Kansas or Oz. The Difference Interaction Analytics Can Have on Performance Management


Blog Editor’s Note:  This is third in a series of three blogs, written from the perspective of how supervisors and agents are affected using a traditional quality management system versus one powered by Interaction Analytics.   

A few weeks ago I wrote a post offering a day in my former life of being a call center supervisor and the efforts I put around trying to deliver performance management using traditional tools that included random call sampling.  Needless to say, the results were less than ideal.  Then last week, Jonathan Wax described an organization that was able to take advantage of Interaction Analytics, and use the solution to help find relevant calls which allowed the supervisors to devote more time to coaching and that led to better trained, happier agents who performed at a higher level.

All this led me down a path of envisioning what my days would have been like if I had access to Interaction Analytics when I was conducting quality management.  Hopefully, by spinning my ‘day in the life’ into what it could have been, you’ll be able to step into my shoes and understand how Interaction Analytics could shape your role if you’re a contact center supervisor, or at least understand the impact it could have to your organization if you’re not on the front lines yourself.

Same Scenario, Different View

So let’s take the exact same scenario from the previous post, and flip it around.

It’s the first of the month and I need to perform my assessments on my agent, Mary Stewart.  A little background – we’re a cable service provider and one of our corporate initiatives has been to reduce the number of “truck rolls” or number of times we send a technician to a customer’s house.  It’s a costly maneuver and we’ve been working with agents to make sure if a customer calls in with a simple problem such as ‘no picture’ that they go through proper troubleshooting steps before turning to the expensive truck roll.

So naturally, since this is an objective that’s important to the company, I want to see how Mary is doing with these types of calls.  And Mary will be interested to know too, since her bonus depends on it.  Since I have an Interaction Analytics system in place, I log into my dashboard and see my team’s results against key metrics.  Mary is doing ok with her legitimate dispatch rates, she’s yellow, but there’s definitely room for improvement.



No More Wild Goose Chase

But the great thing was, I didn’t have to go on that wild goose chase searching for calls to determine this.  Because the metric for an acceptable number of dispatches had been determined, using an Interaction Analytics solution automatically generated those results by classifying the calls and identifying the calls where an appointment was set, which indicates a truck was rolled.

Since it was based on 100% of her interactions, the subjectivity was removed and there was no possibility the score was the result of one or two abnormal calls or something not indicative of her overall behavior.

Now I need to complete an evaluation form for Mary.  No problem.  The audio that comprises those scores is just a click away.  I simply drill down and hear the calls that put Mary in the yellow and fill out my evaluation form while I listen.  And the calls aren’t random, they’re about the metric that I’m measuring.

A Priceless Gift

When it comes time to review with Mary, I’m armed with the best gift of all.  Time.  Because I didn’t spend hours searching for calls, and I know that she’s struggling with her dispatch rate and escalations but is doing great with transfers, I know exactly where to focus my coaching.  I play her examples of her calls where she got off track, and I’m even able to pull up best practice examples from Amy and Maria who are doing really well.

The Results

Because of this personalized coaching, Mary is able to understand how she could do a better job with her troubleshooting and her rates improve.  I can verify this by quickly checking the same metrics next month and seeing the improvement for myself, even before I listen to her calls.  Before Interaction Analytics powered this approach,  I crossed my fingers and hoped the random calls I pulled from Mary were in fact examples of ones where a customer called in, complained of no picture, and Mary did or didn’t do what she should.  And since I saw Mary struggling with in this area early in the quarter and delivered the targeted coaching she needed, she was able to meet her goal, qualify for her bonus, and felt like a valued member of the team.  The company benefitted too, since their expensive truck rolls declined.

Final Thoughts

So you see, making the switch to using Interaction Analytics for performance management is a bit like that moment in the Wizard of Oz when everything switches to color.  Things were ok in black and white, humming along as they had always been.  But having the ability to let the technology do the heavy lifting for you, so you can focus on bringing the human touch of coaching and mentoring to your agents so they can bring better service to your customers is the color you’ve been missing.

Hear how Nexidia customer, Cardinal Health, is using Interaction Analytics to shape its performance management program by downloading this podcast.

Photo by The Western Sky

Categories: Performance Management