Saskatchewan Mining Association Erin Mills Jamie Wolcott June 2, - - PowerPoint PPT Presentation

Ryan Montpellier Erin Mills Jamie Wolcott June 2, 2020

Saskatchewan Mining Association

Presentation Overview

• About MiHR
• The Changing Nature of Work
• Qualitative Research:
• Research with Key Mining Stakeholders
• Quantitative Research:
• Occupational Vulnerability
• Future Workforce Skills
• Conclusion and Q&A

About MiHR

• Mission: To lead collaboration across the Canadian mining sector to

understand labour market trends, identify opportunities, and develop solutions.

• Canada’s Knowledge Centre for Mining Labour Market Information
• 14-person Board of Directors
• 20 staff in Kanata, Ontario
• Over 250 industry volunteers

MiHR’s Board of Directors

MiHR’s Strategic Pillars

Career Awareness and Diversity and Inclusion Initiatives The Changing Nature of Work

• Report is a culmination of a two-year study
• n the changing nature of work in mining,

launched in pursuit of MiHR’s vision.

• Study’s primary research objective was to

increase understanding of how automation, innovation and emerging technologies are impacting the workforce.

Career Awareness and Diversity and Inclusion Initiatives

Research Questions

The research for this report focused on four overriding questions:

• 1. What new technologies are currently being introduced in the sector?

2.Who will be disrupted by these new technologies?

• 3. How will skills requirements change as result?
• 4. What can mining stakeholders do to better prepare for these changes?

Qualitative Research

I. Research with Key Mining Stakeholders

Career Awareness and Diversity and Inclusion Initiatives

Research with Mining Stakeholders – Methodology

A qualitative study involving the participation of 125 Canadian mining stakeholders who have direct, relevant knowledge of the Canadian mining context. MiHR conducted interviews, an online survey, a focus group, case studies, and validation sessions to capture a broad spectrum of views and expertise. The report also includes a comprehensive review of the literature on the impact of digital innovations on the mining industry, both globally and in Canada.

Career Awareness and Diversity and Inclusion Initiatives

Key Findings from the Literature

• Pace of adoption and implementation slow and uneven – peak over next 10-15

years.

• Job loss will occur as a result of new technologies, but will also result in the

creation of new jobs - development, observation, servicing and maintenance of remotely controlled and autonomous equipment, and in data processing and process analysis.

• Automation will likely reduce the number of operational jobs (train and truck

driving, drilling, and blasting) - these areas currently constitute over 70% of mining employment in Canada.

Them eme 1 - Changi ging N g Nature e of

• f Wor
• rk in

in Min inin ing Stron

• ng incentive

ves to i imple lement n new w tec echnol

• log
• gies:
• Increased worker health and safety;
• Increased productivity;
• Cost reduction / improved competitiveness;
• Strengthened environmental sustainability.

Perceived chang nges to mi mini ning ng work k as a result of imp mplement ntation: n:

• Mixed views on job loss or gains - most jobs will be affected;
• Some reluctance/resistance by both companies and employees to the adoption of new

technologies;

• Opportunities and challenges for diverse groups (youth, Indigenous, women, those with

disabilities);

• Rate of adoption is mixed.

Research with Mining Stakeholders - Key Findings

Career Awareness and Diversity and Inclusion Initiatives

Research with Mining Stakeholders - Key Findings

Them eme 1 - Changi ging N g Nature e of

• f Wor
• rk in

in Min inin ing “Technology is a cost saver, a health and safety issue, an improved monitoring issue, better use of information issue, and a performance issue”. “Technologies will not necessarily provoke a reduction in the workforce, but a fundamental change within it”. “There is a huge risk of miscommunication when a new technology is adopted and there needs to be buy in from employees for successful implementation”. “Leveraging these technologies could increase the number of well-educated and skilled people interested in mining work.”

Career Awareness and Diversity and Inclusion Initiatives

Research with Mining Stakeholders – Key Findings

The Theme 2 2 - Increa easin ing S Skills lls R Requir irem emen ents

• Lifelong learning and training is key;
• New technologies may increase access to employment for some

workers and may negatively impact others;

• “Gamification” of mining and the ability to work off site will

attract younger, more technically-savvy and diverse workers;

• Future workforce needs to be adaptable and flexible;
• Increased need for both soft skills and technical skills.

Career Awareness and Diversity and Inclusion Initiatives

Research with Mining Stakeholders – Key Findings

Them eme 2 - Increasing g Skills ills R Req equir irements “Understanding and working with new technologies will require skills to evolve. New roles will be created, including those that do not exist yet and our understanding of technologies and awareness of how we apply them will be critical”. “Innovative changes are good for diversity – it broadens the approach to diversify talent, and allows us to attract new people with new skills and open up the workforce”. “We need curious people, wanting to learn, to maintain and grow their knowledge and embrace innovative and new technologies”.

Career Awareness and Diversity and Inclusion Initiatives

Case Study Highlights

• In 2019, MiHR visited two Canadian mine sites and one training facility − Agnico Eagle (LaRonde

Zone 5), Anaconda (Point Rousse Project), and NORCAT − to learn more about their digital innovations and related training programs.

• These three firms recognize the need for enhanced technological capacity as the pathway to a

sustainable mining future.

Highlights include:

• Agnico Eagle’s piloting of autonomous vehicles underground and related training for control room
• perators.
• Anaconda’s implementation of Sustainable Mining by Drilling and development of the Anaconda

University training platform.

• NORCAT’s advanced simulation training centre – where operators can “sit in the driver’s seat” of

various mining machines in order to be trained efficiently and economically.

Quantitative Research

I. Occupational Vulnerability

Identifying Who Is at Risk

• II. Future Workforce Skills

Anticipating the Skillsets Needed in the Future of Mining

• I. Occupational Vulnerability

Identifying Who is at Risk

Career Awareness and Diversity and Inclusion Initiatives

Motivations for LMI

What’s the Challenge?

Effects of technological innovation are unclear; decision-makers need help to make informed decisions.

• Pros:
• Health and Safety
• Cost Reduction
• Productivity
• Environmental Sustainability
• The degree of disruption is uncertain:
• Innovation can partially or fully replace workers by taking over their tasks.
• Innovation can also introduce new job responsibilities.
• New tech requires new skills

demand for labour will depend on skillset.

• New positions will open up, while others may close.
• The workforce’s ability to adapt is still a question mark.
• The timing of disruption is uncertain:
• The pace of adoption of innovation is an important determinant of disruption.
• Difficult to predict how quickly the new wave of innovation will impact the workforce.

Career Awareness and Diversity and Inclusion Initiatives

Motivations for LMI

How do we address this challenge?

LMI can help identify which workers will face the biggest challenges, and who is likely to face them first. We do this with a composite score that gauges occupational vulnerability.

MiHR’s O Occupa pation

• nal V

l Vulner erabilit ility I Index ( (MOVI) I)

1. Points to segments of the labour pool that would most benefit from resources. 2. Allows us to rank mining occupations by vulnerability, and to understand which specific factors/vulnerabilities most affect these workers.

Career Awareness and Diversity and Inclusion Initiatives

MiHR’s Occupational Vulnerability Index

What makes an occupation vulnerable?

Technological Disruption Scope of Innovation Pace of Innovation: Incentives for Disruption Pace of Innovation: Social and Regulatory Obligations Worker Adaptability Transferability of Skills Geographic Mobility

Sub-Themes Themes

Occupational Vulnerability

Career Awareness and Diversity and Inclusion Initiatives

MiHR’s Occupational Vulnerability Index

What makes an occupation vulnerable?

Technological Disruption Scope of Innovation Pace of Innovation: Incentives for Disruption Pace of Innovation: Social and Regulatory Obligations Worker Adaptability Transferability of Skills Geographic Mobility

Sub-Themes Themes

Occupational Vulnerability

Career Awareness and Diversity and Inclusion Initiatives

MiHR’s Occupational Vulnerability Index

Roadmap to Data

Technological Disruption Scope of Innovation

Technical Feasibility of Automation Frey & Osborne Automatability Score

Pace of Innovation: Incentives for Disruption

Market Readiness of New Technology Presence of Tech Disruptive to Occupation Capital Inputs Presence of Commercially Viable Tech Disruptive to Occupation Labour Inputs Industry Share of Spend in Occupation Environmental Incentives Presence of Environmentally Beneficial Tech Disruptive to Occupation Health & Safety Incentives Presence of Safety-Improving Tech Disruptive to Occupation

Pace of Innovation: Social and Regulatory Obligations

Collective Bargaining Agreements Unionization Rate of Occupation Agreements with Indigenous Populations Indigenous Share of Labour Force in Occupation

Worker Adaptability Transferability of Skills

Similarity to Other Occupations Distribution of Occupation across all industries

Geographic Mobility

Proximity of Employment Opportunities Share of occupation in regions with low diversity of industries Human Capital Skill-Level Category

Key Variables Indicators/Proxies Themes Sub-Themes

Occupational Vulnerability

Career Awareness and Diversity and Inclusion Initiatives

MiHR’s Occupational Vulnerability Index

MOVI Scores for 120 Occupations

Statistic Value Observations 120 Mean 0.44 Median 0.45 IQR 0.32 - 0.54 Max 0.75 Min 0.18 Average Mining Industry Score, Weighted by Headcount 0.57

5 10 15 20 25 0.25 0.50 0.75 1 Number of Occupations Composite Score

Career Awareness and Diversity and Inclusion Initiatives

MiHR’s Occupational Vulnerability Index

MOVI Scores in the Workforce

Statistic Value Mean 0.44 Median 0.45 IQR 0.32 - 0.54 Max 0.75 Min 0.18 Average Mining Industry Score, Weighted by Headcount 0.57

2000 4000 6000 8000 10000 12000 14000 16000 18000 0.25 0.50 0.75 1 Number of Workers Composite Score

Distribution of MOVI across Workers

MOVI Findings

Occupational Vulnerability & Headcount of 120 Mining Occupations

TOP 5 Workers Share MOVI Category Underground production and development miners 11035 15.83% 0.75 Production Occupations Heavy equipment operators (except crane) 6830 9.79% 0.73 Production Occupations Mine labourers 2550 3.66% 0.73 Production Occupations Machine operators, mineral and metal processing 1020 1.46% 0.65 Production Occupations Construction trades helpers and labourers 895 1.28% 0.64 Production Occupations BOTTOM 5 Workers Share MOVI Category Human resources managers 400 0.57% 0.18 Human Resources and Financial Occupations Social and community service workers 35 0.05% 0.18 Support workers Financial managers 220 0.32% 0.20 Human Resources and Financial Occupations Engineering managers 125 0.18% 0.21 Supervisors, Coordinators, and Foreman Industrial engineering and manufacturing technologists and technicians 55 0.08% 0.21 Technical Occupations

MOVI Findings

Broad Occupational Categories

Broad Occupational Category MOVI Headcount Professional and Physical Science Occupations 0.39 4545 Human Resources and Financial Occupations 0.40 2675 Supervisors, Coordinators, and Foreman 0.43 9635 Support workers 0.48 5335 Technical Occupations 0.50 4035 Trades Occupations 0.51 11870 Production Occupations 0.69 31635

Supervisors, Coordinators, and Foreman Support workers Professional and Physical Science Occupations Technical Occupations Trades Occupations Production Occupations Human Resources and Financial Occupations 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 5000 10000 15000 20000 25000 30000 35000 Occupational Vulrnerability Score Headcount

MOVI AND HEADCOUNT

MOVI Findings

Spider Charts

II. Future Workforce Skills

Anticipating the Skillsets Needed in the Future of Mining

Motivation

What skills will be needed in the future?

• Observe the specific skills that are being used

in Canada’s mining industry

• Investigate how they might change in the

future

• Focus on the potential impact of innovation and

emerging technologies

Scope & Limitations

• This analysis only considers occupations that

exist today

• This analysis does not predict the future

production mix

• This analysis does not rank skills by importance
• r frequency of use

Retrospective Analysis

Mining has become more capital intensive

20 40 60 80 100 120 140 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Capital input 12 K/L Labour input 6

Source: Mining Industry Human Resources Council; Statistics Canada (Table 36-10-0208-01 Multifactor productivity, value- added, capital input and labour input in the aggregate business sector and major sub-sectors, by industry), 2019

Retrospective Analysis

How has the mining educational mix changed?

Indices of labour inputs by educational attainment: Mining, Quarrying and Oil & Gas Extraction (NAICS 21), (1980−2017)

20 40 60 80 100 120 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Labour input of workers with primary or secondary education 9 Labour input of workers with some or completed post- secondary certificate or diploma 10 Labour input of workers with university degree or above 11

Source: Mining Industry Human Resources Council; Statistics Canada (Table 36-10-0208-01 Multifactor productivity, value-added, capital input and labour input in the aggregate business sector and major sub-sectors, by industry), 2019

Analysis of Workforce Skills

1. Map / attribute skills to occupations

• Use O*NET database
• Thresholds for ‘importance’ and ‘level’

1 or 0 2. Add up the workers in occupations using the skill

• Use Statistics Canada data
• 120 mining-related NOCs
• NAICS 212 (mining and quarrying)

MiHR’s approach to ‘skills’

Skills Mapping ‘Toolbox’ Analogy

Occupation A Occupation B Workforce in NAICS 212

Analysis of Workforce Skills

• Active L

Lear earning: Understanding the implications of new information for current and future problem-solving and decision-

making.

• Comple

lex P Proble lem Solvi ving: Identifying complex problems and reviewing related information to develop and evaluate options

and implement solutions.

• Crit

itic ical T l Thin inking: Using logic and reasoning to identify the strengths and weaknesses of alternative solutions, conclusions or

approaches to problems.

• Jud

udgment an and Dec Decision M Mak aking: Considering the relative costs and benefits of potential actions to choose the most

appropriate one.

• Oper

erat ation

• n an

and Con

• ntrol: Controlling operations of equipment or systems.
• Oper

erat ation

• n M

Mon

• nitoring: Watching gauges, dials, or other indicators to make sure a machine is working properly.
• Progra

gramming: Writing computer programs for various purposes.

• Read

eading C Com

• mprehension
• n: Understanding written sentences and paragraphs in work related documents.
• Troubles

eshoot

• oting

ng: Determining causes of operating errors and deciding what to do about it.

• Writin

ing: Communicating effectively in writing as appropriate for the needs of the audience.

For a complete list and definitions, please visit the O*NET Online database at https://www.onetonline.org/find/descriptor/browse/Skills/

Observing current industry skills

Analysis of Workforce Skills

Forward-looking analysis

Projected share of workforce using skills of interest, baseline and innovation scenarios: Mining and Quarrying (NAICS 212), (forecast to 2030)

Source: Mining Industry Human Resources Council; Statistics Canada (Census 2011, 2016); O*Net Online database, 2019

Career Awareness and Diversity and Inclusion Initiatives

Concluding Observations

• Technological advancements can offer widespread benefits to the sector;
• Technology can positively affect the mining workforce by allowing for more flexible

work practices, enhancing productivity, increasing worker safety, improving environmental sustainability, increasing diversity and reducing costs;

• Understanding which workers are at increased risk of disruption before changes occur

can better equip employers and employees with how to appropriately move forward;

• Continued skills development, education and lifelong learning will enable workers to

adapt to the changing nature of work.

Career Awareness and Diversity and Inclusion Initiatives

Next Steps

• Refine, optimize and validate the MOVI.
• Explore how other countries (i.e. Australia) are using similar tools and for areas
• f collaboration and knowledge building.
• Collaborate with other sectors and industries to develop a multi-sectoral

approach for upskilling/reskilling workers in vulnerable occupations.

• Develop other tools and resources to provide up to date information on

changing skills requirements and occupational vulnerability to our stakeholders.

Questions?

The Changing Nature of Work:

Innovation, Automation & Canada’s Mining Workforce Ryan Montpellier, Executive Director Erin Mills, Director of HR Research & Labour Market Intelligence Jamie Wolcott, Chief Labour Market Economist