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Inga Sarda-SorensenThe storm rips through New York City Wednesday afternoon.Photographer Inga Sarda-Sorensen took this stunning photograph as the storm descended on New York City Wednesday afternoon. Sales forecasting has none of this going for it at the moment in part because while a sales forecast is a much smaller problem than the weather five days hence, we still do it much as we did a hundred years ago. But what would the forecasting process look like if we had as much science employed as a local TV weather person?
If the interest is in total revenue intelligence, the model would also include inputs from the current customer base including propensity to churn, cross-sell and upsell opportunities, and customer lifetime value. But it might be hard for management to discover this, if for instance, the rep simply indicates on the forecast that the deal is at forecasting stage.
If you apply this logic to every deal in the forecast then you have that range of probabilities that weather people rely on to tell you about Saturday’s conditions.
Mark Twain once said, “Everyone complains about the weather but no one does anything about it.” If you’re tired of complaints about sales forecast accuracy, consider building an accurate model and applying analytics. By this afternoon I will be escaping the constant sunshine and 90-degree weather of Los Angeles and embracing the foliage and autumn chill of New York. I anticipate quality time with family (without wanting to shoot myself), an occasional rainstorm, curling up with a pumpkin latte in a cafe, and waxing nostalgic on times long gone like I always do whenever I make a trip back home.
Naturally, I will be taking plenty of photos -- now that I'm practically a tourist after a decade of calling L.A. Hiko has worked in TV and commercial production ever since he left his native New York in the early aughts. This is not to say that it can’t be done but it’s a hard problem, like forecasting the weather.

Instead, forecasters have been able to bring the forecast down to a range of probabilities through the use of all that data and models for how the oceans and atmosphere, the jet stream and other major parts of the earth work. Too often that means a senior person reviews all the deals, applies his or her experience and follows a gut instinct.
Like the weather person, the sales manager would have a model based on many iterations of patterns that account for all kinds of variables including deal stages and their inputs, sales rep and that person’s track record, the product and its adoption patterns and much more.
To manage all this there would also be powerful analytics to process all the data and the result would not be a single answer such as a dollar number or the determination of whether or not you’ll make your target.
Just like the weather forecast you don’t know until the forecast is in the past, so there’s no such thing as 100%. We have a number to shoot for and often we try to figure out ways to make it regardless of soundness of our reasoning. A company I know has a sales process, which is a model itself, which at a certain point has the rep meeting with a key decision maker. A manager with 5 reps each working 50 deals in various stages might not have the time to go through every piece of deal data so the mistake would get through but it wouldn’t improve the forecast one bit.
The sales process stage is one of the variables in the model that the company uses to evaluate deals.
More importantly, and unlike a weather report, the forecast is also prescriptive because it shows you how you can improve it. He has worked at the world-renowned Anonymous Content and freelanced as a treatment writer for award-winning directors and as a contributing writer for Instinct.
Today they can tell us within a few degrees the weather for many days in advance because we’ve invested in many data gathering and analysis tools like satellites, computer modeling, and analytics.

So we typically see something like a 30 percent chance of rain and a temperature range of about 4 degrees and those ranges are enough to enable us to make plans like going to a picnic or not, or remembering to carry a hat or umbrella. By the way, that person is known affectionately as a HIPPO because the decision was the result of the Highest Paid Person’s Opinion. But also, like a weather forecast you don’t need absolute certainty, you simply need to know the probability of rain on Saturday so you can figure out if you want to golf. So we assume deals are going to close even if it means we have to ignore telltale signs of trouble until it’s too late. If the key decision-maker is not onboard they know the chances of getting the deal done are greatly reduced, so the meeting is an important gating factor. More importantly, the business applies analytics to the deal data rather than expecting managers to review all of it.
Analytics would have no trouble spotting the incomplete deal stage and would down grade the forecast appropriately. The model can tell you the warning signs because with analytics it can tell you how closely any deal fits with the model’s known history of success.
Perhaps the coach in the deal reassures the rep that the decision-maker has already approved, or maybe the decision-maker doesn’t have time to see the rep, or any of a hundred other reasons.
But armed with this kind of knowledge sales people up and down the organization can evaluate scenarios constructed to make their deals match up with the ideal.

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