Workforce Analytics Academy Part VII: Headcount

Author: Lois Melbourne, Co-founder and CEO of Aquire 

Oh the joy of measuring headcount.  Sadly, it is one of the hottest contested HR metrics to be trusted in companies without a concentrated analytics initiative. (Source: Thousands of conversations with HR and HRIT professionals around the world).  Interestingly, the disputes are often around the definition of head to count.  In most cases, once attention has been given to the matter, a head is counted if they are an employee of the company at the time the data being evaluated is measured.  Any other definition of a head should likely require a qualifier be attached to the term headcount.

Qualifiers such as the following may be needed:

  • Full time vs. Part-time headcount
  • Full-Time Equivalency (where a fraction is assigned to the head counted based on the percentage of a work week typically assigned as this person’s work responsibility)
  • Contractor vs. Employee
  • Seasonal vs. Permanent
  • Exempt vs. Non-Exempt
  • Salaried vs. Hourly
  • Active vs. On-leave
There are more qualifiers and even these simplified descriptors often need further qualifiers.  Hear within lies the challenges with coming up with a headcount report.  If you don’t have strong definitions, then it depends on who you ask and what their investment is in the number of people working for your company or within your “four walls”.  If you ask someone doing payroll about headcount, they are likely to look at the number of checks they are cutting and give you the number.  Yet if you have furloughed employees or people on disability, checks may be paused for those employees, so you don’t have the full employed number from the payroll person.  If you ask the building/equipment facilities management, their headcount may include contractors but not permanently telecommuting employees.

So that gives us step 1…

  1. Agree on the definitions of headcount and its qualifiers
  2. Determine where you can appropriately obtain the count and detail of who fits each of these qualifiers.
  3. Test said systems to assure their data is accurate
  4. Publish these definitions and source data systems of record to ALL parties that need or think they need these numbers to do their job.
Repeat Step 3 and 4 often!
By making the definitions public and broadly  accepted, future reports will see an increase in accuracy, meeting the needs of the requesting party.  Without proper headcount data, reporting and agreed upon assumptions, most other data analysis of your workforce is likely to be flawed.  It may only be off a little bit, but based on our experience it is often a large enough margin of error that you don’t want to be staking your job or decisions about other’s jobs upon faulty data.
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