Upon entering a new year, we decided to compile a list of top innovation insights that we either learned or experienced in 2017. For others pursuing entrepreneurial efforts in 2018, we hope you find these highlights helpful:
Constraints push innovation: This might initially seem counter-intuitive, but specific innovation examples where this proves true have been cited by prominent tech leaders such as Navi Radjou and MIT’s Amos Winter. In the DC government contracting space or even in the Silicon Valley culture that Radjou references, the idea of requiring more budget as a prerequisite to accomplishing goals doesn’t necessarily have to be so - monetary constraints might actually be what it takes to get us to our finish lines.
Successful innovators have an ability to perform associative thinking: The ability to connect seemingly unrelated fields or topics - associative thinking - was discovered by prominent business and academic leaders as one of a handful of other skills inherent to the successful innovator*. In our professional experiences, associative thinking has been at the core of multiple, successful start-ups that we’ve worked with. For example, foreign language and technology, deep learning and cybersecurity, natural language processing and cybersecurity - the individual elements in each of these combinations are not related to its pair, yet the combined results have made for some truly innovating and breakthrough technology.
The aforementioned associative thinking finding also corroborates what a CEO of a Fortune 500 company once publicly stated when asked what skills she was looking for when hiring: her ideal candidate was one who had a STEM/tech-oriented background but who had also earned a minor or concentration in something completely different. Perhaps what this CEO was really looking for was an associative thinker whose skills were resultant of such mixed studies (but mixed studies aren't necessarily the only method for acquiring associative thinking skills).
Distribution is a vital, yet commonly overlooked, facet of a start-up: As prominent VC firm Andreessen Horowitz published in an online blog: “The battle between every startup and incumbent comes down to whether the startup gets distribution before the incumbent gets innovation.” In the physical world, the use of 3-D printing, drones, and ‘smart cars’ are just a few examples of how traditional distribution methods are being disrupted - perhaps innovators can investigate these as not only viable methods, but ones that might ensure their incumbents don’t beat them to the punch.
For distribution in the software world, Apple’s app store and the AWS Marketplace are two prominent outlets for distributing consumer and enterprise-level software, respectively. More narrow than AWS Marketplace and relevant to the DC cyber ecosystem (and really the cyber ecosystem at-large), is an online cybersecurity marketplace, WhiteHawk, that helps cyber users and stakeholders navigate an overwhelmingly crowded product area - perhaps this is just the right sort of a venue for a new cyber start-up to be distributing their software because it’s presumed WhiteHawk’s user base already hails from the exact audience that cyber companies are trying to reach.
The significance and importance of data remains: “Data is the next oil” - this has been a frequent statement proclaimed by many business executives since the emergence of ‘Big Data’ several years ago, but can we still claim data as such? Based on work we did in data breach detection at the beginning of this year along with the multiple, high-profile ransomware cases that followed, data was certainly the oil that fueled cyber criminals in 2017.
As for more productive uses of data, multiple Fortune 500 manufacturing executives mentioned their desire to transform their own, internal data into actionable, consumer products - a construct that will enable them to generate new revenue sources while remaining competitive and relevant. We also heard a presentation given by Google’s Director of Applied AI, Scott Penberthy, on how AI has reached a point where it’s now capable of building AI itself. In other words, Google has developed AI that can create AI better than humans - try and wrap your head around that for a minute.
When stuck on a problem, look to design thinking: We were made aware of a concept called ‘design thinking’ while pointed to a Stanford University professor, Bernard Roth, who is an expert in this very topic. When stuck on a problem, Roth’s guidance is to simply reframe it by asking yourself what solving the problem would do for you. When answered, ask yourself again how else you can achieve the same solution - doing this will not only help you realize that you were most likely trying to solve the incorrect problem to begin with, but it will also open entirely new solution space for you.
Of course, there are multiple other innovation insights from the previous year that could be added to this list - these are merely our top choices. Perhaps you can find a way to apply these insights into your innovation endeavors for 2018. Cheers to a great upcoming year!