Successful pharma companies use data as a competitive weapon to develop new sources of differentiation, focus on building superior customer experiences and treat drug launches as a micro-battle. How did your last launch perform vs. expectations, and what were the reasons for under-performance or over-performance?
Reltio Cloud organizes enterprise data for continuous self-learning. It helps businesses manage data like leading digital companies, leveraging continuous data organization and recommended actions to measure and improve their operations. Customers benefiting from Reltio Self-Learning Data Platform include top pharmaceutical, technology, healthcare, retail, and financial services companies across the globe.
The rise of the Chief Patient Officer and the “P–suite” emphasizes a commitment to a culture around patient-centricity across life sciences companies. Patients are becoming increasingly demanding and taking greater control of their own healthcare decisions. They expect all relevant parties like pharma, providers, and payers to collaborate and recommend the best treatment options.
The “Healthcare & Life Sciences (HCLS)” track at Modern Data Management Summit 2018 (#DataDriven18) invited industry leaders who shared their thoughts on themes such as data-driven strategies to excel commercial operations in life sciences, collaborative data management and curation across global regions, account-centric approaches, compliance initiatives, and omnichannel engagement with patients.
This year the Healthcare and Life Sciences track included twelve sessions and panels supported by 20+ speakers. Here are some of the key highlights and takeaways from the sessions.
Having worked in data management for the past 23 years, with most of that time in MDM, I thought I had seen it all. Traditional 20th century MDM has certainly seen its ups and downs throughout its short history, but what excited me about joining Reltio was the idea of starting with a clean slate and building a 21st century Modern Data Management solution from the ground up. A solution that not only revolutionizes MDM, but goes beyond the basic single version of the truth.
The value of reliable reference data cannot be undermined. Due to the nature of IT application development and the reliance upon off-the-shelf application systems, reference data is all too often isolated in silos within many different systems. Inconsistent reference data across multiple systems can cause invalid transactions, revenue leakages and compliance risks.
The healthcare and life sciences track at Modern Data Management Summit 2017 invited industry leaders who shared thoughts on contemporary industry themes such as data-driven strategies to improve commercial effectiveness in life sciences, democratization of master data management (MDM) helping pre-commercial companies with faster product launches, insights-driven customer and patient engagement in healthcare, and real-time data enrichment with data as a service.
There is no better time than now for the pharma & medical device companies to modernize their product information management and comply with IDMP (Identification of Medicinal Products). Non-compliance might result not only in hefty penalties (as high as 5% of annual EU gross revenue) but also in poor operational efficiencies. Experts advise to kick-off the IDMP initiative now and reconfigure the data model later when the final guidelines are published.
Over the last year, we have invested a tremendous amount in resources and cost to ensure that our platform compliance meets both industry and geographic-specific regulatory and compliance requirements. We anticipated the need for companies to want to use Reltio for data (e.g. Patient data) under HIPAA compliance, and were determined to go through the rigor and challenges to achieve full HITRUST CSF certification.
This was a great session, and worth the price of admission to the MIT CDO conference alone. Credit Richard Wang for bringing Daniel and Mark together as their time is obviously precious. Some key takeaways from my perspective were the need to balance speed of execution with reliable data quality. And the agility that a large company such as GSK has been able to achieve by getting alignment, and addressing security and governance issues as they surface.
For life sciences, MDM of product data should form a part of an overall data management strategy that encompasses the management of multiple master data domains and entity types. It is therefore important to leverage a solution that is not only multi-domain capable out-of-the-box, but provides a built-in architecture to relate and connect all domains seamlessly.
The most popular consumer facing applications today such as LinkedIn and Facebook have shown that business facing data-driven applications can be cloud-based, handle multiple data domains, manage structured, unstructured, master, transactional, activity and social data. Companies should expect complete end-to-end modern data management delivered as Platform as a Service (PaaS) instead of relying on recurring "next generation master data management" promises that remain unfulfilled.
Interest was high on graph databases, end-business user trust and access to the information through data-driven applications, and how modern data management platforms were now providing master data management as a core foundation, upon which big data, transactions, analytics and machine learning are fully integrated.
Our modern data management hybrid columnar and graph store, gives us the flexibility of schema-on-read, graph relationship modeling, combined with infinite horizontal scalability across entities and limitless attributes. As technology continues to evolve, and more and more database options appear on the market, we will make sure that our customers will continue to benefit from technologies such as Cassandra, and whatever comes next.
As I listened to the topics discussed, it became clear to me that we are at the crossroads of an unprecedented opportunity in the industry. Never before has storage and processing power been so affordable and accessible. For many of the attendees, better use of data, and being more “data-driven” was certain a topic that no one disagreed with. The trick was, as one executive I spoke to asked "How do we get from here to there?"
The audience agreed that the complexity of data siloed across both companies made it very difficult to analyze information within the legal and time constraints of all pending transactions. If the merger goes through, all work is generally discarded, leaving the combined company to start from ground zero. If the merger is called off, someone is left with hardware procured to support the M&A that is wasted.
Judging by the attendance the topic touched a nerve. There were many questions before and after the session around use cases of how modern data management has been deployed today across industries, and how companies are standing up solutions with immediate end-user facing business value, in a fraction of the time it takes legacy MDM implementations to even get started.