Coronavirus: complex problem-solving in action (Part 3)
The foggy reality of implementing solutions
This post follows from Part 1 and Part 2 and continues examining the Coronavirus pandemic from a problem-solving perspective. As the pandemic appeared and unfolded, the first two parts looked problem discovery and solution identification. This part looks at the realities of implementing solutions for complex problems.
Strategy ≠ Execution (it’s complicated)
Given the huge social, health and economic implications of Coronavirus pandemic, this was a complex problem that needed to be solved. In complex problems, the cause and effect cannot be deduced. With time and through expert analysis, enough clarity emerges to make cause and effect knowable or relatable. Using Cynefin parlance, the problem is now relatively more “ordered”. It can be solved within this domain or “reduced” further until it becomes a simple problem.
COVID-19 aka the novel Coronavirus, quite literally presented a novel problem, challenge and threat to the world. Given its scale, impact and novelty, it was a complex problem by every definition. Over time, this complex problem was “reduced” to a problem that could be “solved” by available resources (health system) using best practices based on an established paradigm (inoculation) and strategy (vaccine).
Having a strategy is not enough. Execution or implementation is where the rubber hits the road. It’s the phase where success or failure is determined.
Take the vaccination drive. Only a handful of countries who have developed the vaccine. Others, which include many prominent and developed nations, have been unable to do so. This immediately makes them rely on vaccine developers for supply, thereby reducing implementation capability. The second determinant of effective implementation is speed. The United States has been the worst hit nation but with locally manufactured vaccines, it seems to be proceeding at speed in vaccinating its people. At the other (extreme0 end, New Zealand, despite its isolation and border closures giving it an early and sustained edge in the fight against Coronavirus has had a slow vaccine rollout. At last report it placed around 122 in the world per capita. In fact, in one day alone India vaccinated more (8 million) people than the population of New Zealand (5 million). The point of the comparison is to show the importance of speed.
Fog of action
For complex problems, and particularly those with massive impact, once the best possible solution has been determined — and established, speed becomes crucial in realizing the solution. Before the vaccine was developed, containment was the key measure. Now, inoculation “cover” is the key measure. How badly a country was hit is a matter of the past. The pressing matter is how fast it can recover — i.e., how fast the vaccination drive can help develop a bulwark going forward.
There is also a risk of being stuck in no-man’s land — temporarily at least.
As countries roll out vaccines, some are experiencing outbreaks of new variants. To control them, some countries have resorted to snap lockdowns. We started with a complex medical problem. Lockdowns were imposed to help relevant authorities sense the problem better. The upside was buying time and controlling wild spread. The downside was that a complex medical problem was now converted into a complex economic and medical problem. Vaccine development brought the problem back into the medical paradigm, from where it could be controlled. Having lockdowns so far down the problem-solving lifecycle, brings back the economic dimension, adding further complexity. We can find ourselves operating at various stages of a problem-solving lifecycle — simultaneously, which brings its own challenges.
Even at the best of times an effective strategy cannot guarantee effective execution. In complex problems, the line of sight between strategy and execution is blurred due to various practical hurdles and the dynamic nature of these problems.
In terms of the problem-solving lifecycle, we are in the solution implementation phase. However, as gleaned from the pandemic responses, this phase is presenting its own challenges.
The difference between strategy and execution is particularly pronounced for complex problems. Complex problems are dynamic and this poses additional execution hurdles. The dynamic and peculiar nature of complex problems make them akin to a maze house with lots of stairs, trapdoors and unexpected twists. Just when we have sussed out one part and reached what seems like the end, another maze is probably lying-in wait. When it comes to complex problems, strategy and execution prove to be rather non-linear concepts.
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