I can’t think of a more difficult situation for a leader than having to deal with the unthinkable: A pandemic. A devastating hurricane. An unprecedented economic or political crisis.
Over the past few weeks we got a feel for that as we watched leaders in the COVID-19 crisis try to predict the course of the pandemic and figure out the immediate needs.
In my career in the communications industry, which is an essential public service, I’ve dealt with plenty of crises: hurricanes, floods, tornados, wild fires, economic and political crises, and even the H1N1 pandemic when it swept through the U.S. in 2009.
Using my experience, in my prior LinkedIn article I discussed the importance of uniting people during a crisis. In this post I want add to that; this time focusing on decision-making during a crisis.
At the onset of a crisis, one of the biggest challenges for a leader is to make decisions in the absence of sufficient accurate data.
Yes, we’ve seen an abundance of predictive models from day one. But we’ve also seen them project vastly different scenarios, making decision-making even harder.
That’s because models are just that—models.
They are statistical calculations based on assumptions. And assumptions can vary* dramatically from one source to another, especially at the beginning of a crisis when there hasn’t been enough time to curate the data.
That is what made it so difficult in the early stages of the COVID-19 pandemic to accurately predict the number of potential cases and, in turn, the number of hospital beds, ventilators, and ICU units that would be needed.
I faced a similar situation when Hurricane Andrew threatened the U.S. in 1992, when as Operations Manager – North Dade for BellSouth, I faced decisions that could dramatically impact the damage the hurricane would have on our operations.
As the storm approached South Florida my team looked at historical data and the predicted models for the storm path. At the time there were eight different models.
Four of those models predicted Andrew would head south of the 25th parallel, whereas the other four models saw it going north. If the storm were to go north or south of the 25th parallel, we would likely be spared a direct hit.
In the end, Andrew followed none of the predictions. Instead, it made a 90-degree turn and traveled straight west along the 25th parallel, hitting South Florida head on.
This is an example of why, in my view, when faced with vastly diverging or conflicting forecasts, your best bet is to plan for the worst-case scenario.
It’s what I did at that time. I decided to move our fleet of repair and installation trucks to a safer spot inland. That way, once the storm had passed, they were ready to be deployed back to begin reconstruction. Other organizations decided otherwise and suffered the consequences when their fleets were severely impacted.
The full crisis cycle
Up until now I’ve been focusing dealing with a crisis at its onset. Dealing with the full cycle, however, can take weeks and months. In my experience, the best way to handle the full cycle is through a framework involving a continuous loop of assessing, planning, communicating, and monitoring during the crisis. I’d like to share it with you in a summarized version.
- First, you must calmly assess the situation and determine the brutal facts so you can make decisions based on facts. (One of these brutal facts may be that you won’t have accurate data for a while. In that case, as I mentioned earlier, you must begin executing the first steps of your worst-case scenario until you have more accurate data.)
- Then, based on those brutal facts, you must anticipate the near-term outcomes and develop a plan to deal with them.
- Next, as I discussed in my previous article, you must make sure everyone is aligned and committed to that plan.
- And finally, for the duration of the crisis you have to monitor your plan and adjust it on a daily basis because things are likely to fluctuate. Also, as sufficient accurate data becomes available, models will begin to get more reliable, which will allow you to make the appropriate adjustments to your plan.
The bottom-line is that, as the leader of an organization during a crisis, you’re going to have to make decisions without all the accurate data, using predictive models built on data that has not yet been curated. The good thing is that models are going to get better over time, but at the onset you’re not going to be able to wait to make a decision.
All of that points to the need for you to be really agile and quick on your feet to adjust to the current reality, which is likely to change from day to day, even hour to hour in some cases.
Resilience wins over time
We’re living through turbulent, uncharted times; times that are difficult for leaders and for everyone else.
But I firmly believe that humans are very resilient.
History proves that no matter what obstacles we face, no matter what difficulties we encounter, we human beings are very resilient. That makes it possible for us to reinvent ourselves and our businesses, and continue to move forward.
This crisis is no different.
What we’ll learn from this experience will help us prepare for the next crisis – not only for us but also for the young people who are watching us deal with the unthinkable and emerge from it stronger than we were before.
[*] For an interesting article on the impact of different assumptions on the COVID-19 models I suggest reading “Why It’s So Freaking Hard To Make A Good COVID-19 Model”by FiveThirtyEight.