4 Ways to Help Pharma Understand and Better Use Big Data

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Jacob Pitkow, senior data analyst, JUICE Pharma Worldwide

The first step is to assess the existing capabilities within your agency. If you have an analytics team that's been responsible for implementing Google Analytics on your branded websites, you shouldn't assume they also have the knowledge to advise clients on the best use of big data. You need to understand what data problems your clients are facing, and what tools and methods can help solve those problems. Do you need expertise in distributed systems such as Hadoop, Spark, or Cassandra? Or do you need expertise in quantitative methods such as clustering, classification, or natural language processing? When it comes to analytics, always invest in talent before you invest in software. Fortunately, this kind of staff is like a pluripotent cell: they can be put to work on projects at every level of the organization.



Alfred Whitehead, SVP, data science, Klick Health

While pharma has been using doctor-level prescription data, modelled sales data, and patient-assistance program data for decades to drive decision-making in incentives, forecasts, go-to-market plans, M&A activity, and targeting, agencies have often been restricted to only marketing-based datasets. Agencies that are only now considering big data and large-scale data integration have already been left behind. To get up to speed and stay in sync with pharma companies, agencies should integrate traditional pharma data sources into analyses, including rep activity and HCP- and patient-facing marketing. This includes gathering and interpreting raw data from all marketing programs — not just aggregate data — and using techniques, like machine learning to gain actionable insight. Agencies also need to pressure-test reports to ensure they encompass interactions on an individual level and not just channel or audience-level performance.


Dan Stein, SVP, analytic services and product strategy, Crossix Solutions

Agencies, with their media expertise, are still well positioned to leverage various data sources to help their pharma clients better understand the role that media and marketing play in influencing the patient journey, including outcomes and business results. While having data in itself can be helpful in providing greater context and understanding, agencies are still crucial as far as determining how to leverage and activate that data within their clients' broader communication efforts. Keeping, and even refining, the agency role vis-à-vis in-house pharma data scientists is arguably more important as analytics companies bring expanded and connected data sets into patient level analytics, including clinical, hospital, EMR/EHR, OTC, and consumer data. Through these enhanced data sets, agencies and their pharma clients can work together to obtain deeper brand and condition insights.


Tony Xenakis, principal, KMK Consulting

Hiring data analysts is one step in a process to produce actionable intelligence. In order to be successful, there should be an analytical data layer to empower data analysts who then should be involved with data gathering and report generation based on the defined needs of the sales and marketing business teams, in order to support strategic objectives. Often, analysts face inbound quality and inconsistency issues addressed too far down the analysis chain, if at all, which hampers progress and undermines insights. Necessary face time with the drivers of sales and marketing is typically less than adequate, and that results in missed opportunities to address changing needs and objectives. Agencies and consultants should work with pharma to establish an integrative process between technology, analytics, and strategy in order to turn big data into actionable intelligence.



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