By | ihrim.org | IHRIM Marketing
For decades, while the theory of performance management has been studied, written about, and improved “on paper,” the actual process has made little progress. Most often, it is still largely a paper-based, period-bound procedure with inputs limited to subjective observations by some combination of three sources: the employee themselves, the supervisor responsible for the review, and perhaps feedback from a few colleagues.
Many experts believe that it will take the infusion of some aspects of artificial intelligence (AI) to truly revolutionize the science of performance management (PM). They cite three main goals as most important for the initial incorporation of AI into PM:
- The ability to collect information seamlessly from multiple sources.
- • The ability for managers to extract meaningful insights from performance metrics in real time, and
- • The minimization (ideally, the elimination) of various psychological biases associated with the performance management cycle.
AI has the ability to deliver on all three of these game-changing approaches. To what extent has it already done so? To answer that question, WSR Co-Managing Editor Bob Greene had to look no further than his own company, Ascentis. Ascentis uses a software platform called Gong (www.gong.io) for “sales optimization.” He interviewed Ascentis’ Director of Presales, Monica Lloyd, and discovered that some of the best currently available AI platforms for performance management aren’t necessarily being designed or delivered by HR services or Human Capital Management companies!
What is Gong and Why Should HR Professionals Care?
On its website, Gong characterizes its offering this way: “We created the Revenue Intelligence category to enable leading revenue teams to get the unfiltered truth about their customer interactions, their deals, and transform the way they go to market…” This leads the reader to believe that the product provides value solely or primarily in the CRM/Sales category of ERP software, operating as one of the many “add-ins” and extensions to larger Sales platform dominators like salesforce.com, Oracle, MS Dynamics, and smaller players like SugarCRM and mondayCRM. But according to Monica Lloyd, at Ascentis, Gong has had a profound impact on performance management of her team of Solutions Consultants.
Lloyd reports that in addition to analyzing sales practices to determine which ones are most likely to lead to sales success, and providing key insights into sales pipeline data, Gong delivers an unprecedented amount of team performance metrics on a real time basis. She uses these metrics in team training, one-on-one employee coaching, and in completing periodic performance reviews. Beyond that, a feature called Gong Insights can provide valuable feedback to the extended organization, including product development and the executive team.
The Gong data collection model begins with integrations to Zoom or other presentation collaboration platforms (e.g., webex, gotomeeting), salesforce.com or other primary CRM platform software, e-mail servers, and (soon, according to Gong) mobile phone communication tools like texting. These multi-sourced data integrations act as omnipresent, objective “listeners,” able to report back key salesperson behaviors without going through a human “filter.” They can listen for best practice sales skills preconfigured by the software designers, as well as additional triggers established by the user during implementation.
As just one example, Lloyd explains, imagine a Sales Director with a team of 12 sales consultants. While she tries to monitor as many online sales presentations as she can, for the recent presentation to Acme Corp, she was unavailable and relies on a report by another sales supervisor who was on the call. He reports that the Sales Director’s team member “really knocked it out of the park! He addressed all the client’s concerns and delivered all our value propositions well.” But less than a day later, she receives a full report on the sales call from Gong. It offers automated metrics like the split of time spent speaking by the client vs. her sales consultant, and even repetitive measurements of the tiny intervals of time after the client finishes a question before her salesperson starts answering. The report concerns the Sales Director, because it shows a very high level of talking by the sales consultant (vs. listening), even during the discovery phase of the call, and that he sometimes cut questions off and began his answers before the questioner was finished composing his or her question. The Sales Director knows that, even if this sales call was successful and turns into a sale, that result might be more due to good fortune than by design. She concludes that her sales consultant needs some re-training on key consultative sales behaviors. The independent and objective AI reports by Gong offered different and generally more reliable information than did the subjective views of her management colleague, and according to Lloyd, this is part of the real value of AI in Gong.