What will data analytics, management look like in the future?

The evolution of analytics and business intelligence has accelerated significantly in the past few years, driven by more robust options and players in the market that make the potential pool of users more diverse and voluminous. One of the fundamental drivers of this trend has been the increased availability of automation tools, which have gone hand-in-hand with machine learning and analytics since day one. 

However, the question of whether automation is entirely good or not, which has been around in one form or another since the Industrial Revolution, should hold some weight in relevant corporate conversations. Perhaps not in a moral sense, but rather with regard to the impact that automation can have on strategies and business intelligence at large, especially when it goes overboard and begins to deter from the concept of human involvement. 

Heavy stuff, right? 

Behaviors to shift
Gartner recently argued that as machine learning gears up and becomes more prominent in the intelligence community, leaders will not be as likely to demand control over the programs involved. More simply put, the analysts feel as though computers are already beginning to make more important decisions in the grand scheme of operations, and that individuals are seemingly taking a back seat, doing what the machines dictate. 

Machine learning might complicate matters for businesses.Machine learning might complicate matters for businesses.

Now, it is worth noting that a perfect ebb and flow of analytics and intelligence in the decision-making process is largely characterized by this machine-centric process in which insights and prescriptive concepts are introduced through IT assets. However, when a company chooses to completely relinquish control over decision-making and operational management, there ought to be a bit of concern about what might happen when malfunctions or other unforeseen issues occur. 

"As smart machines become increasingly capable, they will become viable alternatives to human workers under certain circumstances, which will lead to significant repercussions for the business and thus for CIOs," Stephen Prentice, vice president and Gartner Fellow, affirmed. "In the 2015 Gartner CEO and business leader survey, opinions were equally divided on this issue and indicate that business leaders are starting to take notice of the advances being made and more readily acknowledge that the threat to knowledge work is real."

This certainly has implications for the employment landscape, but the more subversive concern should be related to the stability of these ventures. 

"Extremes are rarely good."

Extremes, as many business leaders already know, are rarely a good thing. Instead, balance and the middle ground will tend to be far safer and more stable. In the case of analytics in the era of machine learning, business leaders should be mindful of the risks that could accompany a completely hands-off approach. Even 10 years from now when technology is far more advanced, there is an argument to be made that decision-making will always demand a human touch. 

Either way, companies should indeed maintain control of their analytics performances through the use of proven data preparation services, as this will boost their outcomes down the road.