When looking towards Silicon Valley, global executives might think of icons like Zuckerberg and Musk as possessing some kind of inimitable magic. In doing so, they miss the point that much of what Silicon Valley does is indeed imitable, and even more so today with the advent of what we call boundary-less innovation.
Let’s begin with a brief tour of how technological innovation drives disruption.
In Dealing with Darwin, Geoffrey Moore suggested that innovation comes in many forms.
However, only technological innovation has the potential to be truly disruptive. And whilst disruption has been maligned of late as kind of faux-concept, we simply mean the methods by which it is possible to obtain potentially exponential growth in any element of business that matters.
Disruptive innovation comes from creative technological thinking of the sort exemplified by Silicon Valley start-ups. It is partially driven by a cultural attitude, but more importantly for our argument, it flows from deep technological competence, mostly in software.
Business pundits talk about Airbnb, Uber, and so on, as being disruptive in the market sense because these companies have reimagined market dynamics, per the “sharing economy” mythology. However, beneath these achievements lies hardcore engineering.
Moreover - and this is important - it is not just hardcore in the sense of using the latest mind-blowing technology. It is creative enough to reconfigure and invent technologies that facilitate “Blue Ocean” differentials, such as Uber’s dispatch algorithms (which they consider the “boss” of their drivers).
Airbnb is a similar story. On the surface, their app is a simple way to find lodgings of a variety and price that Hyatt cannot compete with. However, this apparent simplicity taps into a deep well of technological complexity, like dynamic pricing that is highly localized to micro-regions and demand fluctuations.
Instacart appears to be nothing more than grocery deliveries. However, it succeeds in offering customer choice because of sophisticated real-time tuning of voluminous data that emanates from a multi-sided network of drivers, shoppers, vendors and customers. The technical challenge is only solvable by discovery of data patterns using Apache Spark out of UC Berkeley where many stories like Instacart’s were recently shared during a data science conference.
So how does an executive outside of Silicon Valley obtain his or her own tech innovation lab?
The answer is remarkably simple. Create one - on demand.
Our argument is that any business is highly susceptible to potentially massive gains via the laser-guided application of modern software technologies in-house.
Putting it one way: what might be possible if Hyatt re-imagined their hotel services through the eyes of a team of AI gurus. Or, putting it another way, what would Google do if they were Hyatt?
Assuming this might be a useful prospect, the next question is why in-house?
In a word: agile.
But we don’t mean the software (and lately project) methodology.
We do mean the orders of magnitude speed advantage that comes from aligning the frontier of business innovation with the frontier of technological innovation right inside of the organization, avoiding translation losses across organizational barriers.
We do mean the invaluable advantage of combining the design-thinking discovery of a business facet amenable to technological innovation with the discovery of technological possibilities that might make it amenable.
So how is this possible if you’re not Google?
Three emergent trends are changing the innovation landscape: boundary-less talent, boundary-less organizations and boundary-less IT. Together, they enable boundary-less innovation.
Boundary-less talent is what Interpret-design's advisor Jon Younger refers to in his seminal book (of the same name) as Agile Talent.
Given the pivotal role of technological talent in the new software landscape, it’s not surprising that the work goes to the talent and no longer the talent to the work. Jon’s book gives a thorough analysis of the trends and a well researched vision of its transformative potential for the future of work.
As an aside, Chuck Robbins, the CEO of Cisco, has openly spoken of a future in which only the C-suite executives and support staff are permanent employees of the giant Cisco corporation. Given Cisco’s commitment to networked technologies and virtual meeting technologies, this is hardly surprising.
Let’s be clear that the talent available via platforms like Toptal is a global pool of developers and designers pre-screened (at 0.5% acceptance rate) via rigorous interviews and competency tests. They really are top talent.
The goal of all these platforms, including the Business Talent Group that sources top innovation and product managers, is to curate entire teams ready to go. Indeed, this is already Gigster’s focus.
There are significant tributaries to the talent pool, such as coding bootcamps like Hack Reactor and online “nanodegree” platforms like Udacity (that even offers a nanodegree in self-driving car technology), but let’s skip these for now and examine the next emergent trend of boundary-less organizations.
Leaving aside the “Silicon Valley” companies, like Github, that are entirely distributed with virtually no central office, the speed of business demands assembling talent from multiple locations without the overheads of physically moving them.
And should physical space be needed, even for a short while, work-nomadic services like We Work (and now We Live) are sprouting up across the globe, yet again bringing the work to the people (in their metro cultural zones) and no longer the people to the work.
Moving the work to the talent has also been greatly facilitated by the emergence of highly efficient connected services like Slack, Cisco Spark and myriad collaborative tools that bring “the room” to the meeting rather than the meeting to the room, further enabling boundary-less organizations.
Moreover, there is about to be an explosion of innovation in this area as a shift occurs from connected services to cognitive services whereby AI will help team members to remain focused on what really matters amidst growing streams of data (and distraction).
Lastly, but easily of greatest significance, is the emergence of boundary-less IT which goes way beyond the mere blurring of IT boundaries as many business functions migrate to the cloud.
Boundary-less IT operates on a number of scales, but it is the obliteration of scale itself that matters. The most innovative example is the emergence of serverless software services like Amazon’s Lambda service.
Let’s imagine that a newly deployed Hyatt innovation lab, thanks to some Gigsters from Spain and Iceland, devises a key software function to predict how to maximize the profitability of a radical new idea to create pop-up hotel spaces, taking into account demand, real-estate data, short-term leases, contractors and a large set of variables.
Traditionally, the challenge with deploying such software has been the dominant effort in configuring, managing and deploying infrastructure, such as servers, databases and other plumbing in support of the core business functions that really matter. This is without the significant challenge of scaling the infrastructure for millions of customers, should it become successful.
With Lambda, it couldn’t be simpler. The only deployment is the key business function itself. There are no servers to speak of, or anything else for that matter, except a per-millisecond cost to invoke the service, whether once or one billion times, whether from the web or mobile or even the Internet of Things, which might, for example, include automatic entry systems in Hyatt’s employee-less pop-up hotels.
But wait, how does an employee-less hotel work?
One solution might be the use of facial recognition cameras in hotel doors. But what does Hyatt know about hardcore computer vision?
Nothing, but that’s not a problem.
One of the Hyatt’s lab Gigsters out of South Africa added facial recognition with just one line of code from Algorithmia, a new breed of “algorithms as a service” platforms that collapses the expertise of software gurus, most of them Gigsters, into pretested pay-as-you-go software functions. Algorithms are the new apps!
And what about Hyatt’s famous customer service?
No problem here either. With just another line of code, a Gigster out of Ohio adds an entire video-calling service that taps into a network of - guess what - gigging concierges working out their homes.
By now, perhaps the vision is clear.
At the push of a button, a top technical team can be assembled inside a virtual bubble of connected services where the use of auto-scalable IT enables them to focus their technological creativity where it matters, just like a Silicon Valley start-up.
Of course, there’s still a way to go before companies can truly deploy an innovation labs on demand, but we are getting very close thanks to boundary-less talent, organizations and IT.