DMAIC and Covid-19

The response to covid-19 has been questionable from day 1. To me day 1 was March 16, 2020 when “15 days to flatten the curve” began in the USA. In the context of a Lean Six Sigma improvement activity the stated goal of the improvement activity was to reduce the peak number of covid-19 cases so that the healthcare system and frontline healthcare workers would not be overwhelmed by the forecasted number of covid-19 patients. Unlike Lean Six Sigma there was no preliminary research into why this forecast was believed. We were told that there was no time for collecting additional information. Every day we spent on data collection equated to thousands of lives lost. In the face of such rhetoric less calm heads prevailed. It was leadership based on fear, rather than on sound data.

I guess we got what we deserved. The lack of direction and leadership continues to this day, some 87 days later. The debate over what we did, what we are doing now, what we should do in the future, and how effective any of this has been or will be rages on unabated. Could we have done better? Can we do better now or in the future? I think the answer is yes, yes and yes.

The framework for process improvement used by Lean Six Sigma is Define-Measure-Analyze-Improve-Control, or DMAIC. Prior to define, we first identify the leaderships’ goals, which in turn are driven by the organization’s vision and purpose. In other words, our leaders look at where they want the organization to be at some point in the future and operationalize this vision with metrics that help them measure progress towards that goal. How about this for the covid-19 opportunity statement on day 1?

“Our vision for the USA is for our healthcare system to be able to cope with all major threats to public health. The covid-19 virus is a threat of unknown magnitude to the citizens of the USA. Should the worst-case scenarios come to pass our healthcare system will be unable to cope with the number of cases. We need to act now to prepare for this worst case scenario.”

On day 1 it would’ve been reasonable to use the above mission statement to define the problem as shortages of critical medical equipment such as ventilators, shortages of ICU beds and other hospital beds, shortages of personal protective equipment for front-line healthcare workers, etc.. It was reasonable that the stated scope of the improvement project was to flatten the curve to reduce the number of expected cases to something below the system’s capacity. On March 16 the expected number of deaths in the USA without mitigation, based on the Imperial College of London’s model, was 2.2 million. This horrific forecast made the lockdown for 15 days sound eminently reasonable. However, forecasts are not data, they are predictions made by fallible human models. The Lean Six Sigma motto is “In God we trust, all others bring data.”

By the end of the 15th day of sheltering in place we had more data. The Imperial College had revised their forecast down to about 1/25th the original forecast. Serology studies gave preliminary estimates regarding the number of infected people that indicated a much higher infection rate and a much lower death rate. In Lean Six Sigma work we use the Define phase to refine estimates and then perform a tollgate review to reassess our plans and even to determine if we should continue the improvement efforts. I would argue that this tollgate review, had it been done, might well have resulted in abandoning the shelter in place recommendation and the chartering of a new project. Perhaps the new project would’ve had new goals, such as protecting the vulnerable (the sick elderly) and reopening places where risks were minimal (such as schools). Instead our leaders doubled down and extended the shelter in place order for 30 more days.

In other words, using only the Define phase criteria we could’ve nipped the shutdown of our lives in the bud. In Lean Six Sigma we act on models only until we have data to analyze. Let’s work towards getting systems in place to obtain more timely and more accurate data in the future. We may not have much time to prepare. Due to the sheltering in place we’re engaged in epidemiologists expect a second phase of new cases when we open up. We will need data to help guide our future decisions and to forestall more fear-driven leadership decisions.

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