Spreadsheet Errors: The Hidden Risk In MedTech

Erez Kaminski is the founder and CEO of Ketryx.

Imagine discovering that your financial planner still used a rotary phone to make buy and sell orders on the stock market. Sounds absurd, right?

What if you learned that a recently built high-rise condo you were considering was designed with a slide rule? Would you feel safe living there?

While these examples might seem far-fetched, a similar analogy exists in the life science industry today. Many life science companies still depend on Excel spreadsheets as their primary tool for product development and quality control—even for bringing highly regulated products to market.

Although spreadsheets are familiar and widely used, relying on them for such complex processes can be risky. Spreadsheet errors in MedTech could lead to significant delays, costly product recalls, regulatory fines and, in the worst case, patient harm. This piece underscores the danger of relying on manual data management methods in an industry where precision is critical.

Let's briefly examine why spreadsheets are so prevalent, delve into the challenges they can pose for MedTech and explore how to transition successfully to a more integrated approach.

Spreadsheets are deeply embedded in legacy workflows.

Spreadsheets are a familiar tool in MedTech workflows because they're an easily accessible method of tracking milestones, performing quality checks and upholding regulatory compliance. However, managing complex products with tens of thousands of dependencies through spreadsheets can often lead to version control issues and significant errors.

Spreadsheets don't offer easy traceability.

Spreadsheets are often used retroactively to document traceability—helping visualize which items fulfill specific requirements. However, they were not designed for the complexity of modern technologies like artificial intelligence (AI), machine learning (ML) or interconnected devices. They lack the robust traceability needed to troubleshoot quality issues effectively, making it difficult to isolate root causes. As MedTech companies increasingly embrace AI, spreadsheets cannot keep up with the iterative, data-heavy demands of these products.

Spreadsheets can come with a high cost.

The Conversation cited a 1998 study published by the Journal of Organizational and End User Computing, which found that "90% of spreadsheets containing more than 150 rows have at least one major mistake," primarily due to the increased risk of human error from manual data entry.

In MedTech, where spreadsheets often span thousands of rows, this risk becomes unmanageable. Beyond compliance issues, spreadsheet mistakes can lead to costly financial losses, privacy breaches and exposed trade secrets. Spreadsheets can also slow real-time error detection, which could lead to an increased risk of recalls, compliance violations and patient harm.

How can automation help?

Automated lifecycle management solutions such as connected lifecycle management (CLM) are emerging to replace spreadsheets by offering true interoperability between platforms. Instead of manually copying and pasting data from your system of work (e.g., Jira) into a system of record (e.g., Excel), CLM automates this process, reducing the likelihood of errors. This approach eliminates the need for Excel, streamlining workflows without requiring a manufacturer to migrate all tasks to a single platform.

It's not enough to just embrace these new tools, however. MedTechs must also consider the interplay between the tools that help key team members do their jobs as well as the critical procedures that control product development. Let's briefly define a CLM platform and explore how MedTechs can effectively transition to an integrated approach.

A CLM, by definition, bridges different tools and systems.

A CLM automates tasks like data logging, traceability and document updates, reducing human error and improving consistency across teams. By connecting functions like risk management, design control and testing, it streamlines workflows and ensures details remain auditable and up to date, even during revisions.

Additionally, a CLM integrates development and quality tools, allowing teams to continue using their preferred systems while enforcing SOPs and eliminating the need for spreadsheets to reconcile data. With built-in traceability, teams can quickly identify and resolve issues, avoiding production delays or recalls.

How can organizations successfully implement an integrated, CLM-centered approach?

Not all organizations are ready to adopt a CLM strategy. This resistance is often rooted in risk-averse cultures and the belief that "we've always done it this way." As the market shifts toward more frequent releases and rigorous testing at every phase, clinging to outdated methods risks leaving the company behind.

A discovery phase is essential for assessing a MedTech's current product portfolio and documenting existing lifecycle management processes.

• This evaluation should identify which existing procedures are the most burdensome and error-prone. By pinpointing bottlenecks in how teams execute tasks, manufacturers can uncover gaps and opportunities for improvement.

• The discovery phase should also address how to integrate disparate systems while ensuring data integrity. This phase begins with evaluating the IT infrastructure and determining which data qualifies for migration.

• Engaging cross-functional teams—including R&D, quality assurance, regulatory affairs and IT—in collaborative planning sessions can create a unified vision for CLM implementation and ensure stakeholders have a voice.

• Investing in training programs based on these exercises and the development of best practices can enhance team competencies, ensuring effective usage of CLM tools once deployed as well as adherence to updated processes.

One of the advantages of a CLM is that it's designed to help organizations preserve their investment in existing quality systems and minimize disruption by acting as an overlay. Focusing on interoperability and automating data exchange across different systems and departments is key to enhancing efficiency. Regular internal audits and validation processes are also vital to verify that the technology functions as intended and complies with regulatory standards.

It's time to embrace a better way forward.

By preparing for a transition away from spreadsheets to an integrated CLM system, MedTech organizations can significantly mitigate the risk of manual errors, improve efficiency and accelerate time to market. The need for reliable, automated solutions has never been greater in MedTech, where the smallest errors can have serious consequences. Transitioning to automated lifecycle management isn't just about reducing errors—it's about enhancing patient safety, staying competitive and setting a new standard for quality in the industry.

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