Editor’s note: This is the eleventh article since May 20, 2026 in an ongoing series by Dr. Andrew Maxwell, the Bergeron Chair in Technology Entrepreneurship in the Lassonde School of Engineering at York University. Every week – and occasionally every other week – we’ll present a new article by Maxwell, in a series whose wide-ranging and incisive themes encompass: Canada and innovation policy; productivity and industry; innovation frameworks; AI and higher education; research and intellectual property; technology adoption; entrepreneurship and commercialization; universities and higher education; entrepreneurship education; and AI and the future of work. 

 This is Part 1 of a two-part series on rebuilding competitiveness through culture, capability and system alignment. Part 2 will be published on August 19, 2026.

 By Andrew Maxwell

We know how to measure productivity outcomes, but we still struggle to understand what truly drives them.

Despite world-class research institutions and record public investment, Canada’s productivity continues to lag. The missing ingredient may not be more research, but a deeper cultural shift in how we value and pursue improvement.

1. The comfort of simple solutions

When productivity stalls, our reflex is predictable: increase research funding.

It feels right. It’s visible, measurable and politically safe.

Yet despite record investments in science and engineering, Canada’s labour productivity has grown by only 0.3 percent annually since 2015 (OECD 2024). We are not short of world-class research; we simply have not learned how to leverage it effectively.

Productivity – the efficiency with which an economy turns ideas and effort into value – is measurable, but not linear. Canada continues to treat productivity as the direct output of research, as if invention and innovation automatically translate into economic growth.

The truth is far more complex: productivity is an emergent property of a dynamic system whose elements – technology, institutions, incentives, capability and above all culture – interact in subtle, powerful ways.

2. Seeing productivity as a system

System thinking encourages us to look beyond single causes and see productivity as the product of relationships, not components.

Technology, skills, incentives, governance and culture all influence one another through reinforcing feedback loops.

A new technology changes labour demand; new skills reshape management; fiscal policy alters investment; and cultural attitudes toward risk, collaboration, and improvement determine how – or whether – new ideas take root.

Linear “fixes” miss these interactions. System thinking replaces the search for a silver bullet with the search for alignment.

3. Five interacting drivers of productivity

Economists and policy researchers – from the OECD, the Centre for the Study of Living Standards (CSLS), and scholars such as Nick Bloom, John Van Reenen, and Andrew Sharpe – converge on five mutually reinforcing drivers. When viewed through a systems lens, culture emerges as the foundation that shapes all others.

Productivity depends on how these drivers align and reinforce one another:

• Culture
• Capability
• Incentives
• Institutions
• Technology

4. Culture: The foundation of productivity

Culture – the shared norms, beliefs, and expectations that guide how we collaborate, take risks and learn – is the soil in which productivity grows.

Countries that reward experimentation, celebrate continuous improvement and tolerate failure outperform those that prize safety, consensus and short-term returns. As Sharpe (2022) notes, culture provides the behavioural foundation of growth.

Canada’s culture, for all its strengths in fairness and consensus, can sometimes lean toward caution. We celebrate discovery more than deployment, excellence more than efficiency. We reward scientific breakthroughs and publications but rarely celebrate modest process improvements that enhance productivity on the ground.

Can culture change? Yes – but rarely through persuasion alone. Change is driven by need.

Competitive pressure and opportunity in new markets force adaptation; necessity erodes complacency.

Incentives and metrics reinforce these shifts – what gets measured, and rewarded, changes behaviour. Over time, as more organizations adopt productive habits and share success stories, culture evolves.

To improve productivity, we must cultivate a culture that values continuous improvement, rewards adoption and sees productivity not as a technical problem but as a social commitment.

5. Capability: Turning culture into competence

Even the most supportive culture fails without capable people and organizations.

Bloom and Van Reenen (2010) found that management quality explains up to 30 percent of productivity differences across firms. Training, leadership and teamwork determine whether technology translates into performance.

Yet Canada invests little in management development or the soft infrastructure of collaboration.

Capability is where culture becomes practice – the translation of beliefs into skills. When organizations commit to learning and experimentation, their absorptive capacity expands, enabling them to adopt technologies faster and adapt to changing markets.

6. Incentives: Aligning motivation and measurement

Rules and rewards shape behaviour.

The Bank of Canada (2023) and OECD Economic Survey (2024) both highlight how low competitive intensity and limited reinvestment have dampened innovation.

Incentives – tax credits, procurement policy, and regulatory design – signal what matters. If incentives favour safety and short-term returns, firms behave accordingly.

A system thinking approach to productivity recognizes that incentives must reward adoption, not just invention

 Accelerated depreciation for technology adoption, diffusion-focused R&D credits, and performance-based public procurement could shift the balance. Incentives are the levers through which culture changes faster than rhetoric.

7. Institutions: Connecting discovery and diffusion

Institutions – funding agencies, ministries and intermediaries – determine how knowledge moves through the economy.

Germany’s Fraunhofer Institutes, Finland’s VTT, and Korea’s KITECH bridge discovery and application by identifying industry needs, coordinating applied research and ensuring diffusion.

Canada’s institutional landscape remains fragmented: multiple ministries, overlapping programs and few mechanisms to connect discovery to deployment.

Some promising models – such as Technology Access Centres – hint at what’s possible. Yet to move from pilot to system, we must treat productivity-oriented work as its own legitimate space within the research enterprise, not merely an extension of discovery research.

8. Technology: The visible but over-emphasized lever

Technology remains critical – but adoption matters more than invention.

The OECD Digital Economy Outlook (2023) shows that the gap between frontier and follower firms stems primarily from slow diffusion of proven technologies. For every breakthrough, thousands of organizations fail to implement it due to missing skills, infrastructure, or incentives.

Technology is the spark, not the engine. Productivity rises through broad diffusion, not isolated invention.

9. Why research still dominates the conversation

If we understand all this, why do we still treat research as the master key?

• Visibility and metrics: Research spending is easy to count; diffusion, management quality and culture are not.
• Institutional design: Universities reward funding and publication. Few incentives support diffusion, engagement or adoption.
• Political simplification: “Investing in science and research” sounds visionary and straightforward; improving productivity sounds mundane and business-like.
• Misunderstanding research diversity: We rarely distinguish between curiosity-driven and productivity-oriented research. The result is misplaced expectations: we expect a publication-driven system to produce productivity gains.

10. Creating space for productivity-oriented research

Discovery research and productivity-oriented research are both social processes – but they pursue different goals.

Discovery research expands knowledge and reputation within scholarly communities. Productivity-oriented research investigates how knowledge becomes value: how organizations adopt innovation, how incentives work, how collaboration improves outcomes. It is, in essence, research on research and research on adoption.

Embedding this inquiry within Canada’s research ecosystem would give legitimacy to the study of productivity itself – its drivers, barriers and behavioural dimensions. Understanding how people and systems change is as vital as discovering new technologies.

11. The missing social science of productivity

Innovation and adoption are human processes, often enhanced but not determined by science and technology.

As Everett Rogers (2003) showed, diffusion depends on trust, norms and perceived benefit – not technical merit alone. Behavioural economics explains how bias, inertia and uncertainty affect decision-making. Yet policy continues to treat innovation as an engineering pipeline rather than a social process.

The OECD Innovation Strategy (2023) reminds us that “the diffusion of innovation is primarily a social process.” To enhance productivity, we must integrate the behavioural and social sciences with engineering and economics, creating a science of adoption that studies how ideas spread and systems evolve.

12. Shared responsibility for a systemic challenge

At the heart of the productivity challenge lies culture: society shapes the soil in which innovation either takes root or withers.

Government establishes the fiscal, regulatory and infrastructural conditions that reward modernization. Industry decides whether to reinvest profits in capability or protect margins through inertia. Academia generates knowledge and talent – but must also learn how discovery enters real-world systems.

When one part under-performs, the entire system under-delivers. Productivity is everyone’s job – and no one’s alone.

13. From linear thinking to system learning

A narrow focus on research funding offers the comfort of measurable inputs without confronting the complexity of outcomes.

System thinking asks harder questions:

• How do technology, incentives and culture interact to enhance productivity?
• Where are the weakest connections between research and adoption?
• What forms of research yield the greatest leverage for systemic improvement?

Answering these questions demands collaboration across disciplines – and humility about our assumptions.

14. Looking ahead: Motivating cultural change

True productivity growth begins not with new programs, but with a new mindset.

We must first change how we think about productivity. Improvement requires motivation grounded in necessity and opportunity.

As global competition intensifies, Canadian industries that adapt and invest in improvement will thrive; those clinging to legacy practices will fall behind.

Embedding productivity thinking into our national culture – through incentives, education and visible success stories – can make improvement a shared value rather than a policy objective.

In Part 2 , I’ll explore how universities and funding agencies can strengthen the connections between discovery, people and adoption – transforming knowledge into measurable value.

References

• OECD (2023). OECD Productivity Compendium.
• OECD (2023). Innovation Strategy for a Digital World.
• OECD (2024). Science, Technology and Innovation Outlook.
• Statistics Canada (2023). Multifactor Productivity Trends.
• Bank of Canada (2023). Structural Factors Behind Canada’s Productivity Challenge.
• Sharpe, A. (2022). The State of Productivity in Canada. CSLS.
• Bloom, N. & Van Reenen, J. (2010). Why Do Management Practices Differ Across Firms and Countries? J. Econ. Persp. 24 (1).
• Rogers, E. (2003). Diffusion of Innovations (5th ed.).
• Institutional models: Fraunhofer (Germany), VTT (Finland), KITECH (Korea).