Systems Thinking
Systems Thinking is a practice that differs from the norm of reductionist, linear thinking that we learn from as early as kindergarten. In school, learning is broken into English, Math, and Science. This reductionist thinking is further perpetuated by the hyper specialization that tends to occur as we pursue degrees and embark on a career in corporations organized around many silos: human resources, finance, sales, and production.
Systems Thinking is a set of practices and tools that allow us to understand the connections between these various parts, in an effort to improve the whole. It includes an emphasis on bringing people with various perspectives together. This might manifest in inviting a gang member to a discussion about youth violence or a lowly lab technician to a discussion of next year’s investment strategy or an employer to consider strategies for improving population health. It also includes supporting this broad group of players with visual tools and techniques so that they can build a more holistic understanding of the whole together, surfacing and sharing individual mental models for a better understanding of the system, and unleashing creativity around interventions options to achieve a goal.
While traditional problem-solving techniques like Lean, TQM, and Six Sigma tend to break down the parts and focus on fixing those that seem to be causing the most trouble, Systems Thinkers seek solutions in understanding the whole. For example, an environmental testing company facing a report quality problem could use Six Sigma process to identify those people who generate poor reports and invest in training them OR it could apply a Systems Thinking lens and understand that their strategy of 40% year over year growth was leading them to outgrow the capacity of their space and people resulting in poor working conditions, overwork, and disgruntled employees – something that would be exacerbated by throwing in more training time.
There are two primary tools for applying a Systems Thinking lens to a challenge. The first tool is a causal loop diagram – which is a drawing that describes cause and effect in a system. An example of one used with a client is below:
This cause and effect diagram is not linear like an Ishikawa (fishbone) diagram, but includes feedback which is critical to understanding how a system will change (or not) when we intervene in it with a new strategy. As in the example above we can assume that training will lead to product quality (linear), but that would be an oversimplification. The system is more complex and can be described as a series of causal loops: sales efforts leading to significant growth (R1) is leading to a heavy workload and eroding product quality, potentially threatening customer satisfaction (R5) this leads to rework which is increasing the workload further. Training, if instituted, would increase workload as well, further exacerbating a problem which is leading everyone to consider other employment options, thwarted only by a poor economy. Should they quit, new hires will require even more training (exacerbating workload) making the problem worse (R7). The company was resistant to investing in space and people, which was believed to be the appropriate path to alleviate the problem. This type of causal map can be developed virtually or live with a multi-stakeholder group and used to develop improved strategies for change in a two-day workshop. Through participation in the process leaders can see the whole and build commitment to real change.
A second tool of Systems Thinking is computer simulation. The system described in the causal loop diagrams can be quantified and developed into learning laboratories that can be used to explore the likely effect of strategies under consideration. Examples of widely used models that are accessible to all include the ReThink Health Dynamics Model which allows regions in the United States to explore strategies to improve population health, the Climate Interactive C-Roads Model that is used by world climate negotiators to determine if country commitments will achieve desired global temperature, and the Climate Interactive En-Roads model which allows policy makers to explore strategies for achieving the commitments of the Paris Climate Agreement. These simulators can be used to more rigorously test the mental models developed during a causal mapping session.
