Will mega-information help managers make better decisions?
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.
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/
Crawford, Kate, “The Hidden Biases in Big Data,” Harvard Business Review blogs, April 1, 2013, http://tinyurl.com/
Dwoskin, Elizabeth, “Big Data's High-Priests of Algorithms,” The Wall Street Journal, Aug. 8, 2014, http://tinyurl.com/
Harford, Tim, “Big data: are we making a mistake?” Financial Times Magazine, March 28, 2014, http://tinyurl.com/
Marcus, Gary, and Ernest Davis, “Eight (No, Nine!) Problems With Big Data,” The New York Times, April 6, 2014, http://tinyurl.com/
O'Toole, Kathleen, “Susan Athey: How Big Data Changes Business Management,” Insights by Stanford Business, Sept. 20, 2013, http://tinyurl.com/
Walker, Joseph, “Meet the New Boss: Big Data,” The Wall Street Journal, Sept. 20, 2012, http://tinyurl.com/
Reports and Studies
“Big Data and Privacy: A Technological Perspective,” President's Council of Advisors on Science and Technology, May 2014, http://tinyurl.com/
“Big Data: The next frontier for innovation, competition, and productivity,” McKinsey Global Institute, May 2011, http://tinyurl.com/
“Big Data: Seizing Opportunities, Preserving Values,” Executive Office of the President, May 2014, http://tinyurl.com/
“Gut & Gigabytes,” The Economist Intelligence Unit/PricewaterhouseCoopers, 2014, http://tinyurl.com/
The Next Step
Bertolucci, Jeff, “Does Big Data Need A ‘LinkedIn For Analytics’?” InformationWeek, Nov. 20, 2014, http://tinyurl.com/
Clark, Jack, “Big Data Knows When You're Going to Quit Your Job Before You Do,” Bloomberg, Dec. 30, 2014, http://tinyurl.com/
Schulte, Brigid, “Women flocking to statistics, the newly hot, high-tech field of data science,” The Washington Post, Dec. 19, 2014, http://tinyurl.com/
Bedoya, Alvaro M., “Big Data and the Underground Railroad,” Slate, Nov. 7, 2014, http://tinyurl.com/
Herold, Benjamin, “‘Big Data’ Research Effort Faces Student-Privacy Questions,” Education Week, Oct. 21, 2014, http://tinyurl.com/
Perera, David, “Smart grid powers up privacy worries,” Politico, Jan. 1, 2015, http://tinyurl.com/
Lippert, John, “Lender Charging 390% Uses Data to Screen Out Deadbeats,” Bloomberg, Oct. 3, 2014, http://tinyurl.com/
Shinal, John, “If ‘clean,’ big data can improve U.S. health care,” USA Today, Aug. 28, 2014, http://tinyurl.com/
Todd, Deborah M., “Study finds obstacles with social media data,” Pittsburgh Post-Gazette, Nov. 3, 2014, http://tinyurl.com/
Grossman, John, “Finding Ways to Use Big Data to Help Small Shops,” The New York Times, July 9, 2014, http://tinyurl.com/
Hassemer, Jeff, “Think Small: Why Big Data Isn't For Everyone,” Advertising Age, Jan. 6, 2015, http://tinyurl.com/
Kelleher, Kevin, “What 3 Small Businesses Learned From Big Data,” Inc. Magazine, July-August 2014, http://tinyurl.com/
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.
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.