Several days ago, the New York Times published an article titled, "The Age of Big Data." The newspaper described how companies will need many more data analysts who can "help businesses make sense of an explosion of data — Web traffic and social network comments, as well as software and sensors that monitor shipments, suppliers and customers — to guide decisions, trim costs and lift sales." The article cited a McKinsey Consulting study which predicted that the United States will need 140,000-190,000 more employees with “deep analytical” expertise" in the coming years.
As an example of the importance of big data, consider the online retailer Diapers.com (owned by Amazon). Forbes writer Meghan Casserly describes the firm's use of big data in an article published on the magazine's website. The company has built powerful proprietary algorithms over the past few years based on tons of transactions. These algorithms predict what customers are likely to buy in the future, how much they will spend, and whether they will be profitable for the firm. The company's strategy focuses on building loyal customers who purchase low margin baby supplies initially, and then buy higher margin items such as car seats, strollers, and the like in the future. The algorithms not only help predict purchasing patterns, but they enable Diapers.com and its sister sites to market appropriately to different customers. Perhaps most importantly, the firm can identify which customers will be profitable for the firm. Thus, they can spend their time catering to the most profitable customers, rather than wasting marketing expenditures on consumers who will be a drain on resources.
Every company should be thinking about how it can use algorithms to drive performance. Analytics can be used in a myriad of ways. However, building a strategy based on big data requires the right talent. Therefore, firms need to begin thinking carefully about how they will attract, develop, and retain the talent needed to collect and analyze the huge volumes of data that now exist. Universities need to think about how to educate people for these roles, as demand will be strong. We need to do more than educate people in mathematics and statistics though. We need analysts who can understand business models and strategies, and who have a deep understanding of consumer behavior too. The best analysts will be those who can marry statistical knowledge with a broader understanding of the entire organizational system.