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Tenacity - Improving Customer Experience by bettering Employee Experience

Tenacity - pech
Following some of my posts on AI in customer service environments I got contacted by Daniel Doctor from Tenacity who invited me for a chat with Ron Davis, the founder and CEO of the company.
Which I had. And it was an interesting conversation.
In my articles I spent a lot of time focusing on how AI, machine learning and chatbots can help improving both, the customers’ and the service agents’ experiences by making sure that all relevant data is collated and available, reducing wait times for customers, being able to already suggest good solutions to both, customers and agents, and so on. The objective is at all times to have the customer get a good solution as frictionless as possible and to enable the service agent to concentrate on the hard jobs.
The idea behind this approach is that it reduces customer irritation by having the answer faster and improves the agent situation by making the work more attractive. After all, who of us loves dull, boring and repetitive work. Not many, I bet – certainly not I.
Of course, this is only half of the truth. Service agents, like all employees also react strongly on who they work with, who they work for, whether they have the right tools at hand to get their job done, how their stress levels are, whether their private lives are untroubled, whether they have enough sleep, and so on.
Additionally, the more interesting situation of the dull jobs being taken care of by the machine creates stress, as the customers tend to already have an elevated level of frustration that was caused by the unsuccessful solution attempts they already went through. In this situation the best-suited agent is also a different one than the one best suited for first customer contact. It is the controller as opposed to the empathizer.
This, to some extent, is outside the scope of employment, but it still is a good idea for employers to equip their employees with the education, tools and techniques to deal with stress and to create a healthy social environment.
This is where Tenacity comes into the picture.
The value proposition of Tenacity is to “reduce attrition and absenteeism with an employee engagement solution that will give your call center agents a better quality of life”. The philosophy behind it is that happy employees create happy customers.
Tenacity is tackling this with a solution set that bases on three levers:
·      Stress management
·      Creation of a community of co-workers
·      Creating a sense of meaningful work
And Ron claims that Tenacity has reduced attrition by 1/5 to 1/3 in every(!) call center they are in.
Which is an outstanding achievement.
They have done this by delivering a combination of wellness content, social network and online community that one can imagine as similar to what Reddit looks like.
Now, if you are looking at supporting and promoting the reduction of attrition and absenteeism as mainly an HR function, then you are probably right. However, as all this is about call center performance it is also very much an operational topic. It starts with persons – call center agents – not simply accepting resilience content and other things that are pushed into their faces. Instead this needs to be personalized and be made part of a system.
Tenacity wants to be this system by tackling the above three levers. Agents log in to the cloud based system and are presented with a Reddit-like community where they can interact with colleages and are presented with a dashboard that gives them an overview of their achievements in terms of health goals. The whole system shows gamification elements to encourage usage and allows not only to earn points, but to also meaningfully redeem them. Companies offer the agents some time in the application and they can voluntarily spend additional time in there.
The system is backed by a decision tree based AI that learns from interactions in the team and gets data feeds from performance management-, WFM-, and HR systems that are uploaded into the system. Ron tells me that they are looking into moving towards deep learning once their data sets are big enough, which they aren’t yet. Being a young system there is no direct integration into other systems yet.
With this data the system then can suggest a number of things, like where team-building exercises should happen, or how teams could be organized to improve the overall performance, or how an individual agent can improve the own situation.

My Take

Tenacity wants to re-humanize the call center by using data. This sounds like an oxymoron but depending on which data gets used this seems to be a good way. Their system currently uses organizational-, WFM-, and PFM data, in addition to the behavioral data that it collects. Considering that a person’s motivation level also depends on whom she works with and for, this is clearly a good start and there are plenty of success videos on the site.
The idea of combining resilience content with community, backed by data to allow decision-making based upon facts could be a winning strategy.
Where I am somewhat of split minds is the merits vs. disadvantages of having the system separate. While this reduces distractions it also reduces the potential benefits because the system just might be a click too far away.
Knowing that Tenacity is a young company with a new system and limited resources I do think that integration is key. Integration into the above-mentioned systems, in particular WFM and PFM, but also with a Learning Management System and the customer service systems. I do also think that an integration with the actual call center software would be beneficial to the agents if used for helping them determining stress levels and potentially doing some load balancing.
Tenacity brings an interesting concept into the market but needs to make its stand against the call centre solution-, performance- and workforce management system providers who all have the objective of making the call centre more effective and efficient, albeit with different approaches.
So far signs are positive for them, but as usual only time will tell.

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