Research Brief: 2011 Big Data Attitudes and Perceptions
Executed by Zoomerang—Commissioned by Connotate
Staffing and the Volume of Information are the Primary Big Data Challenges
The “Big Data Attitudes and Perceptions Survey” provides insights from today’s top thought leaders spanning a variety of industries into corporate goals involving Big Data. The survey highlights how enterprises monitor, collect and use information in Big Data projects and presents executives’ views on the importance of these projects to the business.
Big Data is quickly supplanting cloud computing as the topic that is on every CIOs’ agendas. This is amazing considering that the term “Big Data” did not even exist a few years ago and most companies were not taking advantage of readily available data. The survey results clearly indicate enterprises’ rush to incorporate Big Data and most of the executives are opening up their eyes – and checkbooks – to leverage this valuable resource.
There is still more to do and this decade will belong to those companies who are able to efficiently turn Big Data into gold. In fact, industry analyst firm Outsell, Inc. identified the “ability to mine data for building new products and generating income” as the key differentiating characteristic among the leading information companies five years from now. Just like Industrial Revolution started to replace manual labor with machinery, we are seeing Big Data “automation spring” led by large corporations.
Key Findings: (Click here to view survey questions and charted results..)
Staffing and Data Volumes are the Main Hurdles to Big Data Adoption
The primary deterrents to enterprises leveraging Big Data are human effort (45 percent) and the volume of internal and Web information (44 percent). The common perception is that the “Big” in Big Data is the only thing preventing enterprises from reaping the benefits of this trend but this report indicates that companies believe human capital is equally important. This juxtaposition is interesting because it shows the business world’s poor understanding of Big Data. In all other corporate initiatives, the executive and IT teams use technology to optimize operations but that thinking has not translated to Big Data yet: companies view it as a personnel problem just as much as a technological one.
The human effort statistic – staffing – highlights the importance of efficient data monitoring and extraction methods for Big Data. The Internet is a dynamic environment where new information is continuously created and distributed at exponential growth rates. This data has the power to deliver business insights; however, 61 percent of respondents are creating huge obstacles for themselves by manually searching and collecting Web-based data and content. With almost a third (31 percent) of respondents saying they need to collect critical information for their Big Data projects daily, organizations’ anxiety around not having enough people to support Big Data initiatives comes into clearer focus.
According to respondents, the quality of the data is just as important as how the data is collected. Information quality/accuracy was cited as the most important characteristic of Web data, a key source of Big Data, for enterprises by 59 percent of those who completed the survey.
Executives Understand the Importance of Big Data
Data aggregation is establishing itself as an increasingly important function within the enterprise based on the findings of the survey.
- 27 percent of executives are involved in managing their organization’s data aggregation operations and/or budgets
- 58 percent of the companies surveyed spend close to $500,000 on Web data aggregation
- 4 percent of respondents indicated they spent more than $10 million on data aggregation annually
Enterprise Uses for Big Data
At this early stage of Big Data’s adoption within the enterprise, organizations are keeping their initiatives simple as the survey found that the most popular uses of Web data were monitoring the company’s brand as well as the competition. However, it is important to note that 39 percent of respondents have been able to create revenue as a result of their Big Data projects by offering data services. This number will continue to grow as profitable uses of Big Data enable large corporations and small companies to turn raw data into substantial revenue streams.
Mid-Market Lagging in Big Data Adoption
The mid-market (100-10,000 employees) is surprisingly lackluster in their use of Web data within the organization. Consider the following:
- Only 46% of mid-market companies use Web data for competitive monitoring as compared to 70% of enterprises (10,000+)
- Mid-market companies even lag behind the SMB market (less than 100 employees) in two major categories: brand monitoring (39 percent vs. 44 percent) and price monitoring (29 percent vs. 35 percent)
SMBs aren’t without their flaws, however. Only 27 percent of respondents within that segment indicated that they monitor the government (laws, regulations, etc.). Considering that most legislation affects SMB owners first and any compliance slip-up can result in sizable fines, this is a major blind spot they need to address.
Manufacturers Top Industry Adopters
Manufacturing, an industry not traditionally thought of as early technology adopters, is by far the top industry taking advantage of Web data for corporate purposes. Manufacturing is tops in brand monitoring (73 percent) and price (67 percent) as well as second in competitor (57 percent) and government (57 percent) monitoring.
Survey Overview and Respondent Profile
The 15-question survey was completed by 326 respondents who were invited to participate by Zoomerang, an online survey services provider. The survey was conducted in July, August and September of 2011.
Respondents were all located in the United States and worked in a wide variety of industries including:
- Information industry (16 percent)
- Technology (13 percent)
- News/media (12 percent)
- Financial services (7 percent)
- Healthcare (7 percent)
- Government (5 percent)
- Education (5 percent)
- Web services (4 percent)
- Manufacturing (4 percent)
- Energy (1 percent)
- Retail (1 percent).
