Back in 2014, IBM announced a new consulting practice offering several new technology services that would apply big data and analytics processes to human resources problems.
From the above-linked article:
One service, predictive hiring, would use large volumes of behavioral assessments and other employee data to better understand the traits that are characteristic of top performers, and then comb through candidates to identify potential hires.
A predictive retention service would analyze workforce data — exit interviews, for instance — to identify those employees most likely to leave.
What struck me when I first read this article is the flawed assumption that job applicants bring high-performance traits with them through the door, or they don’t. And if an employee is looking to leave the company, it’s due to some shortcomings on their part.
It sounds like an example of Maslow’s law: If your only tool is a [analytic] hammer, every [HR] problem will look like a nail.
Since existing leaders will decide what the “traits that are characteristic of top performers” are, they may well end up defining the ideal employee profile in their own image – a clear example of confirmation bias.
You must remind yourself that when you start to pick apart winners and losers, successes and failures, the living and dead, that by paying attention to one side of that equation you are always neglecting the other…
When a company performs a survey about job satisfaction, the only people who can fill out that survey are people who still work at the company. Everyone who might have quit out of dissatisfaction is no longer around to explain why. Such data mining fails to capture the only thing it is designed to measure…
The reality is that workers’ attitudes in the workplace can and do change significantly over time in response to the organization’s own traits, for better or for worse, depending on whether the work environment is proactive or risk averse, collaborative or politically charged, collective or exclusive.
In order to hit our goals in any organization, we need to build positive energy in the workplace. We need people to be excited about their work…
Can you measure that excitement level? You can’t measure it, but it will show in the results that you do measure, from customer satisfaction to turnover to earnings per share. Anyone in your organization will be able to tell when the excitement level is high, low, or nonexistent. We’d have no trouble reading the energy waves at work if we remembered to stay human on the job.
To her credit, Liz Ryan doesn’t pull any punches in rejecting impersonal, technocratic measurement of employee engagement. I doubt the predictive analytics described above would fare any better with Liz than the hollow ritual of the annual employee survey:
If we really care what our employees think, it’s easy enough to find out… We could ask them how they’re doing… We can be human at work…
We don’t have to insult our employees by having them fill out surveys so the people charged with employee engagement can go to the leadership team and say “Look! The employees are 68% engaged. Look how well I’m doing my job!”
Give up the employee engagement survey, drop the junk-science patina on stupid HR practices and learn how to be human at work. You’ll be amazed how the team’s energy will power your success once you let it start flowing.
Analytics, when created and used appropriately, can be a powerful force for success, but there are also many new technologies that help actively engage employees and cultivate employee positivity and productivity. Gamification platforms are just one such example. Here in Boston, for instance, the WeSpire platform engages and energizes employees around company sustainability and social responsibility programs.
“The best way to predict the future is to create it” is an old saw, but it still rings true – especially when leaders choose to seek out genuine, human interactions and build an energetic, collaborative work culture, which should yield much better employee outcomes and improved individual and team performance.
P.S. – On a related note on hiring decisions, what often passes as “common wisdom” within the HR function really isn’t all that wise. Well said, Natasha Bowman!! ⭐️⭐️⭐️⭐️: