<img src="https://secure.leadforensics.com/133892.png" alt="" style="display:none;">

The COVID-19 pandemic exposed vulnerabilities in the medical device supply chain, from lack of end-to-end visibility to an inability to shift when a supplier can’t meet a critical need, delaying production.

But while inefficiencies were laid bare for many in 2020, unexpected disruptions come in many forms, including transportation failures, natural disasters, cybersecurity breaches and product recalls. These disruptions can hit medical device companies hard. Within a 10-year period, supply and demand disruption can cost manufacturers up to 38% of one year’s earnings, McKinsey found in a 2020 study.

The rise of just-in-time supply chains and pursuit of greater operational efficiencies have increased susceptibility to these risks. Product reliability and quality suffer as a result.

To build a resilient supply chain, medical device manufacturers should embrace four key characteristics: agility, visibility, cost optimization and productivity.

Agility

Medical device manufacturers need to be able to move quickly when conditions change. And conditions changed very quickly in 2020, often from week to week and even day to day. Using real-time production and resource planning for inventory, people and equipment is one way manufacturers can deliver products on time, even in uncertain markets.

From planning to delivery, siloed operations must become a thing of the past. This will ensure greater business continuity. Manufacturers need to protect against unexpected supplier disruptions, such as key suppliers failing or logistic shutdowns preventing shipments. This means building redundancy into their network to keep production lines running. They need a fast but effective supplier qualification process to develop alternative sources and integrate domestic manufacturing options.

Manufacturers should also invest in becoming connected factories, making their manufacturing process more agile and adaptable by integrating new technologies such as AI, Internet of Things (IoT) and mixed reality to improve Overall Equipment Effectiveness.

End-to-end visibility

Visibility – or lack thereof – has contributed greatly to medical device manufacturers’ vulnerabilities during the pandemic, especially in the early months. The inability to see the supply chain from end to end, forecast lead times, evaluate capacity and understand exposure to risk put manufacturers in a difficult if not impossible position in terms of planning production and aligning teams.

Manufacturers need real-time inventory visibility to optimize resources, fulfillment and production planning. They need to be able to adjust labor capacity and logistics in real time based on cross-channel inventory levels, raw material availability and other critical requirements to meet customer expectations. Manufacturers also need to de-prioritize historical data and instead leverage AI and other technology to project a clear view forward with visibility up and down the supply chain.

Cost optimization

Efficiency that doesn’t compromise quality is key to medical device manufacturers’ ability to navigate change. They need to embrace technology that reduces downtime of business-critical assets, improves OEE and maximizes equipment lifecycle.

They also need to right-size inventory levels based on customer demand and capacity constraints to prevent both overstocking and stockouts. And with the increased demand for customization in the medical device industry, such inventory optimization is even more critical. In many cases, variations must be produced and stocked to meet demand, which is hard to forecast without sophisticated analysis and forecasting tools.

Manufacturers can also reduce fulfillment costs with technology that helps them optimize order routing and transportation planning, and conduct real-time freight monitoring.

Employee productivity

People are critical to building a resilient supply chain. Boston Consulting Group outlines key roles – demand and supply planners, line schedulers, capacity planners and procurement managers – that demand the right data and tools to respond quickly to a supply chain shock.

Beyond those with a direct hand in planning, supplier management and procurement, manufacturers need the right people on the right projects for optimum performance. But with social distancing requirements, sick workers at home and a rise in remote work, manufacturers have a responsibility to better utilize their workforce, improve safety and reduce errors to drive productivity.

The right tools can:

  • Improve decision-making with a single source of truth
  • Break down siloes to drive collaboration and improve productivity
  • Optimize HR programs, while reducing costs

Where to start

Gartner found that 70% of the Top 25 companies in the world for supply chain excellence have set up center-of-excellence teams for supply planning, procurement and logistics, and 90% have made significant investments in planning and visibility solutions.

With an eye on how it will affect patients, as well as the business’s health, medical device manufacturers should start with an evaluation of risks, including:

  • Supplier health, reliability and diversity
  • Distribution networks
  • Production processes
  • and more

They must invest in data that helps them look forward, invest in a business continuity plan in case of crisis, and vet and identify alternative suppliers as part of contingency plans. And they must pursue technology that helps them develop the four key characteristics discussed: agility, end-to-end visibility, cost optimization and employee productivity.

McKinsey found that building a resilient supply chain can have a sustainable financial impact, including:

  • An increase in productivity by 20% to 40%
  • A reduction in raw materials, finished goods and work in progress inventory by 10% to 30%
  • A decrease in lead time by 20%
  • Improved Overall Equipment Effectiveness (OEE) by up to 30%

It’s not just about the pandemic. It’s about being ready for future shocks, small or large, which, as we’ve learned in 2020, can come when we least expect them.

Next Read: UDI redefining the medical device industry

Topics

Discuss this post

Recommended posts

Achieving a deeper understanding of the information that's already available to you can trigger major breakthroughs for your business, helping you exceed your goals and propelling you toward opportunities that you might not have even considered. The key to those breakthroughs is figuring out how to unlock the hidden insights in your data. That can seem like a daunting task, given the truly dizzying amounts of data available to businesses in the Industry 4.0 era — especially if they're getting real-time data from thousands of IoT devices. Connecting the dots isn't so hard when you've got a small and manageable set of dots to connect. But as the number of data points increases, the possible connections between them grow exponentially, and it takes a lot of computing power to precisely map all those connections and surface the important patterns and trends. That's part of why the neural networks that power AI and machine learning are so transformative. They make it possible to cut through the noise and detect patterns that would otherwise get missed. How AI Provides Superior Insights You might also think of AI as functioning a bit like a pair of 3D glasses: It helps you see things that would be unclear without it. By using Microsoft's Power BI dashboards, for example, you can draw on the power of AI to monitor your data, surface the important metrics, and then tell the story through powerful and easy-to-understand visualizations. These robust data dashboards can help you do everything from detecting security breaches to figuring out which products are most successfully driving your revenue. Boosting Sales with Better Product Pairings Some product pairings are obvious: syrup with pancakes, or paintbrushes with cans of paint. But others are more subtle and may not be apparent without the powerful combination of a strong foundational set of data and AI-powered analytics, which can help identify those less obvious complementary sales products. For instance, using AI can highlight that when you position product A alongside product B, you can experience a substantial boost of 5% in sales—a significant advantage for your business. How Machine Learning Helps Stop the Churning Spotting and addressing customer churn is another great example of what machine learning can do. It costs more to acquire new customers than to hold on to the ones you have, so the ability to use analytics to detect customers who are drifting way, or at risk of being captured by your competitors, is potentially game-changing. Using predictive analytics, you can reach out to those customers whose interest is waning with well-timed discounts and promotions, or even develop subscription-based models or loyalty programs to help keep them in the fold. Defeating Downtime with Predictive Insights We frequently see manufacturing facilities that are depending on one or two mission-critical machines that do 80% of their business — and those machines are often running 24/7. If one of those machines goes down, the result is painful downtime that can lead to production delays, revenue losses, and unhappy customers. Both your bottom line and your top line wind up taking a hit. But thanks to machine learning and IoT sensors, you can draw on real-time data to identify equipment that may be getting too hot, going out of tolerance, or at risk of developing other kinds of diagnosable hiccups and coughs. And then you can step in to make sure those sine qua non machines continue to function on schedule, protecting your balance sheet and keeping your customers happy. Data That's More Than a Fair-Weather Friend MRP is another place where predictive analytics can help put you ahead of the game. Maybe you're using a kind of "brute force" accounting to decide how to allocate costs among ten different product lines — 20% here, 5 percent there, etc. But with predictive analytics, you can get more sophisticated. You can identify trends like seasonality and other less-apparent cycles, so you can change allocations dynamically to match trends you wouldn't have otherwise known about. Machine learning allows you to factor in a lot of external data that goes beyond what's in your own ERP. Like weather data, for example. Suppose you have a product line that's very sensitive to heat or humidity. You might be able to draw on weather data to augment your existing data, so you can change the chemical properties of the product to make it more humidity resistant. Columbus recently worked with a retail organization that sells high-end outdoor products as a major component of their business. They found that some sizes and products sold better in certain stores than others, and they wanted a better understanding of the optimal product mix in each store. That's the kind of complicated data picture that machine learning can help you bring into focus. One of the other key questions they needed to answer was weather-related: when to bring out the heavier gear, like winter gloves or insulated vests and jackets. So, the ability to analyze weather trends and patterns offered an opportunity to achieve better timing and improve their margins. There are plenty of other ways that the capabilities of AI can help you make it rain — or provide an umbrella to get you through downturns and disruptions. To learn more, schedule a call with Columbus so we can help your organization tap into the full capabilities of AI.
As we begin 2024, it's no longer a question of whether to adopt AI-driven tools and strategies. These days, forward-thinking business leaders are actively considering how to adopt and implement AI successfully, in order to minimize risks and maximize the strategic rewards.
Some of the most exciting capabilities of current ERP systems — the ones with the potential to put ambitious new business goals within your reach — are the ones that leverage the impressive recent advances in artificial intelligence. Experienced leaders know that to reap the rewards of new technology, you need to be clear-eyed and fully aware of the potential rewards and opportunities, as well as the pitfalls that need to be avoided. What do you need to know to take full advantage of the fusion of ERP and AI, without running into unexpected obstacles and dangers? Ultimately, there's no substitute for careful planning, forethought, and guidance from ERP experts. How Do ERP and AI Work Together to Benefit Business? One of the most important ways that AI boosts the capabilities of ERP systems is by helping companies recognize patterns and make predictions. With AI-powered ERP software, you can forecast everything from sales and cashflow to supply chain disruptions and the need for preventive maintenance of equipment. This pattern detection plays out in all kinds of valuable ways. With visibility into open purchase orders, for instance, AI can spot when a supplier with multiple orders is late with one of them, assess the implications for the other orders, and call that to your attention so you can communicate with the supplier as needed. You may be able to resolve the situation easily with a two-minute email, where previously it might not have come to your attention until it was too late. It's especially helpful to have AI monitoring things like potential shipping disruptions. Whether it's a ship blocking the Suez Canal or ports closing due to the outbreak of war, it can make a huge difference to have a system that keeps track of shipping details and alerts you to possible delays an extra day—or even an extra week—in advance. How AI Boosts Workplace Productivity Another of AI’s real superpowers is its ability to help team members spend less time on tedious drudge work and more time on higher-level tasks. AI is tremendously effective at bypassing writer's block, for example. It can expedite critical tasks like summarizing business meetings, generating sales or purchase agreements, and writing business correspondence along with other business documents. Consider the new Microsoft Copilot, which is integrated with Dynamics 365. It combines the power of language models with your business data—including all your Microsoft 365 apps, documents, and conversations. It can help you: • Write documents in Word by generating text and suggesting edits • Analyze and visualize data quickly in Excel • Bring ideas to life impactfully in PowerPoint • Create efficient communications in Outlook … and much more. How AI Helps Elevate Customer Service AI can take customer service to a higher level by helping customers get the information and help they need in a timelier manner. It can also ensure that customers get their deliveries faster by solving or preventing supply chain and logistics issues. Automatic certain customer service tasks with AI means less waiting and happier customers. What Key Trends Are Driving the Adoption of AI in ERP systems? One of the most potent factors fueling interest in AI right now is the success of tools like OpenAI's ChatGPT, DALL-E, Midjourney, and Adobe Firefly. These tools have democratized AI by making it widely accessible in an easy-to-use format. In just the last couple years, the average person’s eyes have really been opened to AI’s possibilities. But contrary to what most people think, AI didn't just burst on the scene overnight— it’s been under the hood of many business software programs for years, slowly developing its capabilities and enabling more sophisticated tools. Microsoft in particular has been at the forefront of this. Remember Clippy in MS Office? That was an early example of an AI-powered assistant. Cortana was another step along the path. ERPs have been drawing on the power of AI for years now to analyze patterns and trends and make better forecasts and predictions. Microsoft's Dynamics 365 has been a leader in this effort as well. These days, Microsoft's Power Apps are a great example of how Microsoft helps companies harness the power of AI to boost and extend their abilities. With Power Automate, for example, you can easily make use of robotic process automation (RPA) and digital process automation (DPA) to automate recurring tasks and create automated workflows using low-code drag and drop tools. With Power Automate, you can even explain a problem in English and have it create a solution for you. So instead of needing to know how to write a SQL query, you can just say something like, “Hey, I want a list of all customers that spent at least $100,000 worth of product from us in the past, including something from this particular product line, but haven't bought from us in the last six months" — and Power Automate will know how to build that query and then either display it in a Power BI view, use it to feed a mass mailing, or do other useful things with it. Which makes it possible to get what you need out of systems without having to understand all the bits and bytes involved. Likewise, the power of predictive analytics, and the machine learning and forecasting tools that are built into ERPs like D365, mean you don't need to be a data scientist to analyze and visualize data in new and powerful ways — helping you see the road ahead so that you can run your business in a proactive (rather than reactive) way. Setting Guardrails: Navigating Potential Risks With power comes responsibility, of course, and a need to be clear-eyed about the possible downsides and pitfalls of leveraging AI within an ERP system. Navigating these issues successfully comes down to making sure you have the right guardrails in place and that they aren't circumvented. One of the most critical issues is to make sure that your data is tagged correctly by setting up good IT governance. What data should only be used within the walls of the company? What should be limited to people with specific levels of access? For example, consider a publicly traded company. If their financial results are inadvertently released before their 10-K is published, the SEC could punish them for it. AI could accidentally leak that kind of data if the right guardrails aren't in place to prevent it. Making sure data is correctly tagged can be a complicated process, and a lot of companies, especially smaller ones, may not have the necessary skills in house. That's an area where a partner like Columbus can step in and help. Copyright and intellectual property is another area where strong guardrails need to be set up. The Writer's Guild strike recently drew attention to this issue. For businesses, the question is: How do you make sure that your data and intellectual property aren't appropriated and leveraged without your permission? This is another reason why data needs to be carefully tagged and protected before it's released. There's a major change management component to this issue as well. It's vital to make sure that employees are aware of the risks and understand the proper procedures to safeguard data, as well as which tools are appropriate to use and which aren't. Policies also need to be created to make sure that employees don't circumvent the guardrails, intentionally or unintentionally. Making sure team members are trained in a consistent and ongoing way is crucial. How Can Enterprise Businesses Prepare for a Future Shaped by AI and ERP? With all of the above in mind, you can’t let the risks of new technology dissuade you from moving forward. Your competitors will be taking advantage of these tools, and you can't afford to be left behind. The key is to implement these tools in a disciplined and measured way, staying cognizant of the rewards and possibilities, as well as the potential pitfalls. This is another area where having an experienced partner like Columbus by your side can help you steer the ship successfully. Want to learn more about how Columbus can help your organization harness the full capabilities of AI? Get in touch with us today.
Right now, companies in the food and beverage industry have a lot on their plate. A key question how to meet all demands and at the same time reach all your business goals? Unifying your technology platform, business strategy and operations is necessary to stay ahead of your competitors. Companies have to keep up with increasing consumer demand for products that are healthy, ethical and environmentally friendly while at the same time meeting regulatory standards and minimizing food waste. And, of course, they still have to do the usual work of keeping margins high, preparing for emergencies, ensuring product quality, staying innovative and minimizing risk at every stage of production.
Like other industries, food & and beverage companies must initiate strategy planning and change management at the very start of bringing their business systems to the cloud. That’s the best way to avoid additional costs, effort, and business interruption. And the trick is to define value with a people mindset.
right-arrow share search phone phone-filled menu filter envelope envelope-filled close checkmark caret-down arrow-up arrow-right arrow-left arrow-down