This is a cross-post from the HBR written by Richard Straub, and is one of a series of perspectives that will be published leading up to the fifth annual Global Drucker Forum in November 2013 on the theme of Managing Complexity.
Nobody would deny that the world has become more complex during the past decades. With digitization, the interconnectivity between people and things has jumped by leaps and bounds. Dense networks now define the technical, social, and economic landscape.
I remember well when the idea of applying complexity science to management was first being eagerly discussed in the 1990s. By then, for example, scholars at the University of St. Gallen had developed a management model based on systems thinking. Popular literature propagated the ideas of complexity theory — in particular, the notion of the “butterfly effect” by which a small event in a remote part of the world (like the flap of a butterfly’s wings) could trigger a chain of events that would add up to a disruptive change in the larger system (such as a hurricane). Managers’ eyes were opened to the reality that organizations are not just complicated but complex.
Why did this interest and work in complexity not lead to major changes in management practices? There are, I think, a few major reasons that it didn’t — and that also suggest that the overdue change might now finally take place.
Complexity wasn’t a convenient reality given managers’ desire for control.
The promise of applying complexity science to business has undoubtedly been held up by managers’ reluctance to see the world as it is. Where complexity exists, managers have always created models and mechanisms that wish it away. It is much easier to make decisions with fewer variables and a straightforward understanding of cause-and-effect. Here, the shareholder value philosophy, which determines so much of how our corporations operate these days, is the perfect example. Placing a rigid priority on maximizing shareholder returns makes things clear for decision-makers and relieves them of considering difficult tradeoffs. Of course we know that constantly dialing down expenses and investments to boost short-term margins inevitably damages the long-term health of the company. It takes a complexity approach to keep competing values and priorities and the effects of decisions on all of them in view — and not just for management, but equally for investors, analysts, and regulators.
Technology was not yet powerful enough to capture much complexity.
When systems thinkers and theorists turned their attention to economies and organizations in the 1980s and 90s, the tools simply did not exist to model their workings at a level that would yield practical insight. Now, the exponential increase in computing power and the progress in mathematics and statistics have propelled us into a new era. With the ability to draw on data bases and map networks at scales that were unthinkable before, we can hope to understand communication flows through large organizations, and the impact of disturbances and managerial interventions on these flows.
The prospect of non-human decision-making is unnerving.
More recently, with the surge of computer processing power, another nagging concern has formed in some people’s minds. Does the fact that massive computing power is required for systems-level comprehension mean that the interpretation of information, sense-making, and learning will become “extra-human” activities? Will the computer take over the role of the knowledge worker? Will we soon reach a tipping point when human brainpower is obsolete? Some technophiles (many of them inspired by Ray Kurzweil’s ideas) respond to questions like this with a resounding yes. Yet for most of us it is a disturbing thought, because we have seen so many of the models designed to predict the future state of complex systems (from economies to climates) fall short of accuracy, to say the least.
The eager futurists talking about machines taking over evaluation of situations and decision-making have set back their own cause, as others see them ignoring an essential fact: sense-making is always informed by values. The idea that we might look for value judgments from algorithms is just badly flawed. But fortunately, the recognition is growing that, while computers can provide us with enormous extensions of our storage and processing capacity, they must and will remain only inputs to human brains, where the ultimate evaluation and deliberation must continue to take place. Think of the brain as our own “complexity processor” and itself our most complex organ: It helps us to address complex issues and yet come up with seemingly simple solutions. Those are made possible when we unconsciously see through the myriad of information elements that are stored in our brain as raw material to build meaningful patterns, or the famous “big picture” that humans can develop best.
The recognition of complexity is at its core a view of the world that that makes us more humble and more open. It is the awareness that too often our interventions will not achieve what we wanted and we will be shocked by unintended consequences. (The fact that, following the creation of the Cap-and-Trade Carbon Emission Scheme as a clever new artificial market, more coal is being burned in Europe than before is a mind-boggling example.) At the same time, it is the acknowledgement that simplistic “can do” thinking and linear approaches in organizations and markets, which are by definition complex, won’t be sufficient. And it is the prod to us to better understand why.
There has been no watershed event to make it true that managers will apply complexity science to their work today, whereas they could not, or would not, yesterday. Rather, there has been a gradual change in mindset, pushed along by the increasingly evident damage of narrow, simplistic thinking. The toolkit that allows us to understand the dynamics of large systems has continued to evolve. And the reassuring truth has been reasserted that, on top of the logic of algorithms, human values and judgment are essential.
Managers, I think, should now get ready to face the full complexity of their organizations and economic environments and, if not control them, learn how to intervene with deliberate, positive effect. Embracing complexity will not make their jobs easier, but it is a recognition of reality, and an idea whose time has come.
