Mathematics makes resilient during a pandemic

At the start of the pandemic, priority was for many businesses to respond to and anticipate what was still an uncertain situation. Gerrit Timmer, co-founder of and Chief Science Officer at ORTEC: “You can compare it to a volcanic eruption that requires companies to adjust their processes immediately. Under normal circumstances, you can use mathematics to calculate the most efficient and effective process. However, there were suddenly additional preconditions and requirements. Despite this, the underlying mathematics remained the same. Those businesses that had already many of their processes running in a semi-automated way could quickly respond to the new reality.”

Predicting the speed of the virus

Of course, admits Timmer wholeheartedly, even with mathematical insight things can turn out much differently than expected. After all, the virus was unknown. But without mathematics, the situation in the first wave of the coronavirus outbreak would have been much less clear, he says, with all the associated consequences. “A great deal of data science has been used to gain a better understanding of how the virus is spreading. Without data science we would have been completely in the dark. At first, we knew nothing; we also lacked any medical knowledge of the virus. And you do need some medical knowledge to create a model that makes any sense. Models are only as good as the medical facts you put into them. Mathematics can help in recognizing certain patterns. But that always takes some time; it is a couple of steps behind. Still, it is amazing how mathematics can have a tremendous impact by bringing insight. This also applies to predictions about the speed of development of the virus, depending on government measures and social behavior. You are not only interested in the number of infections, but also in the impact it has on hospitals and ICU admissions. Mathematics can also contribute to finding the right balance between the pros and cons of government measures, having an effect on multiple aspects of our society.”

COVID-19 radar for analysis

As Timmer said, especially when it comes to significant disruptions, analytics are a powerful tool to determine the effect of the disruptions. “For example, Leiden University Medical Center created a COVID-19 radar to provide insight into the effects of social distancing. TNO analyzed the data and revealed that people were less adhering to social distancing in August, when the number of infections started to increase again. That however was not the case for the most affected groups – the elderly were still mainly staying at home. It were the young people who had more contact with others, but did not get seriously ill. It also turned out that the large demonstration in Amsterdam had not led to more infections. The COVID-19 radar has proved to be very useful to conclude this. Mathematics enables organizations to take better measures than they would be able to without analytics. This applies to hospitals too. In October, when it appeared that a second wave was on the way, hospitals began to scale down their regular care more rapidly. For example, they made 30% less use of ORs, so they could keep space in ICUs for coronavirus patients. That percentage was based on mathematics, predicting the way the second wave would develop and how many ICU beds would be needed.”

At the beginning of the corona crisis, the hospitals suddenly needed new scheduling solutions due to the large number of on-call workers needed. In March, an additional 20,000 people were working in the healthcare sector. Some of these people were subject to different regulations than regular healthcare professionals. ORTEC added extra modules to the standard roster planning software to make it easier to schedule these on-call workers, says Goos Kant, managing partner at ORTEC. “In many hospitals, it was the team leader who used to do the staff planning. Because of the coronavirus crisis, however, several hospitals have now centralized and professionalized their planning. Employees and administrators have seen that a professional roster package based on data science can make a significant difference. This increased demand for central staff planning is also reflected in logistics. Greater absenteeism due to illness and quarantine makes being able to respond quickly more important than ever. It has also become more complicated because demand can suddenly increase or decrease as a result of changing circumstances and government measures. That’s why we’re also supporting with collegial borrowing and lending of personnel between companies.”

According to Frans van Helden, managing director of ORTEC Data Science & Consulting, mathematics can make businesses more resilient. “For example, we helped a multinational decide when and in what capacity to invest, given the great uncertainty in the market. Naturally, you do not want to blindly gamble on the notion that businesses will simply continue in the same vein as before the corona crisis. So, we devised a model that evaluates a large number of scenarios to enable the right choice to be made with a reasoned risk. This model proved successful, also because the management involved was seasoned and educated to provide the right inputs. They understand the necessity for complex but thorough analysis of the uncertainty that occurs in the market and in the supply chain, as well as the output of that analysis. It helps to create explicit scenarios and to model decisions against the background of a large number of these scenarios. It helps to get solid recommendations suited to those disruptions. Now we are not only working on more effective predictions and dealing with data in a smarter way, we are also trying to set up the business process in such a way that you can make crucial decisions later in that process. For example, imagine a production process that takes twelve weeks. Because the process depends on many factors, the final decisions about the end product are already made in week six. If you can postpone those decisions to week eight, that brings you two weeks closer to the delivery date. It means you have more reliable data, enabling you to make better decisions.”