Will mega-information help managers make better decisions?

Executive Summary

Big data—information that can be measured in millions of billions of bytes—increasingly allows businesses to understand their customers and gain advantage over their competitors. These data sets are huge and sometimes messy but, with ever-improving statistical tools, they can yield information that allows managers to act quickly and profitably. Manufacturers can produce what customers want, retailers can gauge when and where consumers will buy and shippers can offer same-day delivery. Even small businesses can benefit from previously inaccessible information. However, business analysts say few organizational cultures wholeheartedly embrace evidence-based decision making, even if they are using smaller, easily accessible data sets. Moreover, managers generally lack the statistical and mathematical understanding needed to manage big-data projects or assess how big-data tools might help their companies. Thus, managers are challenged to glean insights from big data and measure the results. The growing importance of big data also may be increasing the value of employees with quantitative skills while reducing the need for middle managers.

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Provost, Foster, and Tom Fawcett, “Data Science for Business: What You Need to Know About Data Mining and Data-Analytic Thinking,” O'Reilly Media, 2013. A professor of information systems at New York University's Stern School of Business (Provost) and a data-science researcher (Fawcett) explain the principles that underlie big-data analysis, using historical and current examples of real-life business problems.

Stanton, Jeffrey, “An Introduction to Data Science,” 2012, http://tinyurl.com/kb6w75l. In this text for a certificate program in data science, a Syracuse University professor of information science explains how to approach practical questions using statistics and how to perform statistical analysis using free software tools.


Crawford, Kate, “The Hidden Biases in Big Data,” Harvard Business Review blogs, April 1, 2013, http://tinyurl.com/mcrluz4. It's easy to be misled into believing large data sets are accurate and unbiased, according to Crawford, a Microsoft Research principal researcher.

Dwoskin, Elizabeth, “Big Data's High-Priests of Algorithms,” The Wall Street Journal, Aug. 8, 2014, http://tinyurl.com/mepaota. Data scientists need a rare combination of statistics and math skills, computer savvy and problem-solving ability; those who possess those traits are highly sought after by big retailers, manufacturers, Internet giants and other companies.

Harford, Tim, “Big data: are we making a mistake?” Financial Times Magazine, March 28, 2014, http://tinyurl.com/k6l7b5w. Using big-data analytics effectively requires paying attention to traditional principles of statistics.

Marcus, Gary, and Ernest Davis, “Eight (No, Nine!) Problems With Big Data,” The New York Times, April 6, 2014, http://tinyurl.com/knqc3bt. New York University professors of psychology (Marcus) and economics (Davis) list the pitfalls that can afflict those who work with big data. Two common ones: It can generate statistics that aren't necessarily meaningful, and it can encourage users to ask useless questions.

O'Toole, Kathleen, “Susan Athey: How Big Data Changes Business Management,” Insights by Stanford Business, Sept. 20, 2013, http://tinyurl.com/pd5qxyw. Athey, a Stanford University professor of the economics of technology, says that the rise of data-based decisions makes it imperative that all executives understand the basics of decision statistics and automated data analysis.

Walker, Joseph, “Meet the New Boss: Big Data,” The Wall Street Journal, Sept. 20, 2012, http://tinyurl.com/nlzpumr. Hiring managers increasingly use automated big-data analytics to turn up unexpected characteristics that predict who will be the best hire. For example, a software program advised a company seeking call-center workers that people with creative personalities were more likely than those with inquisitive natures to stick with the jobs for six months or more.

Reports and Studies

“Big Data and Privacy: A Technological Perspective,” President's Council of Advisors on Science and Technology, May 2014, http://tinyurl.com/nu2oy5d. White House technology advisers argue that technologies to protect privacy can't keep up with the big-data-related advances and that new laws and regulations will be required to protect individuals' personal information.

“Big Data: The next frontier for innovation, competition, and productivity,” McKinsey Global Institute, May 2011, http://tinyurl.com/cplxu6p. Analysts at the McKinsey & Company consultancy assess big data's effects on the workforce and market competition and its potential for boosting earnings and improving efficiency in retail, health care, manufacturing and government.

“Big Data: Seizing Opportunities, Preserving Values,” Executive Office of the President, May 2014, http://tinyurl.com/n9vda93. A panel of presidential advisers explores the opportunities big data will present for U.S. businesses and government privacy and security agencies, but cautions that current practices for protecting individuals' rights online will not be equal to the new threats posed by big data.

“Gut & Gigabytes,” The Economist Intelligence Unit/PricewaterhouseCoopers, 2014, http://tinyurl.com/kjesgmf. In a survey conducted by a U.K.-based business-forecasting group, 1,135 public- and private-sector executives describe their experiences with data-based decision making and their expectations for future big-data use in their organizations.

The Next Step


Bertolucci, Jeff, “Does Big Data Need A ‘LinkedIn For Analytics’?” InformationWeek, Nov. 20, 2014, http://tinyurl.com/nhf94uo. Companies undertaking big-data projects or adopting new data management methods would benefit from a crowdsourcing network that connects them with data professionals, according to the vice president of an analytics company.

Clark, Jack, “Big Data Knows When You're Going to Quit Your Job Before You Do,” Bloomberg, Dec. 30, 2014, http://tinyurl.com/lgf4xzs. Several Silicon Valley companies have developed software that allows companies to track a wide range of employee activity data and to help retain those who are likely to quit.

Schulte, Brigid, “Women flocking to statistics, the newly hot, high-tech field of data science,” The Washington Post, Dec. 19, 2014, http://tinyurl.com/l5xzuuu. More women are studying statistics and earning university faculty positions as demand grows for big-data professionals, bucking the trend in male-dominated science, technology, engineering and mathematics (STEM) fields.


Bedoya, Alvaro M., “Big Data and the Underground Railroad,” Slate, Nov. 7, 2014, http://tinyurl.com/lro69ey. A privacy law expert suggests that while big data will benefit public health, business efficiency and other areas, ubiquitous collection may also harm vulnerable groups such as minorities.

Herold, Benjamin, “‘Big Data’ Research Effort Faces Student-Privacy Questions,” Education Week, Oct. 21, 2014, http://tinyurl.com/q6noujq. Data privacy advocates worry that the federally funded “Learnsphere” initiative, which will store behavioral data from high school and college students in online courses, violates students' privacy by sharing their personal information.

Perera, David, “Smart grid powers up privacy worries,” Politico, Jan. 1, 2015, http://tinyurl.com/oxlrwxu. The U.S. Department of Energy will begin collecting household electricity consumption data for utility suppliers through “smart meters,” but some legal experts say the program violates consumers' privacy.


Lippert, John, “Lender Charging 390% Uses Data to Screen Out Deadbeats,” Bloomberg, Oct. 3, 2014, http://tinyurl.com/qgwyyew. To choose the most reliable borrowers, Los Angeles-based lender uses large pools of data to screen low-income applicants for high-interest loans that average $600.

Shinal, John, “If ‘clean,’ big data can improve U.S. health care,” USA Today, Aug. 28, 2014, http://tinyurl.com/k8sosou. Data collection companies might be able to profit from the digitization of all U.S. patients' medical records by integrating social media user and consumer data to ensure the records' accuracy.

Todd, Deborah M., “Study finds obstacles with social media data,” Pittsburgh Post-Gazette, Nov. 3, 2014, http://tinyurl.com/kgchaz9. Researchers from Carnegie Mellon and McGill universities say that anyone analyzing large sets of social media user data should adjust for factors such as public health, spending, political outcomes and false information to ensure reliability.

Small Businesses

Grossman, John, “Finding Ways to Use Big Data to Help Small Shops,” The New York Times, July 9, 2014, http://tinyurl.com/lrczsog. The growing simplicity and shrinking costs of data analysis have led to a significant rise in the percentage of small businesses using intelligence software.

Hassemer, Jeff, “Think Small: Why Big Data Isn't For Everyone,” Advertising Age, Jan. 6, 2015, http://tinyurl.com/qctwfso. Businesses with insufficient resources to undertake big-data projects may benefit more from using “small data,” or very basic sets of customer data, according to an executive of a digital advertising company.

Kelleher, Kevin, “What 3 Small Businesses Learned From Big Data,” Inc. Magazine, July-August 2014, http://tinyurl.com/p4rxszc. A North Carolina-based vacation real estate company, a zoo in Tacoma, Wash., and a Phoenix-based online car marketplace were able to improve customer service and be more competitive after working with big-data analytics providers.


American Statistical Association
732 N. Washington St., Alexandria, VA 22314-1943
Membership organization for statisticians that provides information on predictive and Bayesian statistics as well as statistics for business.

Association for Information Systems
P.O. Box 2712, Atlanta, GA 30301-2712
Membership organization for information-systems professionals, academics and researchers.

Data Science Association
7550 E. 53rd Place, Unit 172622, Denver, CO 80217-2622
Membership group that provides information on predictive analytics, algorithms, data visualization, machine learning and other topics.

Decision Sciences Institute
C.T. Bauer College of Business, 334 Melcher Hall, Suite 325, Houston, TX 77204-6021
Membership organization that has information on quantitative methods for decision making in business and other fields.

Digital Analytics Association
401 Edgewater Place, Suite 600, Wakefield, MA 01880
Membership group with information and research on data acquisition, analysis and use.

Gartner Inc.
56 Top Gallant Road, Stamford, CT 06902
Business consultancy that specializes in technology, including big data.

International Institute of Business Analysis
701 Rossland Road E., Suite 356, Whitby, ON L1N 9K3, Canada
Professional organization that provides certification and information on all aspects of business analysis.

McKinsey & Company
55 E. 52nd St., New York, NY 10022
Business consultancy with news and information on analytics and big data.

DOI: 10.1177/2374556815573238