We live in an era of big data, in which today’s enterprises have access to more data and information about their customers, suppliers and partners than ever before. However, with every new opportunity comes new challenges. As a result, enterprises attempting to capture the innovation potential of big data will also need to analyze the risk/reward potential of big data. So how can today’s innovative enterprises rise up to the challenges of big data privacy?
The challenges of big data privacy
The upside to all that customer data, of course, is greater insight into how to become more profitable and more efficient. The downside, though, is that corporations are also exposed to data privacy and protection issues that would have been largely unthinkable just a decade ago.
At one time, it was much easier to put firewalls around the enterprise. Data within the enterprise stayed within the enterprise. But then came the mobile era, the movement to the cloud and the whole trend toward BYOD (bring your own device). Suddenly, it became much more difficult to lock down data within the enterprise when it wasn’t trapped within a hulking mainframe.
On top of that, corporate hackers have raised the risk profile of big data considerably. Almost on a weekly basis, we hear about corporations being hacked into and their data stolen. Customer information, leaked on the Internet, now poses a very real risk for corporations. In some cases, as in the healthcare industry, companies now face substantial legal and financial risk if patient data becomes publicly available.
Customers are also better informed and the rising awareness of how they are the ‘product’ has increased the scrutiny on companies getting innovative with what they can do with big data. Privacy regulators are pushing out new legislation aimed at reducing privacy risks and protecting personal data. Big data needs big privacy.
Data is the new oil for innovative enterprises
But there is no going back. The push is on to collect more data, and the proliferating number of online channels and platforms means that corporations are able to collect more information about their customers than ever before. They now know not only their demographic information (i.e. age, gender, geographic location), but also they psychographic information (i.e. their likes, behaviors and preferences). They can track how long they stay on a website, and where they go afterwards.
By employing sophisticated algorithms, enterprises can literally sift through an unimaginable amount of data to find the proverbial “needle in a haystack.” They can now work on building sophisticated prediction models that run on data. With new algorithms and AI-powered machine learning, the Holy Grail is the creation of the right offer, at the right time, to the right customer. The new advertising and marketing opportunities are almost endless.
No wonder some business analysts and venture capitalists have referred to data as “the new oil” of the digital economy. Data is what fuels the modern innovative enterprise. And all of today’s top innovation trends – artificial intelligence and machine learning, the Internet of Things and mobile – simply accelerate the push even further to collect and then analyze as much data as possible.
Today’s innovative enterprise needs data as much as the corporations of the 20th century needed fossil fuels. Data is what drives the modern enterprise. So with that in mind, how can the modern enterprise balance the risk and reward of big data?
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