Bottom Up Forecasting – Definition

Cite this article as:"Bottom Up Forecasting – Definition," in The Business Professor, updated June 10, 2019, last accessed August 3, 2020,


Bottom-up Forecasting Definition

Bottom-up forecasting is a method of estimating future sales revenue, where the process begins with a micro view and builds to a macro view. At the beginning sales revenue of each product or product line are estimated. Each department presents its projection and the revenue estimate for the entire firm is calculated by combining all these projections. The bigger picture is estimated by adding up each micro view. Besides the specific product or components, other factors such as sales channel, geographic region, customer types are also taken into consideration in this approach.

A Little More on What is Bottom-up Forecasting

Bottom-up Forecasting is a more strategic approach to estimate the future sale revenue as the current situation and capabilities are taken into account to forecast where one can reasonably expect to go from here.

In this method, the number of potential sales per product is multiplied by the average sale value to get the potential revenue. This method examines the factors like production capacity, department-specific expense, and addressable market to estimate a more accurate sales revenue. Practically, a Bottom-up financial forecast is, operating expense plan minus the depreciation expense plus capital expenditures.

Advantages of Bottom-up Forecasting

Bottom-up forecasting is often considered more realistic and accurate. Some of the advantages of using bottom-up forecasting to compute the revenue potential are:

Closer to reality

In bottom-up forecasting, actual sales data are used for calculating the estimated revenue. In this method, the revenue is projected by multiplying the average value per sale by the number of prospective sales per product. Thus, the approach is much more grounded to reality. As a result, the forecasted figures may be more accurate and realistic enabling the firm to make better strategic decisions. Especially, for the businesses which are seasonal in nature or who experience wide swings in sales and profits, the bottom-up forecasting is a more effective method to get a more accurate estimation.

Efficient allocation of resources

In the other approach of forecasting, which is a top-down approach, profits from different products and geographical regions are averaged together to get an estimate. So, from this estimation, it may be difficult for the management to allocate the resources efficiently to get an optimal result. Making decisions regarding the manufacturing and distribution of a specific product may be difficult in this situation. But, in bottom-up forecasting, the estimation is made on an item-by-item basis. In this way, it becomes much easier to allocate the resources more efficiently in a specific product or region.

Greater involvement of the employees

In the bottom-up forecasting, the managers and employees are much more involved in the planning process. Each of their inputs is very important to get an overall estimation. The operating expenses are examined by the owner of the business, as well as the spending by departments. Costs involved in the production, hiring, marketing, and distribution are thoroughly assessed. These figures help the managers and departmental heads to create a more efficient strategic plan. Also, when the managers themselves are involved in a budget-making process, it more likely that they will try hard to adhere to the budget.

As the bottom-up approach deals with real numbers and real situation, it is much difficult to use this approach for getting huge projection. The only way to grow the numbers is to increase the overall exposure and include all the angles to market and sell the product or service.

Another drawback of bottom-up forecasting is that the errors at the micro level are amplified as they move towards the macro level. During the process of expansion, the errors are compounded. To overcome this drawback, the assumptions need to continuously examined and challenged to improve the overall estimate.

References for Bottom-Up Forecasting

Academic Research on Bottoms-Up Forecast

Revisiting top-down versus bottomup forecasting, Kahn, K. B. (1998). The Journal of Business Forecasting, 17(2), 14.

Top-down versus bottomup forecasting strategies, Schwarzkopf, A. B., Tersine, R. J., & Morris, J. S. (1988). The International Journal Of Production Research, 26(11), 1833-1843.

Top-down & bottomup forecasting in S&OP, Lapide, L. (2006). The journal of business, 1.

Top-down or bottomup: Aggregate versus disaggregate extrapolations, Dangerfield, B. J., & Morris, J. S. (1992). International Journal of Forecasting, 8(2), 233-241.

Forecasting item-level demands: an analytical evaluation of top–down versus bottomup forecasting in a production-planning framework, Widiarta, H., Viswanathan, S., & Piplani, R. (2008). IMA Journal of Management Mathematics, 19(2), 207-218.

A positive model of earnings forecasts: Top down versus bottom up, Darrough, M. N., & Russell, T. (2002). The Journal of Business, 75(1), 127-152.

Forecasting aggregate time series with intermittent subaggregate components: top-down versus bottomup forecasting, Viswanathan, S., Widiarta, H., & Piplani, R. (2008). IMA Journal of Management Mathematics, 19(3), 275-287.

Top‐Down Versus BottomUp Demand Forecasts: The Value of Shared Point‐of‐Sale Data in the Retail Supply Chain, Williams, B. D., & Waller, M. A. (2011).Journal of Business Logistics, 32(1), 17-26.

Forecasting inflation through a bottomup approach: How bottom is bottom?, Duarte, C., & Rua, A. (2007). Economic Modelling, 24(6), 941-953.

Top-down or bottomup: Which is the best approach to forecasting?, Gordon, T. P., Morris, J. S., & Dangerfield, B. J. (1997). The Journal of Business Forecasting, 16(3), 13.

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