A staple of the tech trade press is The New Shiny Thing, that cool, mysterious new technology portrayed as both promising and threatening.
Big data. Deep analytics. Internet of Things. Artificial intelligence and machine learning. Blockchain. Chatbots. The list goes on. When we tire of one thing, something newer and shinier comes along.
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IT professionals usually take the time to understand the basic ideas behind these new shiny things, just in case some business colleague asks them. Most business people are looking for new ways to innovate, and all of these things might be winners—that is, if they were easier to consume.
But I’m here to argue that we’ll see a lot less attention paid to new shiny things in the future than we’ve seen in the past.
Why? These new capabilities will simply become integrated features of the IT services we will already be consuming in the cloud.
When Technology Innovation Was Hard
I can’t tell you how many meetings I’ve been in during my career where a business person says, “Hey, we should take a look at XYZ” and the response from IT is, “Well, it’s a lot harder than it looks.” And, historically, IT has been right.
IT environments are connected beasts; no single technology is useful by itself. Each one has to be integrated with other technologies to actually offer a benefit. And that’s where the hard work comes in.
A few years back, when big data was getting hot, a few brave IT organizations decided to take the plunge and build their own Hadoop clusters—no small undertaking in itself. Then the fun began: sourcing terabytes (or sometimes petabytes!) of data from all the existing systems.
The data whiz kids would come back after awhile with a Eureka! moment, and that’s when the really heavy lifting would start: lashing in a real-time analytical engine with the company’s existing applications and processes. Otherwise, no business impact.
Another example is the so-called Internet of Things. Let’s say you’re an elevator maker. To you, IoT means putting smart sensors on all of your elevators, which check their performance and communicate their health. But IoT doesn’t give you a way to act on all of that data. That’s the job of, say, your field-dispatch application.
Once again, there’s a lot of heavy lifting between “IoT is cool” and “IoT is improving our business.”
My favorite example is adaptive intelligence and machine learning. The idea is simple: Applications can teach themselves to get smarter over time. And this capability turns out to be incredibly useful in answering questions for a vast array of everyday business processes.
When is the best time to place this order so I get the lowest price? Of all these job candidates, who is most likely to succeed in this position? Given forecasted demand, what is the ideal inventory level? None of these questions may be exciting individually, but taken together they represent a huge leap forward in how a company does business.
The prospect of setting up AI engines and sourcing prepopulated training sets for each and every relevant business process should scare most sober IT professionals. Not only is it mind-numbingly difficult, but there’s no guarantee the results will be effective.
So the innovative technology sits, available only to those with enough resources and risk tolerance to make the investment.
Innovation That’s Easy to Consume
Now, let’s consider a company that’s using a cloud software-as-a-service (SaaS) provider for its core applications, and let’s say it wants to explore big data. It’s a faster, simpler and cheaper proposition as a result of the cloud move.
Most of its data is already in the cloud. It would be easy for the company to provision a big data service, and try it out without a huge upfront commitment. Better yet, it would have access to third-party data sets to enrich its own. More data, better insights. Plus, the very best tools, as well as guidance on how to use them.
If the data jockeys at the company found something interesting, it would be far easier for them to stitch a recommendation engine together with a production application. Everything needed is right there, ready to use.
Or, better still, the company wouldn’t have to do that at all. The best SaaS applications are already starting to apply advanced analytics to everyday business processes, as an embedded feature.
Let’s revisit our elevator company. If its SaaS field-dispatch application provider also had an IoT service, it would be trivial to connect the two. Instant Internet of Things. No drama.
The exact same thing could be said about AI and machine learning. About blockchain. About chatbots. All the advanced technologies are right there, ready to be integrated into what you’re using today, or they simply become a feature of the SaaS application you’re already using.
And all of the new shiny technologies become a lot less difficult and exotic as a result.
Cloud Changes the Innovation Equation
Here’s the point: With software as a service and platform as a service, the innovation equation shifts dramatically. New technologies present themselves as just another feature of what you’re using today.
It’s sort of like Siri on your iPhone: It’s just there, and you use it if it makes sense. No excitement, no drama.
But the impact of cloud on the innovation equation goes deeper than that. It’s a structural redefinition of how technology innovation gets done in the enterprise.
At a high level, the cloud is an economizer: no massive startup costs before results can be realized.
Cloud is also an enabler: the very best technologies, ready to be put to work to help organizations innovate and differentiate.
And the cloud is an equalizer: small organizations now have access to the exact same capabilities as the largest ones.
Put simply, cloud bends the innovation curve, delivering results orders-of-magnitude faster and at orders-of-magnitude lower cost.
The Organizational Impact
Years ago, many large organizations had chief technology officers. For many of those CTOs, their main role was to scout for new technologies to bring into the enterprise. But that model was flawed in two ways.
First, even if the CTO discovered something promising, it took too long and cost too much to bring it into the enterprise. Second, many of the important innovations, such as mobile, happened without them.
In the cloud economy, that CTO role is diminished even further. Instead of CTOs going to tech conferences to learn about new technology things, we’ll see finance professionals going to finance conferences to learn about how new technology can help them solve business problems. We’ll see HR professionals and marketing professionals and even IT professionals going to their respective conferences to do the same.
The focus will shift. It will be less about the new technology, and more about how it can be put to work to help with everyday challenges.
Make something easy to consume, and more of it will be consumed. That rubric also applies to advanced technologies.
Innovation will become easy—or, at least, a whole lot easier.
Chuck Hollis is senior vice president for converged infrastructure at Oracle.