Complexity and Knowledge Management Navigators…
There has been a significant shift in thinking over the last 3 years or so that has seen the emergence of natural science as a key informant in the development of business systems (e.g. see the emergence of eco-finance, based on the management of natural ecosystems, such as the Great Barrier Reef, as a way to holistically manage/assess risk). This is nothing new to those of us that have been engaged in systems thinking; links between Bertalanffy, autopoiesis (and its evolution to include social autopoiesis), second order cybernetics, Stafford Beer and a general shift to soft systems via Churchman, Ackoff and Checkland.
As managers come to terms with the increasing complexity of their environment they cannot avoid discussions around complex adaptive systems. It is uncomfortable, a seismic shift from the reductionist roots of a twentieth century weed that plagues university undergraduate/postgraduate business programmes (this weed takes time to kill off and, unfortunately, reductionist thinking appears to dominate the vast majority of management thinking, even today), but the banking crisis of 2008 has perhaps finally sounded the death knell for such antiquated thinking. Eco-finance is perhaps a good example, where risk, instead of being treated in isolation, is being assessed against the whole, weighted against the connectedness of the constituent parts and assessed not only in terms of immediate reaction, but future consequences. This thinking is being aided by natural scientists who are working with the banking sector to share lessons learned from the management of natural complex eco-systems. Another signal of the shift that is occurring is the emergence of Integrated Reporting in the field of accounting, not necessarily for the environmental credentials it champions, but for the transparency required by such a process, its assessment of the whole and the context against which that assessment takes place (past actions, current performance and the implications for the future); it does not take a leap to move thinking towards the management of knowledge resources, where future value is tied to past practice and current management.
Before progressing, I need to be clear, the following is conceptual and is not meant to present a detailed scientific position on the links between the concepts under discussion.
There are many lessons to learn from natural science, but I want to focus on one in particular, ‘The adaptive cycle’, which I believe links well to the need to innovate and diffusion of innovations theory. There has been enough discussion on the nature of the Knowledge Economy and the way in which product/service life-cycles are being truncated; the need for ongoing development/innovation being heated by ever increasing connectedness and, as a consequence, diversity – leading to the need to increase interdependency, in order to develop the internal diversity required to match the diversity in the external environment.
Diffusion of innovations Theory tells us that managers need to make sense of their environment, to constantly seek feedback, in order to know when to jump, to reinvent, before the organisation’s fit with the environment drifts to the point where it will begin to experience failure. Eco-system thinking, linked with systems thinking and economics, explains the ability of a system to adapt (linked to the connectedness (flexibility/rigidness) of internal controlling variables and the vulnerability of the system to unexpected shocks) via the ‘adaptive cycle‘ (CS Holling), which sets out a pathway for ‘growth’, ‘release’ and ‘renewal’ in complex eco-systems.
A stylized representation of the four ecosystem functions (r, K, , ) and the flow of events among them. The arrows show the speed of the flow in the cycle. Short, closely spaced arrows indicate a slowly changing situa- tion; long arrows indicate a rapidly changing situation. The cycle reflects changes in two properties: the y axis (the potential that is inherent in the accumulated re- sources of biomass and nutrients) and the x axis (the degree of connectedness among controlling variable). The exit from the cycle indicated at the left of the figure suggests, in a stylized way, the stage where the potential can leak away and where a flip into a less productive and less organized system is most likely (Holling 1986).
Taking a blended view from these two approaches can lead to an interesting landscape for discussion (see above), in terms of managing controlled destruction (a jump or controlled shock) within a complex system in order to renew/reinvent/reorganise in order to maintain growth.
In attempting to make sense of complexity and debates around resilience, it can be good to take time, to pause, and reflect on models that can help make more sense of the environment we find ourselves in. More importantly, it is good to acknowledge that we need help, to look over our limited horizons and learn lessons from complimentary disciplines.
For those interested in further reading: Understanding the Complexity of Economic, Ecological, and Social Systems, C. S. Holling, Ecosystems (2001) 4: 390–405
Check out our next KM Course (Resilient Knowledge Management Practice) in Slough, August 12th – 16th 2013 (Stage 3, Advanced)
Check out ‘Operation Punctuated Equilibrium’ (Resilient Knowledge Management Practice) in Edinburgh, October 24th – 25th
www.punctuatedlearning.com (a real time simulation environment)