As engineers, we often keep our head down, working hard to finish projects. It’s easy to lose track of what is happening in the world, let alone other industries, especially in human resources. 

But recently, there have been really interesting developments occurring in our neighbor (often office neighbors) industry that are starting to affect engineering more and more — and that change falls under people analytics.

I came across people analytics by chance: I love listening to audiobooks and podcasts on my drive to work, and I happened to find one that spoke about “personality metrics,” which is one type of people analytics. The specific personality metric that I first heard about was DiSC. I ended up paying the approximate $50 and took the full DiSC assessment, and was floored, a little creeped out, and pleasantly surprised by what I read. 

According to this assessment, I was a “high DC,” which equated to a “creative pattern” that according to DiSC means the following: “Creative patterns express themselves from opposing behavioral forces. They desire immediate results, yet have an equally strong desire for perfection. They will observe aggression and it will be tempered by sensitivity. They think and act quickly, yet will explore all options before making a decision.”

Additionally, it deemed I “would increase my effectiveness with more warmth, tactful communication, effective team cooperation, and recognition of existing sanctions.” Yowza! That last line cut deep, but I figured I had nothing to lose, and therefore with this recommendation in hand, I made a much more concerted effort over the last couple of years to focus on my communication, and I certainly feel that I have become more effective in the process.

In the years since I took DiSC, I learned about a multitude of other personality metrics, and took many of them: CPI, Predictive Index, MBTI (or Myers-Briggs), How-To-Fascinate, Kolbe, Enneagram, Understand Yourself, etc.  At this point, I’ve taken probably a dozen or so, and amazingly they each feel like they help fill in and give me a little bit more information about myself, helping me squeeze another 5% improvement in performance.  I’ll admit I am probably a personality metric addict — my wife would agree with that — but especially since it is so difficult to get constructive feedback in engineering (due to the long lead time between design and construction).It feels great to get actionable advice that you can act upon within minutes. 

Turns out, I’m not alone. Personality metrics are one of the fastest growing segments within people analytics. According to Talent Analytics Quarterly, people analytics encompasses topics such as workforce scenario planning, real-time engagement/sentiment tracking, talent data benchmarking, attrition planning, and predictive analytics modules. Some of these items are in early phases, others are embedded, with the overwhelming point being that this field is not going away anytime soon. Rather, it appears to be rapidly expanding. According to Forbes, in 2017 69% of companies are integrating data to build a people analytics database. In previous years, this number hovered between 10-15%.


Kelly says…

I had the opportunity to discuss the field of people analytics with three incredible professionals that work with people analytics in different ways – the first being Kelly Reed, Ph.D., who is the managing director, global people & culture solutions with Lockton.

The first item that I tried to understand was the difference between human resource metrics, people analytics, personality testing and employee surveys.  In my interview with Reed, she indicated:

“The simplest way to think of it is that HR metrics is a collection of people data points such as head count, turnover rate, time to fill open positions. Think of these like a sports stats card. HR metrics are all about the question, ‘What is happening or has happened with my workforce?’ People analytics is the process of gathering people data in an investigate manner to answer key business questions. People analytics looks at patterns and relationships across data, often looking at cause-and-effect relationships, starting with a specific question or opportunity. Let’s use turnover as an example. ‘Why is our turnover rate climbing? Why are we losing key people? Where are we at risk of losing more people?’ With people analytics, there is more focus on understanding why, how and what will happen, rather than just what has happened.” 

So, what is the difference between people analytics, personality testing and employee surveys?

“Personality testing and employee surveys are types of people data,” Reed explains. “Personality testing tells us about a person’s job-related attributes. Surveys tell us what people think about their work experience. People analytics can take any kind of people data, including but not limited to personality testing or employee surveys, into account to answer business questions. People analytics can tap into loads of information an organization already has about its workforce.  For example — back to our turnover question — we may be able to see patterns in HR system data indicating current and future spikes in turnover based on factors such as compensation, tenure, time since last promotion, department, size of team, and manager performance ratings, and then we can use this to predict who is likely to leave next and why.

“The Wall Street Journal recently featured an article with various data points that can reliably predict workplace turnover. Microsoft uses people analytics to enable their employees to be able to determine what other jobs in the organization might be a good fit for them. The algorithm gives them a percentage match for other jobs at Microsoft based on data such as their job history, skills and talent assessment results. The advantage that organizations have when utilizing people analytics is that they are light-years ahead of those organizations that don’t in terms of their decision-making speed, precision and accuracy.”

Wowza! At this point, I asked myself what I had stumbled into? I started imagining a computer program that based on my information, would be able to help map out the best career for me. That seemed powerful, but also a little… creepy? I asked Reed about the downside of people analytics and she indicated the following:

“So in the Microsoft example above, they offered that job-matching program to employees based on an opt-in basis only, and they experienced extremely high opt-in rates across the organization. Sustainable people analytics programs depend on a company having a culture of trust. If there is a high level of trust between employee and employer, then there is a greater willingness among employees to share information and trust that it will be used responsibly.

“You can’t put a high enough price on social capital and trust in an organization, especially these days.  The hit to customer brand, employment brand, employee morale and share price can be very real when there is a violation of the implied trust contract. For example, a large e-commerce company had been secretly running an under-the-radar artificial intelligence (AI) for candidate selection, but then suddenly shut it down. It was very predictive but also very biased against females and minorities based on the data that had been used to build the algorithm. This is a good reminder that just because something can be done doesn’t mean it should be.

“If an organization has a pressing business they want to address with people analytics — even if they think the project will have a big impact — they should ask themselves, ‘What would happen if this ended up on the front page of the New York Times?’ or ‘Does it have a creepy factor to it?’ If so, don’t do it or find a more responsible/ethical way to do it. If your organization is new to people analytics or if trust in the organization is low, start small with the fundamentals to build trust and credibility over time. What is our level of organizational trust and credibility with employees? How can we foster and nurture that before diving deep into people analytics? Will employees question if the data we collect is being used for good or for nefarious purposes? Enhancing levels of trust and credibility with employees is the most important first step.”

As with so many things, so many of the largest challenges always seem to come down to communication, transparency and most importantly trust. We’ll finish my interview with Kelly in next month’s column.