According to industry hype, the latest emerging technology will change everything. No technology is an island, however, which is where things get interesting.
Emerging technologies tend to be marketed as “The Answer” to whatever challenge an organization faces, but no technology can drive business success independently, since it must operate within context of the organization’s IT ecosystem.
While it’s well-understood that digital transformation represents a confluence of technologies that can include everything from legacy systems to artificial intelligence, the Internet of Things, cloud and blockchain, not every technology applies to every business or use case.
“The critical takeaway for enterprises is they need to build a platform that’s flexible and capable enough to work across different emerging technologies and apply them as necessary to their applications,” said Blair Hanley Frank, principal analyst at technology research and consulting firm ISG. “The platform isn’t just technical in nature, it’s also organizational.”
Technological change, organizational change, and even societal change are accelerating. Each of those factors influences the other two.
“It can be difficult to predict what’s coming because of the pace of innovation,” said Frank. “You need to develop the organizational muscle to find new capabilities, evaluate new capabilities, figure out how they fit into an overall technology landscape and how you as an enterprise fit into a market. Based on all of that, how [do those capabilities] fit into your business?”
For example, IoT, blockchain, AI, cloud computing and edge computing are hot, but how they’re applied to specific use cases depends on several factors, including the company’s unique value proposition and the industry in which the organization operates.
“Convergence is more important than ever because you have this concept that you’re never going to get maximum value out of [individual technologies] unless you bring them together with other technologies,” said Andy Ruggles. U.S. Tax Reporting and Strategy Leader at PwC. “When you think of applications in a corporate, supply chain or financial context, all of that involves integrating or orchestrating different technologies.”
For example, qualifying for federal R&D tax credits has historically involved one-on-one interviews with individuals. However, using a combination of AI techniques including natural language processing and machine learning, the process can be automated.
“My experience is, you have to lead with the business program, understand the new technology pieces and how you solve problems over time,” said Ruggles. “There are always going to be cases where when you look at technology it opens your eyes to new value opportunities as opposed to just solving [immediate] problems.”
One size does not fit all
There’s a lot to learn about problem-solving and innovation just by looking within and outside of an organization’s own industry. However, just because a particular approach to problem solving works in one context does not necessarily mean it will work the same or as well in another context.
“You could have a blockchain-based, AI-enabled solution that touches both hybrid cloud infrastructure and the edge, in which you’re using predictive modeling to take information from IoT sensors to drive insights on the ground and provide analytics back at the home office to drive your business forward,” said ISG’s Frank. “You may need all of those things all at once, some of those things some of the time, or none of those things. It’s entirely application-dependent. There’s no one-size-fits-all answer.”
However, a best practice is to build common technical and human infrastructures that are modular enough and capable enough to deliver value to the business and its constituencies as the underlying technology and business needs change.
“One of the best ways of doing that, which is kind of boring and old, is to have good, strong APIs and good governance of the interconnections among the different technologies,” said Frank. “It’s about building an infrastructure that’s technically modular so you can swap components and technologies.”
Then again, some of the biggest obstacles organizations face are cultural, not technical. As they build integrations between different systems, they also have to build integrations between departments that may not have spent much time talking with each other historically.
New technology combinations facilitate change and innovation
Many of the things today’s users take for granted failed to meet high expectations in the very early stages because technological advancement had not occurred at enough levels simultaneously or the directions of the foundational technologies had not aligned to the degree necessary. Examples include modern smartphones and video streaming.
“Organizations should constantly challenge themselves. You’ve got to be informed about the emerging technology and how it maps to the underlying business goal, problems you’re trying to solve, or new value opportunities,” said PwC’s Ruggles. “If we want to innovate, we have to ask ourselves whether there is something I’m doing, something I’m not doing enough of, or if I could do it more frequently or accurately, what would it mean to the business? I think the key to innovating is your value proposition and how you improve it.”
Although necessity has been heralded as the mother of invention, ISG’s Frank said innovation is often about solving the next problem.
“The first thing to do is ask yourself how this fits together with everything else you see in the world around you and the technology that’s relevant to your organization, your life and your business,” said Frank. “In many ways, technology convergence and technology evolution are intertwined with one another. It’s hard to know what we don’t know until we figure it out.”
While some innovators are focused on the next breakthrough technology or societal shift, others are deciding how technology ecosystem patterns translate to competitive advantage. Placing too much emphasis on a single technology may result in noise that obscures important signals emanating from the dynamics between and among multiple technologies.
Lisa Morgan is a freelance writer who covers big data and BI for InformationWeek. She has contributed articles, reports, and other types of content to various publications and sites ranging from SD Times to the Economist Intelligent Unit. Frequent areas of coverage include … View Full Bio
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