mobile analyticsA sales rep’s regularly scheduled appointments are interrupted by an alert on his smartphone or iPad. A nearby practice serving a large patient population recently enrolled in a regional health-care plan. In short order, he receives a Google map to that office, details about the practice, as well as patient and physician characteristics, and reminders of key brand, payer and compliance messages. The rep arrives at the unplanned call fully prepared to present his therapies.

This scenario is just one example of how pharma company IT departments can combine Big Data, predictive analytics, technological mobility and social media to accelerate the pace at which sales and marketing teams make the best decisions possible. Technology that can analyze terabytes of information, summarize results in digestible form and place just-in-time insights seamlessly into business processes will transform your sales and marketing organizations into agile teams.

Here are three key opportunities to shift from past-performance analytics to actionable foresights:

  • Automate Customer Segmentation—Collecting and processing all the information necessary for physician segmentations is time and labor intensive—and in many cases, the physician data becomes outdated far too quickly. The worst (all too common) scenario is to create entire marketing campaigns around old data, thereby wasting millions of dollars—and annoying physicians. Big Data techniques (data first, structure later), harnessing new emerging data sources (CLM, EMR and others) and business analytics can completely change the game by providing real-time segmentation and targeting.
  • Coordinate Customer Coverage—Channel strategies are often executed in silos and reviewed infrequently, limiting opportunities to spot synergies and trends. But automating channel analytics can detect and communicate these opportunities instantly. Ultimately, coordination and near real-time budget reallocation between channels can maximize the return on every dollar, which is critical in today’s world of shrinking margins and expiring patents.
  • Optimize Customer Tactics—As our opening scenario illustrated, predictive and automated analytics empower sales reps with the information they need to anticipate customer needs—and pinpoint when and how to meet those needs. Dynamic targeting works continuously to incorporate all available customer segmentations, responses and activities, and then consolidates data and directives into recommendations for the sales rep right now.

In recent years, pharma companies have invested significantly in collecting data that can begin to drive these opportunities: patient demographics, physician prescribing history, closed-loop marketing and more. Still, most pharma companies rely on people-powered analytics instead of automating analytics to ensure critical information is delivered in time.

Competition is increasingly defined by depth of insight and speed of execution, which means IT cannot afford to delay its transition:

  • They need employees with specific skills (business knowledge; understanding of analytical tools, techniques and algorithms).
  • They must transition quickly to a service-oriented architecture, mobile apps, GPS location and Web-accessible business intelligence.
  • Most important, IT must shift its focus from cost center that hosts hardware and software to revenue driver that creates, automates and delivers insights in real time.

Until recently, the sales rep armed with a smartphone full of alerts from predictive analytics programs was considered science fiction. But today, enabling this vision has become a business necessity.

To view the original article that was published in PM360 magazine, click here.

Where does your organization stand in the movement toward analytics automation? What are some of the key benefits (and challenges) your sales, marketing and IT teams have experienced?


maria klAbout the Author

Maria Kliatchko is a Principal at ZS Associates and based in the firm's New York office. Maria is a key leader in ZS's Business Technology practice and advises clients on technology strategy, business intelligence, commercial data integration and customer relationship management (CRM). 


Topics: big data, mobility, pharma sales planning, predictive analytics, Maria Kliatchko