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IBM’s Marlon Gonzalez – a 2024 Manufacturing Leadership Awards Next Generation Leadership winner – shares how emerging leaders can prepare for whatever the future holds. 

Penelope Brown: Hey everybody. Welcome to this month’s Executive Dialogue. I am pleased to be joined by one of our fabulous next-generation leaders, Marlon Gonzalez, who is the supply chain professional team leader with IBM. If you were at Rethink this past June, you probably got an opportunity to see him speaking as part of our Next-Generation Leadership Panel, and that night he was honored at our Manufacturing Leadership Awards Gala. Marlon, thank you for being here with us today.

Marlon Gonzalez: Hi Penelope. I am very happy to be here and really honored to join this conversation with you and with all the audience. I am looking forward to sharing insights and discussing the exciting developments in our industry. Thank you so much for having me here.

PB: Well, let’s get into some of these questions here. In your LinkedIn profile one of the ways that you describe yourself is as an “AI ambassador.” How do you advocate for the use of AI and what are some of the main ways that you can see AI improving supply chains?

MG: As an AI ambassador, I advocate for artificial intelligence by promoting its transformative potential across industry especially in supply chain and manufacturing. I focus on educating peers, clients and partners about the practical application of AI such as automated repetitive tasks, improving decision making through predictive analytics, and optimizing supply chain operations.

Penelope, I truly believe that AI will improve supply chain and the manufacturing industry by enabling more real decision making and collaboration across different parts of the ecosystem for suppliers and customers. So, for example, in the near future—and maybe it’s happening right now—AI can predict demand more accurately by analyzing large data sets allowing business to adjust their production and inventory levels more effectively and it can also help to optimize logistics by analyzing routes, identifying ineffective transportation. The benefits will be very great, so I would like to say to our audience, “Embrace AI. Your company can build more resilient adaptive and customer-focused supply chains.”

“In the near future—and maybe it’s happening right now—AI can predict demand more accurately by analyzing large data sets allowing business to adjust their production and inventory levels more effectively.”

PB: It’s an exciting future indeed and we are looking forward to that. Let’s step back just a little bit here. You started your career with IBM as an intern in 2018 and then, not long after that, everything really went into chaos when the pandemic started. Facing such a huge challenge or such a huge crisis early in your career, how do you think that has shaped your thinking as you continue to move on through your career?

MG: Yeah, this scenario became a pivot moment in my life, pushing me to develop a mindset of resilience and adaptability. These threats not only helped me navigate the challenging time, but also fueled my personal and professional growth in ways I could not have imagined. And on the other side, I’d just say the pandemic highlighted the vulnerabilities with the supply chain from disruptions in logistic to shifts in consumer demand, and it’s underscored the importance of innovation and quick thinking. We were thrust into a situation where traditional methods of managing supply chains no longer worked and we had to innovate in real time, finding new ways to use technology, improve communication and ensure continuity. I invite to the audience to ask themselves two questions: what did you learn from the pandemic and how could you take advantage of an event of such magnitude if it occurs again?

PB: Well as they say, the smooth seas don’t make skilled sailors. I hope that you don’t face anything nearly as momentous for the rest of your career, but if something does come along, I think you’re going to have a skill set that maybe those of us who experienced many good years may not have, or a different way of thinking.

Let’s talk a little bit about your award nomination. Of course, you were one of our winners for our Next-Generation Leadership Award, and one of the things that really stood out on your nomination was how you have developed innovations that incorporate so many different tools and so many different methodologies. So, for example, things like design thinking and agile and project management and Lean Six Sigma. What encouraged you to develop all of those different types of skill sets?

MG: Early in my career I saw that no single methodology could address all challenges. For example, design thinking helped me understand customer pain points and foster creativity. Agile allowed for interactive development and flexibility in project management. Lean Six Sigma provided a data-driven approach to reducing waste. And traditional project management helped me in executing and delivering projects on time and within scope.

“We were thrust into a situation where traditional methods of managing supply chains no longer worked and we had to innovate in real time.”

I was particularly motivated by my work on large scale supply chain projects at IBM, where I need to combine various methodologies to achieve optimal results. Each tool brings something unique to that table. This interdisciplinary approach not only improves project outcomes, but also helped me grow as a leader, ensuring that I could drive innovation and continuous improvement across different areas.

My recommendation to the audience is to always keep learning. The work and the challenge are evolving very fast, so in this case we are talking about work methodologies, but there are also many new emerging technologies to master. And that’s without mentioning the soft skills that are skills that help us to connect with others in an effective way.

PB: Yes, speaking of emerging technologies and skills in particular, at the MLC we talk a lot about how manufacturers need to showcase those opportunities—those kinds of things that happen within careers and manufacturing, especially to digital talent in order to attract the kind of workforce that they need to really take advantage of digital transformation and take that to the next level. What do you think that manufacturers can do to raise their appeal to that digital and that data savvy group of talent?

MG: I am delighted that in the Rethink panel we discussed this topic and we have a little opportunity to talk a little bit more now because this topic not only opens the opportunity to manufacturers but also to all the professionals and students who are passionate about the implementation of disruptive technologies. And, in this case, no matter the generation.

Penelope, I think that to attract digital and data savvy talent, manufacturers need to position themselves as forward-thinking and technology-driven. Manufacturers should actively showcase how digital transformation is impacting their operation and the industry beside them. So highlighting real world examples of how technology is solving complex problems or improving in the manufacturing landscape. I am sure that with this, they can inspire potential candidates. And once you have that talent with you, one of the most effective ways to retain this talent is by creating a workplace culture that embraces innovation and continuous learning, offering professional development opportunities such as certification, training programs and mentorship. So everybody please remember these four words that are crucial for me: invest…in…the…future.

“This interdisciplinary approach not only improves project outcomes, but also helped me grow as a leader, ensuring that I could drive innovation and continuous improvement across different areas.”

PB: That’s a really great answer and a great way to think about it. You know something else that really sort of stood out from your award nomination was that you have engaged in so many ways with so many things within IBM, within your organization, and you know it was really apparent that your leadership was very impressed with your engagement and your willingness to take on all kinds of new challenge. How do you think that other young leaders, like you, can really work on influencing up to put themselves in a good position for career growth?

MG: Penelope, I believe that young leaders in manufacturing need to be proactive, strategic and demonstrate their value through action that aligns with that company goals. One of the most attractive ways to do this is by consistently taking initiative when challenges arise. Come with a solution. Come with an innovative idea that shows your strategic thinking and problem-solving skills. This demonstrates leadership and forward-thinking mindset.

Also, continuous learning and staying ahead of industry trends is a key. I believe that young leaders should embrace digital transformation, be updated about emerging technologies, and advocate for their education.

So by positioning themselves as both leader and learner, they can demonstrate to the management that they are not only ready for growth but also have the company mindset to move forward to the next level.

“Continuous learning and staying ahead of industry trends is a key…young leaders should embrace digital transformation, be updated about emerging technologies, and advocate for their education.”

And, finally, a very personal recommendation is to have an ideal and make that your North Star. For me, being a leader is about serving, and that will be the core of your ideal: how you serve in your community, in your city, in your country, in the society globally. And that’s why people will be inspired to join you or to find their own purpose.

Remember as we said in the Rethink panel, “great leaders create great leaders.” And if you’re asking me which one is my North Star, which one is my ideal? I would say that promote the development of individual and organization through the adoption of emerging technologies, implementing environmentally friendly solutions.

PB: Well, thank you for your time today, Marlon. I know that I’ve got some good ideas from you, so I think that what you’re saying is probably applicable to people at any level of their career. Again, congratulations on your win this past summer. You are an excellent example of an up-and-coming leader for the industry.

Thank you for your time today.

MG: No, thank you. Thank you so much for this opportunity to share my experience and insights on AI, supply chain, manufacturing and leadership. It’s been a pleasure discussing these topics with you and I hope our conversation inspires others in the industry to embrace innovation and continue to grow. Thank you and take care.

PB: Thank you.  M

Portions of this interview have been edited for clarity and length. 

About the Interviewer:

Penelope Brown is Senior Content Director for the NAM’s Manufacturing Leadership Council

Johan Carstens

Head of Smart and Sustainable Manufacturing
Fujitsu Americas

https://www.fujitsu.com/global/solutions/industry/manufacturing/

https://www.linkedin.com/in/johan-hermanus-carstens-85776413b/

John Marth

Senior Industry Advisor
Workday

www.workday.com

https://www.linkedin.com/in/john-marth-bb155548/

Jay Merenda

Strategy Lead, Digital and Data Analytics
Chemours

https://www.chemours.com/en

https://www.linkedin.com/in/jaymerenda/

Scott Nelson

VP Global Operational Excellence
Dover Corporation

https://www.dovercorporation.com/

https://www.linkedin.com/in/scott-nelson-56ab516/

Maurice O’Brien

Director – Strategic Marketing, Industrial Automation
Analog Devices

https://www.analog.com/en/index.html

https://www.linkedin.com/in/maurice-o-brien-46130218/

Jim O’Connor

CIO
Graham Packaging

https://www.grahampackaging.com

https://www.linkedin.com/in/jim-o-connor-11022b10/

Matt Prange

Senior Vice President, Global Supply Chain
Milwaukee Tool

https://www.milwaukeetool.com/

https://www.linkedin.com/in/matthewprange/

Andy Reich

Senior Director of Digital Transformation
Worthington Steel

www.worthingtonsteel.com

https://www.linkedin.com/in/andy-reich-673bb7126/

Aaron Schoonbaert

COO
Price Industries

https://www.priceindustries.com/

https://www.linkedin.com/in/aaron-schoonbaert-7438326/

Keith Sinram

Senior Vice President
Crown Equipment Corporation

https://www.crown.com/en-us.html

https://www.linkedin.com/in/sinram/

Learn how you can join the MLC here:

MLC’s Digital Leadership survey finds that while more organizations have restructured to build an M4.0 advantage, organizational readiness continues to lag.  

KEY TAKEAWAYS:
● Digital manufacturing leaders need to build traditional leadership qualities with new skills such as fostering a data-driven culture and guiding the workforce through change.
● Despite progress in creating digital strategies, many manufacturers lack formal training programs for upskilling their workforce, and many feel that leadership is unprepared for the future.
● Effective digital leadership is characterized by collaboration both internally and externally, while successfully building and navigating digital ecosystems.  

While there are many tried-and-true qualities of good leadership that stand the test of time – innovation, integrity, confidence – the additional skills required of digital manufacturing leaders have evolved just like the technologies giving rise to Manufacturing 4.0.

Today’s operational leaders need an eye toward building data-driven business cultures and decision-making; the ability to collaborate with teams both inside and outside of their organization; the skill to help their teams adapt in times of change; and much more. There are also more traditional leadership skills that look different than they used to; for example, continuous improvement in a digital ecosystem, and a focus on upskilling the workforce on new technologies and methodologies.

The Manufacturing Leadership Council’s 2024 Digital Leadership survey reveals that while organizational structures are adjusting to the needs for digital manufacturing, there are still gaps to address for full business readiness.

Section 1: The Organizational Motto: Be (Mostly) Prepared

Anyone who has been involved with a scouting organization in their youth is likely to recall the famous motto: “Be Prepared.” It seems that more digital manufacturing leaders, as well as their organizations, are (mostly) coming around to this motto as good advice. But at the same time, more than half of manufacturers are not offering any formal digital training to educate or upskill the workforce and leadership (Chart 3), and 88% of respondents feel that their company’s future has at least some future vulnerability due to its current digital transformation preparedness (Chart 5).

Meanwhile, more organizations have created a change management strategy around digital transformation (Chart 1) and/or have restructured or redesigned themselves to better manage digitalization (Chart 2). But understanding the digital roles and skills that will be required by the future manufacturing enterprise is only somewhat understood by most (Chart 4.)

1. Most Have a Change Management Strategy in Place

Q: Has your leadership team created an organizational change management strategy to help support its digital strategy? (Select one)

2. Organizations are Restructuring Around Digital

Q: As part of its digital transformation work, has your company undertaken organizational redesign to better manage the impact of digitalization? (Select one)

3. Still, Formal Training Programs are Lacking

Q: Does your company have a formal training plan to educate workers and leadership around the requirements of digital transformation? (Select one)

4. Future Roles and Skills Needs Only Somewhat Understood

Q: How well prepared do you think your company is in understanding the new digital roles and skills that you will need in the next few years? (Select one)  

5. Current Levels of Digital Readiness Create Vulnerabilities

Q: How vulnerable will your company’s future success be as a direct result of your company’s current level of digital transformation preparedness? (Select one)

Section 2: Digital Leadership is a Team Sport

As technology enables individuals and teams to become more connected both internally and to external customers and partners, the ability to collaborate is key. So too is it key among leadership teams, as leaders need to understand the impact that digital investment and deployment will have on different areas of the enterprise. The top response for “who is in charge” for digital transformation efforts was that it is a collaborative effort (Chart 6). It’s likely a positive sign that most respondents — 85% — rates their leadership teams as either “highly” or “somewhat” collaborative (Chart 8).

Perhaps unsurprisingly, executive management teams most frequently want to know the value of digital investments – the business case for them, and what specific use cases will bring the most bang for the buck (Chart 7).  But only 23% rate their executives as “very prepared” to lead and manage digital transformation (Chart 9).

6. Leadership is Most Often Collaborative

Q: Who is leading the charge around the digital transformation efforts in your organization?

7. Executives Most Often Want to Know Business Value

Q: What is the most important thing your company’s executive management team wants to know about digital transformation? (Select top 3)

8. Cross-Organizational Leaders Collaborate on Strategy

Q: How collaborative is your leadership team across multiple areas of the organization in the development and assessment of its digital strategy? (Select one)  

9. Executive Management is Only Somewhat Prepared for Digital Transformation

Q: How prepared do you think your company’s executive management team is to lead and manage digital transformation? (Select one)

Section 3: The Meaning of Leadership in the M4.0 Era

When asked which statements best describe an M4.0 leader, ecosystem-based external and internal collaboration once again came up as a key theme, along with understanding technology integration and creating an information-driven culture (Chart 10). Additionally, most respondents — 74% — believe that digital operations require a substantially different approach and skill set for leaders (Chart 11).

As for the skills and abilities that respondents believe are most important, the highest degree of importance was placed on using digital technology to reduce costs and improve efficiency, followed by the willingness and ability to rethink traditional business to successfully embrace a digital model (Chart 13).

In business, the definition of a good leader has been and will continue to be one who inspires and brings out the best in others, in addition to making smart business decisions to bring about success. Technology is a burgeoning part of the play, but those individuals who dare to act as visionaries in creating winning strategies will continue to be the ones who find success.  N

10. Leaders Must Navigate Digital Ecosystems and Understand Digital Integration

Q: Which statements best describe what leadership means in the digital era? (Select top 3)

11. Digital-Era Leadership Requires a Substantially Different Approach

Q: Do you agree or disagree with this statement: The emergence of digitally driven operations and business models will require a substantially different approach and set of skills on the part of manufacturing company leadership. (Select one)

12. Digital Acumen, Building a Data-Driven Culture Most Important for Leaders

Q: Which leadership approaches do you feel are most important in the digital era? (Select top 3)

13. Most Important Skills: Reimagined Business Models; Successful Technology Deployment

Q: Looking ahead, what degree of importance would you assign to the following digital leadership skills and abilities? (Rate each on scale of Low/Medium/High)

About the author:

Penelope Brown Senior Content Director, Manufacturing Leadership Council

If you’re looking for insights on digital transformation, cultural change and what’s ahead for manufacturing, it pays to consult an industry leader. Dan Dwight, president and CEO of Cooley Group, fits the bill.

Dwight was named the 2024 Manufacturing Leader of the Year in the Manufacturing Leadership Awards, presented by the Manufacturing Leadership Council, the digital transformation division of the NAM. Additionally, Cooley Group won the Small/Medium Enterprise Manufacturer of the Year and the Manufacturing in 2030 Award.

Recently, Dwight sat down for an Executive Dialogue interview with the Manufacturing Leadership Journal to share his secrets to success. Below are excerpts from the interview.

What leaders need: When asked what qualities manufacturing leaders need in the digital era, Dwight says that they must be willing to undergo big changes, but must also keep their teams in the loop. 

• “Successful leadership in the digital era demands, among other things, a higher level of transparency,” he explained. “Your team needs to see the road map in front of them because successful and sweeping transformations are extremely time consuming with a lot of jagged edges that the leadership team needs to address.”

How cultures should change: As for the wider cultural changes that will help a company through its digital transformation, resiliency and adaptability are crucial, Dwight said.

• “Cooley’s digital transformation began with a cultural transformation built around becoming more agile and adaptable,” he noted. “Every decision we make places long-term resiliency and cross-functional collaboration as our operational North Star.”
• “Cooley decentralized our decision-making structures, eliminating hierarchal instruction and empowering team members to communicate transparently and more frequently,” he added.

Small manufacturers’ advantage: When asked whether small and medium-sized manufacturers are at a disadvantage in the era of digital transformation, Dwight says that Cooley has turned its small size into an asset.

• “Our longevity is built on using our size to our advantage. We are more resilient, more agile, more adaptable than our competitors who are often [much larger] because we constantly invest in pro-growth strategies regardless of the economic environment,” he explained.
• “Our investments in innovation generate consistent new product revenue of over 20%, and our investments in Manufacturing 4.0 digitization generate consistent, robust productivity dividends,” Dwight added.

What’s next? Cooley Group is looking ahead to further transformations, including in supply chain management, Dwight said.

• “Our business architecture and change management team leaders are working within their respective teams across the organization to build into our processes a more outward-looking focus,” he said.
• “For example, our M4.0 implementation leader has added supply chain resiliency to her leadership responsibilities. Her team seeks to build out Cooley’s end-to-end business resilience.”

MLC in action: Dwight says that Cooley Group has always been able to count on the MLC to find the insights that it needs for digital transformation and its Manufacturing 4.0 journey. As he put it recently, “When challenges do arise, the MLC can help us think through what the future might look like.”

Watch a full video of this interview for more insights.

Manufacturers are deluged by data. As companies adopt more advanced technologies, they are increasingly overwhelmed by the quantities of raw data that must be collected, analyzed and put to use.

Indeed, a new survey from the Manufacturing Leadership Council—the NAM’s digital transformation arm—reveals that 70% of manufacturers still collect data manually. Here are some highlights from the survey, which reveals where manufacturers need to improve, and how they’re planning to do it.

Exponential data growth: While the survey’s respondents report an explosion of new data, they also expect to keep on top of it over the next few years.

• Forty-four percent of manufacturing leaders have seen at least a doubling of the amount of data they collect in their organization today compared to two years ago.
• While many manufacturers still lack standardized data due to operating a mix of older equipment and systems along with newer technologies, more than half expect that their data will be in a standardized format by 2030.

Analytical improvements: How are manufacturers planning to use all this new data?

• Nearly 60% of respondents say they are focused on understanding their operations with an eye toward optimizing them in the future.
• While 30% of manufacturers say they are using manufacturing data to predict operational performance, another 60% say that predictivity will be a primary objective by 2030.

Better decisions: Manufacturers use data to make better, more proactive decisions, according to the survey. Today, these decisions are made at a relatively high level.

• Seventy-seven percent of respondents said that the responsibility to employ data in decision-making falls to plant leaders and managers.
• Only 33% said that factory floor employees held that responsibility—a percentage that might grow as manufacturers seek to empower frontline employees with greater decision-making ability.

Looking ahead: As artificial intelligence and other emerging digital technologies become more established, they will likely reshape many if not all aspects of manufacturing operations.

• Thanks to advanced sensors and robust data networks connecting equipment and machinery, manufacturers will collect copious data in real time and act on it almost as swiftly.

Read more: To get a deeper look at the current state of data mastery in manufacturing, download the full survey, Data Mastery: A Key to Industrial Competitiveness.

Manufacturers are deluged by data. As companies adopt more advanced technologies, they are increasingly overwhelmed by the quantities of raw data that must be collected, analyzed and put to use.

Indeed, a new survey from the Manufacturing Leadership Council—the NAM’s digital transformation arm—reveals that 70% of manufacturers still collect data manually. Here are some highlights from the survey, which reveals where manufacturers need to improve, and how they’re planning to do it.

Exponential data growth: While the survey’s respondents report an explosion of new data, they also expect to keep on top of it over the next few years.

• Forty-four percent of manufacturing leaders have seen at least a doubling of the amount of data they collect in their organization today compared to two years ago.
• While many manufacturers still lack standardized data due to operating a mix of older equipment and systems along with newer technologies, more than half expect that their data will be in a standardized format by 2030.

Analytical improvements: How are manufacturers planning to use all this new data?

• Nearly 60% of respondents say they are focused on understanding their operations with an eye toward optimizing them in the future.
• While 30% of manufacturers say they are using manufacturing data to predict operational performance, another 60% say that predictivity will be a primary objective by 2030.

Better decisions: Manufacturers use data to make better, more proactive decisions, according to the survey. Today, these decisions are made at a relatively high level.

• Seventy-seven percent of respondents said that the responsibility to employ data in decision-making falls to plant leaders and managers.
• Only 33% said that factory floor employees held that responsibility—a percentage that might grow as manufacturers seek to empower frontline employees with greater decision-making ability.

Looking ahead: As artificial intelligence and other emerging digital technologies become more established, they will likely reshape many if not all aspects of manufacturing operations.

• Thanks to advanced sensors and robust data networks connecting equipment and machinery, manufacturers will collect copious data in real time and act on it almost as swiftly.

Read more: To get a deeper look at the current state of data mastery in manufacturing, download the full survey, Data Mastery: A Key to Industrial Competitiveness.

Manufacturers are deluged by data. As companies adopt more advanced technologies, they are increasingly overwhelmed by the quantities of raw data that must be collected, analyzed and put to use.

Indeed, a new survey from the Manufacturing Leadership Council—the NAM’s digital transformation arm—reveals that 70% of manufacturers still collect data manually. Here are some highlights from the survey, which reveals where manufacturers need to improve, and how they’re planning to do it.

Exponential data growth: While the survey’s respondents report an explosion of new data, they also expect to keep on top of it over the next few years.

• Forty-four percent of manufacturing leaders have seen at least a doubling of the amount of data they collect in their organization today compared to two years ago.
• While many manufacturers still lack standardized data due to operating a mix of older equipment and systems along with newer technologies, more than half expect that their data will be in a standardized format by 2030.

Analytical improvements: How are manufacturers planning to use all this new data?

• Nearly 60% of respondents say they are focused on understanding their operations with an eye toward optimizing them in the future.
• While 30% of manufacturers say they are using manufacturing data to predict operational performance, another 60% say that predictivity will be a primary objective by 2030.

Better decisions: Manufacturers use data to make better, more proactive decisions, according to the survey. Today, these decisions are made at a relatively high level.

• Seventy-seven percent of respondents said that the responsibility to employ data in decision-making falls to plant leaders and managers.
• Only 33% said that factory floor employees held that responsibility—a percentage that might grow as manufacturers seek to empower frontline employees with greater decision-making ability.

Looking ahead: As artificial intelligence and other emerging digital technologies become more established, they will likely reshape many if not all aspects of manufacturing operations.

• Thanks to advanced sensors and robust data networks connecting equipment and machinery, manufacturers will collect copious data in real time and act on it almost as swiftly.

Read more: To get a deeper look at the current state of data mastery in manufacturing, download the full survey, Data Mastery: A Key to Industrial Competitiveness.

Washington, D.C. – The Manufacturing Leadership Council, the digital transformation division of the National Association of Manufacturers, has announced the election of Dow Global Operations Director for Operational Excellence and Leveraged Services Tim O’Neal and PIC Trailers President Bryan Van Itallie to the MLC’s Board of Governors. The MLC is the nation’s leading networking and executive leadership organization dedicated to digital transformation in manufacturing by focusing on the technological, organizational and leadership dimensions of change.

O’Neal is responsible for improving the performance of people and processes through continuous learning, professional development, effective teams and cost-effective implementations. He also leads strategic initiatives for operations, including digital strategy. He has been with Dow for 23 years and has lead initiatives in environmental, health, safety and sustainability; supply chain; R&D; logistics; and operations IT technology.

Van Itallie leads all aspects of PIC’s business and has led development of a new, metrics-driven vision, mission, core values and strategic plan for the company. He has increased the company’s monthly revenue; developed and launched new intermodal chassis; spearheaded a company culture transformation; and improved talent development and management to better align employee skills.

“The addition of Tim and Bryan brings robust skill sets and deep experience to the MLC board, and we welcome their fresh perspectives,” said Cooley Group President and CEO and MLC Board of Governors Chairman Dan Dwight. “Collaborations like these are essential not only for strengthening the MLC, but also for improving the industry’s future.”

“The MLC is fortunate to have a dedicated group of industry experts to guide and shape our mission as manufacturing’s digital landscape continues to evolve,” said MLC Founder, Executive Director and Vice President David R. Brousell. “These new additions further enhance the depth and breadth of knowledge on our board and solidify our position as an organization that is at the forefront of digital manufacturing.”

As an advisory body, the MLC Board of Governors provides guidance to the MLC on its annual Critical Issues agenda, research studies and programs and services for the MLC membership.

-About the MLC-

Founded in 2008 and now a division of the National Association of Manufacturers, the Manufacturing Leadership Council’s mission is to help manufacturing companies transition to the digital model of manufacturing by focusing on the technological, organizational and leadership dimensions of change. With more than 2,500 senior-level members from many of the world’s leading manufacturing companies, the MLC focuses on the intersection of advanced digital technologies and the business, identifying growth and improvement opportunities in the operation, organization and leadership of manufacturing enterprises as they pursue their journeys to Manufacturing 4.0.

Nearly 30 years ago, in a Seattle-area garage, Jeff Bezos and the few employees of his upstart online retailer, Amazon, knelt on the floor to pack customer orders into boxes. One evening, Bezos suggested ordering kneepads to make the work more comfortable. One of his workers respectfully disagreed and suggested they order packing tables instead – an option that proved to be better for worker satisfaction and throughput. This early example of centering durable needs, rather than immediate or short-term needs, exemplifies the culture of innovation that now permeates Amazon.

During MLC’s sold-out tour of Amazon’s BFI4 Fulfillment Center cohosted by Amazon Business and Amazon Web Services, participants got a behind-the-scenes look at how the company sorts and packages thousands of items per day for delivery to customers. The tour also provided insights into Amazon’s approach to data, supply chain and procurement, offering a deep dive into the progression of the company’s culture from its early days.

During his presentation on the culture of innovation, Clint Schneider, Amazon Web Services’ Digital Innovation Lead for Smart Factories, shared how culture, mechanisms, architecture and organization lead to better innovation. Schneider explained how Amazon’s decision-making process uses the concept of “one-way” or “two-way” doors to make high-quality, high-velocity decisions. A one-way door represents a significant decision like should Amazon build a new facility, while a two-way door represents something less critical, like changing the buy button’s color.

Using the one-way versus two-way door analysis helps the company innovate faster with a bias for action. If it is a two-way door, they know they do not have to deliberate as long. Instead, they can run the experiment and move back through the door to adjust or revert if the decision does not produce the intended results and ROI.

Automation and Innovation at Amazon’s BFI4 Fulfillment Center

“This is what we manufacture,” Julius Yu, General Manager of Amazon’s BFI4 Fulfillment Center shares as he holds one of the thousands of packed boxes filled with a customer’s order that move by the MLC tour group as they walk through the facility. “Everything we manufacture here is unique.”

BFI4 handles millions of units per week, each with a distinct mix of “parts” that are sorted, picked, packed, inspected, sealed, labeled and distributed for delivery. BFI4 is Amazon’s eighth iteration of an Amazon robotics fulfillment center. In total, BFI4 has thousands of mobile robots storing and transporting products between stations where they are manually sorted for storage then picked and packed for delivery.
At the sort station, employees put items into random bins for storage until a customer orders the product. Using a vision system, a camera takes a picture of where the item has been randomly placed so that it can be retrieved and transported via AMR to the pick station when ordered.

After the product is ordered and delivered to the pick station, a control panel tells employees where it is located on the rack so they can move it into a bin to be packed into a customer’s box. Computer vision verifies the number of items in each bin, taking pictures to ensure accuracy.

Harnessing Data to Improve Efficiency

Data, data management, and data contextualization are integral to operations at BFI4. The company generates terabytes of data to ensure end-to-end transparency. Machine learning helps determine which fulfillment center or distribution center across the country should house each product, using historical ordering patterns with about 60% accuracy. These determinations help to improve delivery speeds, and have resulted in more efficient delivery routes. While machine learning hasn’t helped Amazon achieve 100% accuracy yet, Yu is optimistic that advancements in technology, computing power and artificial intelligence will improve precision.

One notable innovation using data is a custom box maker. For orders that include a single item, Amazon’s machine will custom cut cardboard to create a shipping box. The custom box maker relies on product data to determine the correct size of the box so that it can fit snug around the product. The downstream benefits are significant. The company can fit more boxes into trucks, for example, which is a positive for both sustainability and throughput.

An Immersive Amazon Experience

Participants enjoyed a networking reception the evening prior to the tour featuring entertainment by Washington-based 2019 American Idol contestant Kazmyn, food options from local vendors, and a trip to Amazon’s iconic Banana Stand – all hosted in Amazon’s Spheres, an innovative coworking space. The reception gave participants an opportunity to network with fellow tour participants and Amazon ambassadors while immersed in a unique Amazon workspace ecosystem.

Following the tour, attendees engaged with a panel of Amazon experts including Julius Yu, Brian Steward (Director of Worldwide Amazon Business Operations), and Mobeen Khan (Director, Global Business Development and Partnerships), facilitated by MLC’s Senior Content Director, Penelope Brown. The panelists addressed questions about the BFI4 facility, data, culture, safety and Amazon’s processes.

The Amazon tour experience concluded with a session titled “Manufacturing at Amazon: The Future, Faster, Together,” covering three pillars for manufacturing’s future: data as a foundation, AWS supply chain, and strategic procurement.

For participants, the tour proved to be a fascinating opportunity to see how far Amazon has come since those earliest days when employees packed customer orders in a garage and where the company’s culture of innovation may lead it in the future.

As part of its accelerated digitalization journey, Celanese has developed a generative AI chatbot to serve as a user-friendly interface to its Digital Twin.

TAKEAWAYS:
● Digital transformation requires getting the data into the hands of experts who will build, deploy, and scale hundreds of use cases.
● A generative AI chatbot can function as an everyday manufacturing assistant to support those use cases.
● Celanese’s digital platform and standardized knowledge graph, supported by its AI chatbot Celia, is already reaping returns in multiple areas, from troubleshooting and production performance to improved decision making.  

Celanese is on a journey to transform its manufacturing processes into autonomous, integrated, and optimized digital plants — and at the heart of it is a user-friendly, generative AI-powered chatbot named Celia. Think of Celia as a copilot that can integrate into workflows and provide real-time suggestions, explanations, and feedback during industrial processes to users in easily understandable, native language. Celia retrieves that information it’s providing through its connection to the unified digital platform and its comprehensive knowledge graph.

Celia was put in place to provide a synergy between users and generative AI models that will enhance the quality and accuracy of results and foster faster, more informed decision making. Celanese believes its digital transformation is an ongoing journey to put data into the hands of experts who will build, deploy, and scale hundreds of use cases.

With the digital platform that Celanese is using and its ability to scale, the Celia copilot is designed to function as an everyday manufacturing assistant to the company’s manufacturing operations personnel by supporting use cases including incident management, real-time process plant optimization, automatic EIP isolations, connected worker, asset performance management, incident management, and real-time process optimization.

While the project is a work in progress, Celanese, a global manufacturer of special materials and chemical products used in most major industries and consumer applications, has realized real value … and it’s just getting started.

Project Evolution

Celia is the latest development in the company’s accelerated digitalization journey. The journey started with replicating each actual physical asset at its Clear Lake, Texas, manufacturing site in a pilot in May 2022. The digital twin foundation scale was then implemented at 30 sites in 2023. While this is a technological development, it has always been centered around designing solutions for real people that go beyond being just user-friendly interfaces to constituting repeatable processes that leverage design principles and human insights to address future opportunities.

The digital twin implementation alone was a leap forward in troubleshooting, collaboration, historical data tracking and trending, and improved compliance, among other benefits.

“Think of Celia as a copilot that can seamlessly integrate into workflows and provide real-time suggestions, explanations, and feedback.”

Keeping with that human-centric focus, Celia was launched in the fall of 2023 to drive value, insights, and further enhancements to production, processes, and people engagement. Celia’s detailed industrial knowledge graph spans more than 30 manufacturing sites and integrates operational, engineering, and process data to provide a complete digital representation it can use to understand and optimize operations.

With the rollout of Celia across many of its manufacturing sites, Celanese has already successfully improved visibility, collaboration, provided instantaneous insights on troubleshooting and production performance, provided results of forecasts/predictions alongside AI/ML, improved decision making, and reduced time spent on data discovery and analysis.

Transforming Workflows, Reducing Downtimes

In less than a year since launch, Celia has equipped employees with contextualized information at their fingertips. For example, the AI chatbot has leveraged the knowledge graph to transform workflows for operators by enabling tasks such as operator rounds being executed more efficiently. Celia has also provided troubleshooting insights that connect maintenance notifications and work orders, maintenance instructions, operator manuals and standard operating procedures that help advise operators and maintenance staff with recommended actions to take.

Celia has also eliminated energy accounting and billing errors by generating real-time insights into internal operational factors, as well as integrating to external energy prices. Compliance and audits have benefitted from Celia comparing site policies and procedures to corporate policy procedures and generating gap closure actions in just minutes (compared to what previously took days), rather than the time and effort it took to manually do these comparisons to support gap assessments and develop action plans.

“Celia has already provided employees with contextualized information at their fingertips.”

Catalyst inventory management is also reaping benefits with Celia. The AI chatbot now can digitally track, estimate, and inspect the company’s precious metal inventory across manufacturing sites, including incoming and outgoing shipments between the warehouse, vendors, and operating units. Digitally accounting for the inventory enables Celanese to continuously update its estimates of price, amounts and quality — and helps to reduce total amount of inventory.

Lastly, troubleshooting is more efficient with Celia. Celanese has successfully used it to optimize performance at one of its largest facilities by providing anomalies in real-time price forecasting and insights that enabled the company to make decisions on managing downtime that resulted in cost avoidance.

Innovating for the Future

Many tactical approaches focus too much on the discrete business solutions at hand instead of strategically architecting to solve current challenges, while also unlocking subsequent business solutions. Celanese wanted to shift to a platform architecture that would enable an open solution development acceleration model, allowing the company to leverage AI/ML and generative AI at scale to drive value.

The opportunities for future uses of generative AI to create repeatable, optimized, and autonomous digital solutions continue to be explored by Celanese for its chemical and specialty materials manufacturing facilities globally.  M

COMPANY FACT FILE
Name: Celanese Corporation
Sector: Specialty materials and chemical products
Global HQ location: Irving, Texas
Revenues: 2023 net sales of $10.9 billion
Employees: 12,400
Web url: http://www.celanese.com

About the authors:

Sue Pelletier is a contributing editor with the Manufacturing Leadership Journal.