In a previous role, I helped companies build rate cards for their contingent workforces. This undertaking involves gathering and scrubbing a huge amount of data, addition to determining rate thresholds, supply and demand for given skill sets, pay rate rationalization and obtaining end-user buy in. This was important in order to track the contingent workers within the organization so we could measure cost, efficiency, risk and ultimately improve the quality of their talent engagement process as a whole.

“The most severe examples of poor taxonomy typically follow the scenario where companies do not maintain their own internal job database or reconcile titles that are duplicative in nature,” one industry expert shared with me. “Along with this, generic titles like SME, consultant, developer and project manager are in place with vague descriptions; dissecting these lists of sometimes more than 600 job titles can be a challenge.”

I can attest to that. When we would start the task for clients, I would receive data for the portion of the contingent workforce the client was aware of and would see many duplicate job titles and vague descriptions. Then we would track down data on the contingent workforce the client had missed: often SOWs, consultants and 1099s.

Next, we created a compelling business case on why gathering and cleaning this information was important to the program and end user engagement managers and got them involved in the initial clean-up process. Finally, when we’d herded the cats and had what we believed was the entire pool of contingents at the client company, we could get to work on the job titles, pay rate ranges and taxonomy.

Our first task would be to look at the universe of job titles across the company. This was important so that we could create cohesiveness down the road for rates and descriptions. Where could we make them more consistent? Were job titles levels based on skills needed? Did the bill rates match the different levels? Were they classified correctly (exempt/non-exempt; computer professional or not; 1099, SOW or agency)? Most important, was the company getting the talent it needed at the right price? Typically the answer on many counts was a resounding “no.”

Then we would rationalize the job titles and levels and determine what would work for a given client. Working with the data and interviewing end users, we’d use company and industry data to craft uniform job titles, descriptions and levels that were appropriate and scalable for that company across the board. We would take into account the jobs themselves as well as the industry and location. For instance, if you are working with an automotive manufacturer in Torrance, Calif., the talent needed might be IT. But an automotive client in Georgetown, Ky., might call for manufacturing talent. A typical rate card would account for one to three levels of talent with the descriptions based on whether the job itself was also core competency of the company.

Corporate culture and practices could also be integrated into the process to build a talent pipeline and education process benefitting managers and the company as a whole. Could a temp job be a stepping stone to engagement as an employee? Part of the beauty of the exercise is creating a win for managers that gives them greater clarity into the talent they desire and a system that enables them to get that talent each time at a fair price with a minimal amount of repetitive effort on their end.

Next up are bill rate ranges, which are a combination of art and science. Setting up the right bill rate ranges depends on the demand and supply of talent, industry, location and company brand. Technology is critical because it enables:

  • Comprehensive and reliable rate data in select industries and markets
  • Validated transaction data
  • Precise job functions and “job title variants”
  • Forecast of future pay trends
  • Professionalization of the industry (more science, less art)

Once we rationalized the job titles and descriptions and calculated existing ranges were, we tagged and explored deltas and decided upon appropriate bill rate ranges with the program managers, end users and stakeholders. This was built into the tool and helped to drive greater clarity, commonality and ultimately better quality, controlled cost, mitigated risk and efficiency.

Job titles should be consistent and you should want to get them right. Looking at job titles, pay rate ranges and taxonomy for contingent workers is an art and a science. Make sure you or your managed service provider does it correctly and for the right reasons. Educating your end-user managers will help them and the company ultimately save time, money and create a better talent pipeline while mitigating risk.