Adam Cowart is one of our Emerging Fellows, and this is his eighth article written for the program. In it, he explores scenarios. The views expressed are not necessarily those of the APF or its members.
Previously we have challenged what is truly innovation (depending on how you parse the definition, maybe nothing!), and the challenges of systems wide innovation. We can now introduce 4 possible scenarios (among many, many others) to begin to conceptualize what the future of innovation looks like:
1. Baseline. The baseline scenario has organizations, governments, and economies continuing to muddle through. Some continue to sub optimize and exist, others innovate to various degrees, others are shape shifters, able to leap from one new industry to another, evolving as they go along. Over time, we become more fluent in the efficiency and quality of innovation activities, using such measurements as research quotients (RQ), developed by Anne Marie Knott, that measure innovation inputs and outputs to gauge success. Innovation as disruption is still seen as the gold standard, though large, mature firms still struggle with whether to embrace or suppress these disruptions. Innovation is still largely situated.
2. Systems-Bound Mutual Self-Interest: A greater understanding of systems, and systems literacy, coupled with virtual and software based platforms and physical innovative cross-disciplinary spaces point to less sub optimization and unproductive situated innovation. Instead, organizations will bond together in mutual self-interest (perhaps making some a bit uneasy as self-organization looks a lot like vertical integration and monopolization). Definitions of competition and anti-trust will be rewritten and new measurements of social good will come to eclipse GDP as the primary measurement of innovation and economic health.
3. Double-Down on Sub-Optimization and Quick Profit. The insatiable thirst for quarterly profits points to a future of sub optimization that shows no signs of disappearing. In an effort to stimulate the real economy, governments implement varying policies of charging demurrage on the financial market, charging fees or taxing capital that isn’t being used in “productive” ways. This will increase available capital for reinvestment. However, instead of increasing innovation and productivity, it could simply “feed the beast” of sub optimization. Especially when coupled with the relentless focus on quarterly returns, on “maximizing value”. In a world where capital must be reinvested in the firm, the resultant behavior could involve a great deal of tire spinning, or more precisely, short-term cycles of excessive value extraction meant to replicate share buy-back schemes and large dividend payouts. This, coupled with rapid rise and fall “fad” industries, make for rapid boom-bust cycles globally. Think of it as shifting the burden on overdrive.
4. The Rapid S-Curve Economy. Organizations become increasingly amorphous, shape shifters that are constantly seeking out new emergent industries, colonizing them rapidly, then moving on once the industry matures. And the maturity of the industries is also rapid. Organizations become almost nomadic. With either large or scarce reserves of capital for innovation and expansion, organizations move to rapidly create and capitalize on opportunities; one or two players prove successful and monopolize the space; the rest move on to find greener pastures.
What to do? The answer may be in the form of government policy. Governments are still the primary investor in risky innovative endeavours. When will investment programs and structures be put in place to invest in systems wide innovation? Even if it is still sub optimized within the nation-state?
Perhaps this is all just an elaborate way of saying that innovation is messy, often fails, and even when successful we can’t be sure of what positive and negative externalities it will cause. Ultimately, sub optimization is inherently a product of innovation. By correcting one problem we create others. Not all problems are created equal, of course, and we would prefer to have certain problems over others – for example, all the side-effects associated with medications we choose are an unfortunate but necessary trade off. We are both selfish in the sense that we view progress from our own situated perspective, and we are utilitarian in the sense that we generally hope that any negative outcomes of innovation will be less than the derived benefit.
We are left with a future where the nature and impact, not to mention the consistency and payback, of innovation, creating results by doing new things, is unclear. Will we move towards increased sub optimization or will we create and adopt the social technologies we need to generate deep structural results?
© Adam Cowart 2018