What does it mean exactly when a job is ‘ready’ for the Future of Work?
The phrase Future of Work has been tossed around repeatedly over the years. But when people talk about the kinds of jobs that fall (or don’t fall) into that concept, it’s not always clear what they mean. As Guild continues to partner with companies, building out catalogs of programs to reskill and upskill talent, it helps to crystallize what we define as the Future of Work and how to measure it. After all, talent strategy shouldn’t be a guessing game, and if employers plan on upskilling their talent one quarter, one year, or even two years from now, they’ll need a precise framework for the Future of Work and what that entails.
When considering jobs that are Future of Work-ready, we think of three key measurements:
Job Demand — Was there a sustained demand for this occupation over the last few months, and is this demand expected to stay steady or grow over the next 10 years? Note that demand can be geographically specific, so while one occupation isn’t expected to grow in rural Texas, it may see high demand from employers located in metro areas. In that same vein, highly distributed employers, like those in retail, need to think about whether their employees across their entire footprint will have access to new roles as a result of their companies’ upskilling efforts.
Wages — After going through a program, will an employee earn a family-sustaining income where they live, and will the new skills they developed lend themselves to economic mobility in the future? This consideration becomes even more critical in the likelihood that the employee takes on student debt to get through said program.
Skill Resiliency — There are few jobs that exist today that aren’t at risk of automation for at least some of the tasks that the occupations require. Even if an employer doesn’t have an automation effort underway today, market data can give us insights on the likelihood that some parts of the role will be automated in time. It’s neither feasible for employers to invest in upskilling for a role that has a high chance of being automated, nor is it advantageous for an employee to invest in their own reskilling if the new skills will only keep them employable for a short time.
After taking into account these frameworks, employers can then use six quantifiable data points to help decide where to invest their talent development programs. We can use data from third-party partners like Emsi or directly from the Department of Labor to adjust the model and tweak it for specific locations, education levels, or employer-specific business strategies. The six data points are:
- Job volume is the total current employment across the nation
- Wage level is the median hourly wage that someone in this job can expect to earn
- Job posting volume is a rearview-mirror look at the past 12 months and the number of unique job postings for a specific occupation
- Job posting intensity tells us the average number of times a job is posted across job boards
- Automation likelihood is an indicator that’s generated to let us know if an occupation is likely to be affected by automation in the near future
- Job change is the projected growth or decline in employment over the next ten years
By taking some of the guesswork out of the Future of Work, we hope this helps guide companies (and that high-price consultant that was likely brought in), to make good business decisions about how to develop their talent in a way that creates a win-win, mutually beneficial scenario for both employers and employees.