The Human Workplace Needs Human Metrics

April 15, 2021 Eric Mosley

5-minute read

(This post is the fourth in a continuing series, highlighting the five trends that are shaping the human workplace in 2021 and beyond.) 

person working on tabletIt’s a B-school truism that “What gets measured gets done.” Now we occupy a work world in which it’s possible to record every keystroke, every minute of attention, and the physical comings and goings of every person. Work is a place (in person and online) of relentless data-gathering. In other words, what gets done gets measured and vice versa.

Our technical capabilities can outrun our wisdom, and ubiquitous data-gathering raises serious issues of privacy for business leaders and ethicists to address. There’s a positive side, however, to knowing what’s really going on in our workplaces: If leaders put humanity at the center of management, data analysis becomes a tool that enables our most human qualities to flourish.

This is an urgent task. Unique human abilities like collaboration, creativity, empathy, adaptation, and imagination are today’s keys to success. We need to measure the behaviors and interactions that lead to success, and then encourage, celebrate, and reward them. We need to train people to harmonize their differing strengths. We must configure our teams to help humans with diverse skills work well together.

I’ve written that outcomes and key results (OKRs) are blunt instruments for managing today’s workforce. Instead, we should understand our unique human abilities in the real-time narrative of how work gets done. This is the key to improving processes in a rapidly changing environment, because narratives connect real-time actions to outcomes. You find out not just what happened but how it happened. (And this is true for failure as well as success.)

Move HR from Administration to Analysis

HR has rolled out big data administration tools that make processes more efficient; the downside of efficiency is conformity to the way such tools are set up. In the name of uniform standards (to ensure fairness) they can burden with bureaucracy. HR is bringing data capabilities to strategic workforce planning, applicant tracking systems, learning management systems, and the rest; CHROs must shift their focus to the whole organization, not processes. Organizations need data about relationships, because that’s how work gets done.

Human-centric HR applications gather real-time behavioral and emotional data to identify, encourage, and highlight those human qualities. That happens when humans are interacting with each other, not machines.

The insights come when advanced analytics measure interactions, intentions, and emotions, and data analysis is already capable of doing this. Workhuman has a database of more than 50 million authentic work interactions among millions of employees around the globe based on social recognition, a narrative in which managers and peers notice, celebrate, and reward each other’s work behavior.

These interactions can be accurately correlated with many other data points like employee engagement, performance, retention, and trust. They can be correlated with innovation as measured by patents or development cycles. They can be correlated with customer data like acquisition, loyalty, and increasing revenue.

Measure the “unmeasurable”

Advanced data tools make measuring what happens even more powerful. For example, natural language processing can discover the best ways to communicate goals and priorities. It can uncover unconscious bias, such as in a manager who habitually recognizes women for “teamwork” and men for “leadership.”

Imagine a senior leader who is a terrific mentor, as evidenced by the number of employees who, under her guidance, outperform their peers. What makes her so good? In the past, you might call her a natural mentor. You might ask the people she mentors about their experience. You might hire a consulting firm to conduct a 360-degree study of her style.  

Instead of those steps, imagine you already had a narrative between that mentor and her employees based on social recognition – scores of moments when people described exactly what happened with her, advice and insights she gave, and encouragement she offered through the recognition program, emails, or communication apps. Analyzing the natural language of those moments enables you to learn such subtleties as:

  • Qualitative differences in the ways she mentors women and men
  • How her “arc of encouragement” works for new hires
  • How she differentiates between left-brain- and right-brain-dominant employees, and the ways in which she reinforced their strengths or balanced their weaknesses
  • When and how she guided people in their learning and career ambitions

What you learn can teach other managers to become better mentors, and, in turn, better leaders. It might raise awareness of implicit bias or gendered language. It would identify employees who were potentially great mentors in the future. This is a quantified yet profoundly human portrait of work interactions, beneficial to both culture and the bottom line.

Big Human Data

Using aggregate and privacy-protected data from some of the largest companies in the world, Workhuman research has learned what motivations drive results, even when that differs among countries and cultures. For example, a company that prides itself on a “winning” culture can learn how driven, competitive excitement manifests itself via recognition. Some high-performing teams will express that winning spirit as individual excellence, and others might celebrate team victories. Both live the “winning” value in their own unique ways – the opposite of conformity.  

Immense data-gathering and data analysis will continue. We are now capable of probing the nuances of human behavior and motivation via that data. As leaders, let’s develop the best of what data analysis has to offer – the power of our machines to help our organizations celebrate and honor what is most human.

(This post originally appeared in Forbes)

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About the Author

Eric Mosley

Eric Mosley is CEO at Workhuman.

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