Success Stories

Leading with ‘Job Fit’ to jump ahead of hiring targets and break down gender & diversity barriers

In 2019, the Ontario Electrical League (OEL) began using a customized version of Fit First® Technologies’ platform, Jobtimize® to help electrical contractors and electrical apprentices get matched more efficiently. For many years, apprenticeship across the Province had suffered from critically low levels of enrolment and unsustainably high fallout rates. Tradespeople were retiring at a rate far higher than they were being replaced. Jobtimize, the framework for the project, is built using sophisticated behavioral science and job matching technology for a unique approach to matching individuals’ career compatibility and employment options. With this philosophy, the emphasis is put first on discovering who a person is and what their overall ‘job fit’ would be with a particular occupation. Then, secondary to that, the standard résumé-based education and qualifications are considered. As Fit First® reviewed project statistics with their colleagues at OEL – only six months in, the results greatly exceeded everyone’s expectations! By using the ‘Fit First®’ approach, the Jobtimize platform was able to achieve OEL’s key objectives, successfully identifying people who were:

  • Most likely to complete the apprenticeship program.
  • Compatible with the jobs waiting for them in the trade.
  • The right ‘job fit’ with the employers who were hiring.

In addition, OEL had one more important goal for Jobtimize to achieve:

  • Increase diversity within the trade.

Again, by focusing on behavioral traits and interests first, Jobtimize was able to identify those applicants who were naturally most compatible with the jobs, regardless of gender, race, disability or other diversities. Those running the project observed:

Traditional approaches to diversifying the workplace are often forced objectives that yield little success. However, this model is different, because diversity is a natural outcome of leading the hiring process with ‘job fit’.”

The OEL found themselves discovering people with tremendous potential in unexpected packages – including people with very limited work experience or non-traditional backgrounds who may not have been considered on the basis of their résumés. They discovered that allowing the Jobtimize algorithms to screen all applicants for ‘job fit’ first, before any further subjective screening takes place, greatly reduces the risk of unconscious bias in the process, yields a larger and more diverse set of ‘high probability’ candidates, and significantly reduces or eliminates the barriers most often faced by traditionally underrepresented communities.

Now, twelve months since the launch, OEL’s tradespecific version of Jobtimize continues to show very promising results. To date, OEL’s members remain well ahead of their targets for hiring qualified electrical tradespeople and apprentices, backed by these two very impressive statistics:

OEL is running at nearly 200% of their hiring targets. 24% of the hires are from traditionally underrepresented communities (women, visible minorities, newcomers, indigenous or disabled).

The end result has been a shorter, more efficient recruiting process that embraces the candidate’s full potential, ultimately helping place more people in the right jobs, lowering employee turnover and raising employee/employer long-term job satisfaction rates.