As I find myself back in Poland to deliver another round of training courses on entrepreneurship to university researchers, I’m reminded of Steve Blank’s fireside chat at the AUTM® national meeting in New Orleans last month. Specifically, I’m thinking about how the feedback loop that plays a major role in the Lean Startup methodology also has a role to play long before a startup is even a gleam in an entrepreneurial researcher’s eye.
What’s the Lean Startup feedback loop? Well, according to Eric Ries:
The fundamental activity of a startup is to turn ideas into products, measure how customers respond, and then learn whether to pivot or persevere. All successful startup processes should be geared to accelerate that feedback loop. [emphasis mine]
In Lean Startup terminology, this is the build-measure-learn feedback loop. The feedback is relative to a minimum viable product (MVP), which contains just the features that are hypothesized to be essential to customer interest. Getting feedback on the MVP before investing heavily in the full product’s development ensures that, if your product is going to fail, it fails early, allowing you to conserve your resources to pursue other opportunities.
As Laura Schoppe suggested in her AUTM 2015 highlights blog post, all of this is directly in line with proactive management of the innovation/intellectual property (IP) portfolio.
In fact, there are many striking parallels between the Lean Startup principles and best practices for technology transfer.
Fail Early = Screen First
- In the Lean Startup method, part of the goal is to learn as soon as possible if an offering is likely to fail.
- In technology transfer, rapid triage is followed by in-depth assessment of a technology’s market potential. (You can see this mapped out in our Road to Technology Transfer infographic.)
As an example in tech transfer, Fuentek uses a multi-stage process to evaluate client technologies. First, we perform a screening to see if the technology is fit for commercialization. Those that pass the screening ramp up for marketing, which includes a strategic analysis of the market. This cost-efficient approach ensures that those technologies with the highest market potential proceed down the tech transfer road.
Product Value Proposition = Technology Overview
- In the Lean Startup model, the value proposition focuses on what the product does for the target customer.
- In tech transfer, technology evaluation focuses on what the invention does for the user.
At Fuentek, we call articulating the value proposition of a technology the Technology Overview, and you can access a webcast about it here. (The webcast is free; all you have to do is register.)
BTW, Alex Osterwalder’s Value Proposition Canvas could serve as a helpful tool for principal investigators (PIs) to use in thinking through and articulating their technology’s benefits for the user. (At the AUTM meeting, Steve Blank suggested using the Business Model Canvas in this way, but I think using the Value Proposition Canvas is much more realistic.)
Feedback on the MVP = Expert Interviews on the Technology
- In the Lean Startup model, the target customer provides feedback on the MVP, enabling adjustments to be made that increase the product’s potential for success.
- In tech transfer, interviews with industry experts provide feedback on a technology’s commercial potential and what is needed to increase that potential.
More from Becky on the topic of gathering valuable customer feedback has been published in the New Hampshire Union Leader.
Time and again, when we have conducted market research and gathered competitive intelligence on a technology, we’ve gained insights about what the market really needs in order to be interested in that technology. It could be minimum performance specifications or test data or price points. This feedback — which can be used by the inventor to improve the technology to better meet the market’s needs — maps nicely to the build-measure-learn feedback loop.
Applying the Principles to… Research
Ironically, these parallels have been made manifest in the entrepreneurship training we’ve been doing in Poland. During the training, we have been teaching researchers the essentials of how to define a business model, develop a business plan, and secure funding. We introduce them to the key concepts of entrepreneurship — evaluating a business opportunity, determining if market characteristics are favorable for a startup, and so on.
But before all of that, we help them get grounded in these concepts by teaching them how to analyze their own innovations and ideas. We teach them how to identify market dynamics, where their innovation fits in the value chain, who the key players are currently, and the critical factors that will determine whether commercialization is likely to succeed or fail so that they can focus their efforts each step of the way.
An interesting outcome of this approach to entrepreneurship training is that it also has implications for research, as revealed in these comments by several training participants:
“I intend to discuss with my lab how we should refocus our work a bit to be more relevant to the intended users.”
“I think that all the information will help [me] to faster get my goal and be more open to commercialization of my ideas.”
“I especially appreciate the part on Technology Overview, which in my humble opinion is extremely important to scientists.”
To me, the take-home message is that teaching researchers to approach their work more entrepreneurially has benefits even if they do not get involved in a startup company. And that’s particularly important because not all technologies are best commercialized through startups, and not all researchers are interested in starting companies.
Entrepreneurial thinking has benefits regardless.
Note: Fuentek is providing these courses under contract with the Foundation for Polish Science, with co-financing by the European Union within European Social Fund.