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Applying Analytics to Build a Sales All-Star Team
Focus on real-time visibility, not past performance, for sales success.
Posted Aug 22, 2014
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"ABC...Always be closing." When Alec Baldwin delivered his iconic speech in the 1992 film Glengarry Glen Ross, based on David Mamet's play, it laid the foundation for what has become the backbone of all sales programs. Sales, at its very core, requires competitiveness, an innate understanding of customers, and the right data to make better, more informed decisions. Yet, despite the myriad CRM systems used today, sales managers still don't have the visibility and insight needed to know for certain that their sales teams will "always be closing."

Consider the following statistics:

  • $20.6 billion was spent on CRM software in 2013 (Gartner)
  • Only 45 percent of forecast deals are actually won (2013 CSO Insights study)

Doesn't that seem like a lot of money to be right less than half the time?

With sales teams increasingly dispersed across multiple offices, working from home, and on various devices, accurate insight into (and managing) sales performance is more difficult than ever. Traditional CRM systems require sales reps to manually enter their sales activity, including calls made, appointments set, notes from calls, etc.

The problem with this process is that this data is highly subjective, speculative, and likely not recorded in a timely manner—making it extremely difficult for managers to accurately measure the performance of their teams.

In 2002, the game of baseball changed forever when the Oakland Athletics applied analytics and metrics to its roster. Billy Beane, the Athletics' manager, recognized that lower-cost "average" players—based on time-on-base and other overlooked stats—translated to more scoring opportunities. As the 2011 movie Moneyball, based on the 2004 book of the same title by Michael Lewis, showed, the end result was the Athletics achieving the longest winning streak in league history and winning the American League West Championship.

Organizations can apply the same approach to their sales processes. Here's how.

Focus on Predictive Metrics that Matter, Not Outcomes

History is just that, and sales managers can't base past performance on individual sales as a future predictor. The key is to gain real-time visibility into every sales agent's call volume, time on call, and call outcome—regardless of location. This data, however, is only as useful as the actionable intelligence managers derive from it.

Competition is an integral part of sales, and one of the most effective ways to get the most out of sales reps is to introduce competition—against themselves and each other. By benchmarking individuals against targets and averages, managers can incentivize their teams to perform as well as gain insight into how certain individuals are performing compared with the rest of the team.

Manage Based on Data, Not Hunches

Nearly 70 percent of sales organizations have teams operating outside tightly controlled offices or call centers, meaning most likely use unreliable methods for collecting activity and performance data. This makes establishing key performance indicators, tracking them over time, and making data-based decisions to improve sales productivity and effectiveness nearly impossible.

Organizations can take advantage of their mobile sales teams without losing visibility by automatically capturing and analyzing all sales activity data, regardless of agent/rep location or phone—thereby eliminating manual documentation processes and creating reliable, actionable sales intelligence.

As a result, sales managers' forecasts are based on actual activity, not subjective probabilities.

Transform Average Players into All-Stars

Getting the most from employees with varying levels of talent and experience is challenging, even in centralized contact centers equipped with the latest technology. Automated analytics enables managers to flag underperformers on metrics that matter, and identify where and why they're falling short. The same can be applied to top performers. By understanding what top performers are doing well and what techniques are successful, managers can employ these tactics across the team to improve outcomes.

Time is money, and any weak link on the team can result in lost revenue opportunities. It takes time for a new sales rep to get ramped up, and the time it takes to determine a rep isn't working out is time—and money—lost. With analytics, managers can identify underperformers more quickly and tailor training where it's needed.

The centralized office or call center has changed—it is now any location, any device, any channel, anytime—but this doesn't mean managers have to sacrifice visibility into what dispersed agents are doing. Analytics is empowering organizations to manage based on data, not hunches, so that they can transform average players into an all-star team that will "always be closing."


Jeff Fotta is president of Gryphon Networks. Originally the firm's CFO, he has served in several leadership roles with the company and was instrumental in some of the initial client sales and early development efforts.


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