Jagdip Singh’s research involves building and sustaining effective and enduring connections between organizations and their customers, especially in service industries. Jagdip studies how firms organize, implement and support change and knowledge management to balance the competing goals of productivity and quality in the frontlines. He also studies conflicts of interest in professional markets, and its implications for marketing theory and practice.
At the dawn of 1980s, Jan Carlzon and his team at Scandinavian Airlines conceived a then radical idea to turnaround an ailing airline ranked at near bottom in international reputation. Instead of beginning from the top, Carlzon’s strategy elevated SAS’s interactions with customers at the frontlines to the status of “moment of truth” (MOT) for organizational competence and success. MOTs, he said, require Riv Pyramiderna (tearing down the organizational pyramids). It worked. And so was seeded the field of Frontline Marketing.
Defined as the designing, developing, and executing capabilities for interfacing with customers that create sustainable value and germinate organizational learning, frontline marketing is an exciting area of research. My research focuses on understanding how service organizations manage productivity-quality tradeoffs in MOTs involving frontline employees. Productivity-quality tradeoffs during MOTs are often hard to pinpoint, and resistant to managerial control. My research shows that productivity-quality tradeoffs are intrinsic to service work, and change dynamically with market heterogeneity. There is no guarantee that successful organizations today will not spiral down tomorrow to poorer tradeoffs as markets shift and new competitors emerge. And tomorrow comes sooner than we think. How do smart organizations engage these productivity-quality tradeoffs? Read on about recent research.
In today’s markets, the big story is BIG DATA. Technological advances (e.g., web, communications, and devices) are expanding customer-to-firm and consumer-to-consumer contact points, and enabling capture of rich and diverse transaction data at nearly every contact. No doubt marketing data stocks are exploding at a rate that defies Moore’s law (double every two years). Yet, on their own, big data do not reveal big insights. Insights from big data require SMART ANALYTICS. Unfortunately, data stocks are increasing at a rate that is not matched by our capacity for smart analysis and deep insights. I teach a course on marketing analytics that skills students to fill this capacity shortfall and prepares them for Certification in Analytics. Developed in partnership with Rosetta, the marketing analytics course is an innovative integration of theory (e.g., analytical concepts) and practice (e.g., real life data based problems) with emphasis on internet and web analytics. How does the course achieve this integration? What do students think about this course? Read on.