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3 Data Management Predictions for MedTech in 2016

While Manish Sood, CEO of Reltio—a company that develops data-driven applications—was offering his top 10 predictions for data management trends across all industries in 2016, MPO requested a look specifically at the medtech space. Following are his three predictions. 

1. Companies Will Look to the Cloud for Help

While the term “Big Data” has been overused, the reality is that not many enterprises in B2B have the means to handle the deluge of data being thrown at them. The medical device industry, which previously may not have ever considered its data “big,” is beginning to get an increasing amount of data that consists of a variety of types and sources needing to be analyzed for better outcomes. For many, a new breed of cloud-based data management capabilities could be the answer. Today, companies of all sizes can process and manage big data using the cloud at a fraction of the cost of buying and managing their own hardware and software. While there have been unfounded security concerns about the cloud, the economics, flexibility, and scalability will be too great to ignore.

2. Data-driven Applications Will Be Ubiquitous

According to a survey conducted by Reltio this summer, more than half of all life sciences organizations (55 percent) now describe themselves as “very data-driven,” which indicates progress. However, while almost 70 percent of biotech and pharma companies say they're now using data very effectively, only 30 percent of medical device companies say the same. The discrepancy could be attributed to the fact that biotech and pharma have had a head start with data-driven applications. Simply put, data-driven applications combine reliable data and relevant insight, and then create recommended actions for day-to-day business users. LinkedIn is an example of a data-driven application. It “knows” your profile, shows jobs or connections that are most likely relevant to you, and allows you to take action to apply for a position with a click of a button—all within the same app. It can then improve the types of recommendations based on whether you applied for the job, and if you were successful in getting it. 
These same types of data-driven applications are now available for the medical device industry for a wide variety of commercial and R&D operations, from managing HCP and HCO affiliations and key opinion leaders to the very devices themselves. Data-driven applications can continuously measure resulting actions and correlate them back as recommendations to improve outcomes.

3. Reliable Data Will Be the Norm

Despite the fact that there are an abundance of third-party or external public datasets to help in data-driven decision making, bringing that data together and ensuring it's reliable continues to be a high cost IT function for businesses, both in dollars and missed opportunities. A majority of the medical device, pharma, and life sciences respondents from the aforemented Reltio survey found that 74 percent worry that their data is incomplete or missing, while 50 percent say the insights are not actionable. More than a quarter—28 percent—say they still have siloed data even with the millions of dollars invested into solutions that were designed to solve the problem. While LinkedIn uses the power of self-governance and crowdsourcing through recommendations and endorsements to ensure data quality, B2B data-driven applications provide a modern data management backbone that guarantees a foundation of reliable data. They provide features such as built-in address cleansing, common abbreviation and nickname standardization, as well as real-time access to third party data sources, where users can access and acquire needed data through a simple one-click purchase. Companies of all sizes, with or without IT teams, can feel confident that they are getting accurate insights with data quality being continuously managed and maintained.