By Ron Samson
After spending over a decade in workforce development where I’ve designed and evaluated numerous initiatives, and in my current role at Magnet where I lead a team of individuals who analyze labour market information (LMI), I find that the future of work is always forefront in our minds. I recently served as moderator of a panel discussion on the next wave of LMI in Canada and how to ensure it is relevant to Canadians. To me, it’s fascinating to see how someone ends up in a particular job, career or vocation, and how our understanding of work is constantly evolving. For years, I’ve heard researchers predict a futuristic time where we have a world of people without jobs and jobs without people — driven by disruptive innovation, AI and automation.
While there may be some truth to these predictions, they are often not accurate, let alone useful for career planning, nor should they be confused with LMI. What we do know is that the overall returns to education pay off over time in terms of employment and earning trajectories. However, when it comes to which jobs will grow, how industries will change and what the economic conditions will be in specific areas, no one person or tool can accurately predict the future.
Case in point: I have heard for nearly a decade that truck drivers will no longer be needed and that this job will become automated by 2025. However, not since WWII has there been such a great need for truck drivers. Across Canada and many parts of the world, a severe shortage of drivers is now affecting the supply chain and logistics sector. Numerous jobs like truck driving are predicted to have poor long-term prospects, and yet they have strong labour market demand, which creates a paradox and sends mixed signals to job seekers and stakeholders in the skills development ecosystem. The issue is that we don’t know what will actually happen or when changes will occur. Will these jobs remain stable, disappear, require a change of function and skills, or possibly even increase in number?
So the question for me is, how do we meet the realities of today’s workforce while at the same time develop an understanding of emerging labour market needs? Even with LMI’s limitations, without LMI, we are making decisions in the dark. This is where the true value of this data can be derived for all stakeholders in the employment, education and training sectors.
LMI can help policymakers determine where there are skills shortages and identify broader needs related to system-level decisions. It can provide information to administrators in the employment, education and training sectors about emerging training needs and what skills are in demand, and it can provide job seekers and students with a broader understanding of job and career opportunities and the associated skill requirements.
Although LMI offers promise, it can also be misinterpreted and has data limitations. Furthermore, the data itself cannot address systemic workforce development issues, particularly related to racism, discrimination, inclusion in the workplace, decent work and pay equity. LMI can be used to assess the scale and magnitude of these issues and monitor progress. However, LMI cannot create the policies, interventions and societal changes that are needed to address inequities and inequalities in the labour market.
When thinking about LMI, we should remember that when someone makes an employment or career decision, it is an individual choice based on a number of factors. They include interests, aptitude, economic circumstances, advancement opportunities and aspects that relate to work-life balance, mental health and wellness. This is particularly important when it comes to marginalized populations and their lived experiences. While LMI can’t solve all labour market issues, in a world where we have a great deal of information that allows us to make decisions on just about everything, we should at least have good quality information about one of life’s most important decisions.
Canada’s skills development system is still in the infant stage of developing user-centered LMI tools, and this bold new direction of liberating LMI through a greater emphasis on the user and applying design-thinking practices to develop innovative solutions can provide a wide range of opportunities that have yet to be realized. This is a critical step forward and will allow us to develop a better understanding of the kinds of LMI that different users need, how LMI can be used effectively, and its limitations. My question is: How can we incorporate LMI into our practices more effectively? Ultimately, the better our use of accurate LMI, the more empowered we are to make informed decisions leading to improved outcomes for students, job seekers and employers.
LMI is a powerful resource that is continuously being improved. Much like the economy, it is difficult to predict where LMI will take us in the future. Could we live in a world where LMI, matching algorithms, AI, and new tools reduce the need for humans to provide career support? Maybe, but that is probably less likely than a world without truck drivers. As a new father who is considering my child’s future, I would give advice similar to what my dad told me: Stay in school, do something you love, gain workplace experience, seek mentors, don’t stay in a job that causes undue mental or physical harm, and always remember that work is important but it’s not everything, so strive for a fulfilling life. And of course, informed decision-making will more likely lead to a better outcome overall.