Understanding the overall cost of quality in the MedTech manufacturing segment and the role of a modern MES platform in reducing these costs.

Statista projects Medical Technology market to reach US$ 575.80 billion by 2022, out of which the Medical Devices market volume is projected to be US$ 455.10 billion. The industry is expected to grow at 5.95% CAGR and reach a resultant market volume of US$ 768.80 billion by 2027. With US$ 200.20 billion in revenue, the US is the top market for medical devices, and devices sold in the market must comply with FDA regulations irrespective of their country of origin/manufacturing.

Medical device manufacturers have to comply with FDA 21 CFR Part 820 for quality systems and the regulation outlines everything including QMS requirements, design control, record-keeping, and statistical techniques. Strict regulations contribute to high costs of compliance, but for the MedTech segment, compliance costs are just the tip of the iceberg. Quality and the costs associated with it reach beyond the cost of compliance, and meeting compliance requirements is not to be confused with having a great quality organization.

McKinsey published a business case report which explains the overall cost of quality in the segment and possible improvements. This article addresses the cost of quality in the industry and the role played by the MES platform in helping reduce these costs.

The overall cost of quality in Medtech 

The McKinsey report divides quality costs in medical device manufacturing broadly into three areas, the direct cost of ensuring good quality, the direct cost of poor quality, and the indirect quality costs. Brought together they form 6.8-9.4% of the overall sales volume. At current industry sales of US$ 455.10 billion, this figure calculates to US$ 30.94-42.77 billion.

Direct cost of ensuring good quality –These costs include the basic in-process quality infrastructure, from quality system to validation and quality control to auditing. Since quality is everyone’s business, these costs tend to spread outside the quality organization and into operations personnel’s expenditure too. The cost prevention and appraisal is averaged at 2.0-2.5%, however, based on the technology in question it lies somewhere between 1.5-2.0% for disposables and implants and up to 3.5% for electromechanical devices and capital equipment.

Direct cost of poor quality – Remediation costs, routine internal and external quality failures, and non-routine external failures constitute this cost overhead. Remediation costs apply to investigations, CAPAs, MDRs, and field actions and represent 0.4-0.7% of annual sales. Routine internal quality failures include deviation management, scrap and rework, accounting for 2.1% of annual sales. Routine external quality failures predominantly represent warranty-related costs and make up for 0.4 to 1.6% of annual sales. 

Non-routine quality failures represent 1.9-2.5% of annual sales and are the result of significant quality events which makes them most worrisome for manufacturers. Product recalls, warning letters, consent decrees, import bans and consumer litigation all fall under this category and hurt the company more than just financially, including brand value and perception in the market. The McKinsey report reveals that these failures may extend to about 3.8% of annual sales, equating to financial losses of US$ 17.29 billion in 2022.

Not only are these failures costly and hurt the manufacturer’s brand image, they also represent a failure of the quality apparatus in place, since these issues are detected and reported in the market or through an external inspection of the product.

Indirect quality costs – These costs are connected to non-routine quality failures and can cost up to US$ 1-3 billion in revenue and market-cap for a medium to large medical device company. When quality events in the field extend beyond product recalls and cause a consent decree leading to plant shutdowns, these costs can go even higher and thereby pose an existential threat to the MedTech company facing it.

Understanding quality maturity

McKinsey claims that MedTech companies can recover anywhere between 1.5-3.0% of sales if they apply segment-leading quality practices, at current industry sales this equates to US$ 6.80-13.40 billion. The report further highlights 5 sources of maturity that correlate with good quality. We will examine these quality sources from the lens of a modern MES platform aiding the establishment of a better quality organization and helping manufacturers improve their quality maturity.

Operational maturity: product and process design – Identifying andconnecting CQAs (Critical Quality Attributes) also referred to as CTQs (Critical To Quality) or to CCPs (Critical Control Points) in production, with relevant in-process testing steps is seen as a major deliverable for a mature manufacturing process. Further GMP dictates that streamlining the design to reduce product complexity, limiting total components per product, and optimizing CTQ parameters tracked per product directly impact quality outcomes.

An MES platform allows MedTech manufacturers to define CTQs and link them to in-process testing protocols, so any deviation in manufacturing is reported in real-time and any OOS event raises alarms triggering CAPA protocols automatically. The MES covers the entire operation end-to-end and allows the R&D team to build quality and manufacturability right from the prototyping stage. A singular platform also allows the early definition of CTQ attributes and further the linkage of these attributes with execution functionality with compliant data capture and work instructions. 

Operational maturity: people – Deviation issues and recurrence can be addressed through better employee retention and shared quality targets. The MES plays a major role in managing the change required to form a better quality organization by making quality all-pervasive. The platform achieves this by ensuring all human interactions that directly or indirectly affect product quality within the process, are well-defined, qualified, and verified. Operators receive instructions and training through the MES for regular tasks and containment/corrective/preventive actions.

Clear definition of process steps, testing frequency, and linkage with CTQs allows all personnel from quality and operations to function optimally using the MES. It also allows managers to view line performance data and take actions in real-time preventing escalation of internal quality issues.

Operational maturity: production assets – McKinsey points out that the proper maintenance and renewal of production assets is essential for sustainable production and quality management. Preventive maintenance costs between 1.5-2.0% of the COGS are considered ideal.

With an MES MedTech manufacturers can move from preventive maintenance towards predictive maintenance to reduce machine breakdowns and unplanned downtimes. Through IoT the application collects equipment data from automation and equipment sensors, then uses AI and advanced analytics to detect patterns that may indicate an imminent machine breakdown. When breakdowns can be predicted, maintenance can happen without disrupting operation and possible quality issues due to the breakdown or reduced asset performance are alleviated. 

Quality system maturity – Reduced quality costs are realized when an organization has a mature quality system, which is able to perform swift and thorough investigations for internal and external quality events. From a supply chain perspective, the report points out that 56% of the highest performing medical device manufacturers shared their own CQAs or CTQs with their suppliers.

Setting up the right metrics is seen as a vital aspect of a quality system. Metrics like CAPA effectiveness and deviation recurrence rates are considered more important than investigation closure times, which leads to short reviews and improper CAPAs. Given the significance of quality events in terms of patient outcomes and financial impacts, companies often use the MES as the main application for the QMS. For MedTech QMS is better with the MES as the application holds all data which affects quality outcomes and is used for CAPA creation, inspection, testing, qualification, validation, and compliance purposes.

The MES can ensure AQL is implemented in the process and help manufacturers move towards a more risk-based, quality assurance oriented system. MES drives quality process, along with capturing of in-process testing execution and evidence of measurements taken, all on the same platform directly improves the quality of the process and products.

Quality culture maturity – Making quality everyone’s job is seen by McKinsey as a critical aspect of a mature quality culture. Cross-functional collaboration in dealing with validations, maintenance and root-cause analysis is considered essential for improving cultural maturity. The MES directly aids this, as the primary operations platform, by bringing together management, operators, and maintenance engineers, all on the same forum, solving problems and improving quality.

The future of quality is now

The 2017 McKinsey report points towards automated data collection, adoption of global standards like ISO:13485 and better CAPA management, improved yield and line management, coupled with predictive modelling, as a direct result of improvements in quality maturity.

With an MES ‘Predictive Quality’ can become a reality for your manufacturing plants across the world. The predictive quality model works on an assurance and risk-based quality management approach, where CTQ parameters are monitored constantly and automatically by the MES. Any deviation or possible deviation is reported, and actions are taken to prevent a quality event from happening.With predictive quality and an IoT data platform, Medtech operations are encompassed by a virtual process envelope, which essentially makes the operation predictable so that deviations can be detected and their risks ascertained! Tools like the Gartner Magic Quadrant ease the choice of an industry specific application, and manufacturers must use this and other tools to reduce their COPQ (Costs of Poor Quality) and recover internal quality costs through a more mature quality organization.