At the highest level, there are three main metrics in a sales forecasting system: (1) total pipeline, (2) expected sales in the period (usually calculated as the sum of all pipeline deals, weighted by close probability), and (3) business closed so far. For reasons that I think this audience understands, all three are critical to track, each for different reasons. Even more valuable is comparing where you are in the current quarter to where you were at the same point in the last two or three quarters.

While the information in a sales forecasting system captures critical information, virtually everything in the system is just a guess: the size of each deal, when it might close, how likely it is to close, etc. For that reason, the main value of a forecasting system is not to predict future results with scientific precision, but to help impose a uniform discipline on the sales process and to give management a sense of overall trends. This makes a sales forecasting system an ideal candidate for presenting its key information in charts, rather than tables. Heres an example, recapping the weekly progress of the above three metrics for each quarter, through week 35 of the year:

Heres how to read this chart, which I call the tropical fish chart because of the visual impression I get from it:

1. The broken lines are the total pipeline, the solid lines are the weighted average/expected outcome, and the dotted lines are business closed quarter to-date.
2. The Q1 forecasts are in blue, Q2 in red, and Q3 in green. This company’s standard practice is to begin tracking forecast progress for each quarter at the beginning of the prior quarter.
3. There are solid vertical gridlines demarcating each quarter-end (weeks 13 and 26, so far). On the last day of the quarter (OK, in the last minute of the quarter!), the three curves for that quarter should converge at the quarters actual result, shown as a small square in that quarters color. [Note that Ive included a green square for Q3, which is the target for the quarter.]
4. Ive included a thinner, broken vertical line at the current week (week 35, or 9 weeks into Q3) and also at the same point in the two prior quarters (i.e., weeks 9 and 22).
5. In most organizations, the total pipeline curve peaks at an amount much larger than the eventual result for that quarter, and the closed business curve increases monotonically starting in the first week of that quarter. The weighted average curves behavior is harder to predict, since its driven by both the total size of the pipeline and the rate of progress toward closing deals throughout the quarter.

I like this chart because it provides an at-a-glance perspective on how sales are progressing through the quarter, and whether things are on track for achieving target results. Here are a few observations you could make from the sample chart shown above:

• The total pipeline for Q3 is light compared to where we were at the same point in the two previous quarters, especially considering that the Q3 target is significantly higher than the Q1 and Q2 results.
• The weighted average number seems to be roughly on track toward achieving the target result, in spite of the relatively smaller total pipeline perhaps this is because the fewer deals this quarter are making better progress toward eventual closing.
• Closed business is much stronger at this point in the quarter than at the same point in Q1 and Q2. This supports the argument that we are making better progress on the fewer total deals in the pipeline. [And may generate a thank-you note from the manufacturing department!]

As Ive said here and in previous posts, sales forecasting systems are not a good place to look for truth in the sense that we usually think of that word with respect to numbers. The main purpose of these systems is, after all, to predict the future, and thats always messy. But summarizing the information from the sales forecasting system in a coherent, consistent way is a powerful management tool for understanding how well the sales organization is functioning.

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