Big Data Study – The 10 Key Findings



In this Big Data Study, TCS surveyed 1,217 companies in nine countries in four regions of the world (US, Europe, Asia-Pacific and Latin America) in late December 2012 and January 2013. Of these companies, a little more than half (643) said they had undertaken Big Data initiatives in 2012. We also conducted in-depth interviews with more than a dozen executives across industries about their Big Data initiatives between December 2012 and March 2013. In addition, we interviewed two experts in the fast-evolving technologies of Big Data. This data, as well as our consultants’ growing experience in helping large companies leverage Big Data, provide the basis for the findings in this report.

While our findings are numerous, we believe the following 10 are the most important ones:

The Big Data Study: Key Findings

About half of the firms surveyed are using Big Data, and many of them projected big returns for 2012About half of the firms surveyed are using Big Data, and many of them projected big returns for 2012. 53% of the 1,217 firms surveyed had undertaken Big Data initiatives in 2012, and of those 643 companies, 43% predicted a return on investment (ROI) of more than 25%. About a quarter (24%) either had a negative return or didn’t know what the return was. (Read more)

There’s a polarity in spending on Big Data, with a minority of companies spending massive amounts and a larger number spending very little.There’s a polarity in spending on Big Data, with a minority of companies spending massive amounts and a larger number spending very little.Some 15% of the companies with Big Data initiatives spent at least $100 million per company on them last year, and 7% invested at least $500 million. In contrast, nearly one-quarter (24%) spent less than $2.5 million apiece. This has resulted in a big spread between median ($10 million) and mean spending per company ($88 million). Industries spending the most are telecommunications, travel-related, high tech, and banking; life sciences, retail, and energy/resources companies spend the least. (Read more)

Investments are geared toward generating and maintaining revenueInvestments are geared toward generating and maintaining revenue. 55% of the spending goes to four business functions that generate and maintain revenue: sales (15.2%), marketing (15.0%), customer service (13.3%) and R&D/new product development (11.3%). Less than half that amount (24%) goes to three non-revenue-producing functions: IT (11.1%), finance (7.7%), and HR (5.0%). (Read more)

The business functions expecting the greatest ROI on Big Data are not the ones you may thinkThe business functions expecting the greatest ROI on Big Data are not the ones you may think. Although sales and marketing garner the largest shares (a combined 30.2%) of the Big Data budget, the logistics and finance functions (which together get only 14.4% of the budget) expected much greater ROI on their Big Data investments. Furthermore, when asked to rate 75 activities in eight business functions on their potential to benefit from Big Data, companies around the world ranked just as many logistics activities as they did sales activities in the top 25. (Read more)

The biggest challenges to getting business value from Big Data are as much cultural as they are technologicalThe biggest challenges to getting business value from Big Data are as much cultural as they are technological. When asked to rate a list of 16 challenges, companies placed an organizational challenge at the very top: getting business units to share information across organizational silos. A close second was a technological issue: dealing with what has become known as the three “V’s” of Big Data: data volume, velocity and variety. The third challenge was determining which data to use for different business decisions. (Read more)

Nearly half the data (49%) is unstructured or semi-structured, while 51% is structured. The heavy use of the former is remarkable given that just a few years ago it was nearly zeroNearly half the data (49%) is unstructured or semi-structured, while 51% is structured. The heavy use of the former is remarkable given that just a few years ago it was nearly zero. On another dimension of comparison, about 70% of the data is from internal sources rather than external. However, using external and unstructured data has outsized impacts. Companies that expect much bigger ROI on Big Data use more external and unstructured data than do companies expecting lower or no ROI. (Read more)

The companies with the biggest projected 2012 returns on Big Data saw those returns coming from places that the laggards don’t value as muchThe companies with the biggest projected 2012 returns on Big Data saw those returns coming from places that the laggards don’t value as much. To use a gold miner’s analogy, the leaders pan for gold in different places – most of all in marketing, sales and service. The two activities where leaders see much greater potential than laggards are: improving customers’ offline experience and marketing to consumers based on their physical location. ROI leaders also see much greater potential than do laggards in using Big Data to size and structure sales territories. And in customer service, leaders envision greater potential benefits in monitoring product usage to detect manufacturing and design problems. (Read more)

Companies that do more business on the Internet spend more on Big Data and project greater ROICompanies that do more business on the Internet spend more on Big Data and project greater ROI. Companies that generate more than 75% of their revenue over the Internet spend about six times more on Big Data than do companies whose Internet business is 25% or less of total revenue. These Internet-centric companies also projected an ROI on Big Data (88%) that was nearly three times that of the less Internet-centric companies. Furthermore, the depth of the behavioral data that Internet-centric companies gather on their online customers gives them proprietary insights for developing superior new products and services, as companies such as Procter & Gamble Co. and Netflix Inc. have found. (Read more)

Monitoring how customers use their products to detect product and design flaws is seen as a critical application for Big DataMonitoring how customers use their products to detect product and design flaws is seen as a critical application for Big Data, especially by heavy manufacturing companies such as General Electric Co. whose customers depend on their products. (Read more)

Organizing a core unit of Big Data analysts in a separate function appears to be important to successOrganizing a core unit of Big Data analysts in a separate function appears to be important to success. Companies that expected the highest ROI on Big Data in 2012 are more likely to have a separate department of professionals who process and analyze Big Data than are companies expecting the least ROI (or no ROI). (Read more)

In the sections that follow, we explore these findings as we discuss how the survey results in this big data study compared across regions of the world, by global industries and by business function. Lastly, we discuss the implications of our research and provide advice for companies that want to get more out of Big Data and need to know where and how to begin.

We base our prescriptions in Section VII of the Big Data Study on two sources: our analysis of what leading companies at the Big Data game (those with the greatest ROI) are doing differently than the rest, and insights from TCS consultants who are helping our clients capitalize on Big Data.


 


Introduction and Key Findings
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