How can companies improve business results by increasing the digital maturity in their chemical labs? The Digital Chemical Lab, Top Performers Digitalizing Their Chemical Laboratories, shares insights from a survey of over 170 chemical companies examining their lab processes, data, solutions, and digital maturity. The survey benchmarks the level of digitalization against business performance, finding…
- Executive Overview
- Chemical Companies Face Multiple Business Challenges
- Operational Challenges in the Lab Make Improvement Hard
- Why Digitalize? The Status Quo Won’t Scale
- What’s Driving Chemical Companies Digital?
- Digitalization in the Lab – When, not If
- Digitalization Falters beyond the Lab
- Identifying the Top Performers
- Top Performers Have Better Capabilities for R&D and the Lab
- Top Performers are More Digitalized
- Identifying Best Practices for the Digital Chemical Lab
- Prerequisites for the Digital Chemical Lab
- Digital Chemical Lab Basics
- Digital Best Practices for the Chemical Lab
- Enabling Technology for the Digital Chemical Lab
- Enabling the Digital Chemical Lab with a Solution Platform
- Conclusion
- Recommendations
- About the Author
- About the Research
- Executive Overview
- Most chemical companies have started to adopt digitalization
- Digital transformation is further along in the lab than beyond the lab
- Chemical companies report varied levels of digital maturity

- Are more digital in the chemical laboratory
- Have invested in more digital lab best practices
- Use more specialty scientific software
- Value a platform approach to integrate and support the digital enterprise
Conclusion
Chemical companies are challenged to improve their innovation and product development performance while controlling cost. They face significant operational issues that make these business improvements hard to achieve. Digitalization holds significant promise to address these issues and improve performance because it’s proven to accelerate the pace of innovation, increase agility, and improve efficiency. The transition to the digital chemical lab has begun. Today, however, most chemical companies have only partially digitalized. Top Performers, though, have greater digital maturity than their lesser-performing competitors. They’ve adopted more digital R&D and lab capabilities, particularly when you look beyond the basics to best practices. Top Performers have implemented more specialized R&D and lab management systems to support their best practice processes. Based on the survey results, we believe that these capabilities help the Top Performers achieve better operational R&D and laboratory performance and drive better business performance. Our overall conclusion is that digital best practice processes and chemical laboratory management solutions provide a competitive advantage that helps chemical companies drive higher levels of innovation and profitable growth. Finally, we believe that digitalization will lead to significant market disruption across the chemical industries and result in a significant change in market leadership. Digital transformation supported by best practices and a platform of integrated R&D and laboratory solutions will be a key differentiator to enable the future Top Performers that will lead the industry. The time to digitally transform the chemical laboratory is now.Recommendations
Based on industry experience and research for this report, Tech-Clarity offers the following recommendations. Chemical companies should:- Ensure the digital chemical lab prerequisites and basics are in place
- Pursue digital laboratory best practices including reuse, simulation, and knowledge management to differentiate and drive higher levels of innovation
- Leverage specialized laboratory and R&D software to drive better business performance
- Pursue a chemical laboratory systems platform strategy to further improve performance and gain a market advantage
Copyright Notice
Unauthorized use and/or duplication of this material without express and written permission from Tech-Clarity, Inc. is strictly prohibited. This report is licensed for distribution by Dassault Systèmes BIOVIA. *This summary is an abbreviated version of the report and does not contain the full content. A link to download the full report is available above. If you have difficulty obtaining a copy of the report, please contact us using the "Contact" link below. [post_title] => The Digital Chemical Lab (survey results, white paper) [post_excerpt] => [post_status] => publish [comment_status] => open [ping_status] => open [post_password] => [post_name] => digital-chem [to_ping] => [pinged] => [post_modified] => 2022-11-14 22:28:36 [post_modified_gmt] => 2022-11-15 03:28:36 [post_content_filtered] => [post_parent] => 0 [guid] => https://tech-clarity.com/?p=7004 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw ) [1] => WP_Post Object ( [ID] => 6989 [post_author] => 2 [post_date] => 2018-06-18 14:39:59 [post_date_gmt] => 2018-06-18 18:39:59 [post_content] =>
The Manufacturer's Guide to Bridging the Engineering-Purchasing Gap
How can manufacturers deliver every customer order on time without incurring excess cost and delays from part shortages? They have to streamline operations and information flow across departments including Engineering and Purchasing. Today’s disconnected processes and systems aren’t acceptable when people expect business systems to work as well as the Amazon app on their smartphone. It’s time for manufacturers, big and small, to start embracing digital approaches to improve operational performance.
A Practical Shift to Digital
Manufacturers are going digital to meet today’s market demand for innovation and agility. The status quo isn‘t good enough any more, and those that hold on to old ways of running a manufacturing company using emails and spreadsheets will find it hard to compete. But “going digital” doesn’t have to mean huge consulting fees and expensive software. It can be very practical. For example, companies can choose a problem area that causes them trouble, such as collaborating between Engineering and Purchasing to build prototypes or small production runs, and take a digital approach to improving it.The Design to Procurement Gap
Let’s look at closing the communications and information gap between design and procurement. Engineering and Purchasing need to be on the same page to meet customer ship dates or risk losing revenue and customer satisfaction. A simple thing like sharing part requirements gets challenging with different configurations, changing designs, and dynamic supply chains. Experience shows that this complexity leads to errors in the world of office documents, shared drives, emails, and other ad hoc tools that lead to using outdated and incorrect information. Manufacturers need to close the information gap by providing centralized, shared information in a digital format. Information buried in a spreadsheet or a CAD file isn’t much more effective than hand-written notes on a whiteboard. Some people have visibility to the information, and hope that it’s accurate, but others are left guessing. The core of this communication is parts, organized in BOMs, to let people know what, when, and how much they need to buy and make. Beyond this, companies need to gather purchasing information that’s typically spread out in multiple catalogs or websites to make a buying decision. The process is challenging in any organization, whether the responsibility is on one person, one department, multiple departments, or spread out across a global supply chain that includes contract manufacturers. More importantly, it leads to late orders and excess cost. A digital, cloud-based approach can help streamline the process, improve speed, and reduce errors. Let’s look at it from three different perspectives – the Engineering, Purchasing, and Operations views.The Engineering Perspective
What does Engineering need from the design – procurement workflow? They want to make sure that everyone downstream has the data they need to make their products right. But they don’t want to have to reenter a lot of information in a complex tool to do it. And if it’s cumbersome, they’ll wait until the information is finalized so nobody sees it until the last minute. They want to export their BOMs from their CAD tool, add data like materials or other specs, pull in standard part data where they can, have it all easily accessible to the right people, and have everything stay in sync when they make changes. They would also love to be able to access a cohesive design history covering all revisions and changes, a complete digital thread of the product development process. The bottom line is that they want to make sure whoever is buying parts, even if it’s a contract manufacturer on the other side of the planet, has accurate part requirements data so they can get it right and fulfill their design intent.The Purchasing Perspective
What does the Procurement Specialist need from the design – procurement workflow? Clearly they need visibility to the parts they need to order in an accurate, timely parts list. They need to know what’s needed, when, and with what specifications as soon as possible, even if it’s not final, so they have time to plan. They also want to hear about changes immediately, before it’s too late and they have to expedite and/or return parts. Purchasing also wants accurate part information for themselves and others to make the right decisions, to have everyone use the same part numbers so they can manage inventory and where-used, and optimize part buys. They want to optimize their procurement strategy by guiding Engineers to make the right part selections. But they want this without having to use a complex tool or enter information manually that could be imported from suppliers, websites, or catalogs. The bottom line is they want accurate data so they can make sure Manufacturing has the parts they need on-hand, without overpaying or carrying too much inventory.The Operations Perspective
Operations just wants everything to run smoothly. They want everybody to be on the same page so nobody makes mistakes and buys or builds the wrong thing. They want this so that customers aren’t upset about missed ship dates and they don’t suffer from excess cost from poor contracts, rush shipping, or excess inventory. They want to avoid lost productivity and expediting missing or lost parts. They also need to manage spend, so they want to make sure they’re getting the best pricing from multiple suppliers, catalogs, and/or websites. The bottom line is that they want to reduce risk and protect revenue by keeping everyone coordinated to get the product out of the door. They can’t afford ad-hoc tools that don’t work for everyone, but also don’t have time to train engineers and purchasing people to be power users for complicated software. And they probably don’t have the appetite to install new hardware and software, and would prefer simple tools that work but don’t suffer from the shortcomings of office productivity tools.Key Takeaways
The common thread across of these roles is the desire for accurate data and simplicity. Companies can’t afford disconnects in today’s agile, digital-speed world. They have to avoid the errors and inefficiencies of general tools like spreadsheets and generic cloud file storage, leverage common data to avoid mistakes in the supply chain, and develop the ability to easily gather information to make the right buying decisions. It’s time for manufacturers to analyze their basic requirements to close the design to procurement gap, find a solution that fits their needs, and do so in a way that’s consistent with their willingness to take on the learning curve, cost, and complexity of enterprise solutions. It’s a good idea to start small and grow, but stay away from dead-end office automation tools or generic file sharing solutions that don’t address their collaboration needs. Companies of all sizes should consider easy to adopt, easy use, cloud-based solutions to streamline processes and close information their information gaps. [post_title] => Bridging the Gap Between Engineering and Purchasing [post_excerpt] => [post_status] => publish [comment_status] => open [ping_status] => open [post_password] => [post_name] => eng-purch-gap [to_ping] => [pinged] => [post_modified] => 2022-11-14 22:27:52 [post_modified_gmt] => 2022-11-15 03:27:52 [post_content_filtered] => [post_parent] => 0 [guid] => https://tech-clarity.com/?p=6980 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 1 [filter] => raw ) [3] => WP_Post Object ( [ID] => 6963 [post_author] => 2 [post_date] => 2018-06-07 10:14:42 [post_date_gmt] => 2018-06-07 14:14:42 [post_content] =>
Product Development Needs to Evolve to Support Today’s Products
Manufactured products have evolved rapidly over the last decade or so. Items ranging from cars to coffee makers have transitioned from primarily mechanical things to smart, connected products that interact with other products as part of a system in a system of systems world.
- Include all functional departments early in the NPD process, for example inviting corporate IT to specify cloud and enterprise system enhancements
- Change the product design process to incorporate new decisions such as where to place sensors
- Adapt the product innovation process to take advantage of new insights available from smart, connected products in the field, including actual operating conditions
Conclusions and Recommendations
It’s time for companies to make the transition to designing smart, connected products. The business benefits are compelling, and we believe that those that implement these capabilities first will put their competitors at a disadvantage. To adapt, companies need to make changes to their NPD processes and technology. They need to involve more disciplines early in the design process, include a new series of decisions in their design process, and learn from real product performance by “closing the loop” between design and operation.
- Conceptual design and requirements
- Data design
- Sensor strategy
- Communication plan
- Validation and verification
It's time to act. With the move toward a sharing economy, we believe that companies that simply develop and sell products will put themselves at a significant disadvantage to companies that design, develop, and stay in touch with their products throughout the product’s life. Companies that don’t embrace digitalization and start offering more than a physical product stand the risk of being commoditized.
*This summary is an abbreviated version of the report and does not contain the full content. A link to download the full report is available above. If you have difficulty obtaining a copy of the report, please contact us using the "Contact" link below. [post_title] => Guide to Selecting a Smart, Connected Product Design Solution (eBook) [post_excerpt] => [post_status] => publish [comment_status] => open [ping_status] => open [post_password] => [post_name] => digital-product-design [to_ping] => [pinged] => [post_modified] => 2022-11-14 22:28:12 [post_modified_gmt] => 2022-11-15 03:28:12 [post_content_filtered] => [post_parent] => 0 [guid] => https://tech-clarity.com/?p=6963 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw ) [4] => WP_Post Object ( [ID] => 6947 [post_author] => 2 [post_date] => 2018-05-29 19:09:13 [post_date_gmt] => 2018-05-29 23:09:13 [post_content] =>
Listen to Tech-Clarity's Michelle Boucher and PTC's Brad Thomas, Product Manager of the Retail Business Unit discuss predictive analytics for the retail industry. They cover topics such as:
- The value of connecting multiple databases on a single platform
- How applying machine learning to analytics helps retail companies
- Examples of how predictive analytics solutions can help retailers


- How a digital twin helps create competitive differentiation
- How manufacturers can transform product performance and service through better product insights
- How a digital innovation platform supports the digital twin
Listen to Claus Gärtner, Head of Operations & Quality IT at Roche Diabetes Care, René Zoelfl PTC Life Sciences Development Manager, and Tech-Clarity's Michelle Boucher discuss how to support the development of medical devices. This discussion was an interactive panel discussion highlighting topics such as:
- The PLM journey taken by Roche Diabetes Care
- What drove Roche Diabetes Care to adopt a PLM system
- The results Roche Diabetes Care have achieved with PLM
- Perspectives of software solution selection criteria to support quality initiatives.


Jump-Start Your IoT Initiative
Manufacturers are making major business improvements using the Internet of Things (IoT). They’re delivering value to customers in new ways and exploring new business models like selling outcomes versus products or shifting to a predictive service model. Some companies are well on their way to this strategic value, while for others it may seem out of reach. How can your company jump-start your IoT initiative? One proven way to get started with IoT is by remotely monitoring machines, either in your own plants or in your customers’ facilities. This gives you the real-time information you need to quickly identify failures and fix equipment more efficiently, improving service while reducing cost. Remote equipment monitoring provides value in the short term and helps develop a strong analytics foundation for your broader IoT strategy. This Quick Start Guide shares suggestions on what companies can do to get equipment connected, start gathering data, and put the data to use. Let’s get started!
Next Steps
Remote monitoring using the IoT can provide rapid value by helping your company gain visibility to your equipment. The value is strategic, but getting started doesn’t need to be intimidating. You can start small and grow value over time. Your investment can provide a valuable foundation to build on as you connect more equipment or implement more advanced features.

The Journey Toward New Development Approaches

You Don’t Know What You Don’t Know

- Products become much more complex
- Knowledge silos / lack of cross-functional knowledge
- Ensuring product requirements are met
- Lack of visibility into the impact of design decisions across disciplines
- Tools are incompatible across engineering disciplines
- Identifying system level problems sooner

Table of Contents
- Executive Overview
- The Business Value of Systems Engineering
- Start with Process Definition
- Manage Requirements
- Design the System
- Design the System to Be Modular
- Support Product Line Variants
- Enable Detailed Design
- Support Connectivity
- Verify and Validate the System
- Assess Service Requirements
- Consider Vendor Attributes
- Identify Specific Needs for your Company
- Conclusion
- Recommendations
- About the Author
Executive Overview
In today’s world, fierce global competition is driving companies to seek new ways to competitively differentiate their products. Many companies are incorporating embedded software into their products to set their products apart from the competition. Embedded software offers opportunities to incorporate intelligence into a product as well as offer customers a more personalized experience. The Internet of Things (IoT) takes this even further by creating exciting possibilities for new and differentiated services for products with smart, connected devices. While bringing together mechanical components, electronics, and software presents exciting opportunities for innovation, it also brings unique challenges and adds new levels of complexity to today’s products and product development processes. The same goes for connected products as you add sensors, streaming data, and an ecosystem of connected systems. Whether you are a systems engineer or IoT solutions architect, expert systems engineering practices are critical to the success of today’s products. An essential part of implementing expert systems engineering practices is having the technology to support them. This buyer’s guide will help manufacturers select the right software to support systems engineering. This guide is composed of four major sections covering, systems engineering software tool functionality, service requirements, vendor attributes, and special company considerations (Figure 1). Each section includes a checklist of key requirements to investigate when selecting software tools to support systems engineering.Figure 1: Systems Engineering Evaluation Framework
- IoT Solutions Architect
- DevOps IoT
- Internet of Things Solutions Engineer
- M2M and IoT Product Management and Engineering
- Technology Manager, Software Engineering (IoT)
- Solutions Engineer (IoT)
- Principal Technical Architect (IoT)
- Innovation Manager for Industry 4.0
- Product Manager
Conclusion
Expert systems engineering practices are key to taking advantage of innovation available through embedded software and the Internet of Things. The opportunities to create smart, connected devices can help companies set their products apart from the competition, helping them win new customers and increase revenues. However, bringing together systems of mechanical, electrical, and software components is complex. That complexity grows exponentially as companies try to meet the various needs of customers with different configurations. Connected systems add even further complexity as you add sensors, streaming data, and connected ecosystems. Complexity means there is risk things will go wrong. The impact of these problems can have a significant business impact and hurt the profitability of the product. Implementing expert systems engineering practices, with the right software tools to support them, can manage this complexity, making it easier to bring profitable products to market successfully. Even if today’s smart, connected devices are relatively simple, as they evolve and offer critical services such as those that impact safety, they will increase in complexity and need the same level of expert systems engineering practices. These practices and the supporting solution are not just limited to systems engineers either. There are a variety of IoT related roles involved with planning, designing, and architecting connected systems, such as IoT solution architects who will struggle with the exact same challenges as systems engineers. Companies planning for growth should consider both current and future needs. However, there are so many aspects of systems engineering; determining the right solution for your company can be very difficult. Using a high-level list of tool and process evaluation criteria such as the ones in this guide can help narrow down potential solutions by providing a quick “litmus test” to determine if a solution and partner are a good fit before conducting detailed functional or technical reviews. In the end, it is important to ensure that functionality, service, vendor, and special requirements are all considered when selecting a solution.Recommendations
Based on industry experience and research for this report, Tech-Clarity offers the following recommendations:- Identify and weigh systems engineering requirements based on company needs, existing applications, industry, and unique product and process requirements
- Use high-level requirements such as the ones in this guide to evaluate solutions based on business fit before engaging in detailed evaluations
- Consider long-term business and process growth needs and the potential to scale across product lines, departments, and engineering silos
- Consider all stages of systems engineering from process, requirements, design, and validation when investing in systems engineering solutions
- Think about all roles that can benefit from systems engineering best practices such as IoT solution architects
- Select a vendor who will be a trusted partner

Table of Contents
- Introducing the PDM Buyer’s Guide
- The Product Data Management Imperative
- Analyze PDM Capabilities
- Assess Service Requirements
- Consider Vendor Requirements
- Identify Unique Company Needs
- Conclusion
- Recommendations
- About the Author
Introducing the PDM Buyer’s Guide
Product Data Management (PDM) is an important tool to help manufacturers overcome the complexities of designing, developing, producing, and supporting today’s products. Manual and ad-hoc approaches such as shared folders, FTP, Dropbox, box, and hard drives are simply not good solutions to manage critical, complex product information. These approaches may work for very small organizations, but quickly falter as organizations grow and must share information beyond a few core engineers. These techniques also fail to manage data relationships and complex file structures common to 3D CAD systems. PDM systems are purpose-built to address these issues. PDM is a structured, collaborative solution that helps manufacturers control, access, and share crucial product data. Selecting the right PDM system for your business has a large impact on productivity, product success, and profitability.
- Getting files under control so people can find the right revision with confidence
- Making sure concurrent updates don’t overwrite each other to avoid “the last save wins” syndrome
- Making information easily accessible and consumable to teams outside of Engineering for reviews and downstream processes
- Safely sharing information with customers, partners, and the supply chain
- Ensuring intellectual property (IP) is captured and securely accessible regardless of who stored it
- Getting away from complicated shared drive structures that lead to errors
- Making sure people don’t manufacture or purchase against the wrong drawing
- Providing “one version of the truth” versus multiple copies of designs
Conclusion
PDM helps manufacturers address market complexity and improve business performance. As Tech-Clarity’s Managing Engineering Data concludes, “Product data management is the fundamental building block of any engineering software strategy and helps companies get the most out of their precious engineering resources.” When evaluating PDM, manufacturers need to take into account:Product requirements
- Implementation, adoption, and support requirements
- Vendor / business requirements
- Special requirements based on company size (particularly for very small or very large organizations)
- Special considerations to meet industry needs
- Future requirements as business continues to digitalize
Reccommendations
Based on industry experience and research for this report, Tech-Clarity offers the following recommendations:- Identify and weigh PDM requirements based on company needs, company size, industry, and any unique company needs
- Use high level requirements such as the ones in this guide to evaluate solutions based on business fit before engaging in detailed evaluations
- Consider using more simple, commodity technical solutions like cloud or managed services solutions for smaller companies, companies that wish to move quickly, or those with limited IT resources
- Take user adoption into account, including simplified access and increased visualization for non-engineering resources
- Consider using more full-featured, scalable solutions for larger organizations that have more demanding process and scalability needs and can afford the IT resources required to support capabilities such as site synchronization
- Take into account long-term business and process growth needs including digitalization and IoT initiatives


- The business value of requirements management
- How to identify specific requirements needs
- How to select the right solution for your organization


Listen to Tina Kunshier of Boston Scientific and Tech-Clarity's Michelle Boucher discuss how to select the right software solution to support the development of medical devices. This discussion will be a live interview highlighting topics such as:
- The PLM journey taken by Boston Scientific
- What drove Boston Scientific to consolidate PLM systems
- How Boston Scientific executed their strategy for a unified PLM system
- Selection criteria you should look for in a PLM solution, especially for medical device companies
- Advice to improve product development efficiencies and support regulatory compliance

Listen to, PTC's Dave Duncan and Tech-Clarity's Michelle Boucher discuss how to improve the accuracy of service information for field personnel. They share stories about Embraer, Airbus Helicopters, and Kirloskar Oil Engines and explain how they are transforming their service organizations. During this webcast, you will also learn:
- How poor service information affects technician productivity, customer satisfaction, and after-sales operations
- Best practices for producing accurate service documentation based on Tech-Clarity research
- What you can do to keep service manuals up-to-date so that field technicians can trust service documentation
- Tips to support the cultural changes required to support the transformation for a more service oriented company

- Connect data and processes across disciplines and the lifecycle
- Leverage digital data from one step to the next
- Streamline engineering
- Reduce errors
- Improve traceability
- Digital design for medical device companies (overview)
- Digital design
- Digital design transfer
- Paperless manufacturing

Cloud PLM Adoption and Buyer's Guide Introduction
Although manufacturers have started to adopt cloud solutions for many aspects of their business, Product Lifecycle Management (PLM) has lagged behind. The transition, however, is picking up pace. More companies are considering cloud PLM and many already leverage the cloud to get more value from PLM (and achieve that value faster).


- Software capabilities
- Implementation
- User adoption
- Support
- Vendor characteristics / attributes
- Unique business needs
Table of Contents
- Executive Overview
- Identify Your Challenges
- Transition from Document Centric to Product Centric
- Consider the Complete Lifecycle
- Manage the Product
- Manage Requirements (Customer Needs to Regulatory)
- Support Product Development for Hardware
- Support Software Development
- Enable Smart and Connected Products
- Ensure Regulatory Compliance
- Support Quality Management
- Plan for Manufacturing
- Control Suppliers
- Plan for Service
- Assess Implementation Requirements
- Consider Vendor Attributes
- Identify Specific Needs for your Company
- Conclusion
- Recommendations
- About the Author
Executive Overview
Medical device companies are in the business of making people’s lives better. As Joel Hembrock, Senior Designer and CAD Administrator at Medtronic says, “Our patients are the people who benefit from our products. Restoring life is our main focus. [We want] to be giving people their lives back, restoring their health, allowing them to actually live again and not have their disease or any other ailment keep them from being able to live.” It is an exciting time for the industry as technology advancements have opened up new and exciting opportunities that have the potential to further this mission. On top of this, an aging Baby Boomer population will create additional demand for medical devices. Consequently, the industry should see significant growth. In fact, the Evaluate MedTech World Preview 2017, Outlook to 2022 report forecasts a 5.1% growth rate every year for the next five years. However, it will be the companies who can overcome the unique challenges in the industry who will be best positioned to take advantage of this growth. With lives at stake, patient safety is of the utmost importance. As such, the industry faces heavy regulations. Compliance is so critical that if medical device companies do not adhere to FDA, EU and other worldwide standards and regulations, they will not be profitable. However, so much time, effort, and cost go into compliance documentation; it takes resources away from innovating and ensuring high quality products. As a result, it is harder to take advantage of opportunities that will boost profitability. On the other hand, medical device companies who adopt practices focused on high quality devices can expect greater patient satisfaction, improved competitiveness, and higher profits. In fact, McKinsey estimates that firms who embrace quality focused best practices can increase profits by 3% to 4% of revenues. They predict the revenue increase alone could be a $3.5 billion opportunity for the industry[1] and this doesn’t even factor in the profitability improvements of avoiding costly quality issues. Unfortunately, for the industry, quality has been getting worse, not better. The FDA’s Medical Device Recall Report FY 2003 to FY 2012 shows that there has been a striking 97% increase in the number of recalls. To reverse this trend, medical device companies should adopt new approaches that enable a greater focus on quality. One way to achieve this by shifting from a document centric process to one that is product centric. This shift enables more focus on high quality, innovative products that meet patient needs. The good news is that with investments in the right software solutions, this is possible. Software solutions can reduce manual, time intensive reporting processes to a push of a button. Rather than structuring processes around documentation, software solutions can allow you to focus on developing the right products and services that will meet patient needs. For these reasons, some medical device manufacturers integrate quality processes into their core product lifecycle management activities. By incorporating quality processes throughout the product design and delivery lifecycle, companies can improve efficiency. With this approach, instead of wasting efforts searching for compliance supporting documentation and reporting, companies can use that valuable time for can quality and innovation. The result will be higher profitability. Other changes in the medical device industry coming from recent trends such as the transition to outcome-based healthcare in the US. In some cases, to be compensated, medical professionals must show positive patient outcomes. A way to accomplish this is to take advantage of innovation enabled by the Internet of Things (IoT). For example, IoT combined with software capabilities can be used to meet requirements for Unique Device Identifiers (UDIs) that will provide new levels of traceability and communication to demonstrate device effectiveness. the right software solution must be in place to effectively manage it. While UDIs present one possible use case for IoT, the potential opportunities for IoT go even further. IoT and other technological advancements such as augmented reality (AR) and 3D printing, create new opportunities for profitable new business models by enabling services that align with customer and patient needs. However, companies stuck following traditional document centric workflows may struggle to find the bandwidth to innovate with these new technologies. Meanwhile, competitors who can devote the resources to innovation will be well positioned to capture a leading market position. This situation makes it an ideal time to invest in a software platform that enables a product centric approach for the entire lifecycle of your device. As you evaluate your current needs, think through how your business needs may evolve due to the impact of technological advances in medical devices. For example, designing for connectivity may require new approaches to design. You will now need to consider things like sensors, ecosystems, and new IT development roles that will play a critical part of product development. Ensure your software platform will be able to meet both current and future needs as your product portfolio evolves. While you consider investments in software solutions, leverage existing systems that are working well. The new solution should use a platform that will leverage and extend the investments made in existing solutions, such as Manufacturing Execution Systems (MES), Enterprise Resource Planning (ERP) and Product Lifecycle Management (PLM) if you are happy with them. With so much to consider, how do you know what will be the right software technology to support the lifecycle of your devices? This buyer’s guide will serve as guidance to help you select what is right for your company. This guide consists of four major sections covering software tool functionality required for medical device companies, implementation requirements, vendor attributes, and unique company considerations (Figure 1). Each section includes a checklist of key requirements to investigate when selecting software tools. This guide is not an all encompassing requirements list. It provides a high level overview. [1] Ted Fuhr, Katy George, Janice Pai, “The Business Case for Medical Device Quality,” McKinsey Center for Government, McKinsey & Company, October 2013
Conclusion
Medical device companies looking to improve profitability should shift their focus from a document centric process to a product centric process that will enable them to concentrate on quality. The cost of poor quality can be significant. In fact, McKinsey estimates that non-routine quality events cost the industry up to $5 billion. On the other hand, companies that focus on high quality enjoy a significant advantage with a potential increase in profits of 3% to 4% of revenues, according to McKinsey. The FDA has also concluded that a greater focus on quality is required. For example, they have found recalls have increased by 97%, with design errors being the leading cause. With the Case for Quality initiative, quality should be come an area of heightened focus, which a product centric approach supports. Unfortunately, making this shift, while still meeting regulatory requirements is hard. However, with the right technology, companies can make it much easier. The right solution should consider all aspects of the product lifecycle from requirements, through design, testing, manufacturing, and service. It should streamline the regulatory process and automate as much as possible. With traceability across the lifecycle and all deliverables, it will be much easier to provide regulatory compliance documentation. That traceability should also extend to suppliers. The right software solution can make it much easier to bring the right, high quality medical device to market, providing a competitive advantage. When making such a significant investment, you should also anticipate how your requirements will evolve to remain competitive in the future. Technological advancements such as IoT, AR, and 3D printing create opportunities for very profitable new business models that can increase the quality of patient care considerably. Features such as predictive and remote service offer flexibility around downtime to minimize the impact on patient health. These technologies can help medical device companies advance their mission of making people’s lives better.Recommendations
Based on industry experience and research for this report, Tech-Clarity offers the following recommendations:- Identify the top challenges your company needs to solve when bringing medical devices to market.
- Consider a solution that can support the entire lifecycle of your product, from patient needs and requirements to, design, test, manufacturing, and service.
- Look at solutions that will support the Case for Quality. A product centric approach and in integrated PLM and Quality Management System can help keep the focus on quality throughout the entire lifecycle.
- Use a vendor who is familiar with medical device regulatory requirements and has the technology to reduce the manual effort required to comply with regulations.
- Ensure you can manage the device and all associated document, design details, and changes while having traceability across everything.
- Support requirements with a solution that will work across all disciplines and has traceability across all stages and deliverables to support changes and compliance.
- Empower each team member including design, quality, procurement, manufacturing, and service with tools that work for them, while still ensuring a single source of truth for product information.
- Support quality management with traceability from requirements to test and reporting tools to ensure monitoring of trends that impact quality.
- Ensure tight controls on suppliers so as not to put compliance at risk.
- Select a solution that will support manufacturing so that you produce devices as designed and meet regulatory requirements.
- Think about medical device service requirements and use a solution that will support current and future service models such as predictive and remote service.
- Select a vendor who can integrate with your existing solutions while implementing new solutions where needed.
- Consider future needs for potential revenue streams and future needs for technologies such as IoT, 3D printing, and Augmented Reality.

Table of Contents
- Executive Overview
- Chemical Companies Face Multiple Business Challenges
- Operational Challenges in the Lab Make Improvement Hard
- Why Digitalize? The Status Quo Won’t Scale
- What’s Driving Chemical Companies Digital?
- Digitalization in the Lab – When, not If
- Digitalization Falters beyond the Lab
- Identifying the Top Performers
- Top Performers Have Better Capabilities for R&D and the Lab
- Top Performers are More Digitalized
- Identifying Best Practices for the Digital Chemical Lab
- Prerequisites for the Digital Chemical Lab
- Digital Chemical Lab Basics
- Digital Best Practices for the Chemical Lab
- Enabling Technology for the Digital Chemical Lab
- Enabling the Digital Chemical Lab with a Solution Platform
- Conclusion
- Recommendations
- About the Author
- About the Research
- Executive Overview
- Most chemical companies have started to adopt digitalization
- Digital transformation is further along in the lab than beyond the lab
- Chemical companies report varied levels of digital maturity

- Are more digital in the chemical laboratory
- Have invested in more digital lab best practices
- Use more specialty scientific software
- Value a platform approach to integrate and support the digital enterprise
Conclusion
Chemical companies are challenged to improve their innovation and product development performance while controlling cost. They face significant operational issues that make these business improvements hard to achieve. Digitalization holds significant promise to address these issues and improve performance because it’s proven to accelerate the pace of innovation, increase agility, and improve efficiency. The transition to the digital chemical lab has begun. Today, however, most chemical companies have only partially digitalized. Top Performers, though, have greater digital maturity than their lesser-performing competitors. They’ve adopted more digital R&D and lab capabilities, particularly when you look beyond the basics to best practices. Top Performers have implemented more specialized R&D and lab management systems to support their best practice processes. Based on the survey results, we believe that these capabilities help the Top Performers achieve better operational R&D and laboratory performance and drive better business performance. Our overall conclusion is that digital best practice processes and chemical laboratory management solutions provide a competitive advantage that helps chemical companies drive higher levels of innovation and profitable growth. Finally, we believe that digitalization will lead to significant market disruption across the chemical industries and result in a significant change in market leadership. Digital transformation supported by best practices and a platform of integrated R&D and laboratory solutions will be a key differentiator to enable the future Top Performers that will lead the industry. The time to digitally transform the chemical laboratory is now.Recommendations
Based on industry experience and research for this report, Tech-Clarity offers the following recommendations. Chemical companies should:- Ensure the digital chemical lab prerequisites and basics are in place
- Pursue digital laboratory best practices including reuse, simulation, and knowledge management to differentiate and drive higher levels of innovation
- Leverage specialized laboratory and R&D software to drive better business performance
- Pursue a chemical laboratory systems platform strategy to further improve performance and gain a market advantage
Copyright Notice
Unauthorized use and/or duplication of this material without express and written permission from Tech-Clarity, Inc. is strictly prohibited. This report is licensed for distribution by Dassault Systèmes BIOVIA. *This summary is an abbreviated version of the report and does not contain the full content. A link to download the full report is available above. If you have difficulty obtaining a copy of the report, please contact us using the "Contact" link below. [post_title] => The Digital Chemical Lab (survey results, white paper) [post_excerpt] => [post_status] => publish [comment_status] => open [ping_status] => open [post_password] => [post_name] => digital-chem [to_ping] => [pinged] => [post_modified] => 2022-11-14 22:28:36 [post_modified_gmt] => 2022-11-15 03:28:36 [post_content_filtered] => [post_parent] => 0 [guid] => https://tech-clarity.com/?p=7004 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw ) [comment_count] => 0 [current_comment] => -1 [found_posts] => 789 [max_num_pages] => 40 [max_num_comment_pages] => 0 [is_single] => [is_preview] => [is_page] => [is_archive] => [is_date] => [is_year] => [is_month] => [is_day] => [is_time] => [is_author] => [is_category] => [is_tag] => [is_tax] => [is_search] => [is_feed] => [is_comment_feed] => [is_trackback] => [is_home] => 1 [is_privacy_policy] => [is_404] => [is_embed] => [is_paged] => [is_admin] => [is_attachment] => [is_singular] => [is_robots] => [is_favicon] => [is_posts_page] => [is_post_type_archive] => [query_vars_hash:WP_Query:private] => 63fc3750ff21aad5851a537e978569ca [query_vars_changed:WP_Query:private] => 1 [thumbnails_cached] => [allow_query_attachment_by_filename:protected] => [stopwords:WP_Query:private] => [compat_fields:WP_Query:private] => Array ( [0] => query_vars_hash [1] => query_vars_changed ) [compat_methods:WP_Query:private] => Array ( [0] => init_query_flags [1] => parse_tax_query ) [query_cache_key:WP_Query:private] => wp_query:8e8a1df38e696473355c826071f8ea63:0.92392200 17603573530.93367800 1760357353 )All Results for "All"
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