Welcome New Members of the MLC December 2025
Introducing the latest new members to the Manufacturing Leadership Council
Learn more about MLC membership.
Michelangelo Canzoneri
Global Head of Smart Manufacturing,
Merck Group/EMD
https://www.emdgroup.com/en
https://www.linkedin.com/in/mcanzoneri/?locale=en_US
Marc Fuentes
Vice President Commercial
Eclipse Automation
www.eclipseautomation.com
https://www.linkedin.com/in/marcfuentes/
Kevin Hannigan
CEO
InflexionPoint
https://inflexionpoint.ai/
https://www.linkedin.com/in/kevinehannigan/
Jon Hobgood
Global Head of Smart Manufacturing
GE Healthcare
www.gehealthcare.com
https://www.linkedin.com/in/changeagentnow/
Mark Lamoncha
CEO
Humtown Products
https://humtown.com/
https://www.linkedin.com/in/mark-lamoncha-0792b114/
John McGee
VP, Supply Chain and Operations
Watts Water Technologies
https://www.watts.com/
https://www.linkedin.com/in/john-l-e-mcgee/n
2025 in Photos at the MLC
It was a year for top-flight plant tours, a record-setting Rethink, and a glittering awards gala.
United Scrap Tour
The Manufacturing Leadership Council hosted four plant tours in 2025, including this one August 12-13 at United Scrap Metal in Cicero, IL. More than 70 Council members toured the company’s 50-acre headquarters site, where millions of tons of recycled scrap metal is processed into usable commodity materials for mills, foundries, and casting.
United Scrap Tour
In addition to making stops at key operational locations at United Scrap Metal’s site, attendees also took part in breakouts that covered digital systems, company culture, and safety and sustainability practices.
General Motors Tour
In September, MLC members took the Cadillac of plant tours – literally, at General Motors’ Spring Hill, TN, plant, where Cadillac’s electric LYRIQ and VISTIQ and internal combustion XT5 and XT6 vehicles are produced.
General Motors Tour
The Spring Hill factory has a long history within the GM portfolio, originating as a Saturn plant from 1990 to 2007. It has also produced models from Chevrolet and GMC in more recent times and will begin production of the Chevy Blazer in 2027.
Rethink
Emmanuel Boullay, Senior Vice President, Operations, at Intertape Polymer Group, was on the main stage at Rethink 2025 to share how IPG created an M4.0 foundation that has scaled to create data-first operations. IPG was the 2024 Large Enterprise Manufacturer of the Year for the Manufacturing Leadership Awards.
Rethink
MLC Founder David Brousell (left) moderates Handicapping the Global Digital Transformation Race, a panel at Rethink 2025 with leading industry analysts, including (from left) Bob Parker, Senior Vice President, Worldwide Research at IDC; Craig Resnick, Vice President at ARC Advisory Group; Matthew Littlefield, Co-Founder, President and Research Lead at LNS Research; and Julie Fraser, Vice President of Research, Manufacturing and Operations at Tech-Clarity.
Rethink
Will Bonifant, Vice President, Manufacturing and Engineering at The Hershey Company and a member of MLC’s Board of Governors, leads a case study session at Rethink 2025 titled Hershey’s Digital Factory – How Hershey is Driving Manufacturing Excellence. Bonifant shared how Hershey digitally upgraded its production, utilizing automation and advanced analytics alongside frontline teams to drive world-class results.
Manufacturing Leadership Awards Gala
Merck & Co. Senior Vice President, Digital Manufacturing and Chief Digital and Technology Officer Besu Alemayehu, right, was named the Manufacturing Leader of the Year at the Manufacturing Leadership Awards Gala, which took place on June 17 in Marco Island, FL. From left, David Brousell, MLC Founder, Vice President, and Executive Director, and National Association of Manufacturers CEO Jay Timmons look on during Alemayehu’s acceptance speech.
Manufacturing Leadership Awards Gala
The Pure & Gentle team, including Lea Green, center, and Darin Klaehn, left, react with joy to hearing their company announced as the Transformational Business Cultures winner in the Manufacturing Leadership Awards. More than 400 attendees gathered at the 2025 gala, with 116 projects and 49 individuals recognized as finalists.
About the author:
Penelope Brown is the Senior Content Director, Manufacturing Leadership Council
The Best of the Manufacturing Leadership Journal 2025
Celebrating expert insights from a year of manufacturing innovation and leadership.
As manufacturers confronted another year of rapid technological acceleration and shifting competitive pressures, the Manufacturing Leadership Journal has been a consistent source of clarity, context and forward-looking insight. Across 2025’s bi-monthly issues, contributors explored the industry’s most urgent themes: from the rise of AI-driven production and digital supply networks to the growing imperative for sustainability, data mastery and smarter manufacturing. The result is a roadmap of ideas that reflect both the disruptive forces shaping the sector and the practical strategies leaders are using to create value.
Each article published in the Manufacturing Leadership Journal delivers value that helps manufacturers of all sizes progress on their digital journal. In this special best-of collection, we revisit 10 such articles from the past year.
Learn how manufacturers are deploying digital twins to unlock operational excellence, collaborating across supply ecosystems to boost competitiveness, and embracing sustainability as a business driver. Explore the pivotal moment AI now represents for industrial performance and the essential role of data governance in preparing for the next wave of intelligent production. Whether you’re refining your digital strategy, strengthening your supply network or building the foundation for an AI-enabled future, these pieces offer the insights needed to lead with confidence in an era of transformation.
FEBRUARY / MARCH 2025
SMART FACTORIES AND DIGITAL PRODUCTION
AI-Driven Factories of the Future: It’s a Lot More than Just Autonomy
By Brian Legan
The future of manufacturing is about intelligently blending autonomous operations, augmented intelligence and flexibility to redefine production.
Unlocking Manufacturing Excellence with Digital Twins
By Jason Hehman
Manufacturing leaders can leverage digital twin technology to drive operational transformation while ensuring sustainable, long-term value creation.
APRIL / MAY 2025
M4.0 SUPPLY NETWORKS
The Foundations of Enabling an M4.0 Supply Network
By John Barcus
Today’s competitive supply networks are digitalized, responsive and flexible enough to adapt rapidly to changing markets, challenges and opportunities.
How to Boost Competitiveness Through Supplier Collaboration
By Ashutosh Dekhne, Chetan (Chet) Trivedi
Leading organizations consider their supplier networks for their contributions to innovation and overall value, not just cost.
JUNE / JULY 2025
SUSTAINABILITY AND THE CIRCULAR ECONOMY
Building a Practical Sustainability Management System for Manufacturers
By Steven Moskowitz, Ph.D.
Success with sustainability requires a new, strategic way of thinking about and managing the business.
Why Smart Manufacturers Are Betting on Sustainability
By Rodrigo Alves, Austin Locke
Industrial leaders are turning to digital technologies to drive profits and cut emissions.
AUGUST / SEPTEMBER
AI IN MANUFACTURING
Maximizing Continuous Improvement with GenAI
By Saeed Haq, Brian Zakrajsek
Generative AI tools have the potential to raise continuous improvement to a new level – continuous intelligence.
The AI Divide: Manufacturing’s Pivotal Moment is Here
By Danny Smith
As artificial intelligence reshapes manufacturing competitiveness, organizations must act decisively or risk falling permanently behind their AI-enabled competitors.
OCTOBER / NOVEMBER 2024
DATA GOVERNANCE, MASTERY AND ANALYTICS
The Industrial Data Foundation Imperative: Building Manufacturing’s AI Future
By Ashtad Engineer
Manufacturing leaders must prioritize industrial data readiness and governance now, as the gap between data-ready organizations and laggards threatens future AI competitiveness.
5 Key Questions on the Path to Industrial DataOps
By Patricia Henderson, Rohini Prasad
Industrial DataOps enable manufacturers to be more agile, improve continuously, and move toward smart manufacturing.
About the author:
Jeff Puma is Content Director for the Manufacturing Leadership Council
The Best of Rethink 2025
The 20th anniversary of Rethink brought together thought leaders and manufacturers to share digital transformation best practices and lessons learned.
MLC members celebrated Rethink’s 20th anniversary by doing what they’ve done at the past 19 summits: learning about the technology, leadership, and organizations driving Manufacturing 4.0 forward. Over the course of three days, more than 60 speakers shared their insights during keynotes, case studies, panel discussions, (Re)Think Tanks, fireside chats, lightning rounds, and executive interviews.
Here are a few of the exceptional sessions Rethink participants experienced.
Access to the MLC Member Portal is required to view the videos.
Opening Address: What’s Next?
David R. Brousell, Founder, Vice President and Executive Director, Manufacturing Leadership Council
Over the past 20 years, the manufacturing industry has worked hard to understand and adopt the digital model of production, learning much along the way. But as new technologies emerge, the proverbial finish line continues to move, leading to new possibilities, aspirations, and opportunities as well as challenges. MLC’s founder shares his views on what manufacturing might look like by mid-century.
Case Study: 25 Years of Transformation—Triumphs and Pitfalls from a Manufacturing Digital Native
Robert Bodor, CEO and President, Protolabs, Winner of the 2022 ML Awards Small/Medium Enterprise Manufacturer of the Year
Protolabs began as a company aimed at filling a specific manufacturing need: injection molded parts really fast. As one of manufacturing’s original “digital natives,” that speed was a result of automation and digitizing a once-traditional process. Since those early days, the company has expanded its offerings and experienced significant growth. The ongoing digital transformation that followed over the next 25 years as a custom components manufacturer has provided a case study in digital evolution comprised of technology advancements, key acquisitions, difficult trade-offs, and even a few hard lessons learned along the way. Learn more about the company’s ongoing Manufacturing 4.0 journey that has driven its mission to serve customers on the forefront of innovation.
Panel Discussion: Next-Generation Leaders
Angela Accurso, Director of Workforce Programs, MxD
Marlon Alberto Gonzalez Martinez, Storage Order Management Fulfillment Team Leader, IBM
Megan McCarthy, Business Process Manager for Global Manufacturing Electrical, General Motors
Jonathan Miller, Automation and OpEx Manager, Saint-Gobain Life Sciences
Facilitator: Penelope Brown, Senior Content Director, Manufacturing Leadership Council
What’s on the minds of the next generation as they develop into tomorrow’s leaders? This panel discussion examines the hopes, aspirations, and visions for the future from some of 2024’s top finalists for the Manufacturing Leadership Awards Next-Generation Leadership award.
Case Study: Hardwiring Innovation Processes from Tech Into a 155-year-old Company
Craig Slavtcheff, Executive Vice President and Chief R&D and Innovation Officer, Campbell Soup Company
The pace and scope of innovation demanded in food by consumers continues to be high, driven by a range of macrotrends including food exploration and nostalgia, ag-tech, and sustainability. To keep pace, food companies have to innovate on how they innovate, focused on the three drivers of “speed to insight,” “speed to design,” and “speed to execution”. Campbell has looked to the world of tech, including machine learning and AI, as inspiration to transform its innovation processes, building on its 150+ year old history of inventing delicious, nutrition, safe, and affordable foods.
Case Study: Making the World a Better Home through M4.0
Regan Gallo, Director of Operations, Coated Abrasives NA, Saint-Gobain North America
With more than 145 manufacturing locations across North America alone and several acquisitions in the past few years, Saint-Gobain faces steep challenges when it comes to deploying a unified digital strategy across the organization. With takeaways applicable to manufacturing companies of any size, learn where the company has found success, where it needed to make pivots, and the progress it has made as it works to meet its mission – making the world a better home.
About the author:
Jeff Puma is Content Director for the Manufacturing Leadership Council
The Best of 2025 Decision Compass Calls
MLC’s special interest Decision Compass calls deliver real insights from manufacturing leaders
The MLC’s Decision Compass meetings continue to offer members a space to cut through the noise surrounding digital transformation and Manufacturing 4.0. These special interest group sessions delivered practical, unfiltered guidance on the issues shaping modern manufacturing. From data governance and autonomous operations to supply chain evolution and circularity, Decision Compass calls are a trusted forum for leaders seeking clarity, community and actionable next steps.
This best-of selection highlights four standout conversations from 2025. Explore how companies are building data-literate workforces, deploying smarter automation, leveraging emerging technologies to strengthen supply networks, and advancing circular business models that deliver both sustainability and competitive advantage. Whether you’re refining your strategy or looking for inspiration from leaders navigating similar challenges, these sessions capture the insights that matter most to today’s manufacturing decision-makers.
Note: These recordings are archived in the MLC content library, an exclusive benefit for MLC members. Members can log in to view the recordings. Nonmembers will be asked to complete an information form to gain access.
DC Group: Data Mastery, Governance and Analytics
Data Literacy in Manufacturing
Topic leaders: Curt Winegar, Senior Data Analytics Strategist, Pella Corp.
Ada Safak, Advanced Analytics Analyst, Worthington Enterprises
In this panel moderated by the MLC’s Steven Moskowitz, Ph.D., our guests discuss what data literacy is, why it is such an important part of an overall data program, what works, and what can be improved in current deployments.
DC Group: Automation and Operational Excellence
Autonomous Optimization in Manufacturing
Topic leader: Maurice O’ Brien, Director, Industrial Automation Motion and Power Control, Analog Devices
Automation is becoming smarter, more connected, and capable of making more decisions autonomously. New architectures and technologies like decentralized control, sensor fusion, and edge AI enable machines to work more efficiently and create valuable OEE data sets for continuous process improvements. Join us to discover how Analog Devices technologies are enabling the next step towards smarter, more autonomous factories.
DC Group: Resilient Supply Networks
The Role of Emerging Technologies in Supply Chain Evolution
Topic leaders: Jonathan Whitaker, Managing Director of Supply Chain Consulting, NTT DATA and Steve Sarbey, Director Supply Chain Consulting, NTT DATA
To navigate the transformation that emerging technologies are bringing to supply chain management, organizations should begin with proven use cases. To successfully build a roadmap for technology integration, it is essential to identify key pain points, select appropriate technologies, and ensure continuous alignment with strategic objectives.
DC Group: Sustainability and the Circular Economy
Breaking Linear Models: Saint-Gobain Circular Economy Solutions
Topic leader: Anirban Ghosh, Senior Manager of Circular Economy Business Development and Strategy, Saint-Gobain
In this case study, learn how Saint-Gobain Circular Economy Solutions is working to identify new circularity growth areas, incubate new waste-to-value business models, and support and develop their circularity roadmaps, specific projects, reporting and foundational competencies
About the author:
Jeff Puma is Content Director for the Manufacturing Leadership Council
Exploring Digital and Physical Convergence at Eclipse Automation
From immersive tech demos to shop-floor innovation, MLC members got an exclusive look at how Eclipse Automation is turning digital transformation into real-world results.
Eclipse Automation opened the doors to its Cambridge, ON facility for MLC members and guests, showcasing the latest innovations in factory automation, digital twins and the omniverse.
The event included a tour of the 200,000 square foot facility, presentations, a panel discussion and opportunities for manufacturers leaders to network and discuss digital and physical convergence and the factory of the future.
Eclipse delivers advanced systems that help manufacturers accelerate production, improve quality and strengthen resilience across industries—from life sciences and transportation to consumer products and electronics. The company’s Cambridge facility serves as both a hub of engineering innovation and a showcase for its latest advancements in smart automation.
Innovation in Action at Eclipse
The day began with a welcome from Cambridge Mayor Jan Liggett and an opening keynote by the MLC’s Steven Moskowitz, Ph.D., setting the stage for a day dedicated to digital and physical convergence. Eclipse Automation’s newly appointed president, Michael Fisher, delivered a corporate overview “assembling physical and digital momentum.” Attendees were then immersed in a hands-on Omniverse demonstration, offering a glimpse into the collaborative power of augmented and virtual reality. Using an Apple Vision Pro attached to a projector, participants saw how digital twins and real-time modeling can streamline design decisions and accelerate project timelines.
Inside iPort
The highlight of the morning was the guided tour of Eclipse’s iPort facility, where attendees visited three immersive stops.
- At the Gaussian Splatting Galleria, guests stepped into a virtual workspace that erased physical barriers, revealing new ways to collaborate and problem-solve in real time.
- The Factory Automation Galleria offered a behind-the-scenes look at Eclipse’s innovation process—where ideas move rapidly from concept to prototype to production and projects are derisked.
- Finally, at the Eclipse Experience in Motion stop, visitors walked the active shop floor to observe how Eclipse’s multidisciplinary teams bring complex systems to life.
The tour concluded with a stop at the Technology Galleria, where technology partners demonstrated the tools and platforms shaping where factory automation is going.
Where Digital Meets Physical
In the afternoon, attendees participated in thought leadership presentations and discussions. Breakout sessions covering Smart Manufacturing Playbooks and Generative AI at the Edge were followed by a panel discussion where tour participants were able to ask questions about digital transformation, automation and workforce innovation to a panel of experts.
The tour offered a rare glimpse of the technologies and strategies that are redefining the future of the factory.
Photos and video by Ryan Dentinger, Eclipse Automation
Digital Manufacturing in Action at GM’s Cadillac Plant in Tennessee
Robotics, AI and people work together to shape the future.
Henry M. Leland, who founded Cadillac in 1902, believed in creating superior products. Cadillac’s early slogan, “The Standard of the World”, reflected his philosophy of establishing a mark of excellence in the automotive industry.
Over the years, Cadillac delivered on that philosophy with innovations that included the pioneering development of interchangeable parts, the first fully enclosed automobile cabin and first electric starter, the first mass produced V8 engine, fuel injection, and many other accomplishments.
The famous Cadillac Crest symbolized Leland’s philosophy. Featuring mythical birds called merlettes, which are derived from the family crest of Antoine de la Mothe Cadillac, the founder of Detroit whom Leland named his automobile after, the crest symbolized a constant striving for excellence. The crest has undergone more than 30 redesigns and even though the merlettes are no longer used in the logo—they do appear as an “Easter Egg” on the LYRIQ’s dashboard—the message of excellence remains.
Today, Cadillac, which General Motors acquired in 1909, remains the premier brand of its $187 billion parent, and is leading GM’s charge in the electric vehicle market. In early September, nearly 100 members of the Manufacturing Leadership Council toured GM’s 11 million-square-foot, 4,000-employee Spring Hill, TN, Cadillac factory to see how Cadillac’s electric LYRIQ and VISTIQ and internal combustion engine-based XT5 and XT6 vehicles are manufactured. The factory will begin building the Chevy Blazer in 2027.
On the Factory Floor
What MLC members saw was a highly automated and digitalized factory that uses robotics and artificial intelligence to improve safety, quality, and efficiency on the manufacturing floor.
As one example, GM has a joint venture with LG Energy Solutions to make Ultium cell batteries in Spring Hill.
The batteries are inspected in error proofing stations using cameras and laser stations that check connections. AI is used to detect problems. Together with GM’s Avantguard system, which tracks work sequences and steps, these stations have resulted in a significant drop in warranty issues for customers.
In the assembly operation, MLC members witnessed a GM first—a robot installing a seat in a car on a moving conveyor without human involvement. The operation relies on a vision system and Light Detection and Ranging (LiDAR), a remote sensing method that uses pulses of laser light to measure distances and create 3D models, to align the seat and place it in the precise location while also maneuvering through the door holes.
MLC members also saw how GM mixes vehicle types on the same production line. All five vehicle types produced in the factory, including both EV and internal combustion engine vehicles, are assembled on the same line. Automated mobile robots deliver the proper chassis to each vehicle body as the unfinished cars move down the line. With five different models moving down the line at the same time, the company has paired automation and AI with a surprisingly simple way for workers to identify each vehicle model. A color-coded temporary overlay on the vehicle’s fender signals which vehicle they’ll be working on next.
Beyond the Factory Floor
Breakout session topics included supply chain management and manufacturing optimization. In the supply chain session, tour participants learned that the company’s focus is on simplifying and streamlining supply chain operations so that it can achieve more flexible operations. To improve efficiency, their guiding principle is to fit one more part in every box and move that box one less foot.
In the optimization session, GM shared that the company’s automation rationale is based on three factors: safety, continuous quality improvement, and efficiency.
According to GM, the best manufacturers know how to get the most out of their technology, equipment, and people—noting that each brings something valuable to the table. The key now is to select the projects that deliver the most ROI while staying true to Cadillac founder Henry Leland’s quest to be the standard of the world.
Photos by David Bohrer/National Assoc. of Manufacturers
How Manufacturers Can Achieve GenAI Success
Manufacturers are increasingly adopting and using generative artificial intelligence, and it is changing their businesses for the better. But for the use of GenAI to be truly transformative, company leadership must ensure their strategy builds on six specific pillars, according to a recent article in the Manufacturing Leadership Council’s ML Journal.
- Establish an AI control tower: Many businesses are spending money needlessly on duplicative GenAI initiatives. Instead, they should set up an AI “control tower,” a centralized hub for AI tools and use cases that lets them reuse assets to save money and speed up implementation.
- Reimagine future business models and functions: Rather than implementing piecemeal updates, companies should consider larger, full-scale revisions with AI. Those that don’t innovate risk being left behind.
- Ensure confidence in AI: Keeping human team members in the loop as GenAI deployments happen will ensure employee confidence in the transformation—as will having a clearly defined set of processes and rules in place to govern algorithm and model creation and use.
- Address talent and tech gaps: Even as the newness of GenAI implementation wears off, it’s important to continue to provide training. A recent EY AI Anxiety in Business survey found that 80% of workers would feel more comfortable using AI if they were trained on it.
- Develop an ecosystem of alliances: To stay ahead of the curve, manufacturers must establish partnerships. These will be critical in filling gaps in their capabilities in an evolving landscape. Specifically, alliances in these four categories are recommended: technology, professional services, academics and data.
- Drive focused data maturity to be AI-ready: When it comes to data maturity, company leaders should aim to be smart and focused. Not every piece of data needs to be pristine to be included in your models. Rather, a firm’s data strategy should be governed by how the data will be used.
The benefits: This strategy should address seven key needs: accessibility at scale, visibility, timeliness, openness, reliability, expansiveness and trust and security.
Nominations are open: The MLC, the NAM’s digital transformation arm, is now accepting nominations for the 2026 Manufacturing Leadership Awards. Learn more here.
How Data Strategy and Governance Can Drive Success for Manufacturers
Unlocking value from data offers manufacturers new opportunities in a shifting economic landscape.
TAKEAWAYS:
● To improve supply chain visibility and overall operations, manufacturers must be intentional in how they harness and use all their data sources.
● Business strategy alignment, data literacy, and the right technology platforms are key to developing a data strategy that supports data governance.
● Manufacturers need a robust data foundation in order to use AI effectively.
From raw material sourcing to product delivery, virtually every manufacturing process generates vast amounts of data. Yet for many organizations, these data remain siloed, underused, or poorly governed, hindering their ability to make informed decisions and fully leverage artificial intelligence (AI) and Internet of Things (IoT)-enabled devices.
Economic uncertainty and a shifting trade landscape make tapping into available data even more critical for driving better decision-making. In multi-layered manufacturing supply networks, organizations that harness information intentionally can use both their internal operational data and data generated from vendors, customers, and other partners to improve supply chain visibility and overall operations.
To seize this opportunity, manufacturers must embrace a clear data strategy that empowers a robust data governance framework. This approach ensures data are trustworthy and accessible, positions organizations to use data as a true strategic asset, and allows them to leverage more advanced technologies such as machine learning, automation, and AI.
Four Pillars of Data Governance
A successful data governance framework is based on four foundational pillars: trusting data, making data available, ensuring data compliance, and understanding the data (see Figure 1). These pillars help organizations cultivate a mindset to operationalize and analyze information at scale.
- Trusting data: Data quality is the bedrock. Manufacturers must be confident that the data they use for supply chain optimization, process improvements, or customer insights is accurate, complete, and reliable. Without trust in data, decision-making becomes risky, and outcomes are more unpredictable.
- Making data available: Accessibility is critical. Valuable data that sit in isolated systems or are confined to one department cannot drive enterprise-wide value. Governed data must be accessible to those who need them, when they need them, while maintaining appropriate access controls.
- Ensuring data compliance: Regulatory requirements, both local and international, are growing in complexity. Manufacturers operate across borders, interacting with myriad vendors and customers. Data governance must ensure compliance with policies, processes, and ever-evolving regulations, protecting both the organization and its stakeholders.
- Understanding the data: Data are only as useful as they are understandable. Clear definitions, standardized formats, and robust metadata enable teams throughout the organization to interpret and apply data appropriately, fueling both operational and analytical initiatives. Organizations also need to understand the systems from which their data originate and the overall lineage of that data. For instance, were there any areas where data may have changed as various partners within the supply chain transmitted that data? Teams need to understand all points along that data journey.
Figure 1: Data governance pillars
The Importance of a Clear Data Strategy
Data governance frameworks cannot exist in isolation or as reactive, one-off projects. Instead, they must be embedded as a program through a deliberate, forward-looking data strategy that aligns with organizational goals and evolving market landscapes. A clear data strategy provides the vision, structure, and prioritization necessary to make governance actionable and effective.
For manufacturers, the need for such a strategy is acute. The industry is characterized by complex supply chains, a diverse range of vendors and customers, and rapidly advancing technologies such as enterprise resource planning systems and fleets of IoT-enabled machinery. Every innovation and new data source increases both the challenge and the potential reward of effective data governance.
A robust data strategy helps determine which data are most important and why. This allows manufacturers to contextualize governance framework needs and focus resources on areas that drive the most value. A clear data strategy defines the organization’s roadmap for the next several years and should be closely tied with business goals and broader business strategy. The data strategy and other digital transformation initiatives within the company should also be intentionally aligned and inform each other on an ongoing basis.
Data as a Strategic Asset
Treating data as an asset can shift the organizational mindset from passive record-keeping to active value creation. In this context, data become a foundational resource akin to capital, talent, and technology.
This perspective can have profound implications. The rise of IoT devices in manufacturing plants, for instance, provides companies with new sources of data that can yield insights into operations. When governed and analyzed effectively, that data can unlock new efficiencies, reveal actionable insights, and enable predictive maintenance or smart product innovation. The difference between success and failure rests on whether manufacturers have the right frameworks to trust, access, and interpret their data.
A strong data foundation is also key for companies to implement AI effectively. “Garbage in, garbage out” is especially true here: without clean, well-governed data, even the most sophisticated AI tools will struggle to deliver meaningful results.
Three Key Data Strategy Considerations
Building a data strategy that supports effective governance requires manufacturers to address three critical considerations: align business strategy with long-term goals, cultivate data literacy and assign roles, and select and enable the right technology platforms.
- Align business strategy and long-term goals: A data strategy must flow from a clear understanding of organizational objectives. Consider these questions: Where is the business headed in the next one, three, or five years? What are the focus areas for growth, efficiency, or innovation? The answers to these questions should inform which data products are prioritized, how they are governed, and how value is measured.
If supply chain visibility is a strategic priority, for instance, then data governance efforts should focus on ensuring the quality, availability, and compliance of supply chain-related information. - Cultivate data literacy and assign roles: Data governance initiatives can only succeed if teams are empowered and accountable in their use of data. This means investing in data literacy across the organization and ensuring that the right roles and responsibilities exist to execute the strategy.
From data stewards responsible for quality and compliance to analysts and business users interpreting insights, everyone must understand both the importance of data and how to use that data effectively. Training, clear communication, and a culture of curiosity and improvement are essential as new technologies and data sources enter the manufacturing environment. Having a change management plan in place can help with these efforts and overall adoption. - Select and enable the right technology platforms: Technology is the enabler that binds data strategy and governance together. The first step in governance is not governance itself but building toward a centralized source of truth with a modern data platform that supports integration, automation, and scalability while iteratively applying data governance processes and accountability along the way.
Manufacturers should invest in platforms that not only collect and store data but also facilitate sharing, security, and advanced analytics. Centralizing data reduces duplication of effort, minimizes errors, and ensures consistency in how governance policies are applied. Platforms must also be flexible and ready to accommodate new data streams from IoT devices, AI tools, and other digital transformation initiatives. The focus here should be on applying governance as the organization grows, as centralized data allow for better visibility and control of that data.
The Takeaway
For manufacturers, the journey from data chaos to data value starts with a clear, actionable strategy. By focusing on the four pillars of governance—trust, availability, compliance, and understanding—and embedding them into a strategy aligned with business goals, manufacturers can unlock their data’s potential. M
About the authors:
Ravi Bodla is a principal at RSM US LLP.
Liz Rizzi is a manager at RSM US LLP.
Mastering Manufacturing Data for Real Advantage
It isn’t about collecting more data—it’s about building trust, reliability, and governance to act with confidence.
TAKEAWAYS:
● Manufacturers generate massive volumes of data across design, production, logistics, and service, but fragmented systems prevent its effective use.
● Reliable data requires a governance framework that prioritizes quality, availability, lineage, ownership, and integration health as non-negotiables.
● Achieving data mastery is a staged transformation—beginning with strategy and governance, piloted through early wins, and scaled with continuous monitoring.
Manufacturing has never been short of data. Across the lifecycle, the streams are relentless. Design teams generate gigabytes to terabytes of CAD, simulations, and specifications. Planning adds bills of materials, schedules, and cost structures. At the production stage, the firehose opens: sensors, quality metrics, and inventory signals push into the terabyte-to-petabyte range. Logistics contributes tracking and order flows; service adds usage and maintenance histories of similar magnitude. In most factories, the production stage alone accounts for the majority of enterprise data.
Table 1: Data types and volumes across manufacturing stages
What most organizations lack is not information, but trustworthy information—data that is complete, contextualized, and ready to drive a decision now, not after a post-mortem. The short answer to why this is the case: Data production has outpaced absorption.
Most manufacturers have built systems over years, not as a unified fabric but as islands. Operations tech streams millisecond sensor data while enterprise apps still batch overnight. Vendors speak different dialects, IDs don’t match across product, process, and resource, and revisions in PLM rarely flow cleanly to MES or quality systems. The consequences are predictable: delays, re-keying, rising costs, and a persistent disconnect between teams. When data is fragmented, people optimize locally. The enterprise loses.
Reliability as an Operating Principle
Without a governance spine, more data doesn’t mean more truth, it means more delay. The first step is to make reliability an operating KPI, not an afterthought. That means treating five dimensions as non-negotiable:
- Quality: Accuracy, completeness, and timeliness
- Availability: The feed is up when operations need it
- Lineage: We can trace where numbers come from and how they were transformed
- Governance: Clear ownership, access, and compliance
- Integration health: Connections sync with minimal failure
To ensure progress, set explicit targets: think 95%+ accuracy, 99.9% availability, full traceability, and sub-1% sync failures, and audit them on a regular cadence.
When organizations do this consistently, reliability scores rise quickly, and with them, decision speed and confidence.
Data Mastery is a Transformation
Data mastery is a staged change program. It starts with sponsorship and ownership—an executive mandate, accountable data stewards, and an honest inventory of today’s assets and pain points. The next step is to design the operating model—principles, decision rights, policies on quality, privacy, and security, and map the practical workflows for the data lifecycle, issue resolution, and change management.
Implementation should begin with focused pilots in high-value domains, coupled with data literacy training and enablement. Technology follows purpose: catalogs, observability, quality monitors, and automation to sustain new ways of working. Finally, it is run as an operation —dashboards, scorecards, compliance reporting, and a discipline of continuous improvement and periodic governance reviews.
Table 2: A model step by step approach to mastering manufacturing data
The Payoff: Trust in Action
The organizations that will win are not those that collect the most data, but those that can trust their data enough to act on it—confidently, repeatedly, and at scale. When reliability becomes habit, analytics stop arguing with operations. Engineers change a design and see the impact upstream and down. Planners simulate scenarios they believe. And most importantly, operations leaders move from firefighting to foresight. M
About the author:
Buddhi Ratawal is Senior Manager, Strategic Business Development at DELMIA.