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Innovation Meets Scale

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Hill88 helps corporates optimize their innovation strategy and helps early stage startups scale their revenue and business operations.

About That Good Idea...

As described in a recent WSJ article, Wharton professors Christian Terwiesch and Karl Ulrich decided to run a small experiment to see who was more innovative: their MBA students or ChatGPT. The students and the computer were each asked to generate 200 ideas for products that would appeal to college students. Well, ChatGPT won by a landslide. A panel of customers judged the submissions, and ChatGPT had generated 35 of the top 40 ideas. I wasn’t really surprised by these results for the following reasons:

  1. Large Language Models (such as ChatGPT) are trained to sound smart. So… naturally, the short descriptions from ChatGPT will be judged as smarter!

  2. MBA students are not that great at generating new ideas. They should have asked the engineering students, or even better, a cross-functional team.

  3. Ideas are cheap, it’s the execution that counts - which includes steps such as productization, commercialization, and business model optimization.

The last point is really the most important. While I still run into some entrepreneurs that are reluctant to share their product idea, most are eager to tell their story, and how their idea will change the world. As they make their rounds in Silicon Valley describing their vision, they attract co-founders, experienced advisors, early investors, and first employees – while also receiving and incorporating feedback with every conversation. After obtaining their first investment capital, they apply Design Thinking and Lean Startup methodologies to build product prototypes, generating additional feedback that leads to more changes and perhaps even a pivot. When they have finally nailed the idea, they can raise venture capital to scale their fledgling startup into a company.

Does this brainstorming experiment imply that ChatGPT will eliminate our innovation jobs? The authors advocate that instead of fearing this new class of AI, we should adopt it as a new tool to supplement our efforts - that's becoming a common refrain across many knowledge work sectors. And on the execution front nobody needs to worry... yet.

But there is another important takeaway for those that work in corporate innovation. Paul Campbell and I have been spending a lot of time researching how to improve impact within the corporate innovation center. A key culprit is that even the best ideas tend to die on the vine as they attempt to scale up within the corporation. When corporate leadership designed the overall processes for how an innovation center fits within the organization, they had a similar misconception as that WSJ article may imply: it’s all about finding that good idea – the rest is easy. It turns out that the corporate innovator has an even harder job than the startup entrepreneur. Not only do they need to perform the startup entrepreneur tasks I described above, but as they try to scale their proven idea within the company they will encounter the real headwinds - those generated by their internal R&D groups, division heads, and corporate controllers. In the startup world, a good idea attracts interest and money - in the corporate world, an idea will attract more and more “anti-bodies” as it gets better.

Is there a “holy grail” process that allows new projects to thrive and scale up within the corporation without interference? We haven’t found it yet, and the reason may be that each corporation has developed a unique culture – thus it may require a unique process and structure to eliminate its innovation anti-bodies. Perhaps you’ve uncovered the holy grail? Or your good ideas keep dying on the vine – I’d like to hear from you to further test our hypotheses – we might also have a tip or two for you in return…

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