Simon Sinek on Millennials in the Workplace
Currently, WFO combines quality and/or performance data with expected contact center workload, keeping contracted service level constant. What seems striking to me is that agents are assigned to future shifts based on their past performance. But how can you tell, whether the past performance will be matched the in upcoming period? Well, you can’t.
It is only logical to assume that a high performing agent A can replace, say two other agents – B and C, that reach half of A’s performance. It is the perfect example of how modern society plans not only working shifts, but also many other activities, starting from predicting GDP, ending with speculations on the stock market. All estimates are based on the Gauss curve (a curve of a standard distribution) combined with an assumption that the future will simply be a duplicate of the past.
I’m a big fan of Nassim Taleb, renowned mathematician and statistician, author of The Black Swan – a charming book, one of my all time favorites. Taleb talks about how people make predictions based on the past as if there was no probability of dramatically different course of action that could eventually happen in the future.
A brilliant example of this vastly used mind frame is a turkey in a cage that is generously fed day after day. With each day the turkey realizes that nothing except great food and leisure time would ever cross its trail of life because its experience from the past doesn’t even offer a different experience. Of course, the closer to Thanksgiving, the sooner would a butcher cut its throat. From the turkeys’ point of view an unexpected event is going to happen. And this is what Taleb calls the black swan.
When it comes to contact center agents the black swan is the point where the agent all of a sudden burns out or leaves the job. Or both. There is no way of predicting this point in time based on agents’ performance. Of course, if the descent of their performance has been happening for weeks or months, you can expect that something might go wrong. But people tend to hide their real feelings and level of energy up to the point where they become cornered and make radical decisions.
I see a huge potential of transforming the whole WFO industry by taking an extended set of data about the agents into account. Relying on past performance means simply feeding the turkey, and as the yearly attrition in contact centers reaches to up to 35%, the chance that the agent would leave the contact center is realistic. To say the least.
That is why the AgentBalance software solution is built to provide team leaders with data about their agents that can dramatically influence the quality and relevance of coaching sessions, keeping agents in house for an extended period of time. And what is probably even more important, AgentBalance data can predict when the agent would leave the contact center so team leaders get prepared and can act accordingly.
A tool that will help team leaders reveal the level of agents’ energy, job fulfillment and determination to leave can help you minimize the number of black swans on your team and in your contact center. No unexpected agent departures mean major savings on agent attrition, and also keep teams balanced, motivated and high performing.
– Václav Martin, CEO AgentBalance
Photo courtesy of Jozef Kotulič Slovakia (Own work) [GFDL (http://www.gnu.org/copyleft/fdl.html) or CC-BY-SA-3.0 (http://creativecommons.org/licenses/by-sa/3.0/)], via Wikimedia Commons
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