And what can we do differently to improve on that approach?

It comes down to understanding the employee better, right? And that requires workplace services to become more personalized. That may sound simple, but this very critical factor – providing personalized service – is not so easy with out the help of right approach and helping technology.

Most organizations have put a lot of effort into understanding employees, and they do so by creating something called an employee persona, or employee segmentation, etc. But there are a lot of basic flaws and challenges in that model.

One problem is that when we create an employee persona, as an organization, it is typically created in a silo. A small department handles this so-called persona project. Once it’s created, this persona might be utilized for one or two initiatives – but it often doesn’t get practically applied to all workplace services.

Also, the data used for developing personas often relies too heavily on superficial knowledge. I’m referring to demographic data: age, sex, marital status, place, location, etc. That’s not enough information to address the demands of the current modern workplace. An employee’s attitude towards their work, their motivations and frustrations, are all very, very critical pieces of information to achieve success with personalized services. It’s not so much about who the employee is or what they tell you, but rather what they actually do.

This is where Nexthink comes into place. We started thinking, “who else is better equipped to understand an end user and what they do than Nexthink?” Nexthink sits on all of an employee’s devices, making it possible to understand everything about what’s happening in a digital workplace. That’s where the Nexthink end user persona was born.

Can you give more insight into how these personas work?

So, we know Nexthink organically collects large amounts of data points like device hardware, software activities, all from the end-user side. We started a process of contextualization with all these data points that are focused on deliverance to the end user – device hardware, software, application activity, connection, etc.

These data points gave us a tremendous number of insights into understanding the experience of each user. We then sliced these insights into mini capsules of intelligence, which we call personal traits.

The beauty of these personal traits is that they can be measured and tracked in real time. The result is a dynamic persona: the persona of a person who is ever-changing. From there, you’re able to best serve the particular persona or personas of each end user, individually, at scale.

Learn more about IT Personalization

In terms of business benefits, what are the big-picture advantages that customers can expect from rolling out this kind of service?

When we speak about personas traditionally, we’re talking about creating four or five “boxes” of personas. And then we put groups of employees into those boxes. There’ll be one box called “Office Worker”, “VIP User”, “Roadrunner”, these types of boxes. And then we apply those personas to all business objectives, whether it’s VDI readiness assessment, intelligent device refresh, whatever we face. Now it’s not that way. We now have the ability to dynamically create personas based on key personal traits. They keep changing.

Learn more about IT Personalization

With this model, we first identify a business objective for which we want to apply a persona. Based on that objective, we go ahead and create a unique persona style. For example: for VDI migration, I will be using a specific persona. I won’t be using the same persona that is used for the initiative of providing the right device to the right user.

To put it simply, we can now create personas based on the specific needs of a project – instead of having static personas that become useless with each new project.

For more on personalization and building employee personas:

Nexthink’s Persona Insight

Personalized Experience at the Right Cost

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