Knowns and Unknowns: 4 Critical Planning Factors to Consider in the Age of COVID-19
Many of us are struggling right now to overcome worry and fear, both personally and professionally, adjust how we work and remake plans for the coming year. We are all striving to gain new footing in this chaotic world that no longer resembles what we saw only 3 or 4 months ago when we were originally polishing our plans for 2020. (Seems like a long time ago now, doesn’t it…?)
As we navigate unprecedented business shifts like we are currently experiencing, and remaking plans to navigate through this unfamiliar situation, the issue inevitably comes up: how to you plan in such an uncertain environment? As we all remake our plans for 2020 and beyond, I recommend reacquainting ourselves with the Donald Rumsfeld quote about Knowns and Unknowns (from 2013).
“There are known knowns; there are things that we know that we know. There are known unknowns; that is to say, there are things that we now know we don’t know. But there are also unknown knowns – there are things we do not know we don’t know.” Donald Rumsfeld
This framework can help structure our thinking to better enable us to navigate through this changing time and make proactive shifts in our plans. It’s a very different world in 2020 and will be for quite some time. Our recent (and on-going) experience with COVID-19 provides some useful insights and comparisons when revisiting our planning process.
As you rethink your plans for 2020 (and beyond) the uncertainty might seem overwhelming, so here is a way to organize your planning by categorizing the elements you are assessing in four groups of Knowns and Unknowns:
Known Knowns – The easiest category, these are the things you know, or the elements in your plan that if you make a change you know what the result will be. For example, you know how much you pay in rent, you might also know how long it takes to create something – but you also know if you make a change (perhaps having one less person available to work on that team) that it will a certain amount of time longer.
Known Unknowns – This is the next easiest, you can identify a factor to consider but perhaps can’t quantify it or know that you have incomplete or inaccurate information to quantify it. So, you might identify that element but be unclear about the scope of its impact. For example, you might know that having the entire company telecommute for social distancing purposes will result in less productivity and a slowdown of efficiency, but you may not know by how much your business might slow as a result.
Of course, once you telecommute for a period of time that Unknown will likely become Known. Other things may remain Unknown because it isn’t knowable now but will be at some point in the future or will remain Unknown because it isn’t in your control, like what interest rates will be in the third quarter of this year.
By definition planning elements that are Known are accounted for and you can proactively identify and plan for them even if you use a range of estimates or a best case/worse case scenario. Unknowns are much trickier.
And not part of Donald Rumsfeld’s original quote, but useful to include, Unknown Knowns. These are things that you might have overlooked or not included in the planning; information that might not have been communicated may cause these elements to not be considered. This could be as a result of communication gaps or resource bottlenecks, both internally or externally.
For example, in the US when the Center for Disease Control (CDC) originally distributed tests for COVID-19 it distributed 200 test kits (with each kit allowing testing of 300-400 patients) to more than 100 public health labs run by states and counties across the county. Each state got an equal number of test kits, which while fair and providing broad coverage, didn’t prioritize tests to regions that might be most severely affected. So, every state had tests that could be used – but not all states were impacted equally. Although the guidance was only to test those who had been in China (although the virus was silently being spread across entire communities), there was no feedback loop from the states to provide information on the number of visitors they typically got from China. As a result, states like South Dakota had an ample supply of test for anyone that needed to get one, states like Washington or New York who had more travelers from China and more community spread or higher population density never had enough tests. Those factors are elements that could have been considered in determining test kit distribution but weren’t because the CDC hadn’t accounted for the early detection differences in a rapidly spreading highly infectious virus versus a known slow-spreading disease with a low transmission rate. If someone had thought to ask the question how many visitors from China (or other countries) does each state have, the test kit distribution might have been done differently than an equal allocation.
Unknown Unknowns – The final category can be thought of as “Murphy’s Law” because in times like this if anything can go wrong, it will. If there is a point of failure that overrides all planning efforts this is it. The assumptions made here can create critical failure points. These can also be strengths that turn out to be weaknesses. Identifying these assumptions or potential points of failure by using theoretical scenarios and asking the question “Our plan failed, how did that happen?” can help identify these factors.
Again, using the COVID-19 test kits as an example. The CDC wanted to create its own COVID-19 detection test (separate from that developed and already being offered by the World Health Organization or WHO). The CDC test would be centrally managed through their labs in Atlanta and be highly accurate because COVID-19 is a new or “novel” virus which the world haven’t experienced before. The organization had successfully created its own test system several years earlier during an Ebola outbreak so had experience taking this approach. The COVID-19 test developed by the CDC is highly sensitive in detecting the virus so is more accurate, but more complicated to run and takes more time to deliver results than the WHO test.
When the original COVID-19 tests were delivered it quickly became clear based on results at the state level that the original tests were flawed, lacked critical components and delivered faulty results. Since the test kits were centrally controlled, it took weeks for the CDC to remanufacture and redesign the test kits and redistribute them. This was one unknown, not having a quality control process that ensured there wasn’t a single point of failure even in a centralized highly accurate lab. Next, because the US was under a public health state of emergency, any new testing lab had to be approved for emergency test processing by the Food and Drug Administration (FDA) which resulted in all state public health labs and private labs being blocked from running the tests until they went through a multi-week (typically it takes months) regulatory certification process. Because all tests from the states were sent to a centralized location resulting in multiple days before results were available. It also took additional time for development of automated versions of the COVID-19 test to increase the throughput in the labs. Because we hadn’t had a pandemic in recent history, we hadn’t considered different rules that prioritized speed of results in multiple locations for earlier detection over centralized consistency. As a result, although the first confirmed case of COVID-19 was confirmed in the US (in Washington state) on January 21st, by February 29th, only 472 patients had been tested nationwide, and 22 cases of COVID-19 confirmed.
By the time the new tests were in the field and multiple labs across the country were certified to run the tests using automated systems, valuable time had been lost and the public health landscape had dramatically shifted in the battle to slow the spread of COVID-19. Sounds like Murphy’s Law in action doesn’t it? Obviously, we now know that there were several Unknown Unknowns that may resulted in a very different outcome in the spread of COVID-19.
So, as you make shifts in your plans for the coming year amidst uncertainty in the age of COVID-19, make sure you track assumptions and elements in all four categories:
Known Knowns
Known Unknowns
Unknown Knowns
Unknown Unknowns
Hopefully using these categories will help in your planning process. This is the time to use creativity, broaden your planning group for more diverse input and information, question and use a lot of “what if” scenarios in your planning. Be nimble and communicate frequently as you are likely to shift your plans repeatedly this year. The only certainty in 2020 will be the need to continually change and refine our plans as we adapt in this ever-changing environment.
Additional Resources
If you are interested in reading some more articles about the COVID-19 tests and the rollout process here are some links:
https://www.newyorker.com/news/news-desk/what-went-wrong-with-coronavirus-testing-in-the-us