Are We Returning To Scientific Management, But With AI As Its Stopwatch?

I am deeply worried about the future of work. As the founders of Columinity, Barry Overeem and I frequently talk to people in leadership positions across large (European) enterprises about how they use data to support teams and their business.

A disturbing trend in the use of AI and productivity metrics

We’ve noticed a disturbing trend in recent months. More and more, higher management is pursuing tools that use Artificial Intelligence (AI) to analyze mostly individual-level productivity metrics (git pulls, code commits, code reviews, lines of code, work items completed, emails sent/answered, lead time, bug count, engagement in online meetings) over holistic value-oriented, team-based metrics.

I can understand this to some extent from a business perspective. The Return on Investment (ROI) of individual-level productivity metrics comes down to “pushing individuals to work harder and produce more”, which is an easier business case to make to management and their shareholders than the fluffier notion of investing in teams and individuals and hoping they’ll produce better outcomes. It is rational from a capitalist perspective.

A return of scientific management, with AI as its stopwatch?

It feels like we’re revisiting the concept of scientific management that was spearheaded by Frederick Taylor during the later parts of the industrial revolution. But instead of the productivity observers with stopwatches as a form of middle management, we now get AI pattern recognition to analyze individual productivity patterns. Just like scientific management, the various AI-based tools cleverly emphasize “workflow optimization” and “work efficiency” as their aim, and cleverly mask the elephant in the room: individuals will be singled out based on their productivity.

Haven’t we learned from everything that came after scientific management that such a cold, rational and mathematical approach only dehumanizes the workplace, destroys motivation, burns people out and harms teamwork? My field of study, organizational psychology, emerged in response to scientific management and put emphasis on human factors in the workplace. Through a myriad of empirical works, it showed how our social work context shapes high-quality outcomes through factors such as motivation, teamwork, leadership, engagement and autonomy. A relentless focus on individual productivity, now encouraged at scale by AI-assisted tooling, completely ignores this inherently human part of the workplace and undermines trust, teamwork and cohesion.

How to counter this?

Honestly, I don’t know. I don’t see a strong modern counterweight to this disturbing trend. Labor unions were able to mitigate some of the negative effects of scientific management when they emerged during the 18th century, and strong protection of employees and their privacy was enshrined in law in many countries — particularly in Europe. But the power of labor unions has diminished and the protections by laws are increasingly loosened under the lobbying of powerful companies and ever wealthier business owners.

All I can do is provide more ethnical alternatives on a smaller scale. Our company The Liberators has offered Liberating Structures and other forms of employee engagement strategies as better ways to improve the workplace. Columinity is built on the notion that being effective— happy employees, happy stakeholders — is more important than being productive — at any level of the organization. Columinity also begins any analysis at the team-level, and simply does not track individuals. But I admit that we’re also struggling to get higher management to see why this is so important compared to productivity-focused alternatives.

I have to admit, it is disheartening for Barry Overeem and me to see how fast this is changing and how easily scientific management is re-entering the workplace under a new, high-tech guise.

P.s. I wrote the above as a personal reflection on a number of recent experiences. This is not at all a scientific piece.