Coronavirus Analytics that the C-Suite Need

22 Mar 2020 5:18 PM | Anonymous member (Administrator)

Critical tools and indicators need refreshing. This article from Eric Shepherd suggests new data sets that are needed to evaluate the organization’s health.


C-Suite executives are used to managing organizations with the help of Key Performance Indicators (KPIs) and Objective and Key Results (OKR’s). But, during a crisis like we’ve never seen, these critical tools and indicators will need refreshing.

Information and data are the lifeblood of decision making especially during times of crisis. But the data, KPIs and dashboards the C-suite need to manage during this pandemic, will look very different from those of the past. After engaging in calls for the last few days, we have compiled a list of crucial questions to tease out data that the C-suite can use to help with decision making during and after the pandemic.

Data is never perfect. But the more detailed information you can collect, the better the chances of the analytics and projections being accurate. Medical data is sensitive, and most countries restrict access to such data. A sick employee can volunteer their diagnosis, but it is not good practice to ask. In many countries, employers cannot even ask for a projected ‘return to work date,’ which can complicate analytics and predictions further.


There are several ways we can empower the C-suite with useful data. One useful indicator for our model is to take is the average number of days out sick. Given laws and good practice, this data could be sourced from:

  • Estimates by HR and/or managers
  • Global, country and local data
  • Organizational data as people return to work

Analyzing 2019 data can provide a useful indication of the norms for your organization. When analyzing more recent data, you can factor historical norms into your models to help determine the effects of the coronavirus.

However, historical norms must be used with care as they will not reflect the current norms for non-coronavirus related illnesses as more hand washing will reduce colds and flu infections as these are transmitted in the same way as the coronavirus.

The actual questions and data collected will be specific to your organization. We present the following list to help you brainstorm through the process of identifying the data and information that your C-Suite will need to review to make decisions and perhaps add to the organization’s KPI’s and OKRs.

1. Historical trend data segmented by geography and team for how many and the percentage of people are employed and:

  • Working in the office, factory or warehouse
  • Working from home
  • Out sick
  • Working after recovering from sickness
  • Did not return to work
2. Predictions segmented by geography and team for how many and percentage of people employed and:
  • Working in the office, factory or warehouse
  • Working from home
  • Out sick
  • Working after recovering from sickness
  • Will not be returning to work
  • Will be let go temporarily
  • Will be let go permanently

3. Population trend data (from trusted sources) by geography and age, for the number of individuals and percentage of the population:

  • In quarantine
  • Infected
  • Recovered
  • Re-infections

4. How ready are we for remote working?

  • How many of our people
    • Can work from home vs. the need to work in the factory or warehouse?
    • Are currently working from home?
    • Want to work from home but are not now?
    • Do not want to work from home
  • What number and percentage of people that can work from home and have:
    • The internet speeds they need
    • If required, access to an approved virtual private network (VPN)
    • A computer provided by the organization.
    • Personal device or computer that is adequate and secure enough for them to use
  • How many hours, by HR and IT, are required to move someone to home working?

5. Historical trend data and predictions of revenue-generating capacity considering:

  • Number of hours/days worked
  • Workforce availability and capabilities
  • Raw materials or parts available
  • Capability to manufacture
  • Distribution channels function
  • Critical skills required to maintain the revenue-generating capacity
  • Essential functions without a succession plan in place

Data harvested from this data will help the c-suite understand:

  • Resources (hardware, software, support, etc.) needed to support employees
  • Resources to supplement the work of employees (freelancers, retired employees, etc.)
  • The mandates and policies required based “out sick” rates trending in each region, country, state/province, city, and organization’s facility
  • Impact on the organization based on locations predicted to be significantly affected
  • Impact on the organization based on critical functions predicted to be significantly affected
  • Revenue generating functions that are predicted to be degraded
  • Resources can be allocated to reduce the effect on revenue-generating functions
  • New succession plans that need to be developed

Predicting is never accurate, especially when it is about the future! However, we hope that this article provides a stimulus to help you use data-driven-decision making during this pandemic.

And please let us take a moment to thank all the scientists and healthcare professional that are using their talents, to inform us in the short term, cure us in the medium term and keep us safe for the long term.

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