When it comes to big data, analytics and AI, the value does not come from collecting the data, or even from deriving some insight from it — value comes from just one thing: action.
The future of big data- When I started my first business in the mid-90’s I did what most first-time entrepreneurs do — I ordered business cards.
Actually, I first had to get an address and order a phone. After all, I couldn’t order business cards without them. Then it was setting up an accounting system, doing the legal paperwork, building a website, and, of course, writing a really long business plan.
I did everything except the things I should have been doing: telling my story and selling my solution.
But as is so often the case, I got too caught up in the mechanics and lost sight of my purpose. It took me a while to set myself straight.
So much of the big data and analytics space — and, increasingly, the artificial intelligence (AI) market with which it is colliding — remains focused on the mechanics.
The mechanics are important, of course. But they are not the reason that any of these disciplines exist. When it comes to big data, analytics, and AI the value does not come from collecting the data, or even from deriving some insight from it — value comes from just one thing: action.
Big data: Starting on the wrong foot?
The over-focus on the mechanics may have started at the very beginning. I can best sum up the ethos behind big data as: Collect it all. Sort it out later.
The focus was on building massive data lakes that collected every piece of data imaginable with the mindset that it would, at some point, be useful. But that approach is proving difficult to sustain.
“[This approach] is a mistake,” implored Satyendra Rana, Chief Technology Officer of cognitive decision-making platform diwo. “You can’t win that battle. Data keeps growing and growing, and you’ll sink in that lake. You can’t swim in it.”
Many organizations are coming to the same conclusion. Moreover, IT and business leaders are finding that they must change their mindset and focus on both operational and transformative outcomes to uncover the real value of their big data and AI initiatives.
“The mindset shift is essential,” explained David Judge, Vice President of SAP Leonardo. “There are two paths our customers have gone down. The first is an optimization path — automate and draw down the manual activity. Then, there are those that [have focused] on creating new business models [with data], which is substantially more transformative. The companies that have done the best have focused on both.”