Reinventing Opportunity to Close (Part 4): The Sales Forecast Comes Out of the Shadows

David Karel headshot

David Karel

Predictive analytics empower sales execs to call their number with confidence.

[Editor's note: This post is the fourth and final in our "Reinventing Opportunity to Close" series for sales leaders.]

Since we started our four-part series a month ago with an analogy to the movie Groundhog Day, it only makes sense to wrap it up with a post about forecasting—and to run it on February 2.

No disrespect to Punxsutawney Phil, but if you have weather-dependent plans over the next six weeks, the smart money is with Doppler radar and satellites—not celebrity rodents. Likewise, when it comes to sales forecasting, hard data beats hearsay every time.

In our previous posts, we explored how stale and incomplete data and obsolete tools are dragging the opportunity-to-close (OTC) cycle out for many sales organizations—and dragging every member of the team down in the process. Today we turn our attention to sales execs that are tasked with predicting the future, often with vague data and insights that are shadowy at best.

Forecasting has traditionally been an incredibly time-consuming and highly analytical process that demands the intense scrutiny of volumes and volumes of data. And since revenue drives everything, getting the forecast right affects everyone in the organization—not to mention people outside like shareholders. No pressure. That said, three things remain true:

  1. If you're compiling and comparing information manually, you'll never get ahead of it.
  2. If the information you're working with is flawed or incomplete, your conclusions will always be suspect.
  3. If the only day you feel good about your number is the last day of every quarter, you need the sales equivalent of Doppler radar — pronto.

Fortunately, the same technology that's revolutionizing OTC for reps and managers is also improving the forecasting process for execs. The best solutions leverage predictive analytics and artificial intelligence to automate tedious manual processes, evaluate large datasets, and ultimately build statistically derived models that help execs better predict deal progress.

For example, until recently, execs that wanted to factor historical performance data into their forecasts had little choice but to manually track, enter, and compare the information using cumbersome spreadsheet applications. Unfortunately, by the time they collected and loaded even the best data into Excel, it was pretty stale. And then they had to analyze it all—try to identify patterns and make an informed call. So, what happened? A flawed system, with flawed data, yielded flawed results—quarter after quarter after quarter.

Thankfully, the days of relying on stale spreadsheets and static data are gone. The latest platforms pull information from CRM, calendar, email, and other sources to create accurate, up-to-the-minute deal views. This technology not only automates the collection of millions of data points in real time, it also applies machine learning to predict likely deal outcomes.

Now, with instant visibility into deal status, execs are better equipped to identify at-risk deals and make truly informed decisions on the fly. And, better insight into history means more effective plans for the coming quarter. That means execs can focus less on making their numbers and more on beating them.

In the end, the ability to forecast more accurately is a tremendous economic driver. Consistently predictable revenue translates into growth—more hiring, expanded office space, happy shareholders—you get the picture. If your sales organization is still trapped in that endless, old-school, OTC time loop we call Groundhog Day, it's time to break the cycle. So, what's it going to be: Punxsutawney Phil or Doppler radar?