Developing a Successful Data & Analytics Strategy: Four Common Questions

After more than a decade of explosive growth in the availability and diversity of healthcare real-world data (RWD), a comprehensive data and analytics strategy is now table stakes for pharmaceutical and life science organizations.

The right approach provides demonstrable advantages to advance crucial clinical and business objectives that define success—for the business and patients alike.

Simon Andrews

A data and analytics strategy consumes time and resources. The right strategy must balance demonstrating short-term outcomes to build confidence in the approach within an organization, and long-term solutions that truly alter the usual course of business.

Consider these four core pharmaceutical operations and the role that a data strategy plays.

• Research and development: Discovering the next round of drugs and identifying opportunities to repurpose existing therapies and/or seek label expansions
  
  
• Clinical development and medical affairs: Choosing the optimal designs and parameters for clinical trials, negotiating new and emerging forms of evidence generation for regulatory approvals and payer communication, and managing company-HCP interactions
  
• Brand: Understanding the patient journey and identifying intervention points to maximize patient reach, drive commercial and marketing strategies, and forecast demand and revenue to justify investments
  
  
• Commercial & Marketing: Identifying critical accounts and practitioners to influence uptake and allocate commercial resources effectively, drive effective HCP and patient marketing to reduce barriers to diagnosis, and orchestrate activities across all channels.

For each of these functions, the standards for analytical sophistication have risen significantly, increasing the urgency for companies to buy, build, or partner with companies to incorporate data and analytics into their decision-making across the entire development and commercialization life cycle. No matter the size of the organization, data can and should inform all workstreams.

Here are four common questions organizations often need to answer as they develop or expand their data and analytics strategies, as well as considerations for each question.

1. Should I buy data? Buying data outright and bringing it in-house for analysis versus accessing it through a third party is a very common question. Purchasing often requires sophisticated IT and privacy infrastructure, data science, and business analyst personnel, and can be pricey. Accessing data in a managed services-style model is likely a less expensive way to reduce decision burden, take advantage of external institutional knowledge, and see results faster. Both options should be weighed carefully, assessing both the business’s objectives and the sources available to serve those objectives. The decision to buy or rent should be made as your data needs and analytical capacity evolve.
   
   
2. What type of data should I buy? If you’ve made the decision to buy, your foremost need is a core data stack that allows you to understand patients and customers as broadly as possible, with the fewest distinct purchases possible. In today’s world, insurance claims (medical and pharmacy) are effectively nonnegotiable. Availability is high, coverage is high, awareness is high. Specialty pharmaceutical and medical device manufacturers have some special distinctions. Open and closed data considerations are critical and will likely depend on your organization’s most pressing needs. Likewise, formulary and HCO/HCP directories and affiliations data are critical elements in any data and analytics stack. Newer, more leading-edge data sources including electronic health records (EHRs), genomic testing data, patient/consumer data are all being actively used and tested for value but are not at the same level of ubiquity and pay per usage is a great way to generate exposure, prove ROI, and really determine organizational needs. A third-party partner with extensive experience in real-world data and evidence can also help drive decision-making.
   
3. Why is it important to show a return on investment? Demonstrating your data and analytics return on investment can take several forms. Either you could be proving that you are doing an existing activity with more accuracy or faster than before, or you’re answering previously unanswered questions. Ultimately, connecting your data and analytics investments to improved internal decision-making, increased patient reach, and financial savings is the proof. For clinical development audiences, are you able to choose your clinical endpoints with more evidence to recruit faster and with better diversity, and generate another independent source of effectiveness that corroborates the rest of your sources of evidence and value? For sales audiences, are you aligning territories and people more effectively? Are you seeing better response rates among HCPs, or finding HCPs that you weren’t finding before? For rare disease companies, are you reaching more patients than you had expected? The ROI creates the flywheel effect of encouraging broader usage that could demonstrate new ROI. And when the value is proven, champion these results across your organization to further reinforce its impact to key stakeholders.
   
4. Do I have a global data and analytics strategy and how can I ensure it meets privacy and compliance requirements? The data and analytics market in healthcare today skews heavily toward the United States. There are simply more well-established supporting market infrastructures and data sources available than in other parts of the world. However, the needs of patients don’t change based on borders, which makes a global strategy important. Outside the United States, data exists and can be used in research, but the acquisition process, usage rights, and privacy considerations vary vastly. Government entities like the FDA have released multiple guidance documents on the usage of real-world data and evidence in regulatory submissions, encouraging the global shift in data and analytics usage. The European Union has developed goals for building a more available and accessible market for research-ready data by 2025.¹ The landscape is changing and the right partner that understands the global landscape can help build a strategy that meets your business requirements in a privacy-compliant fashion.

In today’s competitive global market, organizations cannot afford to waste time or resources on strategies that do not increase patient access, drive revenue, and ultimately improve patient outcomes. A clear data and analytics strategy is a must, and the modern data and analytics marketplace has enabled life sciences functions to make significant improvements, and the scope is expanding. As the COVID pandemic revealed, when groups bring new data together in privacy-compliant fashions, decisions can be made at extreme velocity.

Data and analytics practices will continue to grow, and the industry can expect modularity that allows companies to buy, build, and partner only for what they need. This will drive innovation including the emergence of new data sources while creating jobs as the industry looks for the best and brightest talent. Understanding how the power of data and analytics, privacy, and other factors that go into creating the right strategy means more now than ever. Now is the time to get your data house in order. Your success, and the impact on the patients you serve, depend on it.

Simon Andrews is the Head of Data & Analytics at EVERSANA. For more on EVERSANA’s Data & Analytics experiences, click here.

Reference

1. https://www.ema.europa.eu/en/news/vision-use-real-world-evidence-eu-medicines-regulation