It’s no surprise that big data, and business intelligence, are booming in the pharma industry. More data had been created in the past 2 years than in the entire history of the human race, and by 2020, about 1.7 megabytes of new information will be created every second, for every person on the planet.
But with all that data comes a major hurdle: Less than 0.5% of the world’s data is analyzed and used, and the miniscule percentage being analyzed is rarely being used to drive results. Like many other industries, pharma has no shortage of data. What it’s missing is the quantitative knowledge needed to make the best use of it.
As pharma brands become more savvy about data, they are realizing that tapping into its full potential requires a “human touch” — whether through data discovery, predictive analytics or the integration of data into more than just the marketing department. Here are the key trends I’ve noticed in my work with Mojo’s pharma clients and with BI teams across the industry.
Data Discovery / Visualization
In a recent survey of 2,800 BI professionals, data visualization was ranked as the most important BI trend. This emphasis on interactive visuals is also in high demand in the pharma industry. Savvy brands are no longer satisfied with slide decks alone, and are instead looking for highly visual ways to interact with their data. By providing user-friendly data visualizations such as those offered by Tableau, data scientists give pharma marketing teams the power to directly engage with their data and ask and answer questions in real time.
As a data scientist, the rise of visualization allows my team to answer a wider range of potential business questions without overwhelming the client. While the pharma brand explores the key business questions, Mojo’s team can hone in on the areas where insights will drive the biggest results. Focusing the data where it matters most takes a complex skillset and a user-experience mindset. However, it can go a long way toward helping pharma marketing teams understand and digest the wide variety of insights we deliver.
With the growing recognition of the need to determine what actually works comes requests for a broader brush in terms of what BI teams are measuring. Predictive analytics connects historical data and brand KPIs with key data-driven insights that highlight what is most likely to drive ROI for a MCM campaign. BI teams will likely experience more demand for predictive analytics in 2017 than ever before.
At Mojo, we provide ROI forecasting to help empower brand managers to make decisions that maximize their budget and returns. But not all ROI forecasts are created equal. When determining the validity of a forecast, it’s essential to first establish consistent KPIs, then use those to outline the spend, sales lift, average net revenue increase and projected ROI. The most comprehensive predictive analytics should measure these metrics per vendor, tactic and segment.
Applications Beyond the BI Team
In pharma, there’s an undeniable focus on data in marketing, and sometimes data insights can seep into sales strategy. But over the last year, I’ve also seen other departments tap into the power of measurement insights. We’ve begun to see procurement teams use data-driven vendor evaluations to negotiate better contract rates and ensure each vendor is delivering with ROI.
As data continues to drive marketing, pharma faces some unique challenges – some regulatory, and some due to the structure of multiple brands under one parent company. If pharma brands want to use data to its full revenue potential, they will need to consider evolving away from the silo system, under which different teams execute different pieces of one task with very little collaboration. And of course, the challenge of properly analyzing data and applying insights will continue to keep already-busy BI teams strapped for resources.
However, with the right combination of BI resources and human insights, pharma brands can use data to drive sales lift, net revenue and key MCM optimizations that drive results. This year and in years to come, look for the rise of techniques and strategies that emphasize the application of data to solving pharma marketing issues, especially the 360 customer journey, the ideal MCM mix and how to evaluate vendor performance to boost ROI.