• Tue. Nov 24th, 2020



Good Ideas Don’t Last Forever

There are scores of good books devoted to where new ideas come from, but when did you last see anything about where do old ideas go to? There is danger when we are not mindful of an idea’s inherent perishability, and continue on with it well past its prime potency. This is what the avant-garde composer John Cage referred to when he admitted that while many people are afraid of new ideas, he was afraid of old ones. 

When was the last time that you had a good idea go bad? Or, turned for insights to knowledge that you had relied upon, perhaps frequently in the past, only to find that it was no longer so dependable? It happens to all of us. Few things have moved the world so successfully in our times as good ideas; ideas about technologies, about customers, about business models, even ideas about ideas, so it goes without saying, therefore, that all of us should be wondering “how good are my ideas?” Just maybe, however, we should also be asking “how perishable are my ideas”? 

We all build our careers on stocks of knowledge that almost certainly have a limited life expectancy. Left untended, such knowledge can easily go from being professionally powerful to becoming a liability. Good ideas, and the knowledge that goes with them, are not exempt from perishability. Of course, there are no guarantees that a particular idea or insight will age badly or well, but, then again, every time you use an idea, or rely upon a belief, you are betting your future on it, so it stands to reason that reflection on the aging of your ideas merits some judicious attention along the arc of your career. How many MBA programs continue to blithely open their first day with Michael Porter’s famous five-forces approach to industry analysis, despite no longer being able to discern an industry from an arena?

Recently, when I was asked to do a retrospective of my fifty year career in innovation, from engineering in industry and government R&D, in big firms and startups, to academics, I was surprised to learn how the very ideas that I considered foundational at the beginning of my career have aged over time.

Looking back over the years, there were four key ideas that I relied upon over and over again:

1.     I believed that change patterns were predictable in the form of S-curves; after all, this had a long, impressive academic heritage including Kondratieff, Schumpeterian logic and lots of empirical economic analysis. But, what if the curves themselves are not what we once thought they were? When I began my professional life as an engineer, we used S-curves to appraise functional achievement of specific technologies: what will lighting efficiency, or battery performance, look like in five years? What will the tensile strength of different structural materials reach in next decade? Today, thanks to Clayton  Christensen’s insights, S-curves are more often associated with technologists than they are with technologies, they represent not only the evolution of devices, but also periodic upheavals in the industry, or arena, that creates these devices. Christensen’s famous S-curves tell us not only did computer hard-disk-drive technology change over time, but that every so often, new, seemingly unknown producers usurped market leadership with these new technologies. This was a profound change in the way S-curves are regarded, and it’s no exaggeration to suggest that Christensen moved innovation from workshops to boardrooms, making it, for the first time, a dependable strategic asset.

Today, it seems to me that S-curves may no longer even represent technologies at all, but, instead, are better at portraying the customer experiences that an industry, or arena, creates; which calls into question our traditional definitions of both innovation and industry way beyond what we have conventionally assumed. Is the shaving experience, for example, influenced more by razor technology, or new business models; Gillette vs. Dollar Shave Club? The curves remain the same, they look the same, but their interpretation is fundamentally different. As a result, to use my old knowledge stock in its traditional fashion is to completely misread the present, and to introduce additional risk into the managerial choices considered.

2.     A second foundational idea that I relied upon was the idea that the innovation journey could be represented as a funnel, beginning with a trumpet mouth for gathering good ideas, followed by an ever-narrowing path, where internal financial screens cull-out less promising ideas so that a few “best” ideas could go to market. Popularized by a future dean of the Harvard Business School, this model offered the illusion of managerial control over what was otherwise a messy experimental process. As a result, the managerial conversations all too often focused on the measurable screens rather than the unruly customers, or the dynamic market context that the firm was innovating within. Today, in a world where “outside-in” has become the mantra for strategy, we recognize that the linearity and sequentiality of the funnel is perversely inside-out, slow, resistant to the ideas of others, and one where learning only takes place at the end of the journey; none of which is desirable, and so another long-term conceptual tool fades in utility as a result,

3.     Once upon a time, we believed that there was an optimal organizational size for doing invention. This was empirically examined, in the mid-twentieth century by such respected and imaginative economists as Jacob Schmookler, Frederic Scherer and Ed Mansfield, often using patent output as a surrogate for innovativeness, and their results tended to indicate that neither the largest nor the smallest organizations were the most innovative; you could either be too small or too large to be a highly productive innovator. Instead, for most industries, it was somewhere in the middle of a curvilinear relationship between organizational size and innovativeness where the highest innovative performance could be found. I, myself, spent a fair portion of my doctoral research examining this issue and agreeing with the inherited wisdom. Today, however, Open Innovation and Crowd Sourcing threaten to render the very question irrelevant. You can rather easily access the ideas and expertise you need from outside your organization, no matter what its size. To even think about optimal size is a distraction that can lead to bad managerial choices.

Interestingly, however, there is, recently, a new footnote to all of this. In a sign of how idea-popularity can itself be a cyclical phenomenon, we are witnessing a revitalized search for alternatives to bureaucracy that once again are opening-up the question of optimal organization size, not just for innovation but inherently linked to innovative performance, and the new best reply is now: “small, self-organizing and autonomous.”  This is a long way from “somewhere in the middle of firm sizes in our industry”. 

At this point, you might be excused for wondering “Gee, didn’t this guy get anything right?”, but the fourth foundational idea has stayed the course and become big, and it is that:

4.   Innovation is a profoundly social phenomenon. Indeed, what we now see, that this engineer regarded so lightly many years ago, is that it is people who inspire innovation, people who do innovation, and people who adopt innovation, and if we can’t get the organizational issues right, no matter what the size, and if we can’t tune organizational culture to outperform, then all the other questions are, indeed, irrelevant. 

In fact, innovation researchers such as MIT/Sloan’s Tom Allen, and Northwestern’s Al Rubenstein, again in the mid-twentieth century, were establishing that idea-flow into, through and out from an organization, in other words, the very life blood of innovation, was a social, not a structural issue; innovation was all about people, skills and their conversational interactions. This is still very much the case and remains a central part of any innovation story. Don’t fix anything, until you get the people issues right.

So, perhaps the fact that only one out of four of my professional essentials has remained unquestionably reliable is not reassuring, but there’s clearly a theme at work here. Our definitions of innovation are getting broader, not narrower. The outside world is more important than the insider’s organization. Social factors in technological change are as important, if not more so, than the technology itself. I don’t think that I would have appreciated this so clearly if I had not consciously articulated, and then reexamined, what I believe in. It’s important to note, however, that it’s not as if what I had once learned had suddenly gone toxic. Rather, the ideas that are no longer at the forefront of my thinking still serve a powerful role in helping me more deeply appreciate the changes taking place and their implications. John Adams, the composer and creator of “Nixon in China,” and “Doctor Atomic,” recently described himself as becoming something of an archaeologist: “fascinated, and often deeply affected, by how the emotional content of a piece changes as performing traditions evolve.” Such moving forward in a professional field, without forgetting the intellectual history of that field, is good advice for everyone who wishes to remain thoughtfully current.

Professional success today is much more about the learning than the knowing, and then being able to adjust on the basis of that learning. In fact, I originally thought that the title of this article should be “Once I knew it all,” representing my confidence, armed with such sound foundational beliefs, in being able to construct a coherent innovation narrative at the beginning of my career. Now, upon reflection, I would prefer, instead, to suggest: “Once, I knew it all, today I need to learn more.”

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