- Tops-Down Sales Estimates.
- Bottoms-Up Sales Estimates.
The typical "Tops-Down" Sales Estimate is generated by a business leader. This person estimates what is likely to happen as strategies change.
The typical "Bottoms-Up" Sales Estimate is generated by a business analyst. This person is "in the trenches", generating a forecast from segment-level data, marketing campaign performance, key performance indicators, or customer projections.
The "Tops-Down" forecast and the "Bottoms-Up" forecast should be directionally similar. If they aren't, somebody must reconcile why the numbers are not directionally similar.
I tend to spend all of my time in the "Tops-Down" realm. My job is to create forecasts that are reasonable. So when a CEO wants to increase the marketing budget by 20%, I need to generate a reasonable sales increase to pair with the marketing increase.
When I don't have good data, I use a simple "square root" relationship to quantify my "Tops-Down" forecast. Let's say that we can attribute $20,000,000 to marketing efforts, and Management wants to increase marketing spend by 20% next year.
- Tops-Down Forecast = $20,000,000 * (1.20 ^ 0.5) = $21,909,000.
I use the "square root" approximation because I want to discount the benefit of additional marketing spend. We seldom see cases where an incremental $1 investment in marketing yields an incremental $1 of sales. The "square root" approximation does a reasonable job of generating a "Tops-Down" forecast.
When the marketing analyst generates a sales forecast at a "Bottoms-Up" level, it should be directionally similar to the $21,909,000 estimate I generated. If I see $21,600,000, or $22,300,000, I feel confident that the analyst did a good job. If I see $24,000,000, I know that the analyst did something wrong --- there must be proof offered to demonstrate that a 20% increase in advertising will yield a forecasted 20% increase in demand.
These are the ways that "Tops-Down" and "Bottoms-Up" approaches reconcile to yield accurate sales forecasts. Ok, your turn. What methods do you use to reconcile sales forecasts?
Hi Kevin,
ReplyDeleteAs you know, I recently wrote about the benefits of using Monte Carlo simulations in forecasts to focus decisions on the probabilities of various potential outcomes. (http://www.retailshakennotstirred.com/retail-shaken-not-stirred/2010/01/why-most-sales-forecasts-suck-and-how-monte-carlo-simulations-can-make-them-better.html)What are your thoughts about implementing such a methodology in this type of situation? It seems to me it's important to understand the variability possible in uncertain situation like this type of forecast.
Sure, Monte Carlo simulations will work just fine. Just need to make the culture of a company comfortable with the methodology, something that is always harder than implementing the methodology itself.
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