Remember the crazy
Air Force One rescue scene
Iron Man 3
? JARVIS, Iron Man’s trusty virtual sidekick, makes rapid assessments of each victim of a mid-air explosion, guiding Tony Stark’s decisions about who to save and how. Spoiler alert: Iron Man defies the odds and rescues them all with some creativity and fast thinking.
The artificial intelligence built into JARVIS may be fiction (for now), but things are rapidly moving towards greater collaboration between man and machine. In many industries, adaptive technologies are drawing on artificial intelligence (AI) as the driver of greater personalization and agility.
In fact, the role of AI in mobile platforms was the main focus this year at both the Apple Worldwide Developers Conference and the Google I/O developer conference. AI already powers much of the most personal piece of tech we all own – the smart phone. It is baked in to all kinds of common apps that seamlessly adapt to user behavior.
Take me, for example. I travel abroad pretty often. Wherever I go, as soon as I land Google tells me the exchange rate, where to pick up my bags, the distance to my hotel (with the option to book an Uber), and provides a list of local attractions and restaurants. This is the kind of “know me” solutions digital natives are coming to expect everywhere, including from their employer.
Continuously Building Skills with Continuous Coaching
A critically important element of that employee-employer relationship is skills coaching.
According to the 2017
CCW Executive Report: Performance & Agents
by the CCW Digital research team, an overwhelming majority (86.3%) of contact center professionals rank one-on-one coaching as “important” to employee development. That is actually 20% more than the next most highly ranked factors, group training and customer feedback.
But what kind of coaching?
A 2017 Gallup study, the
Re-Engineering Performance Management Report
, found that “continuous, ongoing coaching” is the direction most companies want to go. “Traditional performance management systems are outdated and ineffective,” Gallup declares, advocating instead “a culture of performance development.” That means a dedication to constantly and consistently provide employees feedback, guidance and training – i.e., ongoing coaching – rather than just in response to annual evaluations or to a sudden crisis.
That all sounds good in theory. In practice, however, most supervisors do not have the time or resources to continuously coach every employee.
But adaptive technology can fill that gap.
Coaching with (Artificial) Intelligence
Employee coaching can only be continuous, ongoing and truly effective when it incorporates AI-driven automation. As
workforce management applications become more sophisticated in identifying employee character traits, coaching becomes more targeted and engaging. It also becomes much more self-directed. Adaptive technology can surface tailored performance insights directly to employees, in near real time, based on trends and growth opportunities specific to each individual. As a result, no opportunity to keep employees on track to success is overlooked, which also increases engagement.
Let's look at a concrete example:
- Ted the agent's NPS is tanking. The adaptive workforce optimization system automatically identifies the drop, compiles a root cause analysis, and prompts Ted to play a self-guided trivia game focused on building the relevant skills or knowledge. The application chose the gamification approach because it already knows how Ted learns best. It also highlights when Ted has some downtime during working hours and offers to schedule the game for him.
Yet, such self-directed learning is not always successful. That's when a human coach is required. At this stage, AI-driven adaptive technology takes a turn toward the JARVIS-like and helps supervisors effectively prioritize their limited mentoring time, getting the most bang for the buck, by identifying the who, why, what and when of coaching (also known as "segmentation").
Who – knowing which agents will provide the biggest returns on their training (hint: it's not just who needs the most help).
Why – piecing together and concisely sharing the root cause of an employee's struggle. This can sometimes require analysis of up to 13 different steps, from disparate sources.
What – automatically adapting the method of learning and coaching material to each employee, as everyone learns differently (visual learners prefer short video tutorials, others need more play-by-play guidance, etc.).
When – predicting and leveraging employee downtime, as well as cross-checking with other supervisory commitments, to automatically schedule a coaching session.
While your contact center agents are hopefully not in a performance free-fall, the Iron Man-like synergy between artificial intelligence and human creativity is the key to rapid, adaptive and continuous coaching. Even Captain America would have to agree with that.