Guru Madhavan, a National Academy of Engineering senior scholar, has a new book about how engineering can contribute to solving society’s most complex and intractable problems. He published a related article* on the National Academies website. The author describes four different types of problems, i.e., decision situations. Importantly, he advocates a systems engineering** perspective for addressing each type. We will summarize his approach and provide our perspective on it.
He begins with a metaphor of clocks and clouds. Clocks operate on logical principles and underlie much of our physical world. Clouds form and reform, no two are alike, they defy logic, only the instant appearance is real – a metaphor for many of our complex social problems.
Hard problems
Hard problems can be essentially bounded. The systems engineer can identify components, interrelationships, processes, desired outcomes, and measures of performance. The system can be optimized by applying mathematics, scientific knowledge, and experience. The system designers’ underlying belief is that a best outcome exists and is achievable. In our view, this is a world of clocks.
Soft problems
Soft problems arise in the field of human behavior, which is complicated by political and psychological factors. Because goals may be unclear, and constraints complicate system design, soft problems cannot be solved like hard problems.
Soft problems involve technology, psychology, and sociology and resolving them may yield an outcome that’s not the best (optimal) but good enough. Results are based on satisficing, an approach that satisfies and suffices. We’d say clouds are forming overhead.
Messy problems
Messy problems emerge from divisions created by people’s differing value sets, belief systems, ideologies, and convictions. An example would be trying to stop the spread of a pathogen while respecting a culture’s traditional burial practices. In these situations, the system designer must try to transform the nature of the entity and/or its environment by dissolving the problem into manageable elements and moving them toward a desired state in which the problem no longer arises. In the example above, this might mean creating dignified burial rituals and promoting safe public health practices.
Wicked problems
The cloudiest problems are the “wicked” ones. A wicked problem emerges when hard, soft, and messy problems simultaneously exist together. This means optimal solutions, satisficing resolutions, and dissolution may also co-exist. A comprehensive model of a wicked problem might show solution(s) within a resolution, and a dissolution might contain resolutions and solutions. As a consequence, engineers need to possess “competency—and consciousness— . . . to develop a balanced blend of hard solutions, soft resolutions, and messy dissolutions to wicked problems.”
Our perspective
People form their mental models of the world based on their education, training, and lived experiences. These mental models are representations of how the world works. They are usually less than totally accurate because of people’s cognitive limitations and built-in biases.
We have long argued that technocrats who traditionally manage and operate complicated industrial facilities, e.g., nuclear power plants, have inadequate mental models, i.e., they are clock people. Their models are limited to cause-effect thinking; their focus is on fixing the obvious hard problems in front of them. As a result, their fixes are limited: change a procedure or component design, train harder, supervise more closely, and apply discipline, including getting rid of the bad apples, as necessary. Rinse and repeat.
In contrast, we assert that problem solving must recognize the existence of complex socio-technical systems. Fixes need to address both physical issues and psychological and social concerns. Analysts must consider relationships between hard and soft system components. Problem solvers need to be cloud people.
Proper systems thinking understands that problems seldom exist in isolation. They are surrounded by a task environment that may contain conflicting goals (e.g., production vs. safety) and a solution space limited by company policies, resource limitations, and organizational politics. The external legal-political environment can also influence goals and further constrain the solution space.
Madhavan has provided some good illustrations of mental models for problem solving, starting with the (relatively) easiest “hard” physical problems and moving through more complicated models to the realm of wicked problems that may, in some cases, be effectively unsolvable.
Bottom line: this is a good refresher for people who are already systems thinkers and a good introduction for people who aren’t.
* G. Madhavan, “Engineering Our Wicked Problems,” National Academy of Engineering Perspectives (March 6, 2024). Online only.
** In Madhavan’s view, systems engineering considers all facets of a problem, recognizes sensitivities, shapes synergies, and accounts for side effects.
