With the continued growth of the Coronavirus pandemic our leaders are going to be asking for regular updates on our employees health and our business’s productivity. This is not going to be a flash in the pan event either. The path back to normal will be long and gradual which means we need to approach data collection, reporting, and analysis with an emphasis on repeatability.
To that end there’s a number of questions that HR teams are going to need to answer in order to provide a status of and show the progression of the businesses adaptation to these challenges and how our workforce is coping.
What questions are we going to need to answer?
- What % of our workforce can be switched to work remotely if needed?
- What % has already shifted to working remotely due to COVID-19? What is the trend as we ramp this ability?
- What % of our workforce is currently not working due to COVID-19?
- How are infection rates trending in the countries/states/provinces where we have employees?
- What is the trend in our employee infection rates and how do they compare to the relevant country/state/province?
- What is the risk level of our workforce in a given area based on the age distribution and other relevant factors?
- Do we have any locations that are significantly impacted by COVID-related absences?
- What is the average duration of employees being unavailable due to COVID-19 - illness or other?
- What % of our infected workforce has recovered and returned to work?
- What % of our temporarily remote workforce has returned to working on location?
- What is our current productive capacity %?
- How long are impacted employees non productive for?
- How much productive capacity have we lost?
So, what data do we need and how do we organize it to address the questions above?
This is where things get tricky and HR needs to be collecting additional data beyond what they have today. This is likely going to need to come from manager input with HR acting as the central collation point. Ideally this information can be captured and held within your HRIS, but most likely this is going to start out as a spreadsheet as your HRIS may not have the required fields for what we need to measure beyond traditional absence & availability information.
My view is that shortly we're going to be asking managers to provide information to HR when their employees move into quarantine, infection, and start/stop work (when remote) because of illness. This may or may not also be in association with an HRIS event recording absence or similar.
As this data is collated you'll want to make sure you can collect a few key data points as per the below
- Ability to work from home
- Currently working from home
- Date employee stopped working
- Date employee returned to work
- Date employee in a Quarantine status
- Date employee in a Infected status
- Date employee cleared of Quarantine/Infected status
This data can then be merged with the following HRIS information
- Location information: Country, State/Province, City/Location (for site-level metrics and comparison to global/national statistics)
- Personal information: age, gender (optional - for risk assessment and forecasting, data would not include name of employee ID number)
- Employment: employee type (regular, temp/FTC, contractor), Full/Part time
A combination of this event-related data alongside the HRIS data will create the ability to track over time the status of our workforce so we can report and analyze the trend and impact on the business.
Some of these data points can be inferred from your existing systems
It’s going to be a challenging job to collect and keep collated the above data so if you have already or can get data from some additional systems like facilities and IT access you can infer some of these data points. Below are some examples of business logic some of the organizations we have been talking to are using.
- Ability to work from home = Have access to a VPN, Have a laptop.
- Currently working from home = Are accessing the VPN, have not badge swiped into an office/facility.
- Not working due to infection = A leave of absence record with no recent vpn access or badge swipe.
How would we present this information?
Note: the above is mock data
Workforce Composition & Employee Health
Overall metrics on the current workforce showing the total population, working status, remote working rates, and infection rates. We also want to show this trending over time so we have an idea of the growth and ultimately the recession of infection rates.
- Headcount, Headcount % - Quarantine, Infected, Recovered statuses
- Currently Working %
- Working from Home %
High Risk Populations
Comparison against daily statistics by country/state/province produced by health organizations will enable you to compare your infection trend to the prevailing trend in the relevant geographical area. If the area is seeing an acceleration of cases, you should anticipate similar risks for your workforce. If the area has hit an inflection point and is leveling off, the risk to that part of your workforce should be on the wane as well.
Beyond geographic risk, age is the biggest factor on the impact to the employee and we're going to see longer infection periods and mortality rates for older employees than we will for other populations. Obviously any steps the organization can take to protect higher risk populations should be fought for.
- Regional Infection Rates (where available)
- Active, Quarantine, Infected, Recovered by Age, Location, Department
The absence of employees will reduce the productivity of your workforce, potentially impacting customers and creating financial risks such as over-ordering of supplies and raw materials, over-estimating orders and revenues, or committing to delivery dates that cannot be achieved because of workforce impacts beyond the view of the manufacturing location’s management. Questions we need to answer include how many of our employees are currently working, whether from home or their normal location? How many hours have we lost due to infection-related absences? While productivity isn't a major concern when lives are at stake, many of the actions we may take in protecting our employees will show up in either infection rates or in absences and we should be measuring to see what was effective and what wasn't.
- Currently Working % - Active, Quarantine, Infected
- Ability to work from home %
- Lost productive hours (key here are the dates for when people stop and return to work)
Duration of Quarantine and Infection.
As we plan for how our employees are impacted we need to be analyzing how long our quarantined and infected employees are unable to work. Many employees may still be able to work from home while under quarantine and or infection but there will be periods when they are infected and unwell that they won’t be able to work while when their symptoms are significant or while they are recovering. Questions we need to answer include how long is the infection period for our workforce? What is our forecast for our currently infected employees being back to work?
- Days in Quarantine
- Days from Infection to Recovered
- Number of Reinfections, Reinfection Rate
The above metrics and questions are a bare bones set of pertinent information that you could provide to leaders even if you don’t have fully integrated HR systems. Of course, there are many more attributes available that leaders may want to view. These will be specific to each business’ strategy so my advice is to include a number of common HRIS fields into the data collection process when you build your initial data set so you can segment later as needed.
Suggested other data elements to consider adding
- Succession – can we tap into the successors for persons in critical roles? How impacted are these successors?
- Critical roles – prioritize remote work arrangements or advise early preventive quarantine measures for specific roles in certain areas
- Skills data – capture potential temporary backfills for employees that are unable to work
- Set-up expense tracking – spending to facilitate remote working capabilities
- Re-infection rates – tracking of persons previously cleared