Talk Data To Me: The Impact of Substitute Pay on Fill Rate

Substitute Management

Substitute teacher shortages have been widely reported in national and local media outlets across the country. The shortages are so severe in some areas that they have forced school closures.  Data from the Frontline Research & Learning Institute has consistently shown pandemic-induced drops in absence fill rates (the percent of teacher absences being filled by substitute teachers) and smaller than usual substitute teacher pools.

School districts have turned to creative methods to remedy the issue, like recruiting non-instructional school staff and recent high school graduates to substitute teach. Others have turned to more traditional methods to recruit more workers, such as increasing perks and pay. Unfortunately, not all school districts are financially capable of increasing substitute teacher pay. In that case, what can they do?

What impacts absence fill rates?

Frontline Education consistently produces data-driven insights regarding teacher absences, highlighted in national reports and previous Talk Data to Me blogs. We typically cite three absence-related key performance indicators (KPI’s) associated with increasing Absence Fill Rates.

Key Definitions

Lead Time – The amount of time between when a teacher absence is entered into the Absence Management system and when the absence is scheduled to occur.

Employee to Substitute Ratio – The ratio of employees in a district that would require a substitute teacher to the amount of available substitute teachers in the district.

Working Substitute Percentage – The percentage of the available substitute teacher pool that has filled at least one absence in a set amount of time.

So, what does the data tell us? What effect do these KPIs have on absence fill rate? How do differences in substitute teacher pay impact those effects? The answers may surprise you.

State-level analysis

We combined state level substitute teacher average pay data from the Bureau of Labor Statistics with teacher absence data from the Frontline Research & Learning Institute. Since the pandemic greatly impacted absence trends, we chose pre-pandemic absence data (9/1/2019 – 3/1/2020) for this analysis.  The results for the three absence KPIs are unsurprising, as they are intuitive and echo previous Frontline findings:

  • Lead Time – A 24-hour increase in average lead time is associated with a 0.7%-point increase in fill rate. That means the more time that substitutes have to view and accept an absence, the more likely that absence is to be accepted and filled.
  • Employee-to-Sub Ratio – A 1-point decrease in employee-to-sub ratio is associated with a 6.6%-point increase in fill rate. That means the larger the available substitute pool is relative to the number of employees, the more likely it is that a substitute will fill an absence.
  • Working Sub % – A 1% change in working sub percentage is associated with a 38.5%-point increase in fill rate. So, if a larger proportion of available substitutes regularly accepted job openings, fill rates would rise.

Taking state-level differences in lead time, working substitute percentage, and employee-to-substitute ratio into account, an increase in substitute teacher pay equivalent to $1 per hour is associated with a decrease in fill rate of 0.76%. Yes, you read that correctly. States with higher substitute teacher pay tend to have lower absence fill rates. The chart below plots state average hourly substitute teacher wages against fill rate and the negative relationship is clear.

Understanding why this is the case is beyond the scope of this article. Perhaps there are reasons related to regional economic health, labor markets, and competing employment opportunities. But what does seem clear is that state-level data (as opposed to data for individual districts) does not show that higher substitute pay correlates to higher fill rates.

We certainly are not advocating for decreasing substitute teacher pay in hopes of increasing fill rate, nor are we advocating against raising pay for substitutes. We acknowledge that not every district has the flexibility to increase pay and must seek alternative plans for increasing absence fill rates. This analysis suggests there may be more effective ways to get subs to work in your district, which is positive news for districts who don’t have the flexibility in their budget to increase pay.

So, what can you do?

This analysis is clear: the metric with the greatest impact on fill rate is the working substitute percentage metric. In practical terms, increasing your working substitute percentage requires increasing the engagement of your substitute teacher pool and encouraging a larger number of substitutes to actively work to fill absences.

How can you help substitutes stay engaged?

We surveyed 2,400 active substitutes to find out what outcomes are most important to them when searching for and managing substitute jobs. Of the outcomes we asked them about, here are the most important:

  1. View instructions for a scheduled job. Substitutes are more likely to accept a job if they have access to written instructions from the teacher available to them.
  2. Cancel a job they have accepted. The ability to cancel a job they have already accepted is important to substitutes.
  3. Stay informed with messages and alerts from districts. Substitutes report wanting to be kept in the loop about what’s going on in your district.

To help substitutes stay engaged with your district, support them in achieving all of the outcomes listed below in your absence management product. For example, remember to attach instructions to every substitute job, update your settings to allow substitutes to cancel a job they’ve accepted, and keep substitutes in the loop by posting messages about happenings in your district that could impact them. For more information on how to help substitutes achieve outcomes that are important to them, please check out or contact our Absence Management support team.

For more concrete steps to increase substitute engagement, check out this previous Talk Data to Me blog.

Kevin Agnello

Kevin is a Data Analytics Engineer for Frontline Education. He is a former high school mathematics teacher and holds a Master's Degree in Educational Curriculum and Instruction, a Master's Degree in Educational Psychology, and is working on a dissertation toward a Ph.D. in Educational Psychology.

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