The Untold Story:
Big Pharma’s Unstructured Data Crisis (and How to Solve It)
Highlights:
- As the pharmaceutical industry continues to grow and evolve, so does the amount of unstructured data that companies must navigate.
- Pharmaceutical companies accumulate vast amounts of data each year, spanning all stages of research and development. With clinical trials alone producing around 3.6 million data points, three times more than a decade ago, the total amount of data can reach hundreds of terabytes.
- According to a report by IDC, 80% of data generated in the healthcare industry is unstructured and comes from diverse sources, making it difficult to analyze and utilize. It can cause colossal damage hindering the adoption of AI, crucial for advancements in drug discovery and clinical trials.
- The key to tackling it lies in being intentional about managing it from the outset rather than waiting until things get out of hand before taking action.
- Choosing the right approach to managing your data—whether building an in-house team or outsourcing to a third-party vendor—can make all the difference in streamlining your operations and maximizing profitability.
Introduction to Unstructured Data Growth in Pharma
As the pharmaceutical industry expands, so does the volume of unstructured data it generates. Unstructured data includes information that isn't easily categorized or organized, such as text, images, and videos. This data comes from various sources like research reports, clinical trial results, marketing materials, and customer feedback. Managing this deluge of information can be overwhelming and costly, but cutting corners isn't an option for maintaining compliance and delivering high-quality products. Here are some top strategies for managing unstructured data growth in the pharmaceutical industry effectively and efficiently.
The Problem With Unstructured Data Growth
Pharmaceutical companies generate massive amounts of data annually, spanning all stages of research and development. Clinical trials alone produce around 3.6 million data points—three times more than a decade ago—resulting in hundreds of terabytes of data. According to IDC, 80% of data in the healthcare industry is unstructured and challenging to analyze. Despite its potential, only 12% of unstructured data is currently analyzed, leaving valuable insights untapped. Harvard Business Review found that clinical stakeholders cannot access 73% of unstructured patient data, hindering innovation and collaboration.
The exponential growth of data presents challenges in reducing storage costs and facilitating easy access to historical data for researchers and collaborators. Unstructured data can also pose security risks if access controls are not implemented properly. Pharmaceutical companies have reported the largest cybersecurity breaches compared to other industries. Therefore, structuring unstructured data is crucial for understanding and managing it effectively.
Additionally, unstructured data hinders digital transformation and the adoption of Big Data and AI initiatives, which are critical for advancements in drug discovery and clinical trials. About 73.4% of companies report difficulties in adopting Big Data Analytics and AI initiatives due to unstructured data. Technologies like AI and Blockchain are transforming clinical trials and drug discovery in the pharmaceutical industry.
Three Strategies for Tackling Unstructured Data Growth
There are several strategies to effectively manage unstructured data growth.
Optimizing Storage Practices:
- Gain Insights and Tier Storage: Utilize metadata analysis to understand what data you have and how it’s used. Identify inactive data for archiving or deletion and implement tiered storage to place frequently accessed critical data on high-performance drives, with less critical data on lower-cost options like cloud storage.
- Reduce Footprint and Leverage Scalability: Employ data compression and deduplication to reduce file sizes and eliminate redundant copies. Utilize scalable object storage for handling massive amounts of unstructured data cost-effectively. Cloud storage offers scalable and cost-saving options for remote data storage with improved accessibility.
- Implement Lifecycle Management: Establish a data lifecycle management (DLM) strategy to dictate how data is created, stored, archived, and deleted based on its value and regulatory needs, controlling data sprawl and optimizing storage utilization.
Implementing Data Management Policies:
- Define the scope of data policies, including both structured and unstructured data.
- Identify stakeholders responsible for policy implementation and enforcement.
- Develop policies that align with organizational goals and comply with legal and regulatory requirements.
- Communicate policies to all stakeholders and provide training.
- Monitor compliance and review policies regularly to ensure they remain relevant and effective.
- Establish metrics to measure policy effectiveness in achieving goals like data quality, compliance, and cost savings.
Automating Data Management Processes:
- Automate data management tasks such as data entry, cleansing, transformation, and integration using specialized software tools.
- Use AI and machine learning to automate tasks like data classification, matching, and enrichment, extracting more value from data.
- Ensure human oversight to monitor and maintain automated systems.
Build, Buy, or Outsource Data Management
When deciding how to manage unstructured data, businesses can choose to build, buy, or outsource their data management systems. Each option has its pros and cons:
- Building In-House: Provides complete control over the system design and implementation but requires significant investment in time, money, and resources.
- Buying Off-the-Shelf Solutions: Saves time and resources as these solutions are pre-built and extensively tested but may involve yearly licensing fees.
- Outsourcing: Offers flexibility and immediate results by hiring external experts to manage unstructured data growth. It often ensures better ROI and quicker implementation.
The Data Dynamics Advantage
Data Dynamics offers enterprise data management solutions to help organizations structure their unstructured data. Its Unified Unstructured Data Management software includes modules for Data Analytics, Mobility, Security, and Compliance. Proven in over 28 Fortune 100 organizations, the software uses automation, AI, ML, and blockchain technologies to manage global enterprise workloads effectively. Data Dynamics helps companies streamline operations, ensure compliance, secure data, and drive cloud data management, enabling data democratization so users can access and derive insights from unstructured data regardless of their technical background.
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