay aligned with current market conditions and adjust their strategies promptly.

Why Switch to Rolling Forecasts?

1. Agility in Decision Making: With rolling forecasts, you can quickly adapt to market changes. This flexibility is crucial in today’s fast-paced business environment.
2. Improved Accuracy: By frequently updating your forecasts, you can reduce the uncertainty and improve the accuracy of your financial planning.
3. Enhanced Visibility: Rolling forecasts provide better visibility into future performance, helping you identify potential gaps and opportunities early on.
4. Strategic Focus: Instead of getting bogged down in the minutiae of annual budgeting, rolling forecasts allow you to focus on key business drivers and strategic initiatives.

Tools and Techniques for Effective Forecasting

To make the most out of rolling forecasts, leveraging advanced forecasting methods and tools is essential. Here’s a breakdown of some powerful techniques and models:

Regressions

Regression analysis is a statistical method used to understand the relationship between variables. It helps in predicting the future values of a dependent variable based on the changes in independent variables.

• Linear Regression: Simple but effective, it’s used when the relationship between variables is linear.
• Multiple Regression: Expands on linear regression by using multiple independent variables to predict the dependent variable.

ARIMA (AutoRegressive Integrated Moving Average)

ARIMA models are used for time series forecasting. They are particularly useful when data shows evidence of non-stationarity, meaning statistical properties change over time.

• AR: AutoRegressive part indicates that the evolving variable of interest is regressed on its own lagged values.
• I: Integrated part indicates differencing of raw observations to make the time series stationary.
• MA: Moving Average part indicates that the regression error is actually a linear combination of error terms whose values occurred contemporaneously and at various times in the past.

SARIMA (Seasonal ARIMA)

SARIMA extends ARIMA by adding a seasonal component to the model. This is useful for data with regular, repeating patterns.

• S: Seasonal component helps in adjusting the model to account for seasonality in the data.

SARIMAX (Seasonal ARIMA with eXogenous variables)

SARIMAX goes a step further by incorporating external variables (exogenous variables) into the SARIMA model. This is particularly useful when other factors outside the time series influence the data.

Prophet

Prophet is an open-source forecasting tool developed by Facebook. It’s designed to handle time series data that have strong seasonal effects and several seasons of historical data.

• Ease of Use: Prophet is user-friendly and requires minimal data preprocessing.
• Flexibility: It can handle missing data and shifts in the trend.

MLForecast

MLForecast is a machine learning-based forecasting tool that leverages advanced algorithms to predict future trends.

• Advanced Models: Uses models like Gradient Boosting Machines (GBM) and Neural Networks.
• Feature Engineering: Automatically creates relevant features from the time series data.

NeuralProphet

NeuralProphet combines the best features of Prophet and neural networks to provide high accuracy in forecasting.

• Hybrid Approach: Uses both statistical and machine learning techniques.
• High Accuracy: Particularly effective for complex time series data.

Implementing Rolling Forecasts: Step-by-Step Guide

Step 1: Use Dedicated Applications

Spreadsheets might be great for quick calculations, but they’re not cut out for rolling forecasts. A dedicated cloud-based application can streamline the process, reducing errors and saving time.

• Benefits: Automation, error reduction, real-time data integration.
• Examples: Trackura.

Step 2: Focus on Key Business Drivers

Don’t get bogged down in details. Focus your forecasts on the significant drivers of your business, such as revenue, costs, and capital expenditures.

• Identify Drivers: Determine which variables have the most impact on your business.
• High-Level Focus: Keep the forecasts at a high level to avoid getting lost in the weeds.

Step 3: Model Multiple Scenarios

Use rolling forecasts to explore various “what-if” scenarios. This helps you prepare for different potential outcomes and make informed decisions.

• Scenario Planning: Create best-case, worst-case, and most-likely scenarios.
• Flexibility: Quickly adjust your plans based on these scenarios.

Step 4: Separate Forecasts from Targets

Ensure that rolling forecasts are used as a management tool rather than an evaluation tool. This encourages honest and accurate forecasting.

• Avoid Linking to Rewards: Don’t tie forecasts to performance rewards to prevent number padding.
• Transparent Process: Keep the forecasting process open and collaborative.

Step 5: Choose the Right Forecasting Horizon

The appropriate forecasting horizon depends on your industry and business needs. Typically, forecasting four to eight quarters ahead is recommended.

• Industry Specifics: Adjust the horizon based on how quickly your industry changes.
• Review and Adjust: Regularly review the forecasting horizon to ensure it remains relevant.

Practical Tips for Better Forecasting

1. Regular Updates: Update your forecasts regularly to reflect the latest data and market conditions.
2. Collaboration: Involve different departments in the forecasting process to get a comprehensive view.
3. Technology Integration: Integrate your forecasting tool with other business systems for seamless data flow.
4. Continuous Improvement: Continuously refine your forecasting models and techniques based on past performance.

Common Pitfalls to Avoid

1. Over-Reliance on Historical Data: While historical data is useful, it’s not always indicative of future trends. Combine it with real-time data and market analysis.
2. Ignoring External Factors: Consider external factors such as economic conditions, competitor actions, and regulatory changes in your forecasts.
3. Lack of Flexibility: Be prepared to adjust your forecasts as new information becomes available.
4. Inadequate Communication: Ensure that the insights from rolling forecasts are communicated effectively to all stakeholders.

To Sum It Up...

Rolling forecasts are a game-changer for businesses looking to stay ahead in a dynamic market. By leveraging advanced forecasting tools and techniques like regressions, ARIMA, SARIMA, SARIMAX, Prophet, MLForecast, and NeuralProphet, you can enhance the accuracy and agility of your financial planning. Remember, the goal is not just to predict the future but to be prepared for it. So, set your course with rolling forecasts, and navigate your business towards success.

A Friendly Reminder

Forecasting might sound like a daunting task, but with the right tools and approach, it can be as smooth as a leisurely sail on a sunny day. And remember, even the best forecasts won’t always be 100% accurate—just like weather forecasts. But they’ll definitely help you avoid sailing blindly into a hurricane. Happy forecasting!

By following these steps and leveraging the right tools, you can transform your forecasting process and ensure that your business is always ready to navigate the future, no matter what storms may come your way.