Why Managers Haven’t Embraced Complexity

This is the title of an article written by Richard Straub in the Harvard Business Review HR Blog. The notion of applying Complexity science to management has been around for over 20 years. So why hasn’t it caught on? Why are managers and leaders reluctant to see the world as it is: non-linear, turbulent, ambiguous, unpredictable, and uncertain? Straub offers 3 reasons:

  1. Managers don’t want to give up control. 
    Today’s dominating business paradigm is Systems Thinking and the control of information. Before that it was Scientific Management and the control of processes. Imagine the resistance put up by those not willing to give up Taylorism and accept emerging ideas like socio-technical systems, learning organizations, etc. Now systems thinkers who once fought an uphill battle to introduce their ideas are being asked to give up their control of information and don’t resist/deny/block but embrace emerging ideas like complexity, networks, cognition. Reluctant managers will eventually change because they will discover that their old methods can’t resolve today’s problems. “Keep at it, try harder” no longer works and becomes a waste of time.
  2. Technology isn’t powerful enough.
    In engineering school I was taught “When in doubt, make a model”. I later realized that students in business and economics were also told the same thing. So we learned early that models were useful to proxy the real world. We didn’t have powerful computers (only slide rules) to perform detailed calculations; therefore, we learned from experienced craftsmen and professionals the “rules of thumb” they successfully deployed. Fast forward to today and consider the computer horsepower we have to create mathematical models to handle real world complexity. The internet, big data analytics, cloud computing, supercomputers et al are rapidly changing the IT landscape. We now know how human sensor networks can turn stories told by humans into data points that can be analyzed and support better decision-making.
  3. The prospect of non-human decision-making is too unnerving.
    If we had infinite computer processing power, would we be able to create a precise model of a complex system such as Health Care? Aviation? Public education? Electric power industry? Physicist Murray Gell-man says no: “The only valid model of a complex system is the system itself.”
    Machines are designed to perform “work-as-imagined.” Because human designers can’t imagine everything, machines are limited in what they can do. Humans are the best agents in a complex system to deal with unknown unknowns, unknowables, and the unimaginable.

Straub makes the point there has been a gradual change in mindset, pushed along by the increasingly evident damage of narrow, simplistic thinking. Here we are 10+ years into the 21st century and note the number of industrial age ideas still being widely used. The public education system continues run on a factory model. Health care remains using a craft model.

The movement from Safety-I to Safety-II hasn’t happened as quickly as we had hoped. In the latter case, perhaps by embracing complexity and applying ideas like the Cynefin framework and narrative inquiry, we will be able to accelerate the operationalizing of Safety-II.

Click here to read the Richard Straub article.