Accurate labour market information (LMI) and forecasting are essential for enabling the mining industry to proactively plan and manage its workforce. Encompassing data on employment levels, job vacancies, remuneration, worker demographics and other key parameters, LMI facilitates decision-making by human resources practitioners, governments, academia and other stakeholders, such as youth entering the labour market, transitioning workers, immigrants and Aboriginal Peoples. It routinely informs economic and social policy, workforce planning and decisions regarding investment in training.
In Canada, LMI is collected and disseminated by Statistics Canada, Human Resources and Skills Development Canada, Citizenship and Immigration Canada, Industry Canada, all levels of government and various other organizations. Mandated to address the mining industry’s HR challenges, MiHR devotes considerable effort and resources to LMI. Historically, LMI collection has not been well-coordinated or consistent across jurisdictions in Canada. MiHR, together with 36 other sector councils, is changing this by standardizing and streamlining the acquisition, analysis and dissemination of LMI.
To forecast future hiring requirements in the mining industry on occupation-, region- and commodity-specific bases, MiHR began developing the Mining Industry Workforce Information Network (MIWIN) in 2007. To date, MiHR has developed forecasts for the mining sectors of British Columbia, Saskatchewan and Ontario. Soon, we will have pan-Canadian forecasting capabilities.
The volatility of mining employment makes forecasting labour demand particularly challenging. Forecasts are typically based on expectations about economic variables that exhibit fairly stable patterns over time. However, employment in the mining industry is more erratic than in other sectors and is characterized by short-term fluctuations of greatly varied depth and duration.
As revealed by regression analysis, the level of mining employment is highly correlated with metals and minerals prices. An Ontario study shows that the commodity price index is the “best leading indicator” of mining employment. MIWIN’s labour demand forecast is therefore largely based on commodity price expectations. Our Ontario forecast comprises three scenarios — pessimistic, neutral and optimistic — of future commodity price expectations.
To accurately forecast hiring requirements, analysts require information about the occupational structure of the workforce. An “occupational coefficient” is the number of employees in an occupation, as a proportion of all employees in the relevant industry. Hiring requirements for each year are forecast by summing up the following: the change in the number of jobs required due to sectoral economic expansion or contraction, given the prevailing commodity price index and occupational coefficients; the number of retiring workers; and the number of workers who leave the industry due to voluntary separation. The table shows the cumulative hiring requirements of Ontario’s mining sector by 2010, 2013 and 2018, under the neutral, pessimistic and optimistic forecast scenarios, respectively.
The Canadian mining industry will undoubtedly face significant human resources challenges over the next decade. The current downturn will not alter the demographics. Nearly half of all mining employees are over 45 years old, exceeding the ratio for the entire Canadian workforce. A sizable proportion of these workers will retire in the upcoming decade. Meanwhile, skills shortages and declining enrolment in mining-oriented academic programs will exacerbate the situation. A prudent and well-coordinated strategy involving industry, governments, academia and other stakeholders must be deployed to preserve Canada’s leadership in mining. The LMI provided by MiHR, of which MIWIN is a key element, will be instrumental in helping industry stakeholders address these and other critical issues going forward.
Sheldon Polowin, program manager, research and labour market information at MiHR, is responsible for supporting the development of MIWIN.