How sure are you that a startup located thousands of miles away in a remote corner of the world is not silently creating technology that will disrupt your industry?
Well, that’s the question that CEOs of all major companies, not just the tech companies, are asking themselves. After all, the businesses that Uber, Amazon, and Airbnb displaced were hardly tech companies. So, technology has firmly established its potential to disrupt any industry. Under these circumstances, entrepreneurs and CEOs cannot afford to be even the least bit complacent with their company’s position in the market.
But, how can a business shield itself from the challenges of disruptive innovation?
Big data might hold the key to the answer!
A growing number of business leaders are realizing the potential of big data to drive analytics-based innovation as a way of tackling the challenge posed by disruptive innovation. In fact, big data adoption reached as much as 53% in 2017, according to some estimates, with telecom and financial services leading the way. The writing on the wall is clear – innovate rapidly to counter the growing threat of disruptive innovation, or perish.
While it is true that big data is a powerful enabler for businesses to innovate, a surprising number of businesses fail to take the full range of benefits offered by big data, on account of flawed execution. As Ruben Sigala, EVP and Chief Marketing Officer at Caesars Entertainment Corporation, puts it in his interview with McKinsey & Company, “You have to start with the charter of the organization. You have to be very specific about the aim of the function within the organization and how it’s intended to interact with the broader business.”
Source: Big Data Executive Survey 2017 by NewVantage Partners
In order to focus your business’s big data strategy on achieving specific business goals, it is important to first understand what big data can do for your business. Only then your organization’s big data initiatives will produce tangible benefits for your organization. So, here are 4 major impacts of big data in enterprises.
Everything about big data is astronomical in nature. The sheer amount of data created by users of a business can be mindboggling. IBM estimates that 90% of all the data in the world today was created in just the last 2 years at the rate of 2.5 quintillion (1 followed by 18 zeroes) bytes a day. What’s astounding about this is not just the volume of data, but the velocity at which that data is being created. In 2017 alone, the world created as much data as it was created all the way back from 3,000 BCE to 2014 CE. Big data analytics is not only capable of handling such colossal amounts of data, but also generate meaningful insights for businesses from it.
Perhaps, the most challenging and equally promising aspect of big data is the non-uniformity of the data being collected and analyzed. An immense variety of data is continuously generated by users, including videos, images, text, tweets, voicemails, hand-written text, and more. Big data analytics is capable of generating meaningful and reliable insights from all the disparate sets of data. Not only is it capable of analyzing structured data, but semi-structured and unstructured data as well.
The accuracy of the deductions made from a particular set of data depends on the variety, changes in the velocity of data collection, and with the accuracy of the data-collection methods employed by the businesses collecting the data.
Thankfully, with the increase in the size of the data being collected and analyzed, machine learning and data science techniques can improve the accuracy of the deductions and predictions made from such data.
Big data requires the collection of a tremendous amount of user information for the purpose of analysis. This poses a unique security challenge for the businesses. As the amount and quality of such data increases, the value of that data increases. This way, hackers have a higher incentive to breach your security systems and steal that data.
Another related issue is data currency. Consumer behavior, habits, likes, dislikes, and other aspects are constantly evolving. So, the question is – how relevant is the data that was collected, say, 2 years ago?
Businesses should not only employ robust data collection methods, but also have a data archival, data retrieval, and perhaps, data deletion processes. If the data is irrelevant for businesses, then it is in their customers’ and their best interests that such data is deleted, considering the risk of it falling into the wrong hands.
If you think that your systems will be 100% secure and prevent any such breaches, then take a look at this amazing interactive visualization at Information is Beautiful. It will change the way you take security for granted.
The potential of big data to add value to a business is virtually limitless. Whether it is with the marketing efforts, operations, cost reductions, profit enhancements, sales increases, or with other aspects of the business, big data can add value to a business in many ways. But, businesses have to invest an extraordinary amount of time, resources, and energy into realizing those benefits. This is something that most businesses cannot do. That is why, it is important for businesses to focus on a specific set of areas where they believe big data has the highest potential value to contribute to the organization. It can be in terms of improving the sales, creating a sustainable competitive advantage, or something else.
In the end, big data is not a replacement for all the analytics, innovation tools, and development techniques employed by businesses. It is a powerful way of accelerating all of those efforts to produce sustainable data-driven innovation that can survive or maybe even overcome the threat of disruptive innovation.