More than a catch phrase, “big data” now poses big questions for marketers and company decision-makers. The University of Virginia’s Darden School of Business has new ways to help marketing practitioners find the narrative in the numbers and articulate their meaning to leaders who must deploy resources wisely.
Led by Darden’s marketing faculty, the school will offer a new program and develop new knowledge to help practitioners effectively interpret analytics, the facts and figures that comprise big data. Following are new offerings from Darden in the field of big data:
- In December, the Darden Executive Education program “Marketing Analytics: Effective Resource Allocation” will help marketers understand the potential of analytics and bridge the gap between marketing analytics and the language of top-level decision-makers.
- In spring 2014, a new book, “Marketing Analytics: Tools for Effective Resource Allocation,” by Darden Professors Rajkumar Venkatesan, Paul Farris and Ron Wilcox, Ethyl Corporation Professor of Business Administration, will teach readers how to translate business-friendly mathematical concepts into the language of company leaders.
- Ongoing research in the realm of marketing education, marketing productivity and sales management will also provide answers to pressing big-data issues.
“There is a widely held belief that sophisticated analytics are not enough to address the concerns of the C-suite,” or executive leadership, said Venkatesan, who was recognized by the Marketing Science Institute as one of the rising young scholars in the field. He and Farris, who is the Landmark Communications Professor of Business Administration and co-author of the industry’s definitive book, “Marketing Metrics: 50+ Metrics Every Executive Should Master,” outlined the big-data challenges faced by marketers, their clients and academics at the Marketing Science Institute’s spring conference, “Marketing Resource Allocation: Moving From Analytics to Action,” held at Darden.
“Inadequate communication within organizations was one of the most often mentioned obstacles to implementing recommendations derived from data,” Farris said. “People in different silos within an organization speak different languages, and the key presenters of analytics need to know how to speak to them all.”
According to Venkatesan, who co-led the conference with Farris, the organizational focus on analytics should not be too wide or too narrow and it must match the top-of-mind factors of company decision-makers.
“If a data analysis does not consider metrics such as competition, market trends that affect product potential, or customer satisfaction, then it doesn’t meet the needs of top-level decision-makers,” he said.
“Understanding the management issues is most important in communicating the meaning behind analytics,” Farris said. “It can’t be assumed that the data or summary analytics will speak for themselves.”
Also, according to Farris, learn-do and decision cycles are often out of sync with organizational structure and management concerns.
“For example, the ability of a firm to deliver customized promotions must be considered before committing to designing promotion calendars for individual customers, stores or chains,” Farris explained.
To prepare for the revolution in big data, the design of firms will need to shift along with people and budgets. Farris and Venkatesan assert that a series of needs and questions must be addressed, including the following:
- How to create the flexibility to move money across products and functional areas within an organization
- How to test theories and learn in real-time cycles that match decision-making
- How to work with parts of a company’s supply chain in new ways
“Data is coming fast and organizations must respond,” Farris said. “An effective response requires learning loops and feedback systems so that management can truly learn, implement results and demonstrate gains over time.”
The conference discussion also included ways for business schools to train MBA students in the language of business executives.
“Darden will offer a new elective on big data in the marketing area during spring 2014,” Venkatesan said. “Darden’s case method is ideal for teaching the language of both analytics and management to students.”
He added that students can dive into the data searching for nuggets of information with their learning teams before class, and they can discuss and debate the strategic implications of the insights from analytics while in class.
“Graduates who have the business intuition and acumen for analytics will be hot commodities in the job market,” Venkatesan said.
In addition to co-hosting the recent Marketing Science Institute conference, Venkatesan and colleagues from the University of Connecticut received a research grant from the institute for their project, “Mobile Platforms, Location-Based Services and Their Impact on Consumers.” Competition was fierce, with only six winners chosen from among 35 high-quality submissions.