Driving Change in Data Management

This video provides an expert perspective on the critical need for operational simplification and innovation within the pharmaceutical and life sciences data management sector. Tanya du Plessis of Bioforum outlines the historical tendency of the industry to overcomplicate processes and emphasizes a strategic shift toward focusing on data quality and efficiency. The core vision articulated is to simplify existing workflows and concentrate efforts on generating high-quality data that yields meaningful insights, aligning with modern regulatory expectations.

The speaker highlights that contemporary regulations, such as those driving Quality by Design (QbD) principles, are forcing the industry to place greater emphasis on the quality and relevance of data collected. This regulatory pressure serves as a catalyst for change, pushing organizations to streamline operations. The two pervasive complaints heard across the industry—that processes "take too long and cost too much"—are identified as the primary targets for innovation. Bioforum’s focus, as detailed by du Plessis, is specifically on reducing costs and shortening timelines to meet more reasonable expectations for customers in areas like clinical operations and data management.

A specific example of inefficiency targeted for improvement is the database build process. The speaker challenges the industry norm, questioning why a database build should require 12 weeks, and asserts that significant returns on investment (ROI) can be achieved by implementing smarter, more efficient methodologies to drastically reduce these timelines and associated costs. Beyond technical innovation, the presentation delves into the crucial aspect of organizational change management. Driving industry-wide change requires convincing stakeholders to abandon entrenched, outdated ways of thinking and realigning with new processes. The key to securing this buy-in is demonstrating the tangible return on investment (ROI) for the stakeholders themselves, whether through cost savings, accelerated timelines, or improved data quality.

Finally, the speaker stresses the importance of continuous professional development and maintaining an open perspective. Professionals often become overly attached to specific roles or processes, becoming Subject Matter Experts (SMEs) in siloed systems, which inadvertently closes their vision to new opportunities. Accepting and exploring new ways of doing things is essential for fostering innovation. The message concludes with a strong call to action for continuous learning, urging data managers and operations staff to actively seek out and understand new methodologies and technologies available in the evolving life sciences landscape.

Key Takeaways: • Prioritize Simplification and Quality: The industry has historically over-complicated data management processes; the immediate focus must shift to simplifying workflows and emphasizing data quality, driven by the realization that only data that truly matters should be prioritized. • Regulatory Drivers for Change: New regulations, particularly those promoting Quality by Design (QbD), are critical external forces compelling organizations to focus on data quality and efficiency, providing a strong mandate for operational overhaul. • Address Core Industry Complaints: The two most common concerns—excessive time consumption and high cost—must be the central targets for all innovation efforts in data management and clinical operations. • Optimize Database Build Timelines: Significant ROI can be achieved by challenging and optimizing standard operational timelines; specifically, processes like database builds, which often take 12 weeks, should be re-engineered using smarter methods to achieve substantial reductions in time and cost. • Focus on Stakeholder ROI for Buy-in: When driving organizational or industry change, success hinges on convincing stakeholders to abandon old processes by clearly articulating the tangible benefits and return on investment (ROI) that the new approach will deliver to them directly. • Avoid Process Attachment: Professionals must guard against becoming so attached to specific roles or existing processes that they become siloed Subject Matter Experts (SMEs), which can blind them to new, more efficient opportunities and methodologies. • Embrace Continuous Learning: To remain innovative and drive change, professionals must commit to continuous learning, actively exploring new technologies, methodologies, and industry trends to keep their horizons open. • Strategic Vendor Evaluation: When considering new approaches, such as utilizing a new vendor or adopting a different study design, the focus must remain on the real benefits and advantages that will be obtained, ensuring alignment with overall efficiency goals.

Key Concepts:

• Quality by Design (QbD): A systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management. In data management, this means proactively ensuring data quality from the start rather than relying solely on post-collection checks.
• Return on Investment (ROI): The critical metric used to justify change. Innovation in data management must clearly demonstrate how it reduces costs or accelerates timelines to secure necessary organizational buy-in.