Three Reasons Sales Forecasts Don’t Match Results

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“Our sales results never match what’s forecast!” As the saying goes, “if I received a dollar every time I heard this complaint, I’d be contentedly fly fishing in a remote river right now, untethered from the grid.”

Inflated expectations? First, we need to understand what match means in the context of forecasting. If match means equals – as some people believe – we only need one reason: because it’s a forecast. Trying to get sales forecasts to hit actual revenue bang-on is a fool’s errand.

And accuracy might not be as valuable as you think. If I have a customer who reliably places an order for 100 units every month, I can forecast that amount, and – assuming the order is received – my forecast will be 100% accurate. Strange as it sounds, a lot of purchasing is just that way: steady, predictable, consistent.  What is the value of that forecast to my company? Minimal, because they already know it’s coming and they have planned production, personnel, and materials accordingly.

Accurate as it is, there’s little value in my forecast because there’s no intelligence behind it, and little possibility of variability. If you and I are standing in the middle of a nascent hurricane, would there be value to you if I said, “over the next 24 hours, we’re going to experience heavy rain.”? I’d be accurate as all get out, but my statement wouldn’t be particularly valuable. Yet, companies encourage salespeople and their managers to indulge in similar forecast gaming by penalizing them for “inaccurate” forecasts, and rewarding them for playing things safe, and predicting revenue only when it’s solidly assured. This discourages probabilistic thinking and situational awareness – two essential competencies for salespeople today. And vital for planners.

On the other hand, if match means in the ballpark, then companies need to specify what that means in terms of variance, because an acceptable variance for one company might not be acceptable for another. And acceptable variance might change for a given company, depending on market conditions and other forces.

In sales, there are three reasons for forecast variances (defined as the delta between expected results and actual, usually in terms of revenue or unit volume):

  1. Sales forecasts are projections dependent on human decisions, which are exceedingly difficult to predict. That’s true with just one decision maker. And when there are multiple decision makers – for example, with buyer committees or additional levels of approval – forecast complexity skyrockets, often defying intuition and mathematical prediction.
  2. [Stuff] happens – though most sales managers are loathe to admit it. Across a broad spectrum of situations, unanticipated events occur with such frequency that there is vernacular for them: Black Swans. In forecasting, salespeople and their managers seldom allow for them, and they include such things as supply chain interruptions, buyouts, executive defections, sudden strategy changes, and reallocation of project funding.  These are frequently catastrophic deal-killing events, and they are out of the salesperson’s control. Every forecast must consider these possibilities and more, and account for them.
  3. Senior management injects biases. Sales managers commonly demand that their reps carry “healthy” revenue pipelines, and they stigmatize their reps as “low performers” if they don’t project revenue that’s congruent with quota. The result: forecast candor is systemically discouraged, while forecast inflation gets rewarded with a pat on the back.

Sales VP’s often tell me that forecast variances result from sales reps who are “overly-optimistic.” That’s often partly to blame. Optimism can cloud situational awareness, which creates volatility – the bane of CFO’s and production planners. But there are many other risks that come into play, and it’s incumbent on managers to know what they are.

My next article will cover what makes a sales forecast high quality.

The post Three Reasons Sales Forecasts Don’t Match Results appeared first on Contrary Domino.

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