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Using AI to Drive Sales Coaching

By and

Wed Sep 04 2019

Using AI to Drive Sales Coaching
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The research has been definitive—coaching as a management practice and discipline is highly effective as a means of supporting salespeople as they navigate through a challenging, ambiguous, and volatile environment.

At AstraZeneca, the organization considers coaching a significant lever in its strategy to manage change. The company had made continual investments in coaching the frontline sales reps and their managers to high levels of performance; however, it was time to level up.

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Collectively focused on elevating the coaching expertise of its employees, leadership began its coaching evolution by getting serious about how it defined the practice, aligning that definition to what really matters—coaching to business results. The measurement conversation then emerged. Short of having a manager’s supervisor physically observe real-life developmental conversations, the team knew that accurate measurement hinged on repeated, scalable data capture.

Part of the data capture formula was the consistent use of a field coaching form, intuitively designed to capture the manager and salesperson interactions. As a living document, the file grows over time with thousands of field coaching forms submitted each year across the organization. Of course, the measurement question persisted, but this time it was centered on how the plethora of form submissions were going to be read and analyzed. With the challenge in view, AstraZeneca chose to experiment. An evaluative rubric was bolted onto the field coaching form, which plotted against the predictive measures that drive business results. The rubric was proven externally and consists of these hallmarks of a well-constructed coaching conversation:

  • focused

  • balance

  • aligned

  • specific

  • immediate

  • continuous.

Next, AstraZeneca tapped into recent innovations around artificial intelligence (AI) to complement the coaching work being done in the field. The goal was simple—AI would take the thousands of field coaching forms, run them through the established rubric, and automate the initial analysis. As an output, managers would have a dashboard or a picture of what their coaching activities look like. For across dozens of coaching conversations a manager could, at a glance, gauge how focused or balanced they were or whether or not their discussions were specific enough to change a salesperson’s behaviors.

The early results and feedback on this partnership between humans and AI has been enthusiastic. The automated analysis has helped managers calibrate their conversations to go further in shorter time spans. The focus of the coaching sessions is becoming more aligned to what managers are trying to accomplish in relation to revenue targets and broader company goals.

On a human level, the messaging around this experimentation has been important. AstraZeneca focused on positioning this work as being able to do with AI what the company hasn’t been able to do without it. The team centered communications around the possibilities that come from partnering with machines to offload busy work and gain greater individual productivity. Specific to sales managers, AI is the latest enablement tool that helps them become better coaches—they can use this data to move from teaching and telling to true collaboration.

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Of course, this is just the beginning, but the future is promising. With big data and AI, we can start asking the machine next-level questions downstream. Across the United States, for example, questions could be, “Are there geographical similarities?” Or “What are the demographic considerations?” “What are successful managers doing in those environments and how can we replicate success?”

The more we blend human behavior with rapid capabilities of machine intelligence, the more we will be able to capitalize on trends—positive or negative—and facilitate timely knowledge transfer between colleagues. Imagine a salesperson named Tim in the Florida market who is facing a challenge brought on by state-level regulation. AI could prompt Tim to connect with Amy, in the Great Lakes, who has successfully navigated the same issues. To take that idea further, if something is about to change in one person’s market that changed in another’s market a year ago, imagine the positive outputs that could happen before the change itself actually occurs? Consider what that means for overall readiness and responsiveness.

The future is today and while there is much we don’t know, the early successes at organizations like AstraZeneca, companies that are leading when it comes to integrating AI with talent development, serve as a collective opportunity for all of us to level up.

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