Maximize Forecasting Reports with Predictive Accounting

Written by Johnnie Walker
Business PlanningGrowth HubStartup Accounting
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Predictive accounting is a powerful tool that differentiates itself from other reporting methods due to its ability to paint a predictive picture of the future, not just analyze and explain present financial data. This predictive power allows management teams to observe current trends, predict future outcomes and strategically plan how best to use available resources.

Predictive accounting offers a range of advantages to small businesses, enabling them to better monitor their financial performance and anticipate future risks. From increased organization and comprehensive data to accurate financial forecasts, predictive accounting takes the complexity out of managing finances.

What is predictive accounting?

Predictive accounting is an emerging field of financial management that uses data-driven insights to evaluate future trends and opportunities. By utilizing predictive analytics and machine learning techniques, predictive accounting can give organizations greater foresight and more comprehensive analysis for economic forecasting and decision-making. With predictive accounting, companies are able to better anticipate customer behaviors, identify revenue drivers, reduce costs and make more accurate predictions on how their business will grow over time. This predictive power allows organizations to become proactive in predicting problems before they arise and positioning themselves for success.

Predictive accounting stands apart from other reporting methods due to its predictive nature. While descriptive analytics look at what’s already happened, predictive analytics provide insight into what may occur in the future based on current trends and predictive models. Diagnostic analytics dive deeper into what drove a specific outcome, while predictive analytics are more concerned with forecasting possible outcomes. And although prescriptive analytics offer recommendations for action, predictive analytics attempt to forecast how likely those recommendations are to work and their potential impact.

Rather than simply providing a summary of an organization’s financial performance after it has taken place, predictive accounting seeks to predict future trends and mitigate potential risks or opportunities in real-time. In predictive accounting, predictive models are developed using machine learning algorithms that build upon historical data as well as external and non-financial inputs. For example, predictive accounting models can use historical data to forecast the impact of changes in taxation or to estimate the organization’s cash flow over a specific period of time. Another example of predictive accounting would be using customer data to predict when expenses could rise or when new supply chains may need to be established.

Top-down vs bottom-up forecasting

When considering predictive accounting for a financial model, companies have the choice of implementing a top-down or a bottom-up forecast. Top-down forecasts allow for an overall high-level view of the budget, by recreating elements to reach specific goals. Top-down forecasts are based on existing data trends and overall business objectives. This method offers superb predictive accuracy, since it combines long-term and short-term considerations into one single plan. Top-down forecasting uses past performance as a basis for calculating expected outcomes and works best when there is a well-established track record of results within the organization.

On the other hand, bottom-up forecasts provide more granularity when it comes to actuals. They often involve gathering data from direct employees or customers in order to provide more accurate predictive modeling. Bottom-up forecasts often require more time to develop but can be extremely useful when appropriate attention has been given to thoroughly evaluating the data gathered. Companies can identify trends or patterns by examining how departments contribute to the entire budget based on their individual data points. Both top-down and bottom-up forecasting are predictive methods that help companies anticipate future outcomes and inform their decisions as well as budgets year-over-year.

Top-down forecasting

A top-down forecast is a predictive tool used to model future business scenarios that combines corporate-level planning objectives with mathematical and statistical models. This analytical approach provides insights into expected macroeconomic factors such as consumer demand, regulations, political stability, and economic conditions. It is most often used for estimating overall spending, revenue and budget forecasts over a specific period of time.

Specifically, top-down forecasting can provide solutions in analyzing total sales based on industry trends, predicting companywide capital expenditures as part of long-term investments and understanding potential profits when making new business decisions. By considering these larger fiscal elements, top-down forecasting can account for the often-uncontrollable factors that shape a company’s top line revenue performance.

Solutions like trend extrapolation and benchmarking are integrated in top-down forecasting practices to produce more detailed plans that more accurately represent macroeconomic trends and forecasting outcomes. It helps with predictive analysis and offers more direction than conventional bottom-up forecasting models. With these detailed solutions in mind, top down forecasters can take a more holistic approach to modeling financial expectations by combining realistic bottom-up budgeting with top-down macroeconomic analysis.

Bottom-up forecasting

Bottom-up forecasting is a type of predictive modeling that uses bottom-level information as its basis instead of top-level projections. By gathering data from local level sources, bottom-up forecasting helps to create an informed and accurate forecast that takes into account different scenarios based on the market and consumer behavior at a ground level. This type of approach is commonly used for predicting potential scenarios, such as outcomes in marketing campaigns or seasonal sales projections.

Bottom-up forecasting can be used in many different fields to anticipate the trajectory of certain trends or scenarios, such as sales projections and population growth. Depending on what needs to be forecasted, bottom-up forecasting offers solutions based on the variables associated within each local environment. This type of forecasting model is especially effective when bottom-level components hold large importance, such as predicting a budget based on supplier input or capital planning based on regional divisions. Solutions generated by bottom-up forecasting often take into account smaller details like short-term changes in the market that can have an effect on the overall bottom line of a company. These solutions have the ability to be more accurate and better align with the company’s strategy due to their focus on lower-level data.

Bottom-up forecasts take into consideration the individual components of a business, allowing for greater accuracy when predicting future outcomes. Predictive accounting is based on the same principle; that understanding the performance of individual components or segments of the business will help to paint an accurate picture of future financial performance. Predictive accounting harnesses bottom-up forecasting to make smarter decisions about future spending and ensure cost optimization for growing companies. Bottom-up forecasts are therefore ideal tools for predictive accounting practitioners to use as they can rely on bottom-up forecasts to quickly and effectively assess future performance and plan accordingly.

Predictive accounting offers a range of advantages to small businesses, enabling them to better monitor their financial performance and anticipate future risks. From increased organization and comprehensive data to accurate financial forecasts, predictive accounting takes the complexity out of managing finances. Through predictive analytics, small businesses can identify trends in their operations which may result in potential losses or money waste. By pinpointing these elements within a company’s operation, predictive accounting minimizes the risk of costly errors and bad investments – ultimately allowing small businesses to grow more efficiently.

Understanding predictive accounting and its potential uses can take you far in today’s competitive marketplace- and Rooled can help you employ the best practices for your business. By arming yourself with solid forecasting data, you’ll be able to properly align resources and keep up with market trends – a huge advantage for any company competing with larger rivals for market share or simply looking to stay ahead of the curve. Of course, putting these methods into practice isn’t always easy or straightforward, which is why it’s best to turn to experienced professionals like those at Rooled who can guide the implementation process.

About the Author

Johnnie Walker

Co-Founder of Rooled, Johnnie is also an Adjunct Associate Professor in impact investing at Columbia Business School. Educated in business and engineering, he's held senior roles in the defense electronics, venture capital, and nonprofit sectors.