According to some predictions, by 2025 one third of knowledge worker jobs will be replaced by ‘smart machines’. Should we all be worried?
Consider the world of analytics: Why are analytics and business intelligence consistently such hot topics (and hot budget items) amongst CEO’s and their CIO colleagues? Because they give organizations a data-led roadmap to making good decisions, as well as the critical information they need to make decisions that keep them competitive and relevant in their marketplaces. Considering just how critical analytics is, it makes sense to think that if they could be automated, much like many other business processes that are dependent on IT systems, surely organizations could make better decisions, faster and with greater accuracy, right?
Well, theory and practice aren’t always the best bedfellows. The reality is that when it comes to decision making, and especially the really tough decisions that can determine the success or failure of a new product launch, a marketing campaign or a sales expansion play, data is just one (albeit VERY important) part of the equation. But it’s how people – human beings – couple that data with their own intuition and experience, and apply their skill (or just follow their gut!) that is the most important piece in any of the big decisions that need to be made. Machines are great at making very transactional-based decisions (think Mainframes). Stock price goes above a certain level – sell. Goes below – buy more.
But regardless of our flaws, it’s humans that will always make the big complex decisions, thanks to our ability to go beyond just the hard data, and to trust our intuition and experience. Machines just weren’t built for the kind of deep, complex, sometimes vague and incomplete analytical processing that we humans have been born with!
So what does the future hold? The technology providers who can best support people – and not just machines – in making the tough decisions will prevail. That’s why we at Qlik are relentless in our approach to making the analytical experience available for everyone, everywhere with natural, intuitive approaches to the most complex data analysis challenges.
Photo credit: AMagill / Foter / CC BY