Nearly 10,000 have visited my postings of two blogs on Big Data on a couple sites since January 17. There’s no question that big data is “hot” and that the business landscape is shaped by data more than ever before. Google’s Eric Schmidt tells us the world creates 5 exabytes of data every two days. That’s really big data. (FYI: Exabyte—Cisco says annual global IP traffic will reach two-thirds of a zettabyte or 667 exabytes in 2013). But the real big data question is not how much, but so what?
Recently, the Economist Intelligence Unit, with support from SAS Software, set out to answer that question. They surveyed 752 senior executives from a broad range of sectors and countries. They also conducted in-depth interviews with 17 executives, consultants and specialists regarded as data pioneers. Fifty-seven percent (57%) of the respondents had been working with big data for at least three years, and nearly one-half of the respondents said that their companies are well ahead of their peer firms and have a defined data strategy.
What’s significant about the results is that they are reflective of a growing consensus in the field of big data. The consensus research also confirms my blogs on the big data IT fumble and the data scientist as “sexiest career.” The summary highlights of the research are as follows:
The link between effective use of big data and financial performance is strong. Top performing companies, the so-called strategy data managers, process data more rapidly, see the rewards across all business disciplines, place a higher premium on data than their peers, collect more data from everywhere and use data more broadly across the business.
The survey suggests that there is a correlation between big data and financial performance. But a chief problem with all survey research is the omission or de-emphasis of other factors. The firms surveyed tended to be successful firms prior to the use of big data. It’s probable that the big data leverages other success factors.
Still, it’s arguable that big data is a highly significant competitive advantage. At this point in its development, firms without that expertise are liable to be left behind.
Well-defined data strategy is always the top priority, not collecting and processing information. One of the intriguing research bits is that 46% of executives from companies that significantly outperform their peers financially have a “well-defined” data strategy. Inevitably and always, the strategy should be based on key business priorities. The role of the data strategy, then, is to identify the problems the firm wants to solve. But the data component serves those priorities and, therefore, is developed afterwards.
Strategy is key: big data merely supports strategy.
Talent matters as much as technology. Research finds that executives need to ensure that analytic thinking is not confined to the It department. Especially valuable is a sidebar, “What’s in an algorithm?” detailing training that works with employees with little or no knowledge of data science, showing employees how to create a data plan that results in a series of business recommendations. Yet, a close reading of the language of the research conclusion indicates the need for still more clarity on this issue.
As I emphasized in my blog, Big data: the IT fumble, the uses of big data emphasize that IT and data science are very different animals. Any observant employee is aware that when it comes to data or even the use of the term, data, the ship is listing way over to the side of IT. The lack of professional data scientists for the discipline makes the problem even more serious. Data scientists will need to understand the business as well as cognitive and behavioral sciences. One principal at Deloitte Consulting recommends that companies may need to search academic departments or consider sharing a data scientist. So it can’t be emphasized enough that people are at the heart of the discipline, not data.
The biggest gains from big data impact are in customer-facing areas. The report recommends that social media and web-tracking technologies are especially useful for collecting customer data. Loyalty cards and user-generated web content have already led to significant changes in retail and entertainment. Of course, consumer products companies have long used customer data supplied by information and measurement companies like Nielson. Thus, marketing and sales groups have built-in experience and history of using customer generated data, making analogies to web-data an easier reach for those firms.
Evidence of the use and advance of data is everywhere. As the report indicates, an ecosystem of data-focused companies is springing up and creating new businesses. Still further, analysts at the McKinsey Global Institute estimate that just one sector—the US healthcare industry—could create US$300bn in value annually if it used big data to drive efficiency and quality.
The “why” of big data is fairly obvious. It’s the “how” that creates and will continue to create frustration, while at the same time creating significant business success. That’s typical of an evolving discipline.
Flickr photo: by Laura ATL