“How can I decide between a temporary or a full-time hire?” is a common question asked by enterprise organizations when looking at workforce planning. Though IQN focuses on temporary labor management, we can help with this question. Tackling topics like this moves you toward total workforce management, where you make strategic and tactical decisions across your workforce instead of separately around temporary vs. full-time labor.

Choosing between hiring an employee or an independent contractor (what my colleague Brian Hoffmeyer calls “the peanut butter and the chocolate of the business world”) requires considering many complex issues beyond relative costs. The relative costs do matter though, and the more you understand patterns in these relative costs, the more informed workforce planning decisions you can make.

That’s where ATOM can help. ATOM, our Automated Talent Ontology Machine, is next-generation machine intelligence for managing temporary labor. ATOM can help you make decisions about full-time hires too, by showing you patterns in full-time wage rates vs. temporary labor rates. In this article, I’ll share with you some exploratory analysis I did with ATOM’s help to better understand relative costs between temporary and full-time labor.

Visualizing full-time vs. temporary labor costs

Here’s a visualization I created using ATOM’s predictive bill rate benchmarks for temporary labor in the Information Technology domain. I plotted ATOM median bill rates against full-time hourly wages for 22 jobs in 265 U.S. metro areas. The gray line shows where the ATOM rate equals the hourly wage rate plus 30%. I added the 30% to represent the cost of benefits that companies pay to full-time employees.

ATOM for Real-World_chart1

Points above the line represent situations where temporary employees are likely to cost more than full-time. Points below the line represent situations where temporary employees are likely to cost less than their full-time counterparts.

One capability we’re developing with ATOM is the ability to detect empirical clusters of occupations, based on an analysis of skills that commonly appear for each occupation. We found five distinct subcategories of the Information Technology job domain, using ATOM’s community-finding capability:

  • Business – project and program management, quality assurance, business requirements analysis, technical writing, data analysis
  • Infrastructure – system and network administration
  • Security – security analysis and management
  • Software – software and database development, database administration
  • Support – help desk and technical support

In this visualization, the subcategory is shown by color. The population of the metro area is denoted by the size of the bubble.

What patterns do we see?

In the Information Technology domain, most of the temporary wage rates are above the gray linewhat I would call the “indifference line” because it shows the points where employers are indifferent from a cost perspective between the two alternatives. Compare this pattern to what we see when we make a similar plot with Finance jobs:

ATOM for Real-World_chart2

In Finance and Accounting, points are generally at or below the indifference line, meaning that temps may be more cost effective on an hour-for-hour basis than full-time employees.

Returning to Information Technology, we also see some other patterns:

  • Support jobs (help desk and tech/desktop support) are the lowest cost jobs, whether temp or full-time. These points cluster around the indifference line, suggesting that cost is not a substantive consideration in choosing between the two.
  • Software jobs, especially architect-level positions, cost more per hour for temp labor than full-time. Perhaps the most seasoned and skilled professionals seek contract positions in this area, and companies are paying for that expertise. Companies may hire specialized labor on a temporary basis while hiring “commodity” developers as full-time employees.
  • Some infrastructure positions cluster around the indifference line, but others are significantly above it. Delving into the data, I found that temporary system administrators and system engineers charge a premium over their full-time counterparts while network and telecom engineers show similar costs for temporary or full-time.

None of these patterns alone will lead to a definitive decision whether to hire temporary or full-time. But studying and exploring ATOM data sets enriched with other data such as full-time wages published by the Bureau of Labor Statistics can give you contextual information to make your decision easier.

For more information about ATOM and how IQN can help you with workforce planning and total workforce management, contact productmarketing@iqn.com.


2016 CWS Summit

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