Does an Integrated Data Management Solution Achieve Operational Agility in Pharma Companies?

Traditionally, pharma has been slow to adopt technology. Critical to pharma digitization is the use of integrated data solutions and digital technologies that leverages automation and analytics. Pharma companies, life sciences and biotech majors have huge data collated from various sources. The biggest challenge is the integration of data. The data is extremely valuable, and many companies are unable to capitalize on the same due to the lack of a comprehensive platform for data restructuring and integration. Data restructuring and integration solutions is critical in pharma data management. Integrated data solutions help in creating well-timed maintenance schedules and optimal workflows in the production of drugs and deliver greater productivity and efficiency in its distribution thereby reducing operating costs. Bringing down operating costs helps companies come closer to realizing improved operational excellence (OE).

Drug marketing and sales needs efficient operations wherein multiple sites that have different types of raw data in a range of data sources stored on different servers referred to as data silos.

For drug and MedTech companies to work efficiently, data sharing and data storage needs to be efficient and seamless. Data sharing can be a problem with distributive data sources as this can lead to wrong data analysis and process oversight. Integrated data sharing platforms enable centralized data collection that optimize predictive analysis, maintenance, scheduling, and marketing of drugs.

Integrative data management involves use of smart solutions that help optimize maintenance scheduling using predictive algorithms that improve the performance of each unit operation. Through integrated data management solutions, quality is enhanced via real-time monitoring and trending of the process flows. Integrated data solutions and digital tools transform, connect, contextualized data into knowledge that can be used to take action to improve predictive performance of drugs to improve its visibility, quality, safety, yield, and throughput. The pharmaceutical industry is complex, and this complexity has translated to pharma needing integrative data management platforms that can streamline data management and make drug distribution and marketing more effective. For example, tracking drug distribution can be complicated because many different categories need to be captured (ex: Point-of-Sale Data from wholesalers, retailers, distributors). Other areas that can benefit from using integrated data analytics are the pharma supply chain with managing inventory levels, forecasting sales volumes, tracking patient need for drugs, and more.

Integrating data is the key to successful data operations that build a robust data pipeline analyzing and providing feedback to sales and marketing teams. This enables and expedites value measurement of drugs in the market. Drug 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 operationally agile integrative data platforms that lead to:

• Adherance of corporate data and security regulations regardless of data type,data provider and data usage
• Assimilating new data partners and data sources with minimal effort
• Analysis and assessing data across varied formats, sizes, and frequencies
• Generation of intelligence from data feeds effortlessly
• Use of new data feeds with little or no incremental effort

Operational Efficiency leads to interoperability, technology, and compliance seeking a "single source of truth" in a data management solution.  This data management solution or a “single source” AI/ML-driven purpose-built cloud analytics meets end-to-end data management needs in companies. As a big data platform and a one-stop solution for data lakes, data warehousing, data ingestion, data quality, data cataloguing, data lineage, data models, data profiling, data exchange, and commercial reporting.

Improved data integration result in data being pulled from multiple sources, integrated in a data lake (a raw data dump) or a data repository (an organized structured data repository where data with a pre-defined end use has been stored) and analyzed to generate new insights. Integrating data from multiple sources also ensures the highest standards of data governance, traceability, data quality, data privacy and data security used extensively to derive meaningful insights from large volumes of integrated data.

With effective data integration and enrichment, management and use capabilities, pharma majors can generate insight from historical and real-time data. They can gain intelligence about disease mechanisms, achieve manufacturing efficiencies, new formulation approaches to prevent fraud and improve patient adherence and treatment outcomes. These state-of-the-art data management solutions offer competitive advantages for the global pharma marketplace.