Combatting COVID-19 is fast becoming the greatest challenge of our time. While we don't yet know exactly what it will take to succeed, a wealth of knowledge exists from around the world that is ripe for the picking.
But how can we organize that information to extract viable solutions? We have spent the past several years creating highly versatile methodologies to solve complex problems that are not only apt for fighting COVID-19, but also applicable across all disciplines.
Easy as one, two, three
Solving complex problems is a three-step process: frame, ideate and decide (Figure 1).
When framing, you decide what the problem is and equally important, what it isn’t. You then summarize this in a situation–complication–question sequence, that gets to the essence of the
In the ideating phase, you brainstorm alternative answers — options — to your key question. Here, drawing an option map can help you expand and organize the universe of possibilities.
In the last step, you consider what is important in the options — your criteria — and rate them on each criterion. This helps you identify which option offers the best tradeoffs.
When it comes to the framing and deciding steps of the fight against COVID-19, it isn’t necessary to reach a consensus among all stakeholders. Which is good news, considering the sheer amount of people affected by the illness worldwide. However, harnessing the wisdom of such a large crowd can be particularly helpful in ideating.
Ideas to fight COVID-19 are surfacing across the globe but remain unknown to other people who might also benefit from them. For instance, after reading that a startup in Italy was using 3D printing to make ventilators, someone in another country asked how he could help local hospitals using his own 3D printer. Organizing and concentrating knowledge can be useful, and that’s exactly what an option map can do.
To record this knowledge, we asked people for ideas and organized them into a map (see Figure 2). Our efforts are ongoing and the process is challenging, but immensly rewarding.
Gaps, overlaps and option maps
Good option maps obey four rules: they answer a single type of question, proceed to potential options, contain mutually exclusive (ME) and collectively exhaustive (CE) branches, and are insightful. The first two are reasonably straightforward but the last two rules make the exercise difficult.