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Innovation, at its best, is invisible; there is just an audible sigh of satisfaction.
It's not that we are using "the cloud," it's that we can offer what "the cloud" can offer. Better, we can offer what the cloud offers and wrap it up as if nothing has changed. The best innovations just make lives better, without demanding any additional intellectual input.
Innovation isn't always great. In fact, it's very often a terrible idea. Jim McKelvey, the Founder and CEO of Bloc (as was Square) at the FOSS4GNA B2B session, reminded us that we usually don't want to innovate around food products. Few are interested in the "risk" of not eating something fully tested and safe. Indeed, each time I fly in an aircraft, I'm hoping the pilot is not motivated to innovate anything. I am quite convinced Canada Revenue Agency would be upset if I submitted any innovative tax returns. So, while it’s easy for innovators to say that innovation is great, we should also be cognizant that not all recipients of innovation are as foolhardy with risk. And innovation only makes sense within a bigger context. Innovation is useful for the discovery of new things and for the betterment of old things.
As I've suggested before, if an innovation is to be adopted by an enterprise company, there is usually an internal champion who is taking on significant career risk to be an early adopter. These champions are willing to take a chance on changing a process that could well be a central value-creation engine for a company. there has to be a good reason to do this. There is inertia and process to battle; there are budgetary strains and schedules to meet. These champions are rare and should be cherished. To reduce our cherished champion's risk, a good strategy is to make things "look the same, but be better."
This can mean so much, so let's jump into an example that my team has been working on.
Bottomless Geospatial
With regard to geospatial technology. Every day, we are dealing with large and somewhat annoying datasets. While we see videos of "big data analysis" and whizzy UIs, the stark reality of day-to-day data management for the vast majority of geospatial enterprises comes down to moving large files across networks. As our computing resources have advanced, data capture technology has also advanced meaning we are just moving larger files slowly. Because of the size of the problem, the easiest thing to do is just do what was done before and store those large files on increasingly less accessible local or external drives.
But deep down, we all know that those drives are where data dies. If we needed to find a particular data product again, it would be awkward, assuming even that the drive itself had remained functional.
So, while we pander to the devil on our shoulder who says, "Keep this data just in case,” like that box of just-in-case wires, we store data in places that invariably invite ultimate obscurity. However, we live in a time of change, I’m not just talking about technology now, but landscapes. Measuring change has become a central expectation of geospatial, and not just short-term changes but longitudinal change (pun absolutely intended.) Those dusty old external hard drives are going to become increasingly useful.
So, what if we could move that data to a place where it could be accessible and then be prepared for subsequent ease of use?
But, again, better, what if that just looked and behaved like a drive? There would be no navigation to external domains, no logging into additional services, just a place where geospatial data is readily available in useful formats but prepared and managed for practicality. That would be a cloud-native approach, but the central point would be that it looks the same but operates with the additional benefits of cloud-native features.
Now, I could wave my arms and say, "This is a cutting-edge, cloud-native, big data distribution platform." But that wins me nothing but blank faces and an awkward silence. Instead, I reference "a bottomless, secure, geospatial drive." One that you will use to replace the shelves of external hard drives, unlocking years of aerial and lidar survey for subsequent ease of use.
Invisible Innovation
The point of this note isn’t to highlight what we are doing in Sparkgeo (that’s just a convenient byproduct). Instead, I want you to think about invisible innovation. Take an innovative practice, say cloud native geospatial and inject it into a traditional business, say land management, to make a frustrating part of a business process better invisibly. Change nothing but the supporting technology to add additional capabilities without any additional frustration.
Within the context of geospatial and Earth Observation, there is so much innovation that can be completely invisible. An obvious example would be change detection signals that work invisibly which ultimately alert users to some landscape or human change. An algorithm could be looking for a harvest event or a supply chain signal, perhaps even some kind of IoT-based temperature signal. Wrapping that algorithm into a regular workflow could easily create a process which happens almost invisibly, yet contains a lot of innovative technology. Reporting any detected changes would look just like an email, similar to how an individual analyst might report a change. All that innovation which enables tremendous scale is conveniently hidden in a process which operates just like a system did before.
Strategically, this approach to innovation is a little sneaky, but ultimately, it meets the potential customers where they are rather than forcing a change of practice. In this way, the innovation demonstrates an ability to empathize while accelerating.