COVID has instigated a host of strategic and tactical changes in manufacturing which will be permanent features of the industrial landscape for years to come, rewriting leadership’s playbook and redefining the rules of competition.

The fallout of COVID-19 has affected many aspects of the manufacturing industry  over the past year, but one of the most significant has been a heightened urgency about adopting Manufacturing 4.0 technologies and techniques to deal with what was and continues to be unprecedented business disruption.

Many manufacturing executives acknowledge that the equivalent of several years’ change has been compressed into the past year. Companies had to respond quickly to the pandemic crisis, adapting production environments, standing up new health and safety protocols, enabling more front-line workers to do their jobs remotely, and, in some cases, pivoting to produce products, such as life-saving ventilators and masks, that they had never produced before.

A key ally enabling such rapid change, many found out, was M4.0 digitization. Those that had already embraced the digital model had an easier time adapting; those that did not had greater difficulty.

For manufacturing leadership, the time has been both a test and an opportunity. Leaders have had to deal with the daily stress of keeping the business running, making sure employees were safe and engaged, and reacting to often unpredictable changes in demand. But they have also been able to arrive at a broader view of what’s possible. Now, executives across the industry are in the process of deciding what COVID-compelled changes may take root in their companies and which may not.

The Manufacturing Leadership Council’s new research survey on Next-Generation Leadership and the Changing Workforce, one of MLC’s Critical Issues facing the industry, sheds considerable light on what COVID-related changes are top of mind for leaders, how leaders are thinking about their role in the digital era, what knowledge and expertise will be needed in the future, and what key challenges they envision along the way.

New disaster preparedness, resiliency, and remote working strategies will become permanent features of manufacturing leadership’s playbook.

The Effects of COVID

MLC research over the past year has clearly documented that manufacturers want to accelerate their adoption and use of M4.0 as a direct result of the pandemic. The new Next-Generation Leadership survey reveals the implications of this tighter embrace.

A solid majority of the new survey’s respondents, 54.8%, confirm that COVID-19 has increased management’s focus on digital transformation (chart 1). New procedures for remote working by leadership teams and employees, new disaster preparedness and resiliency strategies, and more cross-functional organizational structures are among the most significant implications cited by survey respondents (chart 2).

But when asked whether these and other management strategies and tactics will end up being permanent elements in leadership’s playbook going forward or just temporary, a result extraordinary in the annals of MLC research occurred.

Powerful majorities said that most of the changes they were asked about will become permanent elements of their leadership approach. For example, 68.2% said that new disaster preparedness plans, resiliency strategies, and response teams will become permanent features in their companies. Likewise, 57.3% said that more collaborative, cross-functional organizational structures will take root. And 62.2% expect that remote working by both leadership teams and employees will continue (Chart 3).

Defining Leadership 

As these changes take place, the definition of what operational leadership means in the digital era is becoming more deeply engraved in that metaphorical playbook.

In the new survey, 75% of respondents say that establishing a fact-based, information-driven culture of decision-making in their organizations is the statement which best describes what leadership means in the M4.0 era. This finding is up six points from 2020’s survey.

The two other statements which received the highest responses (survey takers were asked to rank their top three choices from a list of seven options) are: having the skills to orchestrate employees, customers, and business partners in a digitally driven, collaborative business ecosystem, at 55.5%, and understanding what it means to fully integrate digital technology in order to operate the business, at 54.1% (chart 4).

Notable, though, is the finding on aggressively adopting advanced IT and operational technologies. This year, the percentage of respondents citing this statement leapt 11 points to 29.1% of the sample compared to 2020, an increase which may reflect the desired acceleration of M4.0 as a result of the pandemic.

“Establishing a fact-based, information-driven culture of decision-making is once again the most popular definition of what leadership means in the M4.0 era.”

And when it comes to new skills that will be important for the digital era, survey respondents have reinforced the message about culture and collaboration by citing data analysis skills, understanding how to use digital technologies to advance manufacturing, and working in a collaborative environment as key areas of development (chart 5).

Perhaps as a result of the amount of change that has occurred in the past year, manufacturing executives are feeling somewhat better about how well prepared they and their teams are to manage the journey to M4.0.

The percentage of leaders who indicate they are not prepared for the journey has dropped nearly five points in this year’s survey, to 15.2% of the sample, while the percentage of those who have some degree of preparedness has rise slightly over last year (chart 7). For those who still feel that they are not prepared, the most cited reason, by 29.1%, is that they are simply not sure how M4.0 applies to their particular business (chart 8).

Nevertheless, perceptions about how vulnerable their company’s future success might be as a result of their level of M4.0 preparedness remain a mixed bag, with the percentage of those feeling very vulnerable rising to 15.2% of respondents this year, compared with eight percent in 2020, and those not feeling vulnerable at all dropping to 6.9%, from 12% last year (chart 9).

Desired Knowledge and Expertise 

Looking ahead, what do manufacturing executives say are the most important leadership skills and abilities they feel they must develop to be successful with M4.0?

This year, once again survey respondents attach the highest degree of importance to the ability to rethink the business and successfully embrace the digital model. Even though the percentage of those indicating a high degree of importance to this ability dropped nearly six points from 2020, to 66.1% this year, this ability remains far ahead of other factors such as reducing costs and process integration. (chart 11).

“For manufacturing leadership, the past year has been an unprecedented test. But it has also been a time for more expansive thinking about what’s possible.”

And when it comes to a variety of technologies with which they feel they need to develop knowledge and expertise, this year’s survey findings strongly mirror last year’s results. For example, this year manufacturing executives once again attach a high level of emphasis to developing expertise around cybersecurity, advanced data analytics, and simulation and modeling (chart 12).

The quest for knowledge and expertise will play out against a backdrop of demographic and organizational challenges that will reverberate deeply in manufacturing companies.

The Challenges Ahead

As baby boomers retire, companies grapple with the persistent open job problem, and as they seek to understand what functions and skills they will need in an increasingly digital-influenced workforce, many manufacturers executives today see the primary source of next-generation leaders coming from their internal ranks.

But this year’s finding of 45.5% of respondents citing internal sources dropped nearly five points from last year’s survey, with a modest shift occurring in favor of finding talent elsewhere in the manufacturing industry. Fully one-third of respondents this year said they would be looking within the industry for talent. Only a fraction, 13.2%, expect to be sourcing candidates from other industries (chart 13).

These number could shift, of course, as manufacturers attain a greater understanding of what functions and skills they will need in the future. Today, only a fraction of survey takers, 7.4%, indicate they have a solid understanding of the new digital roles and skills they will need. About 65%, however, say these requirements are somewhat understood, up several points from last year, an encouraging sign. But where there is substantial headroom for improvement is in training. Only 22.3% of survey takers this year indicate they have formal training programs in place to educate workers and leadership about the requirements of M4.0 (charts 15,16).

As they work out these issues, leaders today will also be grappling with the structure within which people will work, a structure which has been slowly but inexorably changing over the years to a flatter, more collaborative model of working. In this year’s survey, nearly half of survey respondents, 48.5%, identified understanding how the company should be organized as a result of new technologies as a key challenge for leadership, a finding up a whopping 23 points from last year. No doubt this finding has been flavored by the pandemic experience as more people have had to work remotely, but the effects of M4.0 technologies in empowering more people with information and thereby changing decision-making processes may also be a mounting factor (chart 14).

The effects of M4.0 technologies will also have an impact on workforce size, as a significant number of manufacturers are looking at automation and advanced M4.0 technologies as ways to address the open jobs problem. This year, 41.7% of respondents said these technologies will help offset the difficulty in filling open jobs, up from 36% last year.

What the Future May Hold

As historians have pointed out, sometimes great crises give rise to new and better ways of doing things, enabling progress. The heightened sense of urgency in created digitally-powered agility as a result of the pandemic has fostered a broad set of strategic and tactical changes across manufacturing, all adding up to an opportunity to redraw the boundaries of what was thought possible.

Now, manufacturing leadership has the responsibility to see these changes through. If they are successful in doing so, they will take the industry to a new and better level, raising the bar for all and redefining the rules of competition.   M

Part 1: COVID-19 Impact

1. A Majority Says COVID Has Increased Focus on M4.0

Q: What impact has COVID-19 had on your leadership team’s focus on digital / M4.0 transformation? (select one)

2. Remote Working, Resiliency Top List of COVID-Related Changes

Q: What impact has COVID-19 had on your leadership approaches to managing your manufacturing enterprise? (rank each category)

3. Solid Majorities Say Many Changes Will Be Permanent

Q: How long do you expect these new leadership approaches to continue? (rank each category)

Part 2: Defining the Leadership Role

4. Once Again, Building a Fact-Based Culture is Top Leadership Definition

Q: Which statement best describes what leadership means in the Manufacturing 4.0 era? (Rank top 3)

5. Data Orientation, Digital Acumen Lead Desired Skills

Q: Which new approaches and skills do you feel will be most important for the M4.0 era? (Rank top 3)

6. The M4.0 Business Case Remains Key Question

Q: What’s the most important thing your company’s executive management team wants to know about M4.0? (Select one)

7. Slight Improvement in M4.0 Preparedness

Q:How prepared do you think your company’s executive management team is to lead and manage the journey to M4.0? (Select one)

8. M4.0 Applicability is Key Issue in Preparedness

Q: If your company’s executive management is not well prepared for M4.0, what is the most important reason for the lack of preparedness? (Select one)

9. Perceptions of M4.0 Vulnerability Rise

Q: How vulnerable will your company’s future success be as a direct result of your company’s current level of M4.0 preparedness? (Select one)

10. M4.0 is Largely a Collaborative Effort

Q: Who is leading the charge around your digital
transformation efforts in your organization? (Select one)

Part 3:  Developing Knowledge and Expertise

11. Rethinking the Business is Key M4.0 Skill

Q: Looking ahead, what degree of importance would you assign to the following M4.0 leadership skills and abilities? (Rate each on scale of Low/Medium/High

12. Cyber, Analytics Top List of Desired Knowledge

Q: Looking ahead, what degree of emphasis would you place on the following technology areas in terms of developing knowledge and expertise? (Rate each on scale of Low/Medium/High)

Part 4: Assessing Leadership Challenges

13. Most See Next Gen Leaders Sourced Internally

Q:Where do you see the next generation of leaders coming from for your company? (Select one)

14. M4.0 Organizational Impact is Top Challenge

Q: In thinking about the requirements and implications of M4.0, what do you think are the most important challenges for leadership? (Rank top 3)

Part 4: Workforce Development and Transition

15. Understanding Digital Skills Makes Little Progress

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)

16. Vast Majority Still Without Formal M4.0 Training

Q: Does your company have a formal training plan to educate workers and leadership around the requirements of Manufacturing 4.0?

17. Automation Seen as an Open Jobs Remediator

Q: What impact do you think the increasing adoption of automation and advanced M4.0 technologies will have on workforce levels in your company in the future? (Select one)

Survey development was led by David R. Brousell, with input from the MLC editorial team and the MLC’s Board of Governors.

The pandemic has spurred a paradigm shift in cultural transformation as manufacturing companies have leveraged M4.0 to accelerate digital adoption, collaboration, innovation, and integration across their enterprises, reveals the Manufacturing Leadership Council’s latest M4.0 Cultures survey.    

By Sue Pelletier

It’s undeniable that the COVID-19 pandemic has caused massive disruption  in the manufacturing environment over the past year. Supply chain disruption, already a growing problem pre-pandemic, became more acute as different areas of the world shut down to slow the spread of the virus. Some manufacturers pivoted to retool their factories to supply much-needed personal protective equipment (PPE) and other COVID-necessitated supplies, while others struggled to keep shop floor workers safe and learned on the fly how to manage employees who suddenly had to work remotely.

The impact on manufacturing cultures has been significant. The results of the Manufacturing Research Council’s latest M4.0 Cultures survey reveal that the abrupt shifts and continued disruptions of the COVID-19 crisis have driven leaders to sharpen their focus on M4.0 and accelerate adoption across everything from enterprise connectivity and corporate collaboration, to functional integration and innovation, and to start redefining what health and safety should mean for their employees in the future.

What’s more, while some of the workforce cultural changes, such as PPE and masking for front-line employees, may be temporary, the survey results clearly indicate that a major shift toward an M4.0 culture that is digitally enabled, collaborative, innovative, and data-driven is not only underway more rapidly than ever before, but is also here to stay.

There will continue to be a few bumps in the road ahead, of course. While corporate cultures are increasingly becoming more customer-centric and collaborative, the journey toward M4.0 is still a work in progress for many companies as concerns about the costs and ROI of M4.0 transformation, along with getting full buy-in from both employees and leadership, stubbornly continue to impede the progress of cultural changes. But it is clear that the COVID viral firestorm has made manufacturers acutely aware of the need to continue along that M4.0 journey. With many saying the recent changes in their corporate culture will now be permanent, it’s clear that they are already beginning to see the results, from improved morale and a more efficient workforce, to more productive and innovative operations. And those are exactly the kinds of benefits that will spur them to continue to overcome any remaining hurdles.

“Manufacturers now believe that the M4.0 paradigm shift that has accelerated over the past year has led to permanent changes that will have a lasting impact on their organizations for many years to come.”

Culture Change Accelerates During COVID 

While it might be expected that the pandemic’s disruptions could have slowed the adoption of digital M4.0 plans, that turned out not to be the case. As leadership teams have intensified their focus on M4.0 over the past year (Chart 2), more than half said they have accelerated both enterprise connectivity and M4.0 technology adoption since COVID-19 hit (Chart 1). Corporate collaboration initiatives also sped up for more than 50% of companies, with ramped up functional integration strategies and faster innovation processes also reported by more than 40% of survey respondents.

While COVID has clearly had a significant impact on many areas of corporate culture, one of the key takeaways from the survey is that these are not quick fixes to patch operations until the crisis passes. The results make it clear that manufacturers now believe that the M4.0 paradigm shift that has accelerated over the past year has led to permanent changes that will have a lasting impact on their organizations for many years to come.

For example, one of COVID’s biggest impacts on corporate culture has been an increased use of digital collaboration tools and platforms, which a full 79% ranked as “significant” (Chart 3). An overwhelming 85% said this change is likely to be permanent. Another change spurred by the pandemic that the majority expect to become permanent is the shift toward increased focus on disaster preparedness and crisis management.

Other significant changes slated to become permanent fixtures in corporate culture for many include more regular and open top-down communication with employees, more collaboration between teams who did not previously work together, and an increased sense of purpose and shared values among working teams. Improved employee feedback and communication from the bottom up, while not as widely instituted, is a change almost half of those who have made improvements plan to make permanent.

 

“The survey results clearly indicate that a major shift toward an M4.0 culture that is digitally enabled, collaborative, innovative, and data-driven is not only underway more rapidly than ever before, but is also here to stay.”

While widely implemented pandemic-specific health and safety shifts such as PPE and mask requirements are only planned to become permanent for a quarter of respondents, health and safety strategies are being extensively redefined and are going to mean much more than just accident prevention moving forward, said 61% (Chart 4). Seventy percent of those who shifted to remote and virtual work strategies also say they intend to enable at least some of their workforce to continue working from home in the future. This also reflects the increasing use of digital collaboration tools and platforms that make remote work feasible for many more employees, and which will continue to move companies toward creating a more empowered, collaborative, and responsive workforce for the future.

M4.0 Culture Moving into the Mainstream 

The shift toward a more M4.0-based overall corporate culture is evident in the terms manufacturers now use to describe the current state of their corporate cultures, with customer-centric and collaborative topping the list. (Chart 5). What is clear, however, is that there is a strong belief that continued culture change will be essential in the digital age, with a substantial 71% saying they will need to continue to transform their cultures in the future to fully take advantage of all the M4.0 era offers (Chart 6). For example, 60% consider a move toward more data-driven decision-making should be on top of their change agenda, and more than half believe better integrated, more cross-functional teams would help drive future success. Increased responsiveness, more agile operations, faster innovation and time-to-market for new products, and even more of an emphasis on customer and supplier centricity are also likely to be key elements of necessary culture change (Chart 7).

Many of those changes are already underway. Thirty-seven percent now say they are either satisfied with their current culture or actively working to make the needed changes, up from 24% in 2019 (Chart 8). While these changes may be incremental, there are still many ongoing challenges to cultural transformation, with top concerns such as cost/ROI and a lack of leadership bandwidth/buy in dominating the list, followed by a lack of employee buy-in and no formal strategy.

Collaborative Cultures on the Rise 

With almost unanimous agreement that a collaborative culture is either very or somewhat important to future competitiveness, and three quarters (74%) identifying it as necessary for competitive survival, it is evident that collaboration is top of mind for today’s manufacturers (Chart 10). While the immediate needs of dealing with the pandemic likely led to the slight rise in traditional command-and-control hierarchical structures in some organizations, from 30% in 2019 to 34% in 2021, only 14% of manufacturers predicted that this approach would still hold true two years from now. Even more telling is the rapid rise of those who describe their culture as collaborative, which went from 17% in 2019 to 26% in 2021, and is predicted to surge to a substantial 51% by 2023 (Chart 9).

The key enablers to achieve that desired collaborative culture, according to 61% of respondents, are M4.0 technologies and approaches (Chart 11). This is reflected in the significant increase in the adoption of digital threads across all company functions over the past two years. In manufacturing operations, for example, the use of digital threads shot up from 45% in 2019 to 70% of companies today, while supply chain digital threads are now being used in 50% of organizations (up from 35% in 2019), and further increases are evident in design and engineering, IT, and even in more customer-focused areas such as sales and marketing and customer service and support (Chart 12).

M4.0 Drives Faster Innovation 

Innovation processes have also accelerated in many manufacturing companies over the last two years, with 25% saying they are continually developing new products and embracing change, up from just 19% in 2019. More than half aren’t far behind, defining their culture as “moderately innovative,” and being willing to experiment with new technologies, products, and services (Chart 13). Perhaps most importantly for the future though, almost three-quarters of companies now credit M4.0 technologies and approaches as key drivers to faster and more effective innovation in the years to come (Chart 14).

The source of ideas for these new products, processes, and/or business models has also shifted slightly since 2019, with suppliers kickstarting innovation for 47% of manufacturers, up from just 28% two years ago (Chart 15). External partners and academic and research institutions also are taking on an increasing role in innovation. But, that pales in comparison to the growing role of company employees, whom 86% of manufacturers now credit as the source for new ideas, compared to 74% in 2019.

“While many were already on the road toward M4.0 before the pandemic hit, COVID-19 proved to be a wake-up call that the time is now to start implementing the changes to corporate culture needed for today’s, and tomorrow’s, manufacturers.”

M4.0 Essential to Integration 

The flattening of corporate hierarchies, the elimination of siloes, and the increase in communication and cross-function and cross-training in the workforce are resulting in an increasingly integrated business. More than a third of companies in the survey say they have already made significant changes to become more integrated, up from less than a quarter in 2019 (Chart 16).

As with collaboration, M4.0 technologies and approaches also are regarded as essential ingredients to successful integration, according to 69% of respondents (Chart 17). But when it comes to integrating IT and OT teams, there’s still some progress to be made. While more than half now have at least somewhat integrated OT and IT functions, up from 43% in 2019, only 16% say these areas are fully integrated so far (Chart 18).

Creating a more integrated enterprise remains challenging, however. Issues around effectively managing cultural/behavior change, having the leadership time and focus to change operations while still running the business, and developing the consensus needed for an implementable overall strategy, continue to be the most significant barriers to integration. However, the latest survey also suggests there also growing concerns over getting buy-in from heads of functional areas, understanding the benefits, and obtaining funding and resources to make it happen (Chart 19).

While many were already on the road toward M4.0 before the pandemic hit, COVID-19 proved to be a wake-up call that the time is now to start implementing the changes to corporate culture needed for today’s, and tomorrow’s, manufacturers. The key to future success will be to keep that momentum, born in many cases of necessity, going once the immediate crisis subsides. The role of M4.0 in that continued transformation now seems abundantly clear.   M

 

Part 1: COVID-19 Impact

1 COVID-19 Has Accelerated M4.0 Transformation Across Multiple Areas

Q:What impact has COVID-19 had on your M4.0 transformation strategy in the following areas?

2 50% Say COVID-19 Has Also Increased Leadership Focus on M4.0

Q: What impact has COVID-19 had on your leadership team/management’s focus on digital/M4.0 transformation?

3 85% Expect Increased Use of Digital Collaboration Tools to Be Permanent

Q: What impact has COVID had on your corporate culture, and how long do you expect these impacts to continue?

4  Working Cultures Shifting to Remote, Safer Strategies for Employees

Q: What impact has COVID-19 had on your workforce culture, and how long do you expect these impacts to continue?

Part 2: Overall Company Culture

5 Corporate Cultures Increasingly Customer-Centric and Collaborative

Q: What term would you use to describe your company’s culture today?

6  Strong Majority Believe Culture Change Needed in Digital Era

Q: Thinking about the requirements of the digital age, does your company believe it needs to change its culture to embrace this new era?

 

7  Data-Driven Decision-Making & Functional Integration Top Culture
Change Agenda

Q:If a culture change is needed, which description would best capture what that change would encompass?

8  ROI Concerns & Leadership Bandwidth Remain Key Challenges to Change

Q: What are your company’s biggest challenges
to cultural change?

Part 3: Collaboration

9 51% Predict Collaborative Structures Will Dominate in 2 Years

Q: How would you describe your overall corporate structure today, and where do you expect it to be in 2 years’ time?

 10  Three Quarters Say Collaboration is Essential to Competitiveness

Q: How important do you think a collaborative
culture is for competitiveness?

11  M4.0 Key to Enabling a Collaborative Culture

Q: Is there a clear belief that M4.0 technologies and approaches are key to enabling a more collaborative culture?

12  Extensive Adoption of Digital Threads Across All Functions in Last 2 Years

Q: Which of your company functions are connected to a digital thread to enable end-to-end data sharing and collaboration?

Part 4: Innovation

13  Three-Quarters Say They Are Already Moderately to Highly Innovative

Q:How would you describe your company’s current level of innovation?

14  Almost Three-Quarters Believe M4.0 is Key to Driving Innovation

Q: Is there a clear belief that M4.0 technologies and approaches are key to enabling faster and more effective innovation?

15  Increasing Role for Employees & Suppliers as Source of Innovative Ideas

Q: Where does your company source its ideas for new products, processes, and/or business models?

Part 5: Integration

16  More Than a Third Have Significantly Integrated Organizational Structures

Q: To what extent has your company made changes to its organizational structure in order to create a more integrated enterprise?

17  M4.0 Seen as Key to Enabling Integration

Q: Is there a clear belief that M4.0 technologies and approaches are key to enabling more integrated operations?

18  Increasingly Integrated OT & IT Teams in Last 2 Years

Q: How would you describe the level of
integration between your IT and OT teams?

19  Culture Change Remains Key Challenge to Successful Integration

Q: What are the most significant challenges to improving your company’s integration?

Survey development was led by Executive Editor Paul Tate, with input from the MLC editorial team and the MLC’s Board of Governors.

Spurred by the need for agility and flexibility in a time of crisis, manufacturers appear determined to accelerate their investments in digital technologies.    By David R. Brousell

As the year 2019 was drawing to a close,  it appeared that momentum was building for manufacturers to adopt advanced technologies as a key part of their journey to Manufacturing 4.0, the next wave of industrial progress based on digitization. And then, in February, the unexpected occurred — COVID-19 struck like a bolt of sustained lightning, upending life as we knew it.

By the end of June, U.S. Gross Domestic Product had fallen at a 31.7% annualized rate, the deepest decline since record keeping began in 1947. Nearly 30 million Americans were receiving unemployment checks by the week ending July 11. And by mid-September, there were 6.5 million COVID-19 cases and nearly 194,000 deaths in the U.S.

Between February and April, manufacturing production plummeted 20.3% and even after four straight months of improvement, the industry was still down 6.7% at the end of August, compared to where it was in February. Capacity utilization followed a similar pattern, dropping to 59.9% in April, the lowest rate since data gathering began in 1948, from 75.2% in February, and then recovering somewhat by the end of August when it reached 70.2%. And so the big question around Manufacturing 4.0, a nearly decade-old evolution that had been moving at a slow but steady pace, was would manufacturers be forced to put their digital technology investments on hold or scale them back significantly in order to weather the crisis and, if so, what damage would a hiatus have on the trajectory of the digital model?

The answer to that question was immediate and profound. The pandemic is shaping up to be an unlikely inspiration for change. Manufacturers’ ability to quickly pivot and produce pandemic-fighting materials and equipment was clearly linked to their digital maturity. Companies that had already invested in digital technologies were in a far better position to respond to the crisis than those that did not or did not do so sufficiently.

A poll conducted by the Manufacturing Leadership Council in May showed even stronger evidence that Manufacturing 4.0 was not going to be slowed down – 53% of respondents indicated that their companies would accelerate digital investments as a result of the pandemic.

Spending Acceleration Plans Still Robust 

A new MLC poll, fielded in August, shows that number slipping but still robust. In that new poll, the MLC’s annual Transformative Technologies in Manufacturing survey, 43.7% of respondents indicated that their companies will accelerate spending on information and operational technologies as a result of the pandemic. Twenty-five percent indicated that spending will be unchanged (compared with 36% in the June poll) and 30.3% said that spending would decline (compared with only 7% in June). In addition, more than 79% of respondents also said that their companies would accelerate adoption of technologies that enable virtual working and remote monitoring of operations. (Charts 1, 2). As might be expected, conducting surveys in the midst of an on-going pandemic is an exercise fraught with unpredictability. Because of unknowns such as whether new surges of infection will occur, when a vaccine will be become available, and what the long-term damage to businesses might be, it is very difficult for companies to plan and budget. Current intentions around advanced technology investments could change at any time depending on circumstances.
But the new MLC Transformative Technologies poll, while raising concerns that spending may be cut back as the damage inflected by the pandemic is more fully felt in the months ahead, does offer some encouragement that manufacturers continue to be focused on the future, and what advanced technologies can do to make that future a digital one. Moreover, the new poll has certain strains of consistency with prior MLC surveys, most significant of which is manufacturers’ longer-term view of the transformative impact of advanced technologies.
For example, across a range of 13 technologies surveyed, artificial intelligence once again this year strongly leads in respondents’ investment intentions over the next two years, a position that AI has held in MLC surveys for the past several years. This year, 38.7% of respondents indicated that their companies would invest in AI in the next 12 to 24 months. Digital twin modeling and simulation software comes in second, with 34.5% of respondents saying their companies will invest in this technology within the next two years, and supply chain management software comes in third, with 28.7% (Chart 4).

Manufacturers continue to be focused on the future and what advanced technologies can do to make that future a digital one.

The Promise of AI 

AI has apparently captured the imagination of manufacturers for what it promises to do to improve the effectiveness of automation, mine increasingly growing volumes of data from operations including factory floor equipment, and, as a result, cut costs and boost productivity. In fact, across eight application areas asked about in the survey, AI applied to preventative maintenance of plant floor equipment was clearly the stand-out, with 62% of respondents indicating it as a key application area, the highest by far in the survey. Quality and production planning came in second and third, with 56% and 35%, respectively (Chart 8).

But as it is with all advanced technologies, adopting, implementing, and optimizing their use takes time, and usually more time than initially expected. Right now, just over one-quarter of respondents indicate they are underway with AI on a single-project basis; only 3.6% say they have implemented AI enterprise-wide in all of their factories. Many others are in the process of becoming aware of the technology, conducting research, or defining a roadmap for adoption and implementation (Chart 7).

And when MLC asked about the potential impact of AI and its cousin machine learning, an interesting divergence of opinion emerged, one likely influenced by where on the AI maturity curve a company may stand. Today, only 11% of respondents are of the opinion that AI will be a “game-changer” in production. But over the next five years, this number jumps to 48.6%. </p?
On the other hand, 29.3% of respondents today see AI as significant but not a game-changer. Over the next five years, this group grows to 35.7%, but the rate of growth is markedly less than those who believe that AI will indeed be that game-changer the current hype would have us all believe.

Strong Interest in 5G 

Other advanced technologies are also showing robust investment intentions.
Among communications and networking technologies, so-called 5G technology, in which only 11.7% of respondents have currently invested, is slated for significant growth over the next two years. By then, 45.9% of survey takers expect that their companies will have invested in the technology.

The Internet of Things, which has a much higher current penetration rate of 51.3%, is also showing strength, with 29.7% saying they will invest in the next 12 to 24 months (Chart 3).
In production technologies, predictive maintenance, plant floor simulation and modeling, and collaborative robots garnered the strongest buying intentions over the next two years (Chart 5). And the adoption of digital thread technology, a key factor in enabling companies to share data across different systems and processes, is also expected to grow strongly (Chart 6).

The Challenges Ahead 

The most important reasons manufacturing companies want to invest in these advanced technologies are that they are looking to reduce costs and improve operational efficiency, improve visibility of operations and create agility and flexibility, and, a result, up their game competitively.
But many face an array of obstacles in reaching these goals. Asked to assess a list of 12 challenges associated with adopting and using transformative technologies, survey respondents indicated that the top three hurdles are migrating from or integrating with legacy systems, assessing cost and benefit of the new technologies, and developing a cohesive M4.0 roadmap (Chart 16).
The roadmap issue continues to bedevil many companies. A lack of a roadmap most likely indicates a low level of digital maturity. It may also reflect that companies may not have figured out how to organize around the digital opportunity.
Only about 21% of respondents indicate they have a formal M4.0 roadmap that has been adopted across their organization. About one-third say their approach is informal and tactical and nearly 20% say they really don’t have a strategy at all (Chart 10).
Part of the reason for the lack of organizational cohesiveness around M4.0 may be that responsibility for M4.0 continues to be quite diffused. Who should take the reins in developing a strategy that will affect the entire organization?

Artificial intelligence has captured the imagination of manufacturers by what it promises to do to improve operations.

About 29% of survey takers say that joint IT/OT teams have been charged with responsibility for devising and implementing M4.0 technology strategy and a roadmap, while 27% say that responsibility is the domain of the manufacturing vice president. Another 12.6% say the job rests with their chief operating officer (Chart 11).

As companies strive to sort out the responsibility question, they also struggling with two other key issues – developing M4.0 ROI models that make sense for their companies and finding people with the digital skills that can execute an M4.0 plan (Chart 13). Given the state of the manufacturing workforce, which is still suffering from hundreds of thousands of open jobs, the latter issue may be solved earlier than the former.

Despite all of the challenges, many companies feel they are in front of or at least keeping pace with competitors in the race for digital advantage. Nearly 40% of survey respondents think they are ahead of their competitors to one degree or another, but only about 11% would say they are substantially ahead. About one-third claim they are even with competitors and about 18% believe they are behind (Chart 15).

In coming months, the race will play out against a backdrop of continued economic uncertainty instigated by the pandemic. The pace of digital technology adoption will certainly be influenced by the larger economic context. It may slow down or speed up depending on the circumstances, but one thing appears certain – the road to the future is digital and nothing, not even a pandemic, will change that. M

Part 1: TECHNOLOGY INVESTMENTS AND PLANS

1 Many to Accelerate IT, OT Spending as a Result of COVID

Q: What effect has the COVID-19 pandemic had on your company’s investment posture for information and operational technologies?

2 Pandemic Spurs Remote Technologies

Q: To what extent has the pandemic accelerated the adoption of technologies that can enable virtual working and remote monitoring of operations?

3 5G, IIoT Slated for Greater Adoption

Q: Please indicate your company’s investment posture for the following communications and networking technologies.

4  AI, Digital Twins Lead in Investment Intentions

Q: Please indicate your company’s investment posture for the following IT-related technologies.

5 Simulation, Predictive Technologies to Further Penetrate Plant Floors

Q: Please indicate your company’s investment posture for the following production technologies.

6  Nearly One Quarter Has Implemented a Digital Thread

Q: Has your company implemented a digital thread approach to sharing the data generated by one or more of the M4.0 technologies you have adopted?

Part 2: ADOPTION OF AI AND MACHINE LEARNING

7  One Quarter Underway With AI Projects

Q: Where does your company stand today in adopting AI in plants and factories?

8  Preventative Maintenance is Key AI Application

Q: What are the key application areas for AI and Machine Learning technologies in your plants and factories?

9 Nearly a Majority See AI/ML as Game-Changer in Future

Q: What is your current assessment of the potential of artificial intelligence and machine learning, both today and in five years’ time?

Part 3: TECHNOLOGY ASSESSMENT & IMPLEMENTATION PROCESS

10  Only One-Fifth Has Formal M4.0 Approach

Q: Which statement best describes your company’s current approach to adopting a M4.0 technology roadmap or strategy?

11  Joint IT/OT Teams Lead in M4.0 Strategy

Q: Who is responsible for devising and implementing your M4.0 technology roadmap / strategy?

12  Cost Reduction, OpEx Are Top Motivators for M4.0

Q: What are the three most important reasons your company invests in transformative M4.0 technologies?

Part 4: CHALLENGES WITH M4.0

13  Proof of Payback, Skills Are Chief Inhibitors to M4.0

Q: If your company does not invest in M4.0 technologies, what’s the primary reason?

14  A Majority Struggles to Keep Pace With Technologies

Q: Please indicate the extent to which you agree with the following statement: The accelerating pace at which new technologies are emerging is causing us to fall behind in our efforts to evaluate and understand their potential.

15  A Mixed Bag on Competitive Position on M4.0

Q: Where do you think your company stands in relation to its primary competitors’ adoption of transformative M4.0 technologies?

16  Legacy System Migration is Greatest M4.0 Challenge

Q: How would you assess the following challenges related to adopting and using transformative M4.0 technologies?

17  Few Are ‘Well Prepared’ to Deal With Data Volumes

Q: How prepared is your company to organize, evaluate, and make decisions on the volumes of data that are or will be generated from greater connectivity of devices and equipment?

Survey development was led by David R. Brousell, with input from the MLC editorial team and the MLC’s Board of Governors.

COVID-19 brought a new sense of urgency to digital manufacturing, but M4.0 leadership is still a work in progress, reveals the Manufacturing Leadership Council’s new survey on Next Generation Leadership and the Changing Workforce.
By Penelope Brown

In many ways, the coronavirus pandemic has forced a reckoning with Manufacturing 4.0  and many of its dimensions. In the technology space, it has meant relying on data to help overcome shifts in demand, supply shortages, and, in some cases, the need to institute remote operations. For organizations, it has meant shifting employees’ physical work locations and implementing sometimes complex social distancing protocols at production sites.

For leadership, however, the reckoning may be most pronounced. When the crisis hit, leaders were charged with making decisions for which there was no precedent. They needed to communicate with their teams and colleagues around the clock. They often needed to set up an entirely new infrastructure to keep operations going. Perhaps most importantly of all, they needed to maintain a calm and measured approach at a time of high anxiety, doing their best to ease employees’ fears when they very likely had many fears of their own.

Part 1: Defining the Leadership Role

1 Leadership means data,
collaboration, and integration

Q: Which statement best describes what leadership means in the Manufacturing 4.0 era?

2 COVID-19 has added urgency to M4.0 investment

Q: To what extent has the COVID-19 pandemic created a greater sense of urgency about M4.0 digitization within your company’s leadership ranks?

3 Most agree that M4.0 leadership requires a different approach

Q: Please indicate the extent to which you agree with this statement: The emergence of the M4.0 era of information-driven factories will require a substantially different approach and set of skills on the part of manufacturing company leadership.

4  Digital acumen is a leader’s
most important skill

Q: Which new approaches and skills do you feel will be most important for the M4.0 era?

5 Few executive teams have
strong M4.0 knowledge

Q: What level of knowledge does your company’s executive management team have today about the concept of M4.0, its requirements, and its challenges?

But when it came to M4.0, a gap that has been in evidence for the past few years between the perceived importance of digitization and leaderships’ ability to manage a digital-first operation came into sharp relief.

This is one of the key findings of the Manufacturing Leadership Council’s new survey on Next-Generation Leadership and the Changing Workforce, one of MLC’s Critical Issues facing manufacturing in the digital era. For purposes of the survey, an M4.0 leader is described as one who establishes a fact-based culture of decision making and who has the skills to orchestrate the enterprise in a digital, collaborative ecosystem. These two competencies have been essential to manufacturers’ response to the pandemic. Anxieties and fears can be allayed with facts and information, and many leaders have said that their digital technologies were indispensable in pivoting operations quickly, and in some cases improved performance even over pre-pandemic levels.

Results from this survey also examine the current state of leadership M4.0 preparedness, the future digital skills that companies will need, the differing viewpoints between operations leadership and executive leadership, and what skills leaders need to build for the collaborative, digital, and always uncertain future.

Most leaders don’t deny the importance of M4.0, but there are sometimes clashes between the C-suite and operational leaders regarding its degree of importance.

6  Execs biggest question: What’s the M4.0 business case?

Q: What’s the most important thing your company’s executive management team wants to know about M4.0?

7  Leadership only partially prepared for M4.0

Q: How prepared do you think your company’s executive management team is to lead and manage the journey to M4.0?

8  Separate issues take focus from M4.0 preparation

Q: If your company’s executive management is not well prepared for M4.0, what is the most important reason why?

9 More than half see success threatened by lack of preparedness

Q: How vulnerable will your company’s future success be as a direct result of your company’s current level of M4.0 preparedness?

10  A majority of operations leaders cite importance of M4.0

Q: What degree of importance does manufacturing operations leadership attach to M4.0?

A Sense of Urgency 

While the pandemic underscored the necessity for the digital factory, the organizational ability to lead and manage a digital-first operation is lagging for many manufacturers. While 82% of respondents said the pandemic brought about a greater sense of urgency about M4.0 digitization at their company to either a partial or significant extent (chart 2), only 20% said that M4.0 is well understood by their executive management team (chart 5).

Additionally, most do not feel that their executive leadership is well prepared to lead and manage the journey to M4.0, with only 13% saying those executives are very prepared (chart 7) and 20% saying they aren’t prepared at all. The most-cited reason for the lack of preparation was that leaders are too focused on other issues (38%) or they weren’t sure how M4.0 applied to their business (25%) (chart 8).

While leaders have a need to develop their own digital knowledge and skills, they also must determine what their future organizational structure will look like and what roles are necessary to fulfill business objectives and goals. That outlook continues to be hazy for the digital future, as just 8% said those roles were well understood at their companies, with most respondents (61%) saying they were only somewhat understood (chart 18).

11  Most C-suites believe M4.0 is important

Q: What degree of importance does C-suite business leadership attach to Manufacturing 4.0

12  Many companies lack organizational vision for M4.0

Q: If there is a difference between the degree of importance attached to M4.0 by manufacturing operational leadership and C-suite leadership, which of the following statements best describe why?

It seems that most companies have an awareness of their needs, but many have not yet done what is necessary to address them. In that regard, 79% of companies have no formal training plan to educate their workers and leaders about M4.0 technologies and skills.

Leadership Quality Check 

Many believe that a lack of M4.0 preparedness will be detrimental to future success, with 46% saying their company is moderately vulnerable and 8% very vulnerable (chart 9). The silver lining is that many leadership teams see the importance of digitization; 66% of C-suites believe M4.0 is either very important or somewhat important (chart 11). The same goes for 58% of operations leaders (chart 10).

But what qualities does an M4.0 leader need to have in order to develop, champion, and ultimately usher through to that era of significant digital change? For one, they need to become more familiar with digital manufacturing. Nearly three-fourths of respondents said that leaders will need digital acumen, or the understanding of digital technologies and how to apply them (chart 4).

They also need to walk the talk by leading through the use of data. It’s viewed as important to exercise fact-based leadership, with 70% saying that leaders must become more data-driven and make decisions based on facts rather than experience or gut feelings (chart 4).

Asked to identify the most important M4.0 leadership skill, most said it is the willingness and ability to rethink the business and successfully embrace a digital model (72%), followed by the ability to manage data across the business ecosystem (65%) and use analytics to make data-driven decisions (65%) (chart 13).

Part 2: Developing Knowledge and Expertise

13  Embracing a digital model is essential to success

Q: Looking ahead, what degree of importance would you assign to the following M4.0 leadership skills and abilities?

14  Data analytics, cybersecurity are top areas of emphasis

Q: Looking ahead, what degree of emphasis would you place on the following technology areas in terms of developing knowledge and expertise?

Part 3: Assessing Leadership Challenges

15  Most see future leaders already in the company

Q: Where do you see the next generation of leaders coming from for your company?

16  Digital roadmap, business model are top leadership challenges

Q: In thinking about the requirements and implications of M4.0, what do you think are the most important challenges for leadership?

17  Safety, communication emerge as new leadership priorities

Q: How have recent events changed leadership skills and behaviors for the future?

Part 4: Workforce Development and Transition

18  Necessary digital roles only partially 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?

19  Most companies lack formal M4.0 training plan

Q: Does your company have a formal training plan to educate workers and leadership around the requirements of M4.0?

20  Automation aids in filling chronic worker shortages

Q: What impact do you think the increasing adoption of automation and advanced M4.0 technologies will have on workforce levels in your company in the future?

C-Suite vs. Operations 

Whether at the operational or C-suite level, most leaders don’t deny the importance of M4.0. But some companies see a clash between those groups on the degree of importance. For 35%, development of an overall digital vision and strategy is still a work in progress and accounted for some of the differences (chart 12). A third said that tactical operational accomplishments had been achieved with M4.0, but those had not yet been scaled to the enterprise.

Indeed, the need to develop a technology roadmap was the most-cited challenge to leadership (chart 16), with 57% saying it remains a hurdle. Others said there was a need to understand the business case and return on investment (52%) and also to develop a viable digital business model (47%). The workforce factors in as well, with 46% saying it is necessary to change the business culture and attitudes of employees.

M4.0 leaders are charged with both improving their own digital acumen and leading through data and fact-based decision making.

COVID-19 and Leadership 

If you ask any manufacturing leader about their experience over the last several months, you’re likely to hear things like “never would have believed it,” “biggest challenge of my career,” “once in a generation scenario,” “life-changing.” It’s undeniable that the pandemic crisis and other recent events have made an immense impact on leaders and what they will be taking with them into the future.

Most say that they now have a greater focus on health and safety (61%), increased top-down communication with employees (60%), and more focus on business continuity (57%) (chart 17). Others are thinking of how to improve diversity at their organizations (41%) or how to leverage their industry partnerships (37%) and community partnerships (19%).

It’s unlikely that much of business will return to what we knew as normal prior to the pandemic. What goes and what remains is yet to be seen. But steeped in a crisis they never could have conceived, leaders are now armed with a new set of lessons and skills that are likely to serve them through the future, in good times and bad. The pandemic has accelerated the timeline for the digital factory. Now, it’s time for leadership to catch up.   M

Survey development was led by Penelope Brown, Content Director, with input from the MLC editorial team and the MLC’s Board of Governors.

As manufacturers prepare for an explosion of data over the next few years, they will need to learn fast and embrace new analytical technologies, internal structures, and corporate cultures to turn that data into meaningful business-changing predictive insights, according to a new MLC survey. But many struggle with organizing around the data opportunity and developing ROI models.   By Paul Tate

The amount of data generated by multiple M4.0 technologies is set to explode  across the manufacturing sector over the next few years. Yet, many industrial enterprises are still learning how to deal with the data they already have. What’s more, a lack of effective tools, internal standards, control structures, and skills may hinder their efforts to deliver continual improvements in optimization, productivity, efficiency, and quality.

However, there are also clear signs that many manufacturers are already harnessing advanced M4.0 technologies and embracing new predictive analytical approaches to achieve the business-changing predictive results they seek. The overwhelming majority of manufacturing companies now believe that using and analyzing their data more effectively has become essential to future business competitiveness.

These are just some of the key findings from the Manufacturing Leadership Council’s first survey on M4.0 Data, conducted during March this year.

Data Explosion Ahead 

Over the last two years a quarter of manufacturing company survey respondents say they have already seen their manufacturing data volumes double or almost triple in size. An additional 10% report they’ve experienced higher rises of between 200-500%, and another 12% have recorded even more dramatic increases above 500% (Chart 1).

And that’s only the beginning. Over the next two years, those manufacturers suggest that the rate of increase will rise significantly, with 38% of respondents now predicting increases between two and six times their current levels. What’s more, over a quarter of companies expect their data volumes to surge substantially by more than 500% over current levels in the next two years.

1 Massive Increase in Manufacturing Data Expected Over Next 2 Years

Q: What percentage increase in manufacturing data have you seen over the last two years ago, and what increase do you expect to see in two years’ time?

2 Over 50% Measure Data Value by Impact on Operational Performance

Q: How do you measure the value of the data in your organization?

3 Over 40% Have Corporate-wide Guidelines for Collecting & Managing Data Across the Enterprise

Q: Does your company have a corporate-wide plan, strategy, or formal guidelines for how data is collected and organized across the enterprise, including manufacturing operations?

4  70% Expect Over Half Their Data to Be Standardized in 2 Years.

Q: Considering the mix of new and legacy systems in most operations, what proportion of your manufacturing data is currently standardized around clearly defined corporate standards/formats, and what do you expect this to be in two years’ time?

5 But Data Governance Approaches Still Inconsistent: IT Heads & Joint IT/OT Teams Currently Dominate

Q: Who is responsible for data governance and strategy in your organization?

Measuring Value  

So far, the vast majority of those companies (54%) are measuring the value of those rapidly increasing data volumes in terms of the impact on operational performance (Chart 2), driving value through increases in productivity, efficiency, or quality. Only a handful (4%) has developed ways of measuring data value in monetary terms with an assigned dollar value.

Interestingly, a small number of companies (7%) are now beginning to measure data value against revenues from new data-driven services, a figure that may well increase in coming years as more manufacturing companies develop and deploy innovative data services around their increasingly intelligent products.

Perhaps the most unsettling result here, however, is that despite many years of investment, time, and effort in deploying digital technologies across their organizations, 30% of respondents admit that they have no measures in place so far to value the increasing volumes of data those technologies generate. Establishing a meaningful, data value-centric ROI formula for the digital era seems to be an issue that is currently being ignored, or at least overlooked, by many manufacturing companies. Or that they don’t yet have reliable models on which to evaluate or determine value.

What’s more, organizing and managing that data on a consistent and corporate-wide basis also seems to be proving tough to achieve. Over half the respondents say they do not yet have any corporate strategy, guidelines, or even a plan for the way that data is collected or organized across their companies (Chart 3), although 46% say they have already made efforts along this path.

Establishing consistent data approaches, of course, isn’t easy when many companies still have a disparate set of new technologies and legacy machines in use, often with different data formats and structures. But as data volumes grow, such corporate-wide initiatives are likely to become increasingly important as companies seek to control their data assets in a more consistent and unified way.

“The rapid shift towards more predictive insights will become increasingly important to achieving greater operational efficiency and resiliency.”

6  ERP, Quality, Shop Floor Systems Generate Most Data: Edge & Embedded Systems Begin to Emerge

Q: What are the primary sources of your manufacturing data today?

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7  Productivity, Efficiency, and Quality Improve Most from Increased Access to Data

Q: How has the increase in manufacturing data helped you to improve your manufacturing organization?

8  Shift in Data Projects from Simple Analytics to Optimization & Prediction Over Next 2 Years

Q: What are your primary objectives for embarking on manufacturing data projects today, and what do you expect your primary objectives to be in two years’ time?

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9  A Third Now Using AI to Analyze Manufacturing Data, But Spreadsheets & Shop Floor Systems Still Dominate

Q: What systems do you use to analyze the manufacturing data you collect?

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10  Most Manufacturing Companies Are Still Learning How to Analyze the Data

Q: How would you rank your company’s ability to analyze the data from your manufacturing operations?

Gaining Control 

The good news is that over the next two years the industry may well see some rapid development in the way that companies seek to gain better control over data. The proportion of companies that expect to have over 50% of all their data standardized around clearly defined corporate standards or formats is set to double from around a third today, to 70% in two years’ time (Chart 4). The proportion of companies with only a quarter or less of their data in some kind of standard form today is set to dive accordingly, from 28% to just 4% in the next two years.

Steering those standardization initiatives will be the executives and teams that have been tasked with data oversight in the company. However, survey responses suggest that there is still a range of different approaches to who has governance and control over corporate data strategies in many manufacturing organizations (Chart 5).

Currently, most companies see the traditional IT function as the logical place for the coordination of corporate data, with governance responsibility placed under CIOs and IT VPs (23%), or perhaps joint IT/OT teams (18%). Some have even embraced the more recent concept of a corporate Chief Digital or Data Officer, although this title is still very much in the minority (7%). Again, there is unsettling evidence that many manufacturing companies have yet to tackle what perhaps in other areas of company assets would be considered a fundamental issue, with almost one in five companies (18%) admitting that no-one currently has overall data responsibility at all.

Operational Impact 

The vast majority of data now being handled by manufacturing organizations is generated by the company’s primary ERP systems (92%), quality control systems (80%) and shop floor systems (74%), although new technologies like edge computing systems (20%) and embedded systems in products (16%) are starting to make an impact (Chart 6).

In terms of operational impact (Chart 7), recent increases in manufacturing data have provided many companies with noticeable improvements in plant floor performance, particularly in productivity (77%), efficiency, (67%), quality (65%), and cost reduction (58%). However, it is also interesting that almost one in five companies say that increased access to data has also helped to spur innovation in their manufacturing organizations as well, adding another beneficial dimension to their M4.0 data journey.

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11  Only Half Have a Process to Verify Data Accuracy and Quality Before Making Decisions

Q: Does your company have a process to verify the accuracy and/or quality of the raw data before decisions are made on it?

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12  Over a Third Struggle to Capture the Right Manufacturing Data the Business Needs

Q: How would you rank your company’s ability to collect the right data the business needs from your manufacturing operations?

The Pursuit of Predictive Insights 

Those desired performance improvements currently underpin many of the objectives that manufacturers say are motivating them to embark on new data projects in their organizations (Chart 8). Respondents reveal that today, the two primary objectives for starting new projects are to analyze shop floor data to understand their operations more effectively (70%), and then to use those insights to help optimize their operations for the future (56%).

But perhaps most significantly, they also suggest that over the next two years there will be a rapid shift to using more advanced analytical capabilities to be able to better predict key trends and potential events, up from 20% today, to a substantial two thirds of companies (66%) over the next 24 months.

That rapid shift towards more predictive insights will become increasingly important to achieving greater operational efficiency and resiliency but will also require companies to deploy ever more advanced analytical capabilities and technologies to be able to meet this goal.

Already, a third of companies say they are harnessing the power of artificial intelligence approaches to help them analyze the manufacturing data they collect, using both in-house AI resources (18%) and external AI partners (14%). However, there is still a lot of head room for change. The majority of companies still depend on more traditional shop floor analytics (60%) and even Microsoft Excel spreadsheets (68%) to analyze the manufacturing data at their disposal (Chart 9).

Still Learning 

Most companies, however, are well aware that there is still a lot to learn along their data-driven journey.

Almost half of the survey respondents (47%) admit that their companies are still learning how to analyze data from their manufacturing operations effectively (Chart 10). Less than one in five (18%) believe their companies are currently “very capable” of analyzing the data they have, and 27% suggest they are only “somewhat capable” at this stage.

In addition, only half of the survey respondents say they already have processes in place to verify the accuracy and quality of their data before they start to make decisions based on it (Chart 11), and over a third of organizations say their companies still have only a “low” ability to actually collect the right data the business needs from its manufacturing operations in the first place (Chart 12).

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13  Data-driven Operations Increase Collaborative Decision-Making and Use of Data Performance Metrics

Q: In what way has your organizational structure adapted to optimize increasingly data-driven operations?

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14  Lack of Common Formats, Easy Access, Data Capture Systems, and Analytical Skills Are Main Barriers to More Data-driven Decisions

Q: What are the most important challenges or obstacles hindering your organization from making more data driven decisions?

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15  Manufacturing Data Essential to Future Competitiveness

Q: Looking forward, how important do you think manufacturing data will become to your competitiveness as a future business?

Alongside these areas of concern, there are also a number of other obstacles respondents highlight as potential hinderances to making more data-driven decisions (Chart 14). Most significant is the heritage of legacy systems in many companies which has created a mish mash of different systems across their production networks, producing data in different formats and making it more difficult to consolidate and unify their data strategies (46%). Respondents also point to difficulties in easily accessing the data they need (40%), a lack of the right systems to capture all the data they would like to have (38%), and a lack of skills to be able to analyze their data effectively (33%), as their top challenges.

Changing the Organization 

Nevertheless, an increasing focus on developing more effective data-driven operations is already having an impact on organizational structures and incentives systems in many manufacturing organizations.

For example, around 45% of companies say their approach to decision making has now become more collaborative as their organizations have adapted in their efforts to better optimize increasingly data-driven operations (Chart 13). Fifty three percent of companies have also established dedicated data teams at either a functional or corporate level. And around 35% of companies have specifically embedded data targets into their performance metrics for their employee teams.

“An increasing focus on developing more effective data-driven operations is already having an impact on organizational structures.”

Future Competitiveness 

What is clear, though, is that the vast majority of manufacturing companies now realize that overcoming these potential obstacles and creating better ways of collecting, managing, analyzing, and exploiting manufacturing data is going to make a big difference to the future success of the organization. An overwhelming 73% of respondents now accept that manufacturing data will become “essential’’ to future competitiveness (Chart 15), and another 27% believe it will at least be “supportive”.

Not one respondent claimed manufacturing data will have “no impact” at all.

That universal awareness of the growing importance of manufacturing data to future business competitiveness is perhaps the most significant result of all. However well prepared many companies may be today, there is now a powerful driving force across the manufacturing sector to pursue more predictive insights into operations and products to help make faster and better data-driven decisions. In many ways that constitutes a declaration of industrial intent to determine a better data destiny for manufacturing in the years ahead and that data mastery will be an essential core competency for the future.   M

Survey development was led by Paul Tate, Co-Founding Senior Content Director and Executive Editor, with input from the MLC editorial team and the MLC’s Board of Governors.

As they anticipate an accelerated adoption of new technologies over the next couple of years, manufacturers envision that factories and plants will be a mixture of the future and the past, reveals the MLC’s new Factories of the Future survey.   By David R. Brousell

Those who are worried that future factories and plants  will become lights-out facilities populated with artificial intelligence-powered super robots performing functions once done by flesh and blood human beings can rest easy – at least for the moment.

According to the Manufacturing Leadership Council’s latest Factories of the Future survey, manufacturers don’t share the dystopian vision of the industry often portrayed in popular culture, by think tank organizations, and even by some industry insiders. Instead, people on the front lines of plants and factories see a heterogeneous future, one that is clearly evolving to the digital state but which will be a mixed bag of people and automation for the foreseeable future.

When asked what they expected the future state of their factories to look like, 74% of the respondents to the MLC survey said they envisioned a hybrid of humans and robots, additive and subtractive processes, and digital and analog processes. Only 5.3% anticipated a future where factories are lights out and fully automated (Chart 8).

PART 1: STATUS OF M4.0 ADOPTION

1 More Than Half Undertaking
M4.0 Projects & Growth

Q: What is the overall progress level for M4.0 adoption in your company’s factory or plant operations?

2 Production, Quality Processes Most Advanced with M4.0

Q: At what stage of M4.0 adoption are the following functions in your company?

PART 1: MEASURING DIGITIZATION

3 Production & Nearly One-Quarter Has Digitized Equipment Maintenance

Q: To what extent is your plant floor equipment maintenance and service digitized today, and what extent do you anticipate it will be in 2 years’ time?

4  A Majority Has Digitized Production/Assembly

Q: To what extent is your production/assembly process
digitized today and what do you anticipate the extent will be IP-enabled in 2 years’ time?

5 Primary Most Have Networked, IP-Enabled Plant Floors

Q: How would you describe the extent to which your plant floor is networked and IP- enabled today, and what do you anticipate the extent will be in 2 years’ time?

This sober view no doubt reflects a realism borne from experience on the road to a digital future. As previous MLC surveys have shown, the digital journey is long, difficult, and often not linear. Rethinking processes in order to digitize them takes time and a lot of hard work. Figuring out what to do with increasing volumes of data from the many facets of operations requires analytical technologies and the people to manage them. And a successful pilot project doesn’t automatically mean applicability to the larger enterprise as issues of scale are confronted.

Despite the obstacles, manufacturers see a digitally-inspired future ahead, and one in which advanced technologies will have a profound impact on how plants and factories are run.

When asked whether they agree or disagree that AI and machine learning technologies will enable factories to become “self-learning facilities” in the future, for example, more than 85% of survey respondents supported the basic idea, with 23.4% of that group saying they “fully agree” with the concept (Chart 9).

Before such erudite facilities emerge, however, much distance has yet to be traveled on the road to Manufacturing 4.0, the MLC’s term for the next era of industrial progress based on digitization.

More than 85% of survey respondents expect their facilities to become “self-learning” in the future.

6  Nearly One-Third Are Linked to Customers, Suppliers

Q: To what extent are your production functions electronically integrated with customers and suppliers today and what do you anticipate will be the extent in 2 years’ time?

PART 1: FACTORY ORGANIZATION AND MANAGEMENT

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7  Divergent Views on Future Factory Footprints

Q: Looking ahead, which statement most closely describes what your company’s future factory strategy will be?

8  Strong Majority Sees Hybrid Model in Future

Q: What is the expected future state of your factory model?

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9  Self-Learning Factories Foreseen

Q: Thinking about the impact of technologies such as AI and machine learning, to what extent would you agree or disagree with the following statement: “Tomorrow’s factory will evolve to be a self-learning facility.”

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10  Mixed Picture on Extent of Common Operating Platforms

Q: To what extent has your company established a
common operating platform at its factories?

Many in the Project Stage 

According to the new survey, more than half of respondent organizations has undertaken M4.0 projects, with 30% experimenting with a range of small-scale pilot projects and 29% implementing projects on a single-project basis (Chart 1). Although many projects are at an early stage, most advanced at this point in time are projects in production and assembly and in quality operations (Chart 2).

But, as has been indicated in prior surveys, manufacturers’ intentions to digitize their various processes are remarkably strong.

For example, when asked to what extent they have digitized plant floor equipment and maintenance today, more than one-quarter of respondents said they have done so, with only two percent saying they have done so “extensively” and 24% saying “partially”. But expectations soar over the next couple of years, with nearly 39% expecting to have extensively digitized this area (Chart 3).

Similarly, only 11% said that their production and assembly processes are extensively digitized today, but over the next two years, about 46% expect to be at that level of digitization. And only four percent said they have extensively electronically integrated with customers and suppliers today, but this number is expected to rise to 20% in two years’ time (Charts 4,6).

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11  Strong Intentions for Collaborative Robots, AI, and AR

Q: Where does your company stand in regard to the following technologies?

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12  Production is Key Target for AI/Machine Learning

Q: What do you see as the most immediate application for machine learning/AI in your company today?

All of this process digitization work will be converging with another major trend underway in many companies – establishing a common operating platform across factories. The implementation of a common operating platform, though, depends upon a company’s business model and what it makes; therefore, complete standardization may not be practical or desirable. Nevertheless, 37% of survey respondents said they have extensively implemented such a model in all or nearly all of their factories. Another 36% said this work is in a partial state at only some factories (Chart 10).

The Legacy Systems Issue 

As digitization work proceeds, manufacturers are looking at a variety of new and improved technologies to improve operations and to leverage the data produced from increasingly connected enterprises.

Cloud-based computing, manufacturing execution systems, robotic process automation, modeling and simulation tools, and even 3D printing are already in substantial use in many organizations, survey respondents report. And, not surprisingly, advanced analytics and big data platforms, AI and machine learning, augmented reality and virtual reality technologies, and blockchain technologies for secure transactions are slated for more extensive use in the next couple of years (Chart 11). In addition, the use of collaborative robots, at only at about 18% of respondent companies today, is expected to grow substantially in the next two years (Chart 13).

Investments in these technologies will help modernize factories and plants and also address one of the most significant roadblocks to progress in many companies – dealing with legacy equipment and systems. When asked what their most significant roadblocks are to implementing M4.0, the most cited factor, by 46% of respondents, was upgrading legacy equipment.

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13  Strong Uptick Expected for Collaborative Robots

Q: How extensively are you using collaborative robotics now, and what do you anticipate your company’s level of use will be in 2 years?

PART 1: M4.0 OPPORTUNITIES AND CHALLENGES

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14  Legacy Equipment is Major Tech Roadblock to M4.0

Q: What do you feel are your company’s primary roadblocks to implementing your M4.0 strategy?

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15  Broad Range of Benefits Expected from M4.0

Q: What are the most important benefits and opportunities your company hopes to realize from embracing M4.0?

Close on this factor’s heals was a lack of skilled employees, at nearly 45%, and access to adequate funding for upgrade investments. But there are a number of other challenges as well, including having an organizational structure or corporate culture in place that resists change, the lack of a M4.0 roadmap, and difficulty in scaling M4.0 projects beyond the pilot stage (Chart 14).

Nevertheless, survey respondents appear to be keeping their collective eyes on the prize. Chief among expected benefits from M4.0 this year are better operational efficiency, better decision making through the use of data and analytics, cost reduction, and greater speed and agility.

As they strive for these advantages, a years’ long debate about the ultimate impact of M4.0 appears to be continuing. Is M4.0 truly a game change for the industry or is it just significant but not transformative? Will smart adoption by companies result in creating a unique competitive advantage for themselves or it is just table stakes in the fast-moving, unpredictable world of rapidly accelerating technology? Today, opinions are decidedly split (Charts 16,17).

The answer, if there is one that can be generally accepted and applied, will take time to come into view and may very well depend on knowledge with M4.0 that can only be gained with experience. The Fourth Industrial Revolution is indeed far from over.  M

Modernizing legacy systems is the most often cited obstacle to M4.0 progress.

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16  Split Continues Over Competitive Advantage or Table Stakes from M4.0

Q: Do you believe that the adoption of M4.W creates a unique competitive advantage for your company or is it merely table stakes to remain in the game?

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17 Half See a New Era Resulting from M4.0

Q: Ultimately, how significant an impact will M4.0 have on the manufacturing industry?

Survey development was led by David R. Brousell is the co-founder of the Manufacturing Leadership Council, with input from the MLC editorial team and the MLC’s Board of Governors.

The Manufacturing Leadership Council’s latest survey on Manufacturing 4.0 technologies shows high expectations for a range of advanced technologies including AI and Big Data, but a fragmented approach to implementation and strategy.   By Penelope Brown

From raw material to finished output to final delivery  to product lifecycle, manufacturing generates more data than any other sector of the economy, far outstripping the next-closest entrants of government and banking. In 2010, manufacturing was already producing 1,812 petabytes of data every year, according to the latest data from the McKinsey Global Institute. Worldwide data output has doubled five times since then, and factory data just keeps multiplying along with it.

Transformative technologies in manufacturing are major drivers of this data revolution, either in their ability to produce even more of it, or to capture, analyze, and refine it. Manufacturers are just beginning to dip their toes into this vast data pool, but they are making strides in the world where bits and atoms come together.

Software for quality management, enterprise resource planning, and supply chain management have become commonplace for many manufacturers. Companies are fixing their gaze on artificial intelligence, 5G, augmented/virtual reality, and modeling and simulation software as the next technologies to recast their operations.

Still, that pool of data remains a murky one and the plan for deriving clear and compelling results from it is anything but settled. Technology implementation remains spotty, reactive, and often informal, and it’s often not quite clear who should be in charge. Many are having difficulty in moving away from legacy systems and in determining the ROI from large-scale technology investments.

Sentiment among manufacturers is generally that they are in the exploratory phase for advanced technologies as they determine the best areas for deployment and their ROI potential, and they believe that most of their competitors are in the same place. But, looking ahead, they see significant, even game-changing potential for many of those technologies.

These key findings and others from the Manufacturing Leadership Council’s new Transformative Technologies in Manufacturing survey offer a glimpse into what’s driving the industry’s march toward Manufacturing 4.0 – an often confusing and uneven journey, but one that manufacturers are committed to pursuing, nonetheless.

PART 1: TECHNOLOGY INVESTMENT AND PLANS

1 AI Factors Big in Future Tech Investment

Q: Please indicate your company’s investment posture for the following IT-related technologies.

2 Networks Will Grow with 5G

Q: Please indicate your company’s investment posture for the following communications and networking technologies

3 Simulation and Predictive Maintenance on the Rise

Q:Please indicate your company’s investment posture for the following production technologies.

Technology implementation remains spotty, reactive, and often informal, and it’s often not quite clear who should be in charge.

4 AI Implementation Starts at the Project Level

Q: Where does your company stand today in adopting AI in plants and factories?

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5 Productivity, Process Improvements Seen as Promising for AI/ML

Q: What are the key application areas for AI and Machine Learning technologies in your plants and factories?

AI Stands for All In? 

Leading the pack for exploration and the beginnings of implementation is AI and machine learning. While only 15% of survey respondents currently see it as a production game-changer, that figure jumps to 51% when asked about its impact in five years’ time (Chart 18). Those feelings toward its promise are already being reflected in its use — while 39% say they have already invested, 30% say they will begin investing in the next 12-24 months (Chart 1).

Those investments have shown up mostly in single-project implementations (Chart 4), with many others at various places in the exploration and planning stage – 20% are developing awareness, 13% are conducting research, and 16% are moving forward with defining a roadmap. While only 5% have so far implemented AI in all their factories, 28% are implementing on a single-project basis.

The most popular applications for AI and machine learning are generally around operational improvement – 73% are using them for productivity and cost reduction, 71% for process improvement, and 64% for quality improvement (Chart 5). Not far behind is preventative maintenance at 54%.

Survey respondents also see big data/advanced analytics as highly important, with 42% saying it is a “significant” technology currently and 50% saying it will be a game-changer in five years’ time (Chart 16). As factories grow increasingly connected, the Industrial IoT is seen as a game-changer by just 12% of respondents currently, but that number jumps to 43% when asked about its impact in five years.

PART 2: THE TECHNOLOGY ASSESSMENT PROCESS

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6 Formal M4.0 Roadmaps and Strategies are Lacking

Q: Which statement best describes your company’s current approach to adopting a M4.0 technology roadmap or strategy?

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7 Sentiment Split on M4.0 Leadership

Q: Who is responsible for devising and implementing your M4.0 technology roadmap/strategy?

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8 Tech Evaluation, Adoption Stays on a Growth Curve

Q: Does your company plan to accelerate its evaluation and adoption of transformative M4.0 technologies in the next year or two?

Additive manufacturing/3D printing is seen as slightly less transformative, with 42% saying it has a significant but not game-changing impact on production currently. While 39% see it rising to exceptional status in five years, almost as many — 38% — say it will remain merely significant for their factories (Chart 15).

There was less enthusiasm among survey respondents for collaborative robots and generative design in terms of both their current and future impact, with 26% saying cobots will be a game-changer in five years (Chart 17) and 16% saying the same for generative design (Chart 19).

Help Wanted: Strategy and Leadership 

Outside of considering specific technologies, it’s evident that the approach to an M4.0 transition for many is shrouded in confusion about the tactics and uncertainty about the outcome. While 28% say they have a formal M4.0 roadmap that has been adopted throughout the organization, 25% say they are taking an informal and tactical approach, and 22% say there is no formal process or strategy in place, only a reactive approach (Chart 6). Other respondents said their company has a scattered, group-level strategy that lacks cohesion and coordination (20%).

One step back from that, there is a lack of consensus in even determining who should be in charge of devising such a roadmap or strategy. Just under one-third, 31%, say it should be the manufacturing VP, followed by 30% who say it should be a cross-functional team of executives (Chart 7). Only 6%, respectively, said it should be the responsibility of the CIO/IT team or individual plant managers, and 3% said it was under the purview of a Chief Digital Officer, a role that doesn’t yet exist at most manufacturing companies.

Despite the lack of cohesive strategy or leadership, that hasn’t quelled the appetite for adopting transformative technologies, with 63% saying their company plans to accelerate its evaluation and adoption of M4.0 technologies in the next year or two (Chart 8). The most cited reasons for that acceleration include reducing costs and improving operational efficiency (89%); creating a true, sustained competitive advantage (56%); and improving visibility and responsiveness (49%, Chart 9). Those without such plans say that lack of the right skills (23%), a lack of conviction on ROI (23%), or a lack of financial wherewithal (19%) were holding them back (Chart 10).

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9 Reducing Costs, Boosting Competition Motivates Tech Investment

Q: If yes, what are the most important reasons?

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10 Lack of Skills, Unknown ROI Act as Restraints

Q: If no, what’s the primary reason?

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11 Many Feel They are Behind on Understanding New Technology

Q: Indicate the extent to which you agree with the following statement: The accelerating pace at which new technologies are emerging is causing us to fall behind in our efforts to evaluate and understand their potential.

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12 Most See Themselves as Even with Competition in M4.0

Q: Where do you think your company stands in relation to its primary competitors’ adoption of transformative M4.0 technologies?

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13 Legacy System Integration is the Biggest Challenge

Q: How would you assess the following challenges related to adopting and using transformative M4.0 technologies? (Low = low level of challenge; Medium = medium level of challenge; High = high level of challenge)

Where to Go from Here? 

While some may read about all this indecision and irresolution and reach for a bottle of antacid (or something stronger), most survey respondents believe they’re all in this together. When asked where they think their company stands in relation to their competitors, 39% say they are about even, while 28% even say they are slightly ahead. A fortunate 5% say they are substantially ahead (Chart 12). On the flip side, 16% say they are slightly behind, and 4% say they are significantly behind.

As for what’s holding back movement toward an M4.0 transition, 47% said that migration from or integration with legacy systems as holding the highest level of challenge (Chart 13), followed by measuring ROI (42%) and organizational change management (39%). Planning and project management for implementation (62%), understanding and evaluating technology options (60%), and understanding organizational/management impact (52%) were all seen as medium-level challenges.

But the wave of data continues to just keep building, and most survey respondents say their companies are at a fair-to-middling state of readiness for refining and analyzing data. A majority, 55%, say their companies are moderately prepared, and 35% rank their companies as poorly prepared (Chart 20). Only 7% say their company is at a strong level of data readiness.

That middle-of-the-road status is roughly in line with what respondents say about how much their company understands the concept of using a digital thread to connect and share data, whether just within certain functions or across the enterprise. Nearly half, 44%, say the digital thread is partially understood (Chart 21), and 40% have plans to implement a digital thread, but 35% have no plans at all (Chart 22). For the ones that have deployed such data connectivity, 31% are doing it across their design, engineering, and production functions (Chart 23).

Mayhem in the making? No. Growing pains? Absolutely yes, and they are bound to be here for a while. As the dust settles from manufacturing’s first big strides into M4.0, those that persist are likely to find sure footing, just as the industry has done so many times in its past. While nobody can quite say how the industry will emerge from this sea change, there is no question that it will be an industry transformed. M

The lack of cohesive strategy or leadership hasn’t quelled the appetite for adopting transformative technologies.

PART 3: POTENTIAL BENEFITS OF TRANSFORMATIVE M4.0 TECHNOLOGIES TO PRODUCTION

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14 IIoT is Growing in its Impact for IP-Enabled Factories

Q: What is your assessment of the potential of the Industrial Internet of Things (IIoT), specifically IP-enabling your plant floor equipment and products, both today and in five years’ time?

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15 Most See 3D Printing as Growing in Significance

Q: What is your assessment of the potential of Additive Manufacturing/3D printing, both today and in five years’ time?

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16 Half Believe Big Data Will Be a Game-Changer

Q: What is your current assessment of the potential of Big Data/advanced analytics, both today and in five years’ time?

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17 Less Than Half See Cobots as Significant in the Future

Q:What is your current assessment of the potential of collaborative robots, both today and in five years’ time?

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18 High Expectations Building for the Future of AI

Q: What is your current assessment of the potential of artificial intelligence and machine learning, both today and in five years’ time?

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19 Only a Few See Big Potential in Generative Design

Q: What is your current assessment of the potential of Generative Design technologies, both today and in five years’ time?

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20 Companies Only Moderately Prepared for Data Deluge

Q: How prepared is your company to organize, evaluate, and make decisions on the volumes of data that are or will be generated from greater connectivity of devices and equipment?

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21 Most Have Good Understanding of the Digital Thread

Q: How well understood is the concept of a Digital Thread that connects and shares data across multiple functions in your organization?

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22 Companies Plan to Boost their Data Sharing Capabilities

Q: Has your company implemented a digital thread approach to sharing the data generated by one or more of the M4.0 technologies you have adopted?

Survey development was led by Content Director Penelope Brown, with input from the MLC editorial team and the MLC’s Board of Governors.

Big changes in corporate culture will be necessary for manufacturers to make a successful transition to the digital era, a new Manufacturing Leadership Council survey on Manufacturing 4.0 culture reveals.
  By Penelope Brown

As Peter Drucker once said, “Culture eats strategy for breakfast. ” As manufacturing evolves to an increasingly digital industry, it’s not just the technology that’s changing. The evolution also demands a correlating change in business culture, one that moves away from hierarchy and siloes to one that is more responsive, empowered, data-driven, and collaborative. The Manufacturing Leadership Council created its latest survey, M4.0 Cultures: Collaborative, Innovative, and Integrated, to find out exactly what manufacturers are doing to achieve this goal.

The work in establishing such a culture, if it doesn’t exist already, can be a daunting challenge. It can’t be done with simple, bandage-type solutions such as posting a mission statement on the walls or offering free pizza once a month. It requires an honest assessment of the current company culture, directional consensus and strategy from leadership, buy-in from employees, and continuous reinforcement throughout the organization. With so many complications from the get-go, it can be easy for many companies to quit a culture change initiative before it’s even begun.

But for those who can stick with it, the payoffs are hard to understate. Improved employee morale can lead to a better committed workforce that is more efficient and productive. Unity between teams and focus on a common goal can lead to improved collaboration and faster innovation. Great culture is also an important recruiting tool for companies looking to add new talent. While this might sound merely like feel-good details, all of this has a measurable and significant impact on the bottom line, not to mention opportunities for future growth.

The movement toward collaborative, innovative cultures will only intensify as Manufacturing 4.0 continues to advance. Manufacturers will need to establish the right mix of leadership, strategy, and perseverance to position themselves for a better future.

PART 1: OVERALL COMPANY CULTURE

1 Value statements are the industry norm

Q: Does your company have an explicitly stated culture or values statement?

2 Most see culture as everyone’s responsibility

Q: Who in your company is responsible for corporate culture?

3 Many say their cultures are collaborative and customer-centric

Q:What terms would you use to describe your company’s culture today?

Manufacturers will need to establish the right mix of leadership, strategy, and perseverance to position themselves for a better future.

4 Most see cultural change as a must in the era of M4.0

Q: Thinking about the requirements of the digital age, does your company believe it needs to change its culture to embrace this new era?

Change is a Must 

When it comes to the need to make changes, most respondents agree it’s necessary – 74% in fact said their companies believe culture change is necessary to embrace the M4.0 era (Chart 4). But in terms of the challenges that hinder culture change, survey respondents identified concerns about cost/ROI, a lack of leadership bandwidth to take on a culture initiative, lack of employee buy-in, and no formal strategy (Chart 6). However, 24% said that their company is either satisfied with their current culture or actively working to improve it.

Most companies already have some form of culture declaration in place – 88% of respondents said their companies already have an explicitly stated culture or values statement. But as far as what change would look like for these cultures (Chart 5), top responses included more data-driven decision making, more agile and responsive operations, employee empowerment to make decisions at the lowest level possible, and faster innovation and time-to-market for new products.

Indeed, when asked to select the top three descriptions for their current culture (Chart 3), it appears that many companies may already be on the right track in cultivating these qualities – the most popular responses were customer-centric, collaborative, and empowered. Other top responses were traditional/conservative, agile/responsive, siloed, and hierarchical.

While most respondents felt that all employees are responsible for corporate culture (49%, Chart 2), others said the CEO bears responsibility (25%) followed by the senior executive team (17%).

Collaborating on a Better Future 

A whopping 91% of survey respondents said that a collaborative culture is very important and even necessary for survival (Chart 11). It makes sense, then, that companies are looking at a mix of technology and company structure to improve collaboration.

Survey respondents believe that their overall corporate structure will shift toward one that’s more collaborative in the near future. Today, 39% of respondents described their corporate structure as a matrix, followed by 30% as a traditional hierarchy/command and control, and just 17% saying the company has a collaborative corporate structure (Chart 7). However, when asked where they expected their corporate structure to be in two years, the majority answered collaborative (61%), followed by 17% as a matrix and 14% as traditional hierarchy.

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5 Change would mean better decision making and responsiveness

Q: Which description would best capture what that change would encompass?

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6 Leadership challenges, lack of buy-in hinder path to culture change

Q: What are your company’s biggest challenges to cultural change?

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7 Factories move away from centralized management

Q: How would you characterize how your factories /plants are managed today and what do you anticipate will be the primary way they will be managed in the next 2 years?

PART 2: COLLABORATION

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8 Most manufacturers see only partial or limited collaboration

Q: How would you characterize your company’s collaboration progress so far?

It’s hoped that those structural changes will show themselves with better collaboration results – only 13% said that their company is highly collaborative with an end-to-end approach across the enterprise (Chart 8). The majority said their companies were partly collaborative in an ad hoc fashion (47%) or collaborative in specific areas only (33%). Of the level of collaboration between product design and manufacturing teams, 30% of respondents said that those teams were highly collaborative on a regular basis, while 54% said they were somewhat collaborative in working together occasionally, and 14% said they were collaborative only on a low level.
Many are employing the digital thread to enable end-to-end data sharing in manufacturing (45%), followed by IT (35%), supply chain (35%), customer service and support (29%), and design & engineering (28%) (Chart 9). However, 24% say they aren’t using a digital thread in any part of their company functions.

Innovation: An M4.0 Survival Necessity 

Most survey respondents indicate that their companies are moderately innovative and willing to experiment with new technologies, products and services (62%) (Chart 12); 19% said their companies were highly innovative, continually developing new products, and 16% said their companies operated at a low level of innovation and were mostly committed to their current products and business practices.

A lack of innovation might be keeping some survey respondents awake at night – 41% said they were concerned that a lack of innovation would leave their company vulnerable in the future (Chart 15). Others felt their company wasn’t highly innovative but it wouldn’t leave them vulnerable (21%), while 39% said their company’s current innovation efforts were adequate.

When it comes to sourcing new ideas for products and processes, companies most frequently look to their customers (84%), followed by company employees (74%) and external partners (54%) (Chart 13). In the comments from the survey, several respondents cited their own company innovation/incubation centers, and one comment said “competitors.”

When it comes to improving innovation, most felt that visionary leadership (76%) and the freedom to make mistakes (73%) were the most important enablers (Chart 14). Others cited collaboration with partners and customers (67%) and a strong innovation culture among all employees (66%).

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9 Nearly half connect manufacturing through an end-to-end digital thread

Q: Which of your company functions are connected to a digital thread to enable end-to-end data-sharing and collaboration?

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10 Design, manufacturing teams are frequent collaborators

Q: How would you describe the level of collaboration between your product design and manufacturing teams?

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11 Collaborative culture overwhelmingly seen as necessary for competitiveness

Q: In your view, how important do you think a collaborative culture is for competitiveness?

PART 3: INNOVATION

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12 Only one-fifth of respondents describe their companies as highly innovative

Q: How would you describe your company’s current level of innovation?

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13 Customers are the No. 1 source of new product ideas

Q: Where does your company source its ideas for new products, processes, and/or business models?

Making Moves on Integration 

Once upon a time, in the not-so-distant past, prevailing business wisdom was that you could get the best performance out of people if you kept them focused on the tasks and needs of their own team, department, or division. Intended or not, this could sometimes lead to unhealthy rivalries and dysfunctional relationships that could have far-reaching consequences in allowing a business to operate smoothly. These days, however, companies are moving toward flatter organizational structures with more cross-functioning and cross-training between teams, which can improve employee retention and growth, lead to faster problem solving, and improve overall responsiveness and agility.

While many MLC members will say that IT and OT teams haven’t historically been good bedfellows, the growth of digital technology on the shop floor is increasingly demanding more integration. Currently, 43% say their IT and OT teams are somewhat integrated, working collaboratively but separately, and 29% say they are only partially integrated (Chart 18). Just 10% say that their IT and OT teams are one team, fully collaborative and integrated.

More than half of survey respondents said their companies had already made either significant organizational changes (24%) or partial changes (31%) to create a more integrated enterprise (Chart 16), with 28% just getting started on making changes. The majority of manufacturers are engaging in cross-training for employees, with 39% saying many employees train for and perform different job functions throughout the company, though 42% of respondents said it was only hour employees that participated in cross-training and cross-performance (Chart 17).

While technology and leadership are essential to a successful M4.0 journey, culture, as Peter Drucker would say, is essential to a successful digital transition. The pathway toward change isn’t yet clear, but those who are willing to walk it are the ones who will most likely emerge as winners on the other side. M

All of this has a measurable and significant impact on the bottom line, not to mention opportunities for future growth.

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14 A mix of leadership, collaboration, and culture are drivers for innovation success

Q: What do you see as the most important enabler that drives a successful innovation strategy for a manufacturing enterprise?

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15 More than 40% fear their company isn’t innovative enough to survive in the future

Q: Do you feel that a lack of innovation will leave your company in a vulnerable position in the future?

PART 4: INTEGRATION

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16 More than half of companies have made significant or partial structural change

Q: Has your company made changes to its organizational structure in order to create a more integrated enterprise?

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17 Cross-training takes place at more than 80% of manufacturers

Q: Are your company’s employees cross-trained for different job functions?

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18 IT and OT integration remains a work in progress for most

Q: How would you describe the level of integration between your IT and OT teams?

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19 Top integration challenges are resistance to behavior change and needing to mind current operations

Q: What are the most significant challenges to improving your company’s integration?

Survey development was led by Content Director Penelope Brown, with input from the MLC editorial team and the MLC’s Board of Governors.

Overwhelmingly, manufacturing leaders say a new leadership model is required for the digital age, but much preparation and learning about a new approach has yet to be done, reveals the MLC’s new Next Generation Leadership survey.   By David R. Brousell

It almost goes without saying that leadership will be the linchpin in whether manufacturing companies make a successful transition to Manufacturing 4.0. Leaders will have to establish the business goals of the transition, determine appropriate investments, and devise implementation and execution plans based on a timeline – all standard duties of a leader.

Manufacturing company executives will need to exercise many of the traditional skills and competencies associated with leadership in their journey to M4.0, the next wave of industrial progress based on digitization, but the rules of the old playbook may not be enough.

What’s coming into sharper focus, according to the Manufacturing Leadership Council’s new survey on Next Generation Leadership and the Changing Workforce, is that leaders in the M4.0 era will need to develop a new layer of competencies around the digital model. Called digital acumen, these competencies include understanding the potential of advanced technologies to create new competitive advantages, redesigning decision-making processes to leverage real-time data availability, and managing increasingly information-empowered employees in a collaborative working environment.,

These are some of the highlights of the MLC’s new leadership and workforce survey, which also looked at the state of leadership preparedness with M4.0, areas where leaders need to develop knowledge and expertise, challenges leaders face around culture and M4.0 planning, the state of unfilled jobs, and the role of automation in dealing with the workforce issue.

What M4.0 Leadership Means

What is crystal clear at this stage of the industry’s journey to M4.0 is that few of today’s leaders dispute the idea that the digital era requires a different approach and set of skills on the part of manufacturing company leadership. To underscore the point, more than 80% of the new survey’s respondents agree that they must write a new leadership playbook for the digital era (Chart 2). What this means in practice, says a strong majority of respondents, is that leaders, leveraging the powerful capabilities of advanced information and analytic technologies, must establish a fact-based, information-driven culture of decision making.

In addition, it means that leaders must develop both a deep understanding of what it means to fully integrate digital technology in company business operations and skills to orchestrate employees, customers, and business partners in a digitally-drive, collaborative business eco-system (Chart 1).

Tall orders, particularly for highly tenured executives that have relied primarily on their experience and intuition, but they are part and parcel of the overall goal of developing digital acumen – thinking digital first. The new mentality means not only understanding how to apply digital technologies to improve manufacturing, but also how to drive down decision making in the organization (Chart 3).

And, all of this needs to be accomplished as, you guessed it, the business of manufacturing runs hard on a day-to-day basis.

PART 1: DEFINING THE LEADERSHIP ROLE

1 ‘Fact-Based Culture’ Leads M4.0 Leadership Descriptions

Q: Which statement best describes what leadership means for the Manufacturing 4.0 era? (Top 3)

2 Strong Agreement on Need for Different Leadership Approach

Q: Please indicate the extent to which you agree with this statement: The emergence of the Manufacturing 4.0 era of information-driven factories will require a substantially different approach and set of skills on the part of manufacturing company leadership.

3 Digital Acumen is Key to the New Approach

Q: If you agree, which statement best characterizes the new approach and skills? (Top 3)

Today, few manufacturing executives dispute the fact that the digital era requires a different approach to and set of skills for leadership.

4 M4.0 Knowledge is Still in Ramp Up Mode

Q: What level of knowledge does your company’s executive management team have today about the concept of M4.0, its requirements, and its challenges?

The State of M4.0 Readiness

That challenge – essentially changing the wheels on the car as it travels at 60 miles per hour — helps explain how hard it is for many companies to get behind the wheel of the digital model of doing business. Today, only a fraction of survey respondents, 13%, say that M4.0 concepts, requirements, and challenges are well understood in their companies. Just over one-third say that they are superficially understood and more than one-quarter indicate they are just beginning to gather information about M4.0 (Chart 4).

But the good news is that many companies are working hard to develop the requisite knowledge. Just over 50% of survey respondents say, for example, that their company’s executive management team is somewhat prepared for M4.0, with another 10% saying they are very prepared. On the other side of the ledger, 26% indicate that their teams are not at all prepared and, in a finding that is noteworthy although not troublesome at this point, seven percent say there is resistance to M4.0 in their companies (Chart 6).

The lack of preparedness, of course, has mostly to do with that fast-moving car. Just one-third of respondents, 34.7%, say that their state of readiness is a function of being too focused on other issues. The lack of understanding about M4.0 requirements plays into the situation, too, as does the related issue, cited by 27% of respondents, of trying to understand how M4.0 applies to their specific businesses (Chart 7).

But the biggest challenge by far, say 62% of survey respondents, is changing corporate culture and the attitudes of employees toward the digital model. Not far behind is understanding the business case for M4.0 and developing a roadmap to get there (Chart 12).

As a result of where they are on the M4.0 preparation curve, many manufacturing leaders understandably express concern about their companies’ future success. In a critical finding, nearly 80% of survey respondents indicate that their companies’ future success is vulnerable due to their current level of M4.0 preparedness. Thirteen percent of respondents said they feel very vulnerable and another nearly 29% said they feel moderately vulnerable. Clearly, these leaders grasp the idea that the digital model is not optional (Chart 8).

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5 Top M4.0 Question: What’s the Business Case?

Q: What’s the most important thing your company’s executive management team wants to know about M4.0?

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6 Management is Getting Prepared for M4.0

Q: At this point in time, how prepared do you think your company’s executive management team is to undertake the journey to M4.0?

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7 ‘Other Issues’ is Chief Reason for Unpreparedness

Q: If your company’s executive management is not well prepared for M4.0, what is the most important reason for the lack of preparedness?

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8 Majority Sees Some Vulnerability Around Preparedness

Q: How vulnerable will your company’s future success be as a direct result of your company’s current level of M4.0 preparedness?

Wanted: Knowledge and Expertise

The velocity that a manufacturing company can attain to move along the preparedness curve is directly related to how fast and how well the company can build M4.0-related leadership skills and competencies and develop knowledge and expertise around new technologies.

First and foremost, say survey respondents, leaders must develop a willingness and ability to re-think the business and understand and embrace a digital model. Equally important is using computer-based analytics to make data-driven decisions. Not far behind are competencies around getting better at cross-functional integration of processes and functions – what the MLC refers to as the One Company model – and developing collaborative skills to manage flatter organizations (Chart 9).

And in terms of developing knowledge and expertise in technology areas, survey respondents placed significant emphasis around cybersecurity and advanced data analytics. Also important are digital factory techniques to link design and production processes and simulation and modeling technology used in the design phase of product development (Chart 10).

PART 2: DEVELOPING KNOWLEDGE AND EXPERTISE

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9 Embracing the Digital Model is Crucial Leadership Trait

Q: Looking ahead, what degree of importance would you assign to the following leadership skills and abilities?

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10 Cyber, Analytics Top Techs for Knowledge Development

Q: Looking ahead what degree of emphasis would
you place on the following technology areas in terms
of developing knowledge and expertise?

PART 3: STATUS OF AI ADOPTION

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11 Majority Sees Home Grown Next Generation Leaders

Q: Where do you see the next generation of leaders coming from for your company?

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12 Cultural Change is Top Challenge for Leadership

Q: In thinking about the requirements and implications of M4.0, what do you think are the most important challenges for leadership? (Rank top 3)

Despite the persistence of the workforce issue, most manufacturing companies don’t have a formal strategy to attract next-generation workers.

PART 4: WORKFORCE DEVELOPMENT AND TRANSITION

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13 Just Over One-Third Have a Strategy to Attract Next Generation Workers

Q: Does your company have a formal strategy to identify and attract next-generation workers for your factories or plants?

A Workforce in Transition

In the U.S., the problems of unfilled job openings and attracting younger people into the workforce have persisted for many years. Yet, a majority of companies, 54% according to the survey, do not have formal strategies to identify and attract next-generation workers. And among the 36% that do have a strategy, only 13% consider those strategies to be very effective (Charts 13, 14).

And so the issue of unfilled jobs across many categories of job functions drags on. Most prominent among jobs that are open for at least six months are production supervisors, quality control specialists, mechanical engineers, and process control engineers. And those that are open one year or more include cybersecurity professionals, digital design and modeling specialists, and maintenance engineers (Chart 16).

Looking ahead at the digital roles and skills that will be required, the survey offers some encouragement that manufacturers are beginning to turn their attention to understanding future needs. Almost half of survey respondents, 48%, say they have some understanding today what the digital roles and skills will be. But with only six percent indicating that these requirements are well understood, there is obviously much distance yet to be traveled before the industry as a whole has a clear picture of what the workforce of the future will look like (Chart 17).

In the meantime, given the persistence of the workforce issue, a significant number of manufacturing companies are looking at automation as at least a partial cure. Thirty-five percent of survey respondents indicate that automation and advanced technologies will help offset the difficulty in filling open jobs and another 28% expect that these technologies will actually reduce the number of workers they require (Chart 18). A small group, 11%, thinks they will require more workers in the future as a result of automation.

However this trend plays out, it’s clear that manufacturing leaders face no ordinary times. The advent of the digital era, the rush of new technologies such as artificial intelligence and collaborative robotics, and the churning demographics of the workplace have combined to erect an unprecedented challenge before manufacturing leaders.

What is the key to victory? The answer may lie within. Leaders will have to adapt to changing times, develop digital acumen, and lead differently. And that’s both the challenge and the opportunity. M

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14 But Strategies Have Been Only Somewhat Effective

Q:If yes, how effective has the strategy been?

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15 Vast Majority of Companies Have Open Jobs

Q: Does your company have open production/operations jobs today that it has been trying to fill?

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16 Many Job Roles Remain Open for Extended Periods

Q: If yes, what types of jobs and how long have they been open?

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17 A Majority Has Some Understanding of Digital Roles

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?

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18 Automation Seen as Partial Cure for Open Job

Q: What impact do you think the increasing adoption of automation and advanced M4.0 technologies will have on workforce levels in your company in the future?

Survey development was lead by Executive Editor Paul Tate, with input from the MLC editorial team and the MLC’s Board of Governors.

The MLC’s first survey of AI and machine learning in manufacturing reveals growing experimentation with the technologies and a sober view of their effect on jobs.   By David R. Brousell

Opinions about the impact of artificial intelligence today range from the apocalyptic to the miraculous. Media darling Elon Musk of Tesla, for example, thinks AI is an “existential threat” to human civilization. Oracle CEO Mark Hurd believes a battle between the United States and China for “AI supremacy” will have important consequences for the global economy. And Ginny Rometty, IBM’s CEO, is convinced that AI has the power to transform industries in positive ways.

Whatever your view of AI, a term coined in 1955 by the computer scientist John McCarthy, the technology is at the forefront of discussions throughout society today, leading a debate about the future of work, jobs, and even what it means to be human. And as the manufacturing industry transitions to the digital era, AI is being viewed as central to leveraging the vast amounts of data that factories and plants will generate to do everything from improving operational efficiency to creating new, competitive advantages.

“Industrial AI can give the Fourth Industrial Revolution a huge boost and take Industrie 4.0 and similar initiatives to the next level,” said Roland Busch, Chief Operating Officer, CTO, and Member of the Managing Board of Siemens AG, in an article posted on the World Economic Forum’s website in January.

In an attempt to separate the hype from the reality of AI, and to take the measure of where AI and its cousin machine learning stand in manufacturing today, the Manufacturing Leadership Council undertook its first ever survey on manufacturers’ attitudes, plans, projects, and expectations with the technology earlier this year.

Chief among the survey’s findings is that, despite the hype, the 64-year old concept is at an early stage in most manufacturing companies. And while many companies expect AI to displace significant percentages of their workforces, they also anticipate that many of the displaced workers will be retrained for other roles in their companies, undercutting the notion that AI will inevitably lead to a vast wasteland of unemployed people. Moreover, a majority believes that while AI and machine learning are significant, they will not be transformative for the manufacturing industry.

PART 1: CHALLENGES TO AI ADOPTION

1 65% See Workforce
Changes Stemming from AI

Q: What percentage of your current workforce headcount do you expect will be replaced or removed by 2025 as a result of AI adoption?

2 But 60% Also See
Retraining for Those Displaced

Q: What percentage of the workforce displaced by AI adoption do you expect to be retrained for other roles in your company by 2025?

A majority of survey takers believes that AI and machine learning are significant but will not have a transformative impact on the industry.

3 Top 5 Challenges to AI

Q: What do you see as the biggest challenges to AI adoption in your organization today?

4 A Majority Sees AI as Significant But Not Transformative

Q: Ultimately, how significant an impact will AI and Machine Learning have on the manufacturing industry in the future?

Small Projects the Norm 

Digging deeper into what the survey data reveals about the status of AI and machine learning adoption, at an overall corporate level, 20% of respondents indicated that they are experimenting with a range of small-scale pilot projects in their companies and another 12% said single projects have been implemented. The largest group, 40%, are either in the stage of developing awareness of the technology, conducting research, or defining a roadmap (Q10).

The good news is that, over the next two years, survey respondents expect AI and machine learning investments to increase, in some cases substantially. More than 30% of respondents said they anticipate spending increases of between one and 10% in that timeframe, while 22% said 10-25%, and 14% indicated an increase of 25 to 50%.

At a departmental or functional level, manufacturing and production, with 60% of respondents indicating they have begun the adoption of AI, are the leading areas for the technology at present. Supply chain follows, at 30%, and research and development comes in third at 28%. But many other areas of the enterprise, from sales and marketing to quality operations, are also getting involved (Q11).

On the factory floor itself, 24% of survey respondents said they are implementing AI and machine learning on a single-project basis, while 48% are still going down the awareness, research, and roadmap trail (Q12). And among the application areas being addressed, process improvement, production planning, and preventative maintenance are getting the most attention.

PART 2: AI STRATEGY & ORGANIZATION

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5 Few Have a Formal AI Strategy Today

Q: How would you characterize your company’s approach to AI and Machine Learning today?

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6 AI Importance May Rise Dramatically

Q: How important do you think AI and Machine Learning is to your company in terms of business impact today, and how important will it be in in 2 years?

A Lack of Formality 

As companies proceed with pockets of AI and machine learning activity, they are doing so largely on an informal basis, suggesting experimentation with single or pilot projects to address a specific need or opportunity. Only 12.5% of survey respondents said their companies have a formal plan and strategy in place for the adoption and use of AI and machine learning technologies today (Q5).

But as knowledge of and experience with the technology matures, and as the number of applications increase, the informality will inevitably give way to more structure. And this shift could come in relatively short order as the perceived importance of AI and machine learning grows.

Interestingly, the survey suggests that a possible inflection point in that perception could come in the next couple of years. Today, only 12.5% of survey takers attach a “high importance” to the business impact of the technologies, but over the next two years, this group grows to 41%, a shift, should it occur, that would amount to a dramatic change in attitude (Q6).

Before that happens, though, manufacturers will need to work out some process issues as well as grow their own knowledge bases about the technologies. Right now, for example, fewer than one-third of respondents say their companies have a dedicated budget for AI and machine learning technologies (Q9). And just under 11% say they have a high level of confidence that their companies have the internal expertise to successfully manage and support deployment of the technologies. About 20% of survey respondents say that their software providers function as the primary source of support on AI and machine learning projects today, while just 16% say an in-house AI development team fulfills that important role (Q14).

Process Improvement Focus 

As might be expected at this stage of adoption, many of the anticipated benefits of AI and machine learning tend to center around improving existing processes. Just over 52% of survey respondents identify predictive insights and better decision making, for example, as “high potential” benefits of the adoption of AI and machine learning technologies.

Cost savings, at 45% of the sample, and better planning, at 43%, come in fourth and fifth in terms of having high potential. But respondents also seem to be thinking broadly about the possible business impact of the technologies. Nearly 48% selected increased competitive advantage arising from the technologies as a potential benefit (Q16).

Respondents’ assessments of potential benefits in specific functional areas also tend to focus around process improvements. In production operations, for example, the top three expected benefits are increased uptime of factory assets, production process innovation, and improved predictive maintenance of plant floor equipment (Q17). And in their supply chain operations, survey takers cited better planning, more predictive insights, and increased agility as their most desired improvements (Q18).

But before they can truly understand the effectiveness of AI and machine learning technologies in any area of their organizations, manufacturers will have to get better at measuring them. Right now, nearly 48% of respondents said they do not have metrics established to measure the impact of the technologies; encouragingly, 38% said they do.

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7 Manufacturing, IT in AI Driver’s Seat

Q: Who is in charge of AI and Machine Learning efforts in your organization?

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8 Much Headroom for Growth of Internal AI Expertise

Q: What level of confidence do you have that your company has the internal expertise to successfully manage and support AI and Machine Learning deployment?

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9 Fewer Than One-Third
Have an AI Budget

Q: Does a dedicated budget exist within your company for AI and Machine Learning technologies, training, and education?

PART 3: STATUS OF AI ADOPTION

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10 Awareness Building, Pilots Characterize AI Status Today
for Performance Assessment

Q: What is the overall progress level for AI adoption at your company? (Check all that apply)

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11 Production Leads Corporate
Functions in AI Adoption
for Performance Assessment

Q: Which of the following corporate functions has begun the adoption of AI? (Check all that apply)

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12 Nearly One-Quarter Implementing AI Projects in Factories

Q: What is the progress level of AI adoption in your plants and factories?

Characteristic of the early stage most manufacturers are at with AI, few companies have a formal strategy in place for the technology.

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13 Process Improvement,
Planning Key AI Factory Applications

Q: What are the key application areas for AI and Machine Learning technologies in your plants and factories? (Check all that apply)

Adoption Challenges Abound 

Among the most significant and provocative challenges attending AI and machine learning are the effects that these technologies may have on the workforce. There is little question that there will indeed be an impact, perhaps even a dramatic one. But people in manufacturing, who have had to cope with skills shortages and the problem of unfilled job for many years, may have a perspective on the issue that is markedly different from those outside the industry who fear a dark future for the human race.

A powerful majority of survey respondents, 65%, does indeed believe that AI adoption will result in workforce headcount level changes by 2025. That number breaks down to 39% saying the impact will translate to a one to five percent replacement or reduction of their current workforces in the next six years. Another 18% expect the impact to range between five and 10% and nearly seven percent see a 10 to 20% impact. Fully one quarter see no impact at all (Q1).

But a noteworthy percentage of respondents, 60%, expect that those displaced will be retrained for other jobs. That number breaks down at about 18% expecting that one to five percent of those displaced will find other jobs, another 18% anticipating five to 10%, , nearly seven percent expecting an offset of 10-20%, and about 16% foreseeing 20% or more being retrained (Q2).

In addition to the workforce issue, there are a number of other significant challenges associated with the adoption of AI and machine learning technologies.

Chief among these are understanding the technologies, at 67% of respondents; understanding the business case for them, at nearly 56%; and data issues, at 53%. The need to upgrade legacy technology systems in order to use AI and machine learning, cited by nearly 49%, is also a substantial challenge for many companies (Q3).

And on the critical question of what impact overall AI and machine learning will have on the manufacturing industry in the future, an interesting but not unusual schism has occurred in the survey data. A majority, 53%, say that AI and machine learning, while significant, will not add up to a force so powerful as to transform what they do. On the other side of the isle, 39% do indeed see AI as not only a game changer for their companies, but also amounting to a new era of technology affecting the business (Q4).

MLC surveys on the impact of Manufacturing 4.0 have revealed a similar dynamic. Several years ago, survey data was pretty much evenly split between those who thought M4.0 was significant but not transformative and those who thought it was truly a game-changer for the industry. But those numbers have slowly shifted over the years toward the more imaginative view as experience and knowledge have developed about the potential of digitization.

Could a similar route be traveled by AI?

The Road Ahead 

The answer to that question will, of course, come with the passage of time, but, in the interim, those manufacturers who are trying to educate themselves about the technology, undertaking research, and even engaging in some pilot projects would be well advised to move ahead deliberately and with a sense of urgency.

Artificial intelligence is a force to be reckoned with. It will come at manufacturing from many directions and affect many functions within the manufacturing enterprise. AI will be part of many different types of application software products, to ERP and supply chain systems, to quality and maintenance systems, and customer-facing systems. It has the potential to be a pervasive influence on those systems, the processes supported by them, and job functions and roles. It could, as Roland Busch of Siemens said, take manufacturing to a new and better level. It could also cause unwanted disruption.

But it is not a force unto itself. People can and should remain in conscious control of deciding when to use it and how much to use of it. Like any technology, and certainly as we have learned with social media, technology can be used wisely or not so wisely.

The decision rests with us.M

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14 Manufacturers Tap Broad
Array of AI Expertise

Q:What is the primary source of support for the development of AI & Machine Learning competencies in your organization?

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15 Growth in AI, Machine Learning Investments Foreseen

Q: What level of increase in AI and Machine Learning investment do you plan, or expect to see, in your
manufacturing operations over the next 2 years?

PART 4: BENEFITS OF AI ADOPTION

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16 Top 5 Potential Benefits Foreseen

Q: How would you assess the potential benefits of AI adoption for your overall business? (% of those indicating high potential benefit)

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17 Top 3 Production Benefits Expected

Q: How would you assess the potential benefits of AI adoption for your production operations? (% of those
indicating high potential benefit)

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18 Top 3 Supply Chain Benefits Desired

Q: How would you assess the potential benefits of AI adoption for your supply chain? (% of those indicating high potential benefit)

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19 Most Lack Metrics on AI Effectiveness

Q: Do you use a specific set of metrics to measure
the effectiveness/impact of your AI & Machine
Learning deployments?

Opinions about the impact of artificial intelligence today range from the apocalyptic to the miraculous. Media darling Elon Musk of Tesla, for example, thinks AI is an “existential threat” to human civilization. Oracle CEO Mark Hurd believes a battle between the United States and China for “AI supremacy” will have important consequences for the global economy. And Ginny Rometty, IBM’s CEO, is convinced that AI has the power to transform industries in positive ways.

Whatever your view of AI, a term coined in 1955 by the computer scientist John McCarthy, the technology is at the forefront of discussions throughout society today, leading a debate about the future of work, jobs, and even what it means to be human. And as the manufacturing industry transitions to the digital era, AI is being viewed as central to leveraging the vast amounts of data that factories and plants will generate to do everything from improving operational efficiency to creating new, competitive advantages.

“Industrial AI can give the Fourth Industrial Revolution a huge boost and take Industrie 4.0 and similar initiatives to the next level,” said Roland Busch, Chief Operating Officer, CTO, and Member of the Managing Board of Siemens AG, in an article posted on the World Economic Forum’s website in January.

In an attempt to separate the hype from the reality of AI, and to take the measure of where AI and its cousin machine learning stand in manufacturing today, the Manufacturing Leadership Council undertook its first ever survey on manufacturers’ attitudes, plans, projects, and expectations with the technology earlier this year.

Chief among the survey’s findings is that, despite the hype, the 64-year old concept is at an early stage in most manufacturing companies. And while many companies expect AI to displace significant percentages of their workforces, they also anticipate that many of the displaced workers will be retrained for other roles in their companies, undercutting the notion that AI will inevitably lead to a vast wasteland of unemployed people. Moreover, a majority believes that while AI and machine learning are significant, they will not be transformative for the manufacturing industry.

Small Projects the Norm 

Digging deeper into what the survey data reveals about the status of AI and machine learning adoption, at an overall corporate level, 20% of respondents indicated that they are experimenting with a range of small-scale pilot projects in their companies and another 12% said single projects have been implemented. The largest group, 40%, are either in the stage of developing awareness of the technology, conducting research, or defining a roadmap (Q10).

The good news is that, over the next two years, survey respondents expect AI and machine learning investments to increase, in some cases substantially. More than 30% of respondents said they anticipate spending increases of between one and 10% in that timeframe, while 22% said 10-25%, and 14% indicated an increase of 25 to 50%.

At a departmental or functional level, manufacturing and production, with 60% of respondents indicating they have begun the adoption of AI, are the leading areas for the technology at present. Supply chain follows, at 30%, and research and development comes in third at 28%. But many other areas of the enterprise, from sales and marketing to quality operations, are also getting involved (Q11).

On the factory floor itself, 24% of survey respondents said they are implementing AI and machine learning on a single-project basis, while 48% are still going down the awareness, research, and roadmap trail (Q12). And among the application areas being addressed, process improvement, production planning, and preventative maintenance are getting the most attention.

A Lack of Formality 

As companies proceed with pockets of AI and machine learning activity, they are doing so largely on an informal basis, suggesting experimentation with single or pilot projects to address a specific need or opportunity. Only 12.5% of survey respondents said their companies have a formal plan and strategy in place for the adoption and use of AI and machine learning technologies today (Q5).

But as knowledge of and experience with the technology matures, and as the number of applications increase, the informality will inevitably give way to more structure. And this shift could come in relatively short order as the perceived importance of AI and machine learning grows.

Interestingly, the survey suggests that a possible inflection point in that perception could come in the next couple of years. Today, only 12.5% of survey takers attach a “high importance” to the business impact of the technologies, but over the next two years, this group grows to 41%, a shift, should it occur, that would amount to a dramatic change in attitude (Q6).

Before that happens, though, manufacturers will need to work out some process issues as well as grow their own knowledge bases about the technologies. Right now, for example, fewer than one-third of respondents say their companies have a dedicated budget for AI and machine learning technologies (Q9). And just under 11% say they have a high level of confidence that their companies have the internal expertise to successfully manage and support deployment of the technologies. About 20% of survey respondents say that their software providers function as the primary source of support on AI and machine learning projects today, while just 16% say an in-house AI development team fulfills that important role (Q14).

Process Improvement Focus 

As might be expected at this stage of adoption, many of the anticipated benefits of AI and machine learning tend to center around improving existing processes. Just over 52% of survey respondents identify predictive insights and better decision making, for example, as “high potential” benefits of the adoption of AI and machine learning technologies.

Cost savings, at 45% of the sample, and better planning, at 43%, come in fourth and fifth in terms of having high potential. But respondents also seem to be thinking broadly about the possible business impact of the technologies. Nearly 48% selected increased competitive advantage arising from the technologies as a potential benefit (Q16).

Respondents’ assessments of potential benefits in specific functional areas also tend to focus around process improvements. In production operations, for example, the top three expected benefits are increased uptime of factory assets, production process innovation, and improved predictive maintenance of plant floor equipment (Q17). And in their supply chain operations, survey takers cited better planning, more predictive insights, and increased agility as their most desired improvements (Q18).

But before they can truly understand the effectiveness of AI and machine learning technologies in any area of their organizations, manufacturers will have to get better at measuring them. Right now, nearly 48% of respondents said they do not have metrics established to measure the impact of the technologies; encouragingly, 38% said they do.

Adoption Challenges Abound 

Among the most significant and provocative challenges attending AI and machine learning are the effects that these technologies may have on the workforce. There is little question that there will indeed be an impact, perhaps even a dramatic one. But people in manufacturing, who have had to cope with skills shortages and the problem of unfilled job for many years, may have a perspective on the issue that is markedly different from those outside the industry who fear a dark future for the human race.

A powerful majority of survey respondents, 65%, does indeed believe that AI adoption will result in workforce headcount level changes by 2025. That number breaks down to 39% saying the impact will translate to a one to five percent replacement or reduction of their current workforces in the next six years. Another 18% expect the impact to range between five and 10% and nearly seven percent see a 10 to 20% impact. Fully one quarter see no impact at all (Q1).

But a noteworthy percentage of respondents, 60%, expect that those displaced will be retrained for other jobs. That number breaks down at about 18% expecting that one to five percent of those displaced will find other jobs, another 18% anticipating five to 10%, , nearly seven percent expecting an offset of 10-20%, and about 16% foreseeing 20% or more being retrained (Q2).

In addition to the workforce issue, there are a number of other significant challenges associated with the adoption of AI and machine learning technologies.

Chief among these are understanding the technologies, at 67% of respondents; understanding the business case for them, at nearly 56%; and data issues, at 53%. The need to upgrade legacy technology systems in order to use AI and machine learning, cited by nearly 49%, is also a substantial challenge for many companies (Q3).

And on the critical question of what impact overall AI and machine learning will have on the manufacturing industry in the future, an interesting but not unusual schism has occurred in the survey data. A majority, 53%, say that AI and machine learning, while significant, will not add up to a force so powerful as to transform what they do. On the other side of the isle, 39% do indeed see AI as not only a game changer for their companies, but also amounting to a new era of technology affecting the business (Q4).

MLC surveys on the impact of Manufacturing 4.0 have revealed a similar dynamic. Several years ago, survey data was pretty much evenly split between those who thought M4.0 was significant but not transformative and those who thought it was truly a game-changer for the industry. But those numbers have slowly shifted over the years toward the more imaginative view as experience and knowledge have developed about the potential of digitization.

Could a similar route be traveled by AI?

The Road Ahead 

The answer to that question will, of course, come with the passage of time, but, in the interim, those manufacturers who are trying to educate themselves about the technology, undertaking research, and even engaging in some pilot projects would be well advised to move ahead deliberately and with a sense of urgency.

Artificial intelligence is a force to be reckoned with. It will come at manufacturing from many directions and affect many functions within the manufacturing enterprise. AI will be part of many different types of application software products, to ERP and supply chain systems, to quality and maintenance systems, and customer-facing systems. It has the potential to be a pervasive influence on those systems, the processes supported by them, and job functions and roles. It could, as Roland Busch of Siemens said, take manufacturing to a new and better level. It could also cause unwanted disruption.

But it is not a force unto itself. People can and should remain in conscious control of deciding when to use it and how much to use of it. Like any technology, and certainly as we have learned with social media, technology can be used wisely or not so wisely.

The decision rests with us. M

Survey development was lead by Executive Editor Paul Tate, with input from the MLC editorial team and the MLC’s Board of Governors.