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How stay at home orders impact on-site work

How stay at home orders impact on-site work

As more and more states enact stay at home requirements to combat the spread of the Covid-19 virus, are people actually responding to these mandates? Initial studies have started to come out, but we wanted to see if there was a more data-driven way to find out: for example, we would expect the activity at factories and facilities to decline proportionally to folks beginning to work remotely. 


Is there a way to easily measure this?


Yes…utilizing IoT (Internet of Things) technology. IoT devices are sensors and devices that perform relatively simple tasks. 


The real power in these devices is the data they aggregate. A great example of this was presented by Kinsa and their bluetooth thermometers. Kinsa collects temperature data from people using their products around the USA. By analyzing the data they are able to determine when people’s temperatures are increasing or decreasing, relative to their typical (baseline) temperatures. 


This information can then be used to track the critically important spread of Covid19.


The same analysis can be performed using data gathered in work facilities. If work environments are outfitted with IoT sensors that sense the environment, movement, machinery or assets, one can use this information to understand the relative activity and utilization of the facility. 


This understanding of level of utilization can then be used to construct models for production capabilitya critical aspect of building a pandemic tolerant economy.


Given Elemental Machines' focus on life sciences and healthcare, we decided to look at just such a utilization scenario, using data gathered from our network of thousands of IoT devices deployed across hundreds of R&D facilities in the United States for the first three months of 2020. 

weekday_activity_v2Average on-site activity during WEEKDAYS by region


From the above map of the country you can see the activity levels at facilities grouped by different regions of the country. We chose these divisions to reflect generally the severity and timing of areas of the country that were affected by the coronavirus.


We can see that the first two months of the year had a relatively steady level of on-site activity in all regions. However, as we get into the first week of March we see facility utilization suddenly dropping in the West and in the Northeast, not surprising given the first hot-spots were Seattle, California, New York City, and Boston and that these were the first regions of the country to issue stay at home orders. 


States in the South and Midwest regions were slower to announce states of emergency and to issue stay at home orders. It’s interesting to note that activity in these regions actually rises sharply in the beginning of March before dropping off like the rest of the country. Given that these regions had at least a week’s heads-up on what’s to come, this sudden spike in activity was likely due to people scrambling to do extra work to prepare for expected stay at home orders in these regions. 


But things get more interesting if we dive deeper into the data… Looking at WEEKEND activity sheds much more light on behavior patterns. The graphic below shows only the weekend activity across the same regions. Weekend activity in the Midwest and South (where they had more warning about upcoming shutdown orders) spiked tremendously, with the South showing an 800% increase in weekend activity the weekend of March 14/15, just before shutdown orders were issued.

weekend_activity_v2Average on-site activity during WEEKENDS by region


The charts below summarize these findings more clearly across the four regions and split by weekday/weekend. It’s very clear to see the trends here, namely that the Northeast and West were caught off guard and didn’t have the same flurry of pre-shutdown activity as the Midwest and South regions. The good news is that across all regions, on-site activity is at an all-time low, hovering around 25% of normal. 

utilization regions

We will continue analyzing these macro utilization trends as COVID reaches it peak and dissipates (shortly we hope!).  Our goal is to then provide this information, free of charge, to any life sciences R&D facility for future business continuity planning.


In addition, Elemental Machines, during this Covid-19 crisis, is happy to provide free monitoring of your facilities to optimize remote work planning.


Free Monitoring


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