The Embarrassment of Complexity
October 11, 2013 Editor 0
Roger Martin recently diagnosed a kind of complexity that is manufactured by us and largely unaddressed: inter-domain complexity. It comes about as fields of knowledge are segmented into multiple domains, and each domain develops deep algorithmic knowledge and specialized tools that work by ignoring many of the variables actually in play. Martin notes that the difficulty of reintegrating such simplified and divided disciplines is what gives us the feeling, when we look at any large, adaptive system, of being overwhelmed by massive, un-addressable complexity.
If inter-domain complexity exists, the biggest problem it poses stems from our lack of ability to connect the real detail complexity that underlies everything, across domains. While we can never hope to obtain, to quote Murray Gell-Mann (one of the great complexity thinkers of our time), more than “a crude look at the whole,” we can work to improve one of the crucial preconditions to tackle inter-domain complexity. This is our ability for integrative thinking.
Martin, quoting Peter Senge, refers to the problem that in situations of dynamic complexity, the links between causes and effects are “subtle.” The challenge is not so much to make progress in turning these subtle links into more precise ones. This is at best a necessary, but not a sufficient precondition. The truth is that complex systems are beset and energized by a phenomenon called non-linear dynamics. In other words, what produces complexity is not so much the presence of many direct cause-effect links which operate with subtlety versus precision, but rather the presence of indirect, non-linear relationships between the variables, parts, and dimensions of the whole. What make complex systems so complex, therefore, are their multiple feedback loops and their indirect cause-effect relations which, moreover, play out at different speeds and on different time scales.
These are the reasons that we arrive at what I am calling “the embarrassment of complexity” – when it dawns on us that the categories we normally use to neatly separate issues or problems fall far short of corresponding to the real world, with all its non-linear dynamical inter-linkages.
So how do we move beyond this embarrassment? Can we reach out across different domains to achieve some kind of synthesis, synergy, and perhaps even synchronicity in the ways we perceive, analyze, and interpret the world? Note that the “syn” in all those words comes from the Greek for “together.” Integrative thinking offers both the ability to see things together, by recognizing patterns that bind together the parts, and a way of sharing with others is what is at stake.
We should begin by recognizing something that has made our embarrassment much more acute in the past decade. We have come to rely much – too much? – on instruments and tools that a dynamic information and communication technology sector, drawing on all the research that preceded and accompanies it, has bestowed on us. Computers and the modeling that can now be done through them have become indispensable for the financial sector and the real economy; for the military; for moving people, goods, and ideas across the globe. They permit us to collect, process, store, and transform the new precious raw material of our age: information.
But there is an indisputable downside to this growing digital reliance: the lower priority placed on training, cultivating, and rewarding independent human judgment – which we must retain if we hope to master the tools we have created instead of being mastered by them.
When decision-support tools become too powerful and ubiquitous, when continuous monitoring, benchmarking, ranking, and other performance technologies allow governance by numbers to take over, the human faculty of independent judgment takes a backseat. Don’t get me wrong: of course, indicators, curves, algorithms, and the analyses based on them are vital. But all must still be interpreted. Figures speak for themselves only to those who understand how they have been constructed and in which context they are to be used.
Faced with the densely compressed information that numbers, algorithms, and indicators offer, managers increasingly tend to rely on what they suggest as action to be taken – sometimes, as the financial crisis so dramatically demonstrated, to our great peril. Time-starved administrators, policymakers, and decision-makers grow less confident to challenge them. Even if they know all the caveats, flaws, and imperfections of these tools, they are overwhelmed by their apparent objectivity, availability, and time-saving utility.
Indeed, given this plethora of benefits, human subjective judgment begins to look like a quaint, if not obsolete, survival trait of human evolution.
And it’s no wonder, then, that indicators and related numerical instruments take on a life of their own. Their promised utility seems beyond doubt: they do reduce complexity. Their power stems from their ability to make people perform in the way in which the goals of their performance have been set.
Yet such numerical complexity reduction has unintended consequences. It leads to a certain kind of conformity in thinking and in how people see and interpret the world. The ability to induce independent human judgment in young minds becomes ever more rare in our educational systems. Overwhelmed by the increasing reliance on computational instruments, our faculties to discern, to raise critical doubts, to judge between alternative interpretations, are devalued and they deteriorate.
Let us be clear: No human group can survive, let alone effectively cooperate, without being able to develop a shared outlook on the world which is the precondition for acting together. But it is also the case that social groups thrive by making room for plurality, dissenting voices, and different perspectives. This is why management continues to advocate diversity as integral part of any successful organization. This is why what I call competent rebels are needed everywhere: individuals who are able to combine professional capabilities with the fresh, challenging outlook required for progress.
Confronted with the embarrassment of complexity and faced with the challenge of overcoming inter-domain complexity, let us remember that integrative thinking does not spring out of models, indicators, or computer graphs, unless we put it into them. It requires the ability to combine parts of the whole, however crudely, into an approximation of the look at the whole which we will never see entirely. It requires us to draw on the faculty of human judgment to focus on the smaller picture in order to comprehend the larger one.
This post is part of a series of perspectives leading up to the fifth annual Global Drucker Forum in November 2013 in Vienna, Austria. For more on the theme of the event, Managing Complexity, and information on how to attend, see the Forum’s website.
- Africa: How Complexity Science Can Get Aid Working
- Interpreting Innovation Dynamics with Complexity Theory
- Supporting creativity through knowledge integration during the creative processes. A management control system perspective
- Africa: The Value and Challenge of Complexity Science
- Africa: The Value and Challenge of Complexity Science
- Intellectual Capital in the Caribbean Hospitality Industry: Two Case Studies
Subscribe to our stories
- Digital transformation in the banking sector: surveys exploration and analytics August 3, 2020
- Why Let Others Disrupt You? Take the Smart Self-Disruption Journey! August 3, 2020
- 5 Tips for Crowdfunding During the Pandemic August 3, 2020
- innovation + africa; +639 new citations August 3, 2020
- SME Innovation: 10 Priorities for Support Post-COVID-19 July 7, 2020