The drive towards better patient outcomes, evidence-based medicine and reduced costs has brought data to the forefront of healthcare transformation. The ever-growing efficacy of data can be gauged from the fact that the global healthcare analytics market is predicted to reach USD 50.5 Billion by 20241, growing at a Compound Annual Growth Rate (CAGR) of 28.3 percent.
Considering the wealth of data now available to pharma companies, it is paramount to leverage this data and gain strategic advantage in today’s hyper-competitive and rapidly evolving marketplace. But unlike in the past, where companies acquired data and maintained it in isolation, the future will be all about developing strategic partnerships in data management. The solutions of tomorrow will be built around the convergence of rich information flowing in from different quarters.
Why Does It Matter?
The healthcare industry is witnessing humongous amounts of data coming to its shores not just from internal operations but from partners and stakeholders in the larger ecosystem. In fact, data availability brings into focus many such aspects that not too long ago were considered inconsequential. Wearables such as smart watches that were not considered significant have now become strategic tools owing to their ubiquitous use and the amount of rich data they capture.
Pharma companies are increasingly trying to extend the ambit of their marketing campaigns by engaging with key stakeholders, including care providers, pharmacies and research organizations who have significant influence on the prescription behavior of physicians and prescription adherence of patients. Physicians too are adopting multiple channels of engagement. They are, in fact, turning away from traditional channels and moving towards social media, online forums and industry conferences. Hence, it is crucial for pharma companies to not just use these channels to engage physicians and other stakeholders, but leverage data and insights from them for a more potent marketing and sales engine.
Traditionally, pharma companies have invested in data warehouse appliances. However, they typically lack one unified data warehouse in the company. Each functional team such as marketing, sales and operations (across geographies) provisions and maintains its own data platforms, separated by firewalls and standards. This makes it impossible to collaborate and build a 360-degree view of the entire business. At best, only the top management has access to one standardized view of the business. Often, that too is neither completely accurate nor available on time, making strategic decisions difficult.
Leveraging Data Effectively
Being able to acquire data is just one step in the overall journey. The key to successful data operations is building a robust data pipeline that analyzes and provides feedback to enable and expedite value measurement. Companies can no longer afford to build data warehouses and expensive platforms with certain hypotheses about value of the data. Pharma leaders must invest in developing agile data platforms that, among other things, enable:
Integration with new data partners and data sources with minimal effort
Ingestion of new data feeds with little to no incremental effort
Analysis and processing of data across varied formats, sizes and frequencies
Generation of insights from data feeds in an effortless manner
Compliance with corporate data and security regulations regardless of data provider, data type and data usage
The Design Principles
Considering all the sweeping changes happening in the industry, business and technology teams in pharma companies are now in a hurry to build systems and processes that can deliver quick results. There is, of course, no cookie-cutter approach for pharma companies to build data management systems and processes. However, certain design principles such as the ones mentioned below can enable the data system to yield results faster and more efficiently.
- Seamless integration across technologies and data sources
- Integrated analytics and reporting for faster and easier data exploration
- Built-in data governance, quality, security and discovery layers
- Scalability and Agility
- Data provisioning agnostic of source, size, structure and speed
- Platform deployment, maintenance and scalability as per business needs
- Simplification and Standardization
- Standardized data assets, processes and policies, and tool kit
- Simplified and well-defined Key Performance Indicators (KPIs)
Getting the Strategy Right
A precursor to building a data management system that enables business outcomes is to envision data management and governance at an enterprise level. The leadership must first build a centralized data strategy. Cloud-based data platforms today enable the building of large global systems in a hub-and-spoke model that ensures a core central data governance layer, while also enabling remote modules that drive local data compliance. The other pre-requisite is to identify the future needs and map the maturity of the current system (to adapt to changing needs).
In the foreseeable future, global healthcare spending is expected to rise at a CAGR of 5 percent.2 The need for a more efficient, outcome-based, preventive and affordable healthcare system has never been more pressing. Data management will be a strong ally in enabling this, if healthcare companies can get it right.