How Industry-Academia Collaborations Create Impact

• What activities are considered impactful? For industry, they include initiatives that increase organizational capabilities. For academia, they include activities that generate knowledge and make a defined contribution to society.
• Collaborative projects are most likely to be successful if partners track their initial inputs, take specific steps to bring about transformations, and aim to achieve desired outputs.
• Partners can both predict and exploit the outcomes of their collaborations if they understand how their existing capabilities could be extended and enhanced by the mutual exchange of knowledge.

 
Collaborations between universities and businesses have accelerated in the past few years, especially in the areas of innovation, technology transfer, strategy, and policy deployment. These elements spark growth in knowledge-based economies and are increasingly important in developing countries.

Historically, these partnerships have been greatly beneficial to corporations. While companies usually focus on generating higher revenues, cutting costs, refining product offerings, and improving customer service, they frequently turn to universities when they are seeking new ideas, technologies, and ways of doing business. Business schools in particular provide fresh insights and perspectives into social and economic research, enabling companies to generate innovative services, products, and processes.

Academics sometimes don’t realize that such collaborations offer different but equally valuable benefits for universities, a topic that I explore in research I recently conducted with five co-authors. One of the biggest advantages is that these collaborations enable universities to demonstrate the kind of impact they are making in practice and policy in both the public and private sectors. Universities even can predict the potential return on investment for these partnerships, which helps business and management school leaders set their planning and governance strategies.

This is vital because more governments are demanding that universities provide evidence that they are making a positive societal impact. For example, in the U.K., the government seeks to stimulate the transfer of knowledge between academia and industry through schemes such as Knowledge Transfer Partnerships. My co-authors and I believe that, when school leaders thoroughly understand all the benefits, they will make a greater effort to support and facilitate relationships with business.

What Is Impact?

Business and academic leaders have slightly different definitions for what constitutes impact. In a business setting, activities that create impact include knowledge transfer and dissemination, innovation diffusion, product and service commercialization, workforce development, strategy deployment, and technology advancement.

But a business really sees impact when new strategies increase its capabilities in tangible ways that go beyond cost-cutting and incremental performance. Operational improvements have far-reaching effects when they improve efficiency, lead to better working practices and systems, incorporate new technologies, use people more effectively, and result in redesigned products and services. The effects of these improvements can be assessed, measured, and collated.

By contrast, universities most often associate impact with the generation of new knowledge, and partnerships aid that goal in three distinct ways. First, when companies and universities collaborate on projects, their exchange of information creates new knowledge for both organizations. (In the U.K., such projects allow schools to contribute to the increasingly important Knowledge Exchange Framework metrics, which measure the ways universities work with external entities to benefit society.)

When companies and universities collaborate on projects, their exchange of information creates new knowledge for both organizations.

Second, partnerships give professors opportunities to integrate practice-based cases into their teaching materials and give students opportunities to apply theoretical learning to real-world projects. (In the U.K, these activities support the Teaching Excellence Framework, whose goal is to improve excellence in student learning.)

Finally, partnerships provide scholars with the material to write white papers, conference papers, and peer-reviewed journal articles. (In the U.K., this benefit enables academics to contribute to Research Excellence Framework impact case studies.)

Structured for Success

Despite their value, industry-academia collaborations present a range of challenges:

• The implementation process can be difficult to control.
• Collaborations can be undermined by both spillover effect (when unrelated events impact the project at hand) and knowledge creep (when people assume everyone else knows what they know).
• Partners might provide each other with inconsistent or only partial access to appropriate data.
• There will be varying degrees to which employers and stakeholders of the partners will accept, understand, and integrate changes.
• The impact of newly developed organizational capabilities can be difficult to measure.

Industry-academia partnerships are more likely to be successful if the organizations implement two frameworks. One is the “iron triangle” model of project management, which considers the trade-offs between the time, quality, and costs related to any endeavor. This model is useful because it is simple, easily understood, and appears to be applicable in almost every context. Partners can work together to establish the parameters of these three components.

The other is the “input-transformation-output” framework (which I discuss in detail with co-authors Paul Forrester and Iain Reid in the book Essential Guide to Operations Management). With this tool, partners can track what resources exist before they begin working together, how these resources change as the project proceeds, and what results are achieved.

To help businesses and universities understand how to use this framework, my co-authors and I worked with more than 20 organizations to create a model we call Mechanisms for Collaboration, which I outline in detail below.

The Three Phases

Inputs consist of the resources that are available, including knowledge capital, staff, infrastructure, processes and procedures, innovation, suppliers, services, and materials. In our Mechanisms of Collaboration model, we list these common inputs:

• An industry partner willing to change.
• A university partner with the capacity to engage.
• A defined strategic problem or opportunity.
• A dedicated resource or team.
• An agreed-upon project plan.
• An appropriate budget.
• A sense of where the market might head in the short term.
• A transformation strategy known as Plan-Do-Check-Act.

As the project proceeds, transformation occurs when partners:

• Embrace the goal of change.
• Recognize that impact could take 12 to 24 months.
• Acknowledge that they may need to pivot.
• Facilitate the work of the team.
• Generate current data as a baseline.
• Use academic theory and cases as catalysts for developing new products or processes.
• Practice resilient project management.
• Guard against project drift.
• Use appropriate metrics to track progress.
• Document wins as well as areas for improvement.

These transformative actions lead to substantive outputs as the partners:

• Embed change in a sustainable manner.
• Communicate regularly with all stakeholders.
• Check the validity of the metrics of progression.
• Disseminate information about what has been done and how it was achieved.
• Use metrics to record and share ongoing improvements.
• Create an archive to log innovation.
• Celebrate successes by praising people and teams.
• Reflect on what went well and what could have been even better.
• Push forward with more improvements even after the end of the project
• Consider the next project.

This framework stems from our belief that when universities and companies form partnerships without a clear sense of purpose and direction, they are less likely to see tangible benefits. However, when they are aware of—and act upon—the mechanisms of effective collaboration outlined above, they not only will substantially increase the ROI of their interactions, but also will be able to demonstrate that ROI clearly to funding agencies.

Tracking the Benefits

Peter Drucker famously said, “What gets measured gets managed.” When it comes to partnerships between industry and academia, a more accurate phrase might be “What gets measured gets done.”

After we refined our Mechanisms for Collaboration framework, we created a tool that would allow us to chart the progress of projects. Our Knowledge and Impact Flow Matrix is an extended version of the Ansoff Matrix that identifies growth strategies.

In essence, our matrix tracks the capabilities and the resources of both the university and the business as they work in partnership. Capabilities might be external aspects such as customers and technologies; resources might include knowledge capital, staff, procedures, infrastructure, or services.

Both capabilities and resources are defined by whether they are existing, extended, or new. Existing capabilities refer to the services, sales, or processes that are already in place. Extended capabilities are those that an organization might realize by offering improved services or delivering greater efficiencies. New capabilities describe what the organization could achieve if it served different customers, offered different services, or underwent a fundamental restructuring.

By charting the flow of information between them, both the university and the company can predict and exploit the opportunities they have when they collaborate.

In a collaboration, knowledge flows between one partner and the other. For instance, the university might share some of its proprietary extended knowledge with the company. By incorporating that knowledge into its existing processes, the company develops an entirely new capability. The university can study the effects of that new capability, potentially developing new resources of its own.

Here’s an example. Say faculty at a university understand how to use a decision-making framework such as the Analytical Hierarchy Process, and they show company executives how to use the framework to make better-informed decisions when selecting suppliers. The professors and the executives work together to co-develop a bespoke product or service that the company can offer. The company gains a competitive edge in its industry and sector. The university gains knowledge about the real-world application of a theoretical framework, and faculty can incorporate this knowledge into classroom learning.

By charting the flow of information in this way, both the university and the company can first predict and then exploit the opportunities they have when they collaborate. Such a model gives a tangible shape to the intangible concept of impact.

What Next?

Today, governments and funding organizations want evidence that they will see a return on investment when they support collaboration between businesses and educational institutions. Therefore, it is more important than ever that universities reliably prove or predict what kind of impact a partnership will have. The tools described here offer a vital step toward this goal.

We know that impact occurs much faster when collaborators employ specific policy templates such as Knowledge Transfer Partnerships. We also know that collaboration is most successful when it is actively facilitated by both partners, who provide collective input and inspired co-creation. Therefore, we conclude that business school leaders must make such collaborations a strategic priority if they want to transform their institutions—and make an impact on society.