The idea behind the Fourth Industrial Revolution — society’s pivot from industrial-based to information-driven business — is gaining momentum, and for good reason. It’s been accompanied by significant anxiety, with fears that robotics, artificial intelligence (AI), and globalization are setting the next generation of workers on a jobless crisis path. And it’s not just media hype — this was a significant World Economic Forum topic this year.
Although this conversation seems to be everywhere due to a confluence of forces (aging workforce demographics, global economic shifts, etc.), in my career, I’ve seen a slow but steady march to where we are today. We’ve been automating processes through computing power and software for decades in a continuum — everything from how we bank with ATMs to how we communicate with smartphones.
What is different today is the volume and velocity of data. Never have we had access to the second-by-second creation of so much information. And just like smartphones accelerated expectations of access and convenience, the same is taking place in business. The scalability of the internet of things (IoT), AI in the data center, and software-embedded machine learning is creating large shifts in business data expectations and demands.
This is putting today’s workers and organizations in a real bind, from how to manage a never-ending and growing mountain of data to determining what data is valuable and having confidence that the necessary data is available to make smart decisions.
Business leaders I speak with have two simultaneous concerns: 1) how to take advantage of this mass of data, and 2) worries of being behind/outflanked compared to competitors. I tackled some of these same concerns when I served as CIO at ADP. The conversations with my team and vendors usually focused on technology first — evaluating infrastructure state, discussing cloud strategies and reviewing our mobile strategy, among other concerns…