analytics charts

Why H.R. Won't Invest in Analytics

Sarah Watters
Senior Consultant, Levvel.io

Editor’s Note: Change is hard. I’m not breaking any news with that statement. But when organizations admit there are useful tools to help them just assess, analyze and plan potential change… and they don’t even pick up those tools… well, I don’t have too much sympathy for that. I said, “Good day,” sir! Luckily, Sarah Watters is much more patient and understanding than I am …

 

Modern companies gather and leverage data on almost everything: clicks, swipes, logins, groans by the Keurig. But when it comes to gathering data on people – on hiring, processes and performance – organizations are far less zealous in their efforts to gather, analyze and adjust the numbers that might make a difference.

Deloitte reported that 71% of organizations see people analytics as a high priority but only 9% of organizations had an idea of the metrics that drive performance within their organizations. So, even though organizations clearly recognize that gut instincts may fall short compared to data-driven decision-making, most have yet to start implementing basic methods of gathering that data.

 

Even though organizations clearly recognize that gut instincts may fall short compared to data-driven decision-making, most have yet to start gathering that data.

But not all organizations! In recent years, “people by the numbers” (a.k.a. “people analytics” or “people data”) has become de rigueur in certain settings, as some human resources departments – historically seen as a function designed to maintain order and processes – pivot to creating more widespread value. Products aimed at better understanding the workforce have taken center stage, coupled with case studies on companies playing a significant role in pioneering people analytics.

Organizations that were early adopters of people analytics have used this knowledge as a competitive advantage. For example, it has offered the telecom giant Sprint better insight into employee attrition and given Best Buy information on talent retention, while Google and GE have challenged traditional hiring and absence policies after data led them to try other approaches.

These organizations have learned that data can enhance employee experience and improve customer experience, while also enhancing the bottom line. These are all large companies with room to experiment, but there are gains to be had from people data no matter what the size of the company.

 

There are gains to be had from people analytics no matter what the size of the company.

So, despite the potential gains and the examples set by these leading companies, why don’t more organizations adopt people analytics? Let’s look at three potential explanations rooted in behavioral science and what we can do about them:

Delayed benefits

It’s pretty annoying when you eat salad for a few days and go to the gym but neither you nor your scale notice a difference, right? You’ve changed your behavior but there’s been no tangible result. Impactful change often requires a lot of patience and effort upfront. The problem is that, as humans and as organizations, we’re myopic. We don’t want to wait to see the payoffs – we want instantaneous play out from effort to reward.

A survey by TIAA-CREF revealed that people spend more time researching what new TV to buy (we can watch it tonight!) than which retirement plan best suits their circumstances. Through this present bias, we’re overvaluing outcomes that are closer in time to the present while often discounting arguably far more important outcomes that will play out in the future.

Perhaps unsurprisingly, many organizations act like the humans running them and don’t bother gathering people data because the payoff is delayed. Insights emerge over time and patience is required to acquire data sets that are large enough for statistically significant results and patterns.

 

Many organizations act like the humans running them and don’t bother gathering people data because the payoff is delayed.

If it ain’t broke, don’t fix it it can be improved

We don’t like change. We especially don’t like change if our current state of affairs seems to be working fine. If eating mac and cheese for dinner every night is working for you, why change? You do you. In behavioral science, this is called the status quo bias.

Why do we dislike change? In part, it’s because we don’t know if the change will be worth the effort. It can take time for outcomes to be observable. Why spend time and effort investing in a change that may not end up providing the desired results?

When someone comes up with an idea or suggestion that upends current processes or systems, often the first things that come to our mind are reasons not to change, why it would be “too difficult” or “impossible.” We raise potential flags by suggesting, “What about this or that or the other thing?” We – individuals and organizations – will rationalize any and every reason not to change the status quo.

We don’t know if the change will be worth the effort.

Confirmation bias

We seek information that confirms that what we’re currently doing is working or what we believe is the truth. Warren Buffet, one of the greatest investors of our time, recognized our susceptibility to confirmation bias, acknowledging, “What the human being is best at doing is interpreting all new information so that their prior conclusions remain intact.”

The problem is that when we don’t recognize counterfactuals to our own judgments and processes, we jeopardize our ability to do better. In other words, we may be forgoing opportunities and better options by wanting to trust our gut instead of garnering data-driven insights.

When it comes to other people and interpersonal relationships, it’s normal for us to expect the best in others, which means we may be blind to their shortcomings. We judge them as good fits once then, thanks to confirmation bias, are unlikely to question that judgment again. This can have particularly important implications when it comes to how we view our colleagues’ productivity and fit – and that of future colleagues and recruits – at work.

Our organizational systems can get similarly stuck. Imagine J-Corp has been using the same hiring process for years. Management and the executive teams believe that they’re attracting great people and there’s no compelling argument to counter this belief that their “tried and true” hiring process is the best approach. J-Corp’s current processes may be perfectly adequate – maybe they’ve cracked the code to hiring good people – but it doesn’t mean they can’t do better. Confirmation bias might make J-Corp reluctant to shift away.

 

When we don’t recognize counterfactuals to our own judgments and processes, we jeopardize our ability to do better.

What now?

It’s not unusual for organizations to come up with reasons as to why gathering people data is just not for them. They need to hire too many people, they need to hire too quickly, or that their current hiring processes have worked well so far and have always been this way. They might, understandably, prioritize client-facing challenges for financial or reputation-related reasons. There may also be a general lack of urgency in terms of understanding whether the right people are being hired and determining just how well current employees are performing.

Since we often lack the discipline required to see a long-term vision play out, it is helpful to start with simple, easily accessible, quantitative objectives. Whether you’re a small or large organization, start with a few select metrics and gradually grow toward more robust, powerful analytic abilities.

For example, consider measuring the time to fill positions and turnover rates and/or adopting an engagement survey with questions like eNPS (employee net promoter score). Where possible, harness inertia and overcome delayed benefits by building momentum with some quick wins.

 

Since we often lack the discipline required to see a long-term vision play out, it is helpful to start with simple, easily accessible, quantitative objectives.

In an article for Google’s re:Work, Yasmine Gray from Tribeca Technology Group explained that she started by just logging the job applications they received in a spreadsheet, eventually enabling her to create a hiring dataset with information like how many times someone applied for a role and when. This is a promising way to overcome the status quo bias you’re likely to encounter in your own organization. Just start.

Also, focus on the many peripheral benefits that the organization might accrue from harnessing people analytics, such as how it could provide a competitive edge for your organization, improve candidate experience, or increase perceived fairness among current employees. This will likely also help in starting conversations around how the status quo might benefit from a refresh. Additionally, look at what other companies of your size or in your industry are doing: what are they measuring? How well do you stack up?

Organizational Mindset

Within an organization, it can be extremely hard to recognize change needs to happen and even harder to set it as a priority. Just as we seek to develop and improve our own personal skills, organizations need to assume a similar growth mindset. Put simply, a growth mindset implies that we have the capacity to learn and improve our abilities. After all, there’s an important difference between answering “Can I do my job?” and “Can I do my job better?”

 

A growth mindset implies that we have the capacity to learn and improve.

Be uncompromising as individuals and uncompromising as an organization. Ask: What will make this company better in both the short and in the long term?

It’s daunting to start something out of nothing, to see beyond the good to the great, especially when there’s no apparent urgency. Nonetheless, it’s important to drive improvement in company practices and processes, just as it is to support individual employee growth. Start small, think big. Determine benchmarks, set goals and look around. Objectively, how does your organization stack up? People analytics may not be glamorous (to most) but it’s certainly powerful.

Organizations of all sizes can start to adopt people analytics by understanding the very human reasons that we don’t. Then we can design steps like these to overcome those biases, move forward and catch up to – then surpass! – the handful of organizations that have already adopted people analytics for good.

 

Sarah Watters
Senior Consultant, Levvel.io

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