One of the most common reporting challenges companies face is balancing headcount over time by adding and subtracting Hires and Terminations.
The process seems like it should be simple, especially when someone with a background in finance or accounting first looks at the issue. The misconception is that the company’s headcount will balance in much the same way money in a financial statement balances, where the analyst takes an initial amount of money the company has, and adds the money that came in for the month (e.g. customer sales, invoices) and subtracts the money that went out for the month (e.g. transportation, payroll cost, rent) and results in a final amount for the month, which then starts over the next month.
If that’s how a financial statement is balanced, it seems that the same concept should be easily applied to balancing headcount reporting metrics. It might seem that a company should be able to use the following formula:
Starting Headcount + Hires – Terminations = Ending Headcount
And everything would balance and net out.
Unfortunately, accounting does not seem to work out the same way in HR as it does in Finance. Rarely (if ever) does this simple formula work when counting people instead of money.
There are a number of common reasons why this formula fails when applying it to the reconciliation of headcount reports over time:
Fortunately, One Model can solve all of these issues in balancing headcount relatively easily by creating a new set of metrics specific to the company’s data that include populations that might not normally be counted, and exclude or include Hires and Terminations at the beginning and end of a time period.
This Reconciliation Headcount Reporting Metric is effectively a more accurate mathematical equation that balances headcount to reflect these quirks in people data to match the financial statement approach to reconciliation. Each customer that works with One Model will have a slightly different version of a Reconciliation Headcount metric based on the methodology they use to count a Hire or Termination. An example formula for this metric may look like this:
(Ending Headcount + Terminations on the Last Day of the Previous Time – Terminations on the Last Day of the Current Time Period) – (Starting Headcount + Hires – Terminations – Divestitures)
When properly constructed, the new metric will correctly sum to 0, eliminating the problem HR sometimes has in justifying apparent irregularities in reconciling headcount. If the Metric does not equal 0, it means that there is at least one person or event in the data that does not have a requisite hire or termination to balance it out and that the company should investigate the record.
One Model can also provide the company with a set of metrics that explain the difference between the events and populations that are included in the inputs for the new metric calculation and what the company would otherwise use for standard reporting on headcount, hires and terminations.
Once the Reconciliation Headcount Metric is created, it can be used to monitor and understand data changes over time that might not be apparent in a less refined approach to reconciliation.
The following is an example of the Headcount Reconciliation Metric for Company A across 4 months. If all factors that affect headcount are included in the reconciliation calculation, then each month the Headcount Reconciliation Metric would show as 0.
Without the Reconciliation Headcount Metric and One Model, it could be difficult to pinpoint the source of these discrepancies. In fact, it might not be possible at all, depending on how the data was reported.
If an analyst was lucky enough to be using lists of individuals to perform the reconciliation and had the actual records for all relevant points in time (the beginning and end of each month), they might be able to figure out the specific people accounting for the differences in December and January by using vlookup formulas in Excel to locate each difference. Of course, this would make the entire reconciliation process very time consuming
Reconciling headcount may not even be possible in all situations. In some cases, the analyst may be adding or subtracting data from past months’ reports that have already been aggregated. Using aggregated data would make the reconciliation process almost impossible, since the data in the source system may have changed since the reports were run, and the analyst would not be able to pinpoint the specific people whose situations are creating the discrepancies.
The One Model platform has a unique feature that eliminates all of these problems and makes the reconciliation process very easy. This feature is called List Reports. In One Model, a user can take a metric and then look within it to find the data points that are causing the discrepancies.
In the example of Company A, where it appeared that there were discrepancies in the December and January headcount reports, the analyst creates a List Report that includes the Headcount Reconciliation Metric, Worker Number and Name of every individual accounted for in that period. Any individual whose status changed during the time period but was not properly accounted for in the reconciliation process would be flagged as a + or - in the Headcount Reconciliation column. The List Report can then be filtered to show only those individuals whose records are the cause of the apparent accounting error.
In the example of Company A above, there was a net discrepancy of one for the month of December. By exporting the data and filtering out the 0s, only one record had a +1 in December:
In only a couple simple steps, it was easy to determine that Joe Williams’s record is the source of the discrepancy in the headcount for December.
After identifying Joe Williams, the next question is why his record caused this discrepancy. Since it appears that his record caused an addition to headcount, it may make sense to first look at the data for hires and see if a new code was added to Company A’s HRIS that was not included originally.
In the example for Company A, Joe entered Company A through an acquisition that was not coded as a hire.
This Headcount Reconciliation Metric can now be used to better understand net internal change within Company A.
In the example below, Company A’s Headcount Reconciliation Metric is broken out by Department. In disaggregated form, it’s easy to see that in December the company had 1 net move into Commercial and 1 net move out of HR. Even more helpful, it’s possible to see that while Headcount balanced at the overall level for November and February, there were actually movements across departments in those months. The fact that those movements netted to zero made them seem to vanish from the reconciliation metric, but One Model still makes it possible to identify this movement.
One Model’s List Report Identifies the Individual Change Records
Looking again at December, adding the Department field into the List Report reveals a department change for a different worker. In this situation, we see that Chris Jones moved from HR to Commercial in December.
Using the Reconciliation Headcount Metric, makes it possible to look at internal movements and understand how the company’s headcount has changed internally over time.
While customers can traditionally use events like Transfers, Promotions, Demotions to pinpoint internal movement, these methods can often be deceiving. Very often customers do not have strict business processes about what is being counted in these movements and events in the HRIS are coded as Transfers when they’re technically a data correction. A Promotion may get coded as such when it really is a Transfer or Lateral move because the manager wants to send a positive message to an employee. While the net difference derived from the Headcount Reconciliation Metric doesn’t necessarily resolve all of those issues, it allows the analyst to see the specific internal net change across time.
The examples above used months, but the time period could have been any (e.g. year, quarter, week). If you want to know more about One Model or Headcount Reconciliation, we’d be happy to talk to you. Personally, I love talking about people data and how to construct metrics to drive business decisions.
Want to learn how your company can benefit from using One Model? Have questions on your team's specific challenges in balancing headcount and internal net movements? Learn more about the benefits of One Model and sign up for a demo.