2017 has been a year of major changes in the contact center market. There have been more acquisitions than in any year I can remember. There have also been more partnerships announced, which have at least in part been enabled by the advance of cloud-based systems. The move to the cloud has continued apace, along with the addition of new capabilities that allow employees to access systems from mobile devices. Vendors have of course announced many updates to existing systems, as well as exciting new developments around technologies such as video, collaboration, artificial intelligence, machine learning, predictive analysis and bots. Moreover, several new vendors have popped out of the woodwork with innovative new products.
NICE is one of the vendors leading the way in acquisitions, product updates and new developments, many of which have been to support its efforts to produce one of the first customer engagement hubs – CXone, which I recently wrote about. In order to reach this goal, the company has continued with new acquisitions, such as of Workflex to support advanced workforce engagement, and new product developments, one of which, Adaptive Workforce Optimization, is designed to take employee engagement to a more personalized level.
There are two assumptions at the foundation of AdaptiveWFO, both of which resonate with my own thoughts. First, very satisfied, properly trained and motivated employees handling interactions deliver better customer experiences, which results in happier customers. Second, employees are people and like to be treated as individuals just as customers do. Do this and they will be happy and the loop will continue. If organizations accept these as goals and seek to achieve them, they must have a more detailed and complete view of their employees that they can use to personalize work schedules, training, coaching, performance targets and more.
At the heart of AdaptiveWFO is a rules-based analytics engine that produces employee personas. Employee personas are much like customer personas or profiles and as such they take the analysis of employees to a far greater depth than what is now available. The concept is quite simple: identify a series of metrics that “define” an employee, gather the data needed to calculate the metrics and visualize the outputs in an easily usable format. Though this is a simple concept, it is hard to achieve.
To get organizations started, NICE has defined three categories of metrics: performance metrics, attributes and preferences. Performance metrics include such things as AHT, quality scores, CSAT and NPS; attributes uses categories like controller, hard worker, competitor, or innovator, and preferences include characteristics like “morning person” or “learns best through visual techniques.”
NICE currently supports a pre-defined set of these metrics but is developing capabilities that will allow its customers to create their own. The analytics engine has rules specifying where and how to collect the data (which can be internal or external data sources) to calculate the metrics and how to calculate them. It then does so and presents them in a visual form. This is quite hard to describe but is similar to the spokes of wheel where the spokes vary in length depending on the score for each metric, in each category – you will get a much better idea if you take a look at its website.
This data is then fed into other WFO applications (quality management and workforce management), where it is used to create personalized recommendations and actions that fit best with the persona. For example, schedules and training can be aligned with personal preferences and variable incentives and rewards from gamification can be aligned with performance metrics. It also allows managers and supervisors to make decisions and take actions that are personal to employees, all with the intent of making employees happier and changing their behavior to better deliver business goals.
I see this new product very much relating to our research findings and my own observations – customers expect interaction-handling to be personalized for them. Doing this will make them happier and more likely to remain a customer and buy more. Something similar can be said about employees – they would prefer their work schedules, training and rewards to be personalized. Doing this will make them happier and want to stay in their role for longer, thus reducing agent turnover, which most organizations I work with have been searching for ways to accomplish for a long time. Our research shows that happy employees create happier customers and are twice as likely to deliver on key metrics such as AHT and CSAT. AdaptiveWFO is a tool that not only helps address these issues but has one of the most innovative ways of presenting employee personas I have come across. It also continues NICE’s tradition of investing in new products and enhancing its existing ones with the primary goal of improving interaction handling and the customer experience.
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