The Rise of Customer Reference Data
The digital revolution is dramatically transforming customer engagement and life sciences is no exception. According to Tech Pro Research, 70% of companies have a digital transformation strategy in place or are working on one, but research by McKinsey & Company shows that pharma is lagging behind 33 other sectors in terms of digital maturity.
The Data Leadership Forum, hosted at Veeva’s Data Research Center in Fort Washington, PA, convened some of the brightest minds in life sciences for a thoughtful debate about how to accelerate the pace of digital transformation and lay the foundation for long-term success.
Customer Data is Mission-Critical in an Evolving Industry
Increasingly HCPs are minimizing face-to-face visits with pharma reps and turning to a broader range of digital channels for information including email, video chats, and websites. Getting visibility into these interactions in a single, integrated view is critical to personalizing customer engagement and improving field effectiveness. This data is often scattered across multiple systems and teams are keen to consolidate it into a single, cohesive view of the customer.
“Having a golden record for customer demographics is critical,” said Mike Miner, executive director of sales operations at Astellas.
At the same time, as more HCPs become part of larger, integrated healthcare networks, they have less autonomy to make prescribing decisions, which are increasingly made at the organizational level. As sales teams shift to account-based selling models, they want better visibility into the relationships between HCPs and their healthcare organizations (HCOs) in order to map out effective and efficient engagement strategies.
“If I know how healthcare providers and healthcare organizations are connected, that gives our team a big competitive advantage,” said Steve Davenport, associate director of commercial data strategy and management at Biogen.
Another theme that emerged was the need to source accurate customer data as quickly as possible when launching new drug therapies. With homegrown systems, compiling this information can be slow and burdensome. As a result, many teams are opting to license the data, which allows them to reach new customers in record time.
“We replaced our in-house solution with Veeva OpenData. I am so thankful we did because we just got into a new market,” said Steve Davenport. “With Veeva OpenData, we can quickly infuse new records into our system versus trying to build that data from scratch. We can go a lot faster and it allows us the flexibility to grow.”
Quality is Essential for Digital Transformation and AI
As patients and HCPs turn more to digital channels to evaluate drug therapies, pharma companies are striving to design intelligent customer journeys fueled in part by predictive analytics and AI. For this to become a reality, the right data governance structure must be in place to integrate and analyze vast amounts of data from across multiple systems.
“We have a rich abundance of data,” said Bryan Timer. “The c-suite sees the promise of AI and wants new tech and messaging quickly but doesn’t always understand the data infrastructure needed to make it happen.”
To overcome the inertia that often hinders innovation, many pharma companies are spinning up dedicated teams to pilot and test new programs. When programs are successful, the company can invest more to scale.
“We have a dedicated customer engagement team that uses AI and machine learning,” said Christine McDonough, director of data governance at Astellas Pharma. “Our job in data governance is to provide them with the data sets they need to drive innovation.”
Early findings show that for AI to become a reality, the right data foundation must be in place and the data itself must be accurate, timely, and standardized.
“Bad data is amplified in machine learning and AI,” said Steve Davenport. “The first thing we’ve learned is the importance of having outstanding data to base your machine learning on.”
Maintaining data quality is an ongoing challenge for the majority of teams. According to the Veeva 2018 Customer Reference Data Survey, two-thirds of pharma companies are dissatisfied with the quality of their customer reference data and 71% have quality improvement initiatives underway, placing emphasis on delivering clean, complete, consistent information the entire company can leverage.
“When it comes to data quality, perception matters,” said Steven Davenport. “Do people believe in your data and make big, tough decisions based on it? That is the ultimate measure of quality and value.
New Leadership Roles Are Emerging
“As an industry, we don’t like to change,” said Bryan Timer, director of data analytics and transparency at Merck. “To meet the challenges of tomorrow we have to innovate and change our ways.”
“Driving change requires executive sponsorship,” said Steve Davenport.
Increasingly, that executive sponsorship is coming from chief data officers (CDOs), who are focused on building data-driven cultures, breaking down silos, mandating the proper use of data, and harnessing it into actionable insights that provide a competitive edge in the market.
According to McKinsey, 20% of the top pharma companies have hired a chief digital officer versus two-thirds of similarly-sized companies in other regulated industries such as banking, finance, and insurance. This gap is reflective of the “wait and see” attitude that is commonplace in the pharma industry, but nevertheless, it’s imperative for organizations who want to succeed to take bold action today.
Across the board, these leaders say to be best positioned for success, teams need embrace innovation, keep up with the rapid pace of change, and stay informed on best practices.
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