The Difference Between Bottom-up and Top-Down ARR Forecasting Models and How to Choose the Right Model for Your Business

Financial forecasts are an essential tool for early-stage SaaS companies due to their need to demonstrate growth, stability, and viability to investors. Even internally, financial forecasts lay the foundation for leaders to make informed decisions and craft long-term business strategies with the appropriate context. As investors anticipate a recession, they are expected to be more wary of unproven businesses, making it more important than ever for SaaS companies to use data-based forecasting models to prove their investment worthiness. 

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There are two common approaches to financial forecasting: bottom-up and top-down. Here is how they differ and the benefits and drawbacks of each. 

What Is a Top-Down Approach to Financial Forecasting?

Businesses that choose a top-down approach to financial forecasting begin with a thorough assessment of the market in which they operate. This assessment includes analyzing the size of the market, distribution of market share, and historical sales trends. Forecasts are made with these trends and market information in mind. This method can help business leaders evaluate their unique strengths and weaknesses in the context of the industry and adjust their strategies accordingly. A top-down approach begins with a thorough analysis of the industry and uses that as a baseline to conduct forecasts. 

What Is a Bottom-up Approach to Financial Forecasting?

Bottom-up forecasts, on the other hand, begin with an analysis of the company’s product or service and the resources that are needed to bring these offerings to market. Business leaders who favor this approach analyze the resources that are available to them, including the size of their staff, the available funding, and the size of their client portfolios. This lays the groundwork for forecasts to determine how much time a business would need to meet their goals using their chosen strategy. 

The Differences Between a Bottom-up and Top-Down Approach to Financial Forecasting

Speed of Results Delivery

A top-down approach is typically favored by businesses that wish to receive insights as quickly as possible. Industry data is often publicly available and easily accessible, so finance teams can collect and analyze that data with minimal resources. 

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A bottom-up approach, however, demands a thorough analysis of each business activity and its financial impact on the business. While this approach can offer unique benefits to those who adopt it, it is undeniably time-consuming. 

Level of Variability in Data

Each business is unique and must take the appropriate approach to build forecasts that reflect their unique operational qualities. While a bottom-up approach can deliver this, it is also more likely to result in statistical outliers that might not be useful in the early stages of entering a new market. 

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A top-down approach can deliver an industry-wide view that offers business leaders the opportunity to identify sales trends and market opportunities. Since it tends to be more optimistic than bottom-up forecasts, a top-down approach can also be used to convince investors of the potential for profitability for businesses operating in their chosen sector. 

Level of Employee Engagement

Since a top-down approach utilizes easily attainable industry data, there is little need to involve team members who are not directly involved in managing finance functions. For business leaders who wish to create a culture of engagement and collect feedback from employees at all levels, a bottom-up approach can enable managers and team members to make better spending decisions using insights from the resulting forecasts. 

Level of Accuracy

Unlike top-down forecasting, financial forecasts generated using a bottom-up approach use actual sales data to project future revenue. Industry-level data can offer businesses a clearer understanding of the sector they operate in. As software businesses aim to differentiate in an increasingly saturated market, it is important that their chosen approach reflect their unique product and the impact it can have on revenue. This alone can make bottom-up forecasting significantly more accurate than top-down forecasting. 

How SaaS Companies Can Choose the Right Forecasting Model for Their Unique Needs

To understand which forecasting model can serve their needs best, SaaS businesses must clearly outline what they wish to achieve. Finance teams are increasingly expected to be essential partners in strategic decision making. However, they are often spread thin. Finance teams must juggle controlling operational finances, decision support, transaction processing, and management activities—and the pressure to deliver results in each of these areas can reduce resources available for forecasting activities. 

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As a result of this pressure, finance teams must evaluate the following before they can choose a forecasting model that is designed to fit their needs:

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• Availability of past financial data
• Relevance, completeness, and accuracy of past financial data
• Timelines and deadlines set by leadership teams
• Uniqueness of their product offerings

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Once a forecasting model is chosen, finance teams should always retain the flexibility to pivot and generate forecasts using a different approach. As business needs change and evolve, the forecasting model that yields the appropriate results can also change. This means finance teams should always have access to financial data that is complete, accurate, and reliable. In industries that are rapidly growing and changing, finance teams should develop the ability to deliver accurate insights amid increasing uncertainty. 

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Financial forecasting is crucial for any SaaS business to maintain business continuity and stakeholder visibility while managing business growth effectively. However, business leaders must choose the appropriate methodology for the needs of their unique business model. The right forecasting model can help business leaders generate the insights their investors demand—when they need them and to the degree of accuracy needed. 

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To learn how modern software can help your SaaS company build the right foundation for your chosen approach to financial forecasting, schedule a demo with us today. If you found this article helpful, please share it on social media. 

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