On December 9, McKinsey Quarterly did a reprint of a 1995 article by Jay Forrester, who died on November 16, about system dynamics. As said in the intro to the article, Forrester “extended [feedback loops and other now-common techniques] from industrial operations to business strategy, employment cycles, social problems, and the fate of the world.”
For readers who are not familiar with the subject of system dynamics (hereinafter SD), SD is about modelling (typically non-technical systems) using the methods of ordinary differential equations. It is in particular applied to systems with elements of human decision-making and long time delays. See a causal-loop diagram of the situation facing COIN in Afghanistan produced by PA Consulting Group, below and to right (source: http://www.comw.org/wordpress/dsr/wp-content/uploads/2009/12/afghanistan-1300.jpg). Such diagrams are generally seen as great pedagogical tools, though the one below is on the complex side.
On a personal note, I like many other engineering-minded MBAs have always been intrigued by SD: i) I am engineer, with a degree in technical cybernetics and systems theory, and believe in the practices of engineering; ii) SD is just engineering practices applied to non-engineering phenomena; and iii) SD has proven and robust predictive powers, also in non-engineering domains (properly applied),
That said, SD has been and is controversial for a number of reasons: cross-disciplinary, sometimes obvious, sometimes counterintuitive (but correct), a technocrat’s solution to political issues, and often very complex. It nicely explains the Kondratieff cycle (in the National Model), though economists would claim that such cycles have been studied and explained by economists since 1925. It was the conceptual basis for Forrester’s book Urban Dynamics, which essentially and controversially stated that low-cost housing in certain areas in Boston increases poverty in same area, it does not reduce it. It was also the basis for Limits to Growth, which was commissioned by the Club of Rome, and included a large number of quantitative simulations of a world with exponential economic and population growth in combination with finite resources.
A most insightful and elegant attack on the complexity of SD was indeed delivered by NY Times in an April 2010 article about the same SD model as referred to above, though NY Times somewhat incorrectly framed the issue as a PowerPoint issue, rather than as an SD issue. Their heading was “We Have Met the Enemy and He Is PowerPoint”. (See the original article here: http://www.nytimes.com/2010/04/27/world/27powerpoint.html, and PA Consulting’s response here: http://www.paconsulting.com/afghanistan-causal-diagram/.)
Given the importance that for example McKinsey attaches to SD and Forrester’s work by republishing Forrester’s 1995 article, and given SD’s great predictive capabilities, also in in competitive situations, it is nevertheless a puzzle why SD is not more applied in the management consulting profession. One could for example use it to predict industry end game structures, supply and demand cycles, or technology adoptions; explore alternative policies for resource allocation across business functions; or optimize supply chains; all stuff that serious strategy reports are built of.
Before exploring this issue in more detail, I should say that it is not all bleak. I had in May 2015 the pleasure of attending a talk by John Stermann, Professor of System Dynamics and Engineering Systems at MIT, on “Interactive Simulations to Catalyze Science-Based Transformation” and the contribution of SD to “the implementation of sustainable improvement programs to climate change and the implementation of policies to promote a sustainable world.” And in Norway we have a local SD tools vendor, Powersim, and Dr. Jørgen Randers, one of the authors of the Limits to Growth study, is professor at BI Norwegian Business School. But again, regarding SD in business, we shall see that it has had limited impact on serious, hard-core strategic decision making.
Methodologically, I decided to approach the puzzle from three perspectives:
- Is SD taught at Norwegian universities?
- Is SD used in client engagements by major general consulting firms, say by McKinsey, BCG, Bain, PwC, Deloitte and PA Consulting?
- What are the fundamental reasons for the lack of interest in SD from the business community?
Questions (1) can be answered fact-based: If restricting ourselves to Norwegian universities, both BI Norwegian Business School and University of Bergen appear to have strong offerings in the area of SD, measured in terms of faculty and course offerings. The University of Bergen has indeed a Master’s programme on System Dynamics (see http://www.uib.no/en/rg/dynamics/73101/masters-programs-system-dynamics). Other Norwegian universities do not appear to have similarly strong offerings in this area, though they often appear to refer to SD in courses on for example dynamic strategy.
Question (2) can also be answered fact-based: Deloitte (after the acquisition of Systems Dynamics, Ireland in 2015), PwC, McKinsey; and PA Consulting appear to have or have had practices, but concentrated in a few locations, dependent on a few individuals, and coming and going with these individuals. McKinsey’s web site (including McKinsey Quarterly) lists only 12 articles including the term ‘system dynamics’, though I believe they used to use the term business dynamics. Regarding Bain and BCG, I have found limited traces of SD, though specific individuals may be using their SD expertise in their daily work. The above is corroborated by using advanced search on LinkedIn (# of current employees using key word ‘system dynamics’): Deloitte: 89; PwC: 62; McKinsey: 24; PA Consulting: 19; Bain: 9; BCG: 3. All caveats apply.
Question (3) is vexing: First, the complexity issue of SD is real, see the PA Consulting infographic above. However, no engineer would say that a fracture-mechanics based model of the development of a fracture in a weld in an oil pipeline should be simplified to make it more pedagogical, but less accurate. Indeed, there is an accepted and respected technical and scientific discipline called CAE (Computer-Aided Engineering), comprising FEA (Finite Element Analysis) and CFD (Computational Fluid Dynamics), which is all about simulating engineering phenomena in extreme detail, and routinely on grids of size 10-100 million nodes, which is about 100 000 times larger than the largest SD models I have ever seen in use. And CAE originated in the late seventies, while SD dates its origins back to 1961. The CAE community used 20-40 years to overcome initial scepticism from their more practically inclined engineering peers, but the SD community has more than 50 years after the origins of SD still not been able to convince the business community about its merits.
Second, some of the problems with SD may be linked to typical issues addressed or problems solved using SD. As an example, last issue of System Dynamics Review includes articles on: understanding decision making about faculty gender balancing; a competence development framework for learning and teaching SD; and quantifying the impacts of rework, schedule pressure, and ripple effect loops on project schedule performance. Not exactly the stuff that high-flier consulting careers are made of.
Third, a more fundamental issue is the modelling of future outcomes in continuous time and as many small decisions, and based on (at least partially) known mathematical relationships. Today’s business reality is that strategy value is typically generated in discrete time and concentrated in a few large bets characterized by competition, optionality, uncertainty and flexibility. In such situations, game theory, real options theory, or multi-player decision trees may offer better modelling frameworks.
But again, there are situations in business where SD provides deep strategic insight and actionable recommendations and for which there are no applicable alternative and equally valid theoretical frameworks (except that you may believe that you have genius gut feel and rely on that). Look for situations where you have already tried action A to improve metric M, only to see M deteriorate (= counterproductive policies) or strategies for evolving industry structures. Feel free to contact me at email@example.com if you believe that you are facing such situation and would like to explore the use of SD.
And if you just want to learn more about SD, there are a number of journals and blogs, see for example System Dynamics Review (of System Dynamics Society, see http://www.systemdynamics.org/) or SDwise (at http://sdwise.com/).
I wish all readers of CI Perspectives a Merry Christmas and a Happy New Year. And I commit to increasing CI Insight publication frequency in 2017.