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Case Study: Eli Lilly Provides a Better CRM System for Its Reps Describe why the Veeva CRM system was critical to Eli Lilly. What are

Case Study: Eli Lilly Provides a Better CRM System for Its Reps

  1. Describe why the Veeva CRM system was critical to Eli Lilly.
  2. What are the potential disadvantages of Veeva eDetailing? Provide examples to support your answer.

Eli Lilly Provides a Better CRM System for Its Reps The Problem Physicians are arguably the most important component in pharmaceutical sales because they write the prescriptions that determine which drugs their patients will use. Therefore, influencing the physician is the key to success for pharmaceutical sales representatives. Historically, large pharmaceutical salesforces, called drug reps, have been responsible for these marketing efforts. Their strategies have involved physically visiting physicians' offices and providing drug samples. As of October 2015, there were more than 80,000 drug reps in the United States, marketing to some 830,000 physicians. Drug reps typically try to see a given physician every few weeks. However, the number and persistence of drug reps has placed a burden on physicians' time. The problem has become so acute that half of all physicians require an appointment before they see a drug rep, and another one-fourth will not see a drug rep at all. In addition, the Pharmaceutical Research and Manufacturers of America (PhRMA; www.phrma.org) provides voluntary ethics guidelines called Interactions with Healthcare Professionals. These guidelines prohibit drug reps from providing restaurant meals to physicians and from giving physicians small gifts and reminder items such as pens and notepads. Pharmaceutical companies, therefore, have customer-management needs that are more complex than those of other industries. These firms have to deal with tightening restrictions on salespersons' access to physicians and other healthcare decision makers. This changing environment has caused the pharmaceuticals to shift their CRM strategies from frequency-based interactions to technology-supported methods. Let's consider Eli Lilly as an example. Eli Lilly and Company (Lilly; www.lilly.com) is a global pharmaceutical company based in the United States that maintains offices in 17 other countries plus Puerto Rico. The firm's products are sold in approximately 125 countries. The company employs 16,000 sales representatives, medical liaisons, and account managers who call on healthcare professionals and administrators around the world. In the past, Lilly's drug reps employed multiple sales force automation products, data management systems, and reporting tools. The old systems required the reps to record call comments at the end of the day rather than during or immediately after a meeting with a physician. This system caused the reps to keep very sparse notes, or none at all. It frustrated and fatigued the reps, and it ultimately led to lost insights concerning the physicians. Another problem occurred because drug reps in different countries used different CRM systems. This situation made it difficult for Lilly executives to obtain an accurate, integrated view of the entire business. Moreover, staff members had to do a great deal of work each month to manually produce standard, consistent business information at headquarters. Exacerbating these problems, reps were calling on physicians with personal computers running the Windows XP operating system. They had to wait while the machines took several minutes to boot, and they had to rely on less-than-persuasive PowerPoint presentations. In addition, reps required between three and five days of training to learn the system. The IT Solution Lilly urgently needed to upgrade its CRM tools. The company therefore turned to Veeva Systems' (www.veeva.com) cloud-based, mobile-friendly CRM product. The firm's reps now use Veeva on their iPads to plan physician calls, record and report on those conversations, present drug information, and analyze trends. The Veeva system also enables Lilly drug reps to perform eDetailing. Detailing refers to the activity of drug reps when they call on physicians and provide them with detailsscientific information, benefits, side effects, or adverse eventsrelated to particular drugs. eDetailing means using interactive, online CRM tools in the drug presentation and sales process. Two examples of eDetailing are: Virtual details: Web-based, self-guided information programs with no live communication between drug reps and physicians; Video details: online, live, or phone-assisted browsing through virtual sales presentations. In addition to these examples, Veeva eDetailing enables drug reps to conduct integrated online surveys, market segmentation, and targeting. Because it is becoming increasingly difficult to physically meet with physicians, drug reps depend on eDetailing to deliver the relevant information about their brands and drugs. The Results An initial benefit of the Veeva system was that Lilly sales reps could be trained in only half a day. The new system also enables reps to interact with physicians, nurses, and administrators in a customer-centric manner. Veeva was much easier and faster to deploy than the company's original on-premise CRM software. (We discuss on-premise software in Plug IT In 4.) In fact, the Veeva system saved Lilly millions of dollars per year due to lower IT support costs and improved efficiency. Lilly's Veeva solution forced the company to standardize its previously separate data stores. Lilly now uses Veeva Network to integrate its customer data from around the world. Field reps can utilize these data to access Lilly's interaction history with customers to tailor their presentations. These presentations can be made either in person or online. Further, the company can identify customers with similar profiles who should receive similar presentations. The Veeva initiative's success resulted from close partnerships among Lilly's IT group and the company's sales operations team. The data standardization process also provides the potential for Lilly to integrate its data with public data, such as U.S. census data. This process could lead to insights into drug prescription trends and healthcare spending across different demographic groups.

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