Business analytics against the complexity of big data and the Internet of Things

The digitalization of private life and business models, with the proliferation of clouds, mobility, social media, and smart objects, poses numerous questions regarding the collection, use and the potentiality of enormous amount of data. That’s how analytics can help companies manage the growing complexity of current society.

Today, it is taken for granted that social media, mobility, analytics, and cloud computing, now defined with the acronym “Smac”, are guiding our private and professional habits towards a new digital frontier, revolutionizing purchasing behaviour, ways of communicating, and business models. But another burgeoning phenomenon promises to accelerate the digital disruption: the Internet of Things is destined to add another level of control to our lives, transforming consumption, actions, physical and even emotional states, all on the basis of mathematical calculations.

According to Cisco and NetConsulting, in 2013 the number of intelligent objects reached 10 billion globally, and in 2020 that number will rise to 50 billion. Finding applications in a variety of fields from automation to domotics to medicine, they will generate terabyte upon terabyte of information that will travel through the web and feed company databases.

We are in the age of big data, where anyone can access knowledge and develop their own business even if they have limited capital. It is no coincidence that Jeremy Rifkin speaks of the “third industrial revolution at zero marginal cost”, because all you need is a simple Internet connection in order to take advantage of digital opportunities, even entering the market as an innovator, without rigid entry barriers.

Bits are becoming predictive knowledge (mathematical deductions based on the past can be used to make future decisions). But on the other side of the coin, tracing every single operation generates an information surplus and the risk is that you won’t be able to isolate the correct information to focus on, losing your objectives in useless or irrelevant details. Archiving and maintaining data is also very costly, due to both the need for adequate security measures to minimize the danger of theft or violation, and because it requires high-performance and high-volume storage systems.

Then there is the privacy issue for those who generate and share (knowingly or not) their own information online or via smart objects. To whom does this information belong? Is it legal for companies to consider themselves the owners of users’ personal information? As Alex “Sandy” Pentland of the MIT Media Lab suggested in an interview with the Harvard Business Review, yes, insofar as we reach a “New Deal on Data”, that is a future scenario characterized by total transparency. The individual must be aware of what will happen to their information, freely choosing to allow access to it and for which purposes. Only in this way can the citizen, the client, or the employee understand the effective advantages to be gained from sharing their personal information with third parties.

If big data and analytics are ultimately used to increase sales and profits, they also allow for improvements to the services offered (user loyalty is achieved only through positive experiences and satisfaction, with interesting and personalized offers). Today, companies like Google and Facebook are striving to justify to their millions of users all the data that they swallow up, and must always be able to offer services that meet users’ expectations (no one gives something for nothing).