The Problem with Employee Experience
Time to call out the lazy thinking in this field.
Background
I’ve written several articles criticising the direction of HR Analytics (aka People Analytics) over the last few years, about how HR is pursuing the wrong priorities. In my most recent article, I talked about ‘time-wasting’ endeavours such as trying to improve employee experience. I also wrote a couple of articles on UX measurements, the most recent in which I argue that at the heart of it, the two most critical UX measures are utility and usability, and how one could go about quantitatively measuring it. So I thought it would be interesting to combine my thoughts across these 2 domains.
And so I dedicate my 26th weekly article to discussing the topic of defining and measuring Employee Experience.
(I write a weekly article on bad thinking and bad practices in data analytics / data science which you can find here.)
Poor Definitions & Measures
The simplest and often talked about measure of employee experience is the employee net promoter score or eNPS. This is simply a direct translation of the original customer-oriented NPS (which research has since debunked, by the way!). eNPS asks the question “How likely are you to recommend your company as a good place to work?” This is intellectually lazy and analytically bankrupt. The measure tells us NOTHING — it is an outcome measure and questionable at that; it is not actionable.
The commonplace definition of employee experience is how employees perceive the workplace. As shared in many prior articles, I am not a fan of latent (i.e. abstract) variables. How would you data-define perception? How would you data-define workplace? And what is it about the workplace that the employee is supposed to perceive? Companies attempt to tease this concept apart through surveys, with questions around opportunities and growth, around teamwork and managerial support; while others focus on outcomes such as retention rates and referral rates without any meaningful insights on what information signals are contained within these metrics.
Utility & Usability in Employee Experience
I am a big advocate for first principles approach when it comes to problem-framing and diagnostics. And so here’s my first principle approach to unpacking employee experience. Employee experience should be a logical extension of user experience. User experience is typically defined as utility, usability, trust, and appeal. Of the 4 attributes, I argued in my article that we need only focus on utility and usability to move the needle. In that article, I had defined utility as the attempted use of a product’s set of functionalities. I then further define the % of the functionality set being utilised (attempted) as utility value; the higher the %, the higher the utility value extracted for the user. I had also defined usability as the success rate of using a product’s set of functionalities, i.e. the % of attempts leading to successful usage of a given functionality. The higher the %, the better the usability.
Can we apply an equivalent definition of utility and usability for employee experience?
Let’s first unpack the equivalence of utility in employee experience. “Attempt to use” is the key here.
We first need to inventorise the existence of employee value propositions, equivalent to the designed features and functionalities in the user experience space. Some employees are looking for equitable compensation, some for job autonomy, some for promotion opportunities, some for worklife balance, some for job variety. Therefore, does the company have ‘features and functionalities’ to meet these expectations? We can identify the existence of these employee value propositions by looking at HR policies and structures. For example, equitable compensation as a value proposition can be identified by salary benchmarking — is your company’s salaries at the median percentile or better when measured against comparable companies in the same industry? Consider another example — worklife balance. We could identify the existence of this particular value proposition by noting the existence of hybrid work policies, number of personal leave relative to similar industries, etc.
Once we’ve identified the existence of these value propositions in a company, the next thing we do is to measure the attempted utilisation rate. In the equitable compensation example, we can measure the number of employee requests for salary increases, particularly by those falling below the median benchmark. In the worklife balance example, we could measure the number of employee requests to work from home.
Table 1 below provides a more comprehensive set of examples. Bear in mind that it is not the intent of this article to propose a complete solution articulation in this space, but rather to argue that the proposed construct is tenable.
Let’s now unpack the equivalence of usability in employee experience. “Successful usage” is the key here.
We define usability in employee experience as the success rate in extracting the utility value from the value propositions. In the above examples on utility, it is simply the success rate on the attempted use. We are not necessarily seeking a 100% success rate on all value propositions, since there are valid reasons for non-success of the request plus the fact some of the value propositions have a scarcity limitation, such as promotion opportunities. We can set certain benchmark success rates fo which deviation against would imply a less-than-desired usability outcome.
To measure the final employee experience metric, we can measure it as usability-adusted utility for each value proposition, and then combining that into a weighted aggregate that cuts across all value propositions.
Conclusion
Employee experience has been in the HR lexicon for a considerable amount of time; it’s often inter-spliced with concepts like employee journey and employee engagement. But the needle has not really shifted very much in terms of achieving more clarity and insights. With the framework of employee experience utility and usability as the foundation, we can actively investigate the role of surveys and qualitative measurements. For example, surveys could focus on reasons for low perception of utility value (e.g. perhaps because of low awareness and communication gaps) and impedences for low success rate (e.g. unsupportive supervisors). In this way, the information gathered has convergence and provides for supported and triangulated insights.
