Avoiding the Ripple Effect of Bad Data: Systems and Data

This is Part 2 of a series on maximizing efficiency and improving data analysis. Read Part 1: Why Going Paperless is Essential and Part 3: Using Process Automation to Reduce Human Error.

Although medical device manufacturers have increased their investment in enterprise data automation, particularly enterprise resource planning (ERP) and manufacturing execution systems (MES), digital and automation processes have lagged, leaving sluggish systems in place and lost data on the rise. Those responsible for device history records (DHRs) have been saddled with piles of paper, inefficient processes, spreadsheets, and other standalone systems to monitor, collect, and aggregate data surrounding production and quality processes.

When executives from all life sciences industries were asked about their top quality management challenges, LNS Research found that 18.4% emphasized disparate information systems and data sources and 20% of executives in manufacturing operations management cite disparate systems and data sources among key challenges in addressing top manufacturing objectives for life sciences companies. Yet, a number of manufacturers continue to rely on partially digitized processes. Any paper-based DHRs still in use are not automatically integrated with electronic systems and quality processes, which, in turn, impedes the ability for information to be entirely transferred. This lack of complete connectivity between solutions represents the biggest functional gap and data-related weakness in the manufacturing software on the market today. Despite there being a number of electronic systems available, if siloed, many of these systems insufficiently track data and documents from different areas throughout the production life cycle, resulting in information gaps, blind spots, inefficient data tracking, and other preventable errors.

Poor, little, or manual communication between disconnected information systems like ERP, MES, learning management systems (LMS) and quality management systems (QMS) severely limits the throughput between manufacturing, quality, and other critical business areas. This impedes physical operations and generally undermines stakeholder collaboration. All disconnects, bad data, and the lack of visibility and collaboration across the enterprise, result in a host of business inefficiencies. According to IBM, poor data quality in the U.S. alone costs $3.1 trillion a year. Additionally, disconnected information systems can cause issues within inventory management, time-logging systems, and personnel training, increasing overall costs that affect an organization’s bottom line.

Implementing Complete Digital Systems
Employing robust software with connectivity capabilities can improve the flow of data between systems, provide a centralized access point for greater visibility across teams and sites and culminate in an overall cost savings. Implementing complete digital systems allows organizations to create productive connections between enterprise systems, data sources, processes, and people throughout all sites and provides a holistic view of data. Any software solutions selected for electronic DHRs (eDHRs) should have the ability to capture and share real-time production data across all systems and departments seamlessly, connect users across the shop floor, eliminate data integrity issues before problems spread through the production cycle and allow for operators to input data directly into an eDHR and pull product materials from the organization’s ERP.

According to Aberdeen, approximately 47% of manufacturing organizations believe they must become more data-driven to remain competitive. By integrating the disparate enterprise applications in manufacturing IT ecosystems with a fully digital eDHR, organizations can close the digital gap and glean truly actionable, data-driven performance insights to deliver significant quality and productivity improvements.

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Terrance Holbrook is the director of product at MasterControl, where he is responsible for market research, product design and development of functionality for MasterControl’s full suite of solutions. He has 25 years of experience in manufacturing and seven years of experience in international medical device development. Holbrook has led the AI/ML development for Fortune 50 companies, launched over 400 products and hosted FDA inspections and mitigations, ISO certifications, and international registrations. Holbrook holds patents on risk-based upgrade and validations and has four patents pending. He has a bachelor’s degree in business administration from Purdue University and an MBA from Westminster College.