What is employee engagement & how can we measure it?

Marie Wallace — Mon, 10 Jun 2013 12:45:24 +0000

Last week someone sent me on a New York Times article referencing a controversial piece of research from Leadership IQ which claimed that “low performers are more engaged than high performers”. Now since this statement is rather counter-intuitive, at least for my definition of what it means to be engaged and a high performer, I wanted to investigate further. I had a bit of a mooch around the Internet and was really suprised at the number of articles positively referencing this research and thus questioning the business value of raising employee engagement levels. I then decided to take a closer look at the study itself and check out some of the critical analysis from across the Internet, including a particularly good critique from Jim Harter, Gallup Chief Scientist for Workplace and Wellbeing (No, Low Performers Are Not More Engaged Than High Performers).

In looking deeper at the breadth of discussion on this topic it became clear that there is no concensus on the definition of employee engagement which makes measuring it rather subjective. The subjectivity is further exacerbated by the fact that engagement measurements are generally done through surveys which are themselves inherently subjective. To make things worse, it’s impossible to directly ask someone if they are “engaged” so lots of other questions have to be asked in order to infer engagement, and frequently these questions end up giving you something that looks more like an employee happiness measurement.

I doubt that anyone would really argue that being mentally “engaged” with something, be that a project, job, marriage, customer, or whatever, has a positive impact on your personal performance as it relates to that something. So measuring engagement is a reasonable thing to want to do, however only if you are measuring “engagement that matters”. So this got me thinking that maybe our problem is the abstract definition of engagement, if we had something more specific then we would have a more objective approach to measuring it.

I suspect that the current definitions of engagement are constrained by nothing more than the fact that historically the only way we had of measuring engagement was through surveys (and you can’t create a bazillion surveys with a gazillion questions). However in this bright new world, where increasingly more and more employee actions and interactions are captured in electronic systems and available for measurement, we don’t need to. There is no reason why we cannot measure engagement at a much more granular and applied level, tailoring measurements specifically for the types of jobs. For example; it may be really important in a customer facing role that the employee love the company, however in a back-office role it may be more important that they love their job. In an ideal world they would love both, but what can ya do!

Enter Workforce Analytics …

All this ambiguity around the definition, and subsequently measurement of, engagement is a wee bit of a problem for data scientists who want to build analytics models to programmatically tackle this challenge. Data scientists need absolutes and don’t do well with ambiguities. It’s hard to build an analytics model if you don’t know exactly what it is you are trying to model.

This is the problem we need to address with workforce analytics. We need to be more precise about modelling engagement and subsequently measuring it by analyzing all the digital breadcrumbs that people leave across electronic systems; social (create, share, comment, recommend, tag, like), communications (phone calls, meetings, e-mails), project mgmt (projects, activities, events, travel, engagements), and so on.

Now I’m not suggesting that surveys are not a valuable tool to use when measuring engagement, but on their own I believe they are completely inadequate. It’s a case of “Don’t tell me how you feel, show me what you do” :) In fact, I would even hypothesize that they may be way more useful as a very fine scalpel that should only be used AFTER the initial analysis has been completed. In this way you could dynamically construct micro-surveys very focused on a particular question. For example; the workforce analytics suggests that a group of sales folks are highly engaged with customers but are negatively engaged with their colleagues in sales support, whereas another group is highly engaged with the sales support team. Maybe this warrants a targeted survey on these two groups of people in order to find out why there are such engagement differences.

So to wrap up… Engagement is an area that is crying out for some focused workforce analytics and until such time we move from the subjective to the objective we will never end up with accurate recommendations for how we can improve organizational performance through engagement.

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Sentiment vs. Opinion? Content vs. People

Marie Wallace — Fri, 07 Jun 2013 11:21:45 +0000

Reblogged from Marie's Ramblings & Ruminations:

In the real world, when we think about sentiment we think about a person and their opinion. Joe hates X, while Jane loves it, and Frank is on the fence. When we want to reward our best customers (our brand advocates) or convert our detractors we again think about Joe, Jane and Frank. Yet in the virtual world of social media, the software programs that try to identify sentiment frequently only think about the content.

Mapping content to people…

Marie Wallace — Thu, 06 Jun 2013 08:42:20 +0000

If content analytics is the heart of you social media analytics strategy, then social network analytics is the brain :-) While content analytics can understand content, SNA allows you to more accurately profile your community, understanding individual needs, interests, influences, and preferences. It allows you to more effectively map your content (and message) to the right people, at the right time, and on the right device.