Medical device manufacturing is on the verge of major transformation. Over the last 30 years, industries such as automotive, aerospace and consumer goods have modernized their product innovation strategies with advanced analytics models to scale manufacturing and keep up with evolving demands.
Now it’s time for the medical device industry — a sector with a growing need for high-volume cost-efficient production — to do the same.
Merger and acquisition activity in the sector over the last 10 years has broadened sales and distribution networks for medical device manufacturers. This market consolidation has brought a major opportunity for these organizations to build new efficiencies across manufacturing sites, systems and supplier networks more efficient. Creating this new level of efficiency will ultimately drive increased production output, improved product quality, lower costs and strengthened supplier relationships for product innovation — all critical aspects to solving many of today’s top healthcare issues.
The medical device industry was ready for a new, analytical manufacturing model in 2019, but the coronavirus pandemic has catalyzed the transformation from a nice-to-have to a core business mandate. While industries like aerospace had decades to embrace advanced technology, analytics and workflows, given today’s market dynamics, medical device manufacturers will have to make the same shift in their factories in a fraction of the time. Before COVID-19, some projected maintaining the status quo and not embracing digital transformation could mean losing 21% of profits, according to a report by KPMG. That figure is now arguably growing.
The best place to start is with inventory. When teams have a real-time, accurate and harmonized view of inventory levels, they’re better positioned to quickly balance inventory across even the most complex and multi-sourced supply chains and ramp production up and down to respond to demand changes. They can also make faster decisions in the factory that further organizational goals, speed time-to-market, create competitive advantages and give healthcare providers what they need to improve patient outcomes.
Using analytics for a competitive edge
The daily factory management problems facing medtech manufacturers — managing shortages, optimizing inventory, dealing with supplier delivery issues and more — are not new. These are all common battles, especially when teams rely on antiquated systems. Spreadsheets and home-grown business intelligence solutions have served manufacturers and factories well in the past are no longer sufficient, given the growing complexity of contract manufacturing, which is amplified by globalized supply networks and the disparate systems and processes that come with the industry’s uptick in M&A activity.
Teams often turn to spreadsheets because they don’t have readily available and centralized data. Leading medical device companies are now tapping into a combination of analytics, automated workflows and dashboards, advanced collaborative tools and artificial intelligence to boost visibility and actionability across the factory. The new analytically driven approach makes it possible to manage these daily factory management challenges and drive improvements in weeks, rather than the months it took manufacturers in the past, because teams can:
Quickly prioritize and respond to changes that can’t be predicted with traditional tools, and prescribe urgent actions to factory employees.
Get a global view of supply and demand data and optimize inventory across single sites and multi-site networks.
Fix inventory and delivery issues when plans change.
Share inventory information and collaborate faster with colleagues on inventory issues and opportunities without sending emails and files back and forth.
Standardize inventory processes with built-in workflows so teams know what to do and use best practices every time.
Every manufacturing team needs a clear view of supply chain operations so they can prioritize, troubleshoot, collaborate and innovate in real-time. Analytics helps teams deliver on all four needs. While two of the biggest challenges to embracing new technology are adoption and change management, medical device manufacturers can luckily bypass lengthy deployments by looking at similar manufacturing innovations in other industries. Their neighbors in aerospace and automotive have built and used this analytical model for years. This includes fostering a company culture that embraces change, proactively involving employees in the implementation process and getting their buy-in by showing how the technology will help them perform better in their specific roles and introduce the technology with clear user guidelines and repeatable processes.
Necessity: The mother of invention and driver of change
We’re seeing similar catalysts for change in the medical device sector as we did in the automotive industry post-World War II and in the aerospace industry with the shift from military to commercial aircraft. The COVID-19 pandemic has highlighted the need for agility and speed-to-market and intensified cost-cutting pressures in medtech manufacturing. Outside of the health crisis, an aging population, more health-conscious consumers and increasing healthcare expenditures are driving strong market growth. In fact, before COVID hit, the medical device industry was expected to reach nearly $800 billion by 2030, KPMG reported.
Competitiveness relies on continuous innovation and efficiency. Manufacturers that infuse analytics into their factory operations are in a much better position to outperform. Embarking on the transformation improves decision making and net working capital, and strengthens customer relationships and outcomes through better products, lower price points, and faster deliveries.
Richard Lebovitz is the founder and CEO of LeanDNA, an analytics platform for factory inventory management. Built by lean experts, LeanDNA empowers supply chain professionals to dramatically reduce excess inventory, deliver on time, and establish operational command. – Medical Design & Outsourcing