[Panel Question 1: How to make accessible the knowledge of AI researchers and experts to Quebec’s industries and SMEs?]
Transferring knowledge from academia to industry is a long-existing problem because each operates in separate bubbles. Academia wants to solve cool technical challenges, while businesses want to maximize profit.
Once a business reaches the point where it is making a profit from a process, this becomes a core capability, which can only be changed by risking the business’s cashflow. Of course, this is the last thing they want. This resistance is the main obstacle to corporate innovation.
There are three issues that come up when considering how to make accessible the knowledge of AI researchers and experts to industry and SMEs:
– The company’s willingness to innovate;
– Maintaining the company’s core vs innovating at the edge; and
– The innovation value chain, or how new practices diffuse through the organization.
WILLINGNESS TO INNOVATE
Nathan Furr and Jeffrey Dyer in their book “The Innovator’s Method”, state that the biggest obstacle to adopting innovation in a company is social – the organization’s willingness to deal with uncertainty. Leadership talks about innovation, however when it comes to dealing with the risk of innovation, they tend to pull back because of the risk to the current business model.
Infusing a culture of innovation in business requires a change in management mindset. Instead of setting bold goals to transform the company, innovation is an experimental, iterative process that requires management to step aside. Management has to change from making decisions to asking questions and giving people the right resources to find the answers.
Academia must recognize that just showing up with answers won’t overcome industry’s resistance to change. Researchers need to work with industry partners early on, through low-risk pilot projects to learn what works and doesn’t in real-world applications. Case studies from these projects give management the confidence to expand the innovation to the larger organization.
Successful corporate innovation succeeds not because of big bets, but because they’ve learned to manage risk.
EDGE VS CORE
A venture’s core competency is what the company does most efficiently and effectively. The core creates profits and cash flow, which must be protected at all costs for the company to survive.
The edge is the boundary between what the company can do and what it can’t. One of my favourite business thinkers, John Hagel III, explores how change takes place within companies, from edge to core. He describes the edge as where technological innovations begin to offer new capabilities that a company can consider integrating into its processes and its products.
Edges are where unmet customer needs and unexploited capabilities first appear on a company’s radar. Team members connected to what’s happening at the edge bring new ideas to the core. Collisions between academia and industry tend to happen at the edge.
However, where edge participants see limitless possibilities, management’s conservative tendencies perceive a threat to the core. Management does not want creative destruction. Overcoming this resistance means bringing the core closer to the edge. Academia can be a bridge to expose management to value innovation and new technologies that are emerging on the edge.
Management’s responsibility is to find the alignment between what the edge perceives and what the core needs to improve its ability to execute the business model and generate continued cashflow. As the edge gains a credible voice in the company, the organization becomes more agile and less vulnerable to environmental and market uncertainty.
INNOVATION VALUE CHAIN
Innovation adoption in a company is a gradual process. Morton T. Hansen, the author of the book “Collaboration”, has found that ideas communicate through an organization in a three-step innovation value chain:
– Step 1: Idea Generation – ideas usually happen at the edge but can also happen at the core as people see better ways to perform existing processes;
– Step 2: Idea Conversion – the screening mechanism to select new ideas and execute test cases; and
– Step 3: Idea Diffusion – getting support from the core and the whole organization to adopt the idea.
A company’s capacity to innovate is only as good as the weakest link in this chain.
Academia must recognize that even though they see how the technology innovation can help the company, the company needs to go through the full sequence to integrate the innovation into their processes and products. This takes time to show results. In addition, there are many points where innovation adoption will fail.
HOW TO FACILITATE KNOWLEDGE TRANSFER
The public sector has an important role in bringing together academia and industry and facilitating the diffusion of innovation from edge to core. A primary mechanism, used where I work at NRC’s Industrial Research Assistance Program (NRC-IRAP), is providing targeted advisory services and financial support to enable industry to take risks. I especially like using our “Accelerated Review Process”, or “small IRAP”, to support quick test case sprints of 3 to 6-month duration.
The government also plays a role in fostering more creative collisions between academia, the edge and the core of industry through targeted challenges, calls for international consortia and innovation clusters such as Scale.AI.
Successful knowledge transfer from researchers and academia to Québec’s industries and SMES starts with a willingness to step outside of our bubbles and work together to strengthen our cores, while reinventing them to create the future we really want.