At a high level, bottom-up forecasting is a projection of micro-level inputs to assess revenue for a given year or set of years. For example, revenue teams often use this method to estimate the business's future performance based on individual sales or rep performance.
Put another way, bottom-up forecasting is like looking at the health of a complex system, like a vehicle, by looking first at its most basic parts, like its engine components.
How Revenue Teams Use Bottom-Up Forecasting
Let's take a closer look at how teams put this forecasting method into practice. For example, if we want to create a sales forecast template, we'll typically begin by defining the number of orders expected to come from each business channel. If we wanted to go deeper, we could even start further down with advertising conversion rates or the productivity metrics within a specific team.
Next, we estimate how much will be charged for those sales and what the business nets from that sales. Once we identify the value of low-level transactions after refunds exchanges, returns, charge-backs, and production costs, and other pertinent factors, we have the metric that we can use to estimate revenue in broader terms.
Another example would be to take the performance of an average sales rep. If the entire company is performing at the rate of this rep, we can extrapolate what revenue would look like across the business.
Bottom-up vs. Top-Down Analysis
The key difference between the top-down and bottom-up approaches is the perspective taken to perform your analysis. Bottom-up forecasting is ideal for estimating how specific performance metrics impact revenue. But to understand the true health of a complex business, we should look at it in more than one way.
In a top-down analysis, we estimate demand at an aggregate level. This type of assessment weighs historical outcomes to predict future performance.
If we're considering purchasing a company's stock, for example, the information we're using will be the product of a top-down analysis. In this case, we're looking at the business as a unit. So, we'll look at total revenue and stock performance over a given time.
Top-down methods are useful when reporting to groups like agencies, investors, partners, and other external stakeholders. In short, a top-down analysis is relevant when looking at the company from an outside perspective.
There are some similarities, however. When working from a top-down perspective, we create a system-wide analysis that gives us a holistic representation of total performance. Bottom-up forecasting does this too, but it relies on the health and functionality of the organization's specific internal components, which are then extrapolated up to the aggregate level.
In other words, a top-down approach looks at the business as a complete unit, whereas a bottom-up helps assess individual parts for optimization. That said, forecasting is imprecise by nature. Whether we look at a company from a bottom-up or top-down perspective, we're going to tap into some critical inputs while missing out on others.
Bottom-Up Forecasting Pros and Cons
- Team engagement: By analyzing teams' impact and extrapolating them upward, we can decide whether or not a given individual's experience is good, bad, or neutral, then provide support to encourage or prevent it.
- Flexibility: Using the bottom-up approach makes it easier for teams to see where they fall short, so they can quickly pivot and fix problems.
- Limited visibility: What we see and know about our immediate circumstances may not paint an accurate picture of reality. If our forecasts only index on a select group of metrics, we miss other contributing factors that could just as easily derail our projections.
- Potential conflict: Any time we look at and consider the functions and perspectives of individual units, we run the risk of creating or exacerbating conflicts.
Top-Down Forecasting Pros and Cons
- Fast and straightforward: Unlike bottom-up forecasting, a top-down approach offers a simple analysis of the organization viewed as a single unit. Here, our results will be systemic in nature.
- Lack of detail: With a top-down approach, we lose a level of detail. While top-down is fast and broad, we miss the context that a bottom-up view can offer.
Top-down vs. Bottom-up Sales Forecasting: What's better?
If we think of a company as an automobile, we can compare the top-down approach to looking at the car from the outside. Likewise, the bottom-up approach would be like inspecting the vehicle's internal components. From the outside, we would look at the condition of the exterior, the speed, performance, and other aggregate factors. By looking under the hood, we can diagnose specific problems, assess the value of certain systems.
Similarly, a bottom-up approach helps leaders examine various aspects of their organization in comparison to their competitors. But a top-down approach becomes critical as a business scales, especially if you can leverage consumer data and buying trends accurately.
Neither approach is solely right or wrong, and both are key components of revenue intelligence software, which connects, analyzes, and actively monitors every data point across your revenue team so sales leaders can examine the health of their pipeline — from a both a high-level and individual deal-level view.