Manufacturers will be pressing ahead with their M4.0 investments as they expand their digital deployments in operations, a new MLC survey reveals.

Despite economic uncertainty, manufacturers are moving ahead with digitizing plant and factory floor operations and are anticipating significant progress in doing so by 2025.

This is one of the key findings of the Manufacturing Leadership Council’s new survey on Smart Factories and Digital Production (formerly called Factories of the Future) that was conducted in January. The survey was designed to assess how manufacturers are utilizing digital technologies across their production plants and factories, what technologies they expect to invest in to further their digitization plans, what benefits they expect from digital transformation of their operations, the challenges in achieving those benefits, and the potential impact of digital transformation on the industry’s competitiveness.

Here are the key findings. Selected graphs from the survey follow.

Economic Outlook and Impact on M4.0 Investments

Manufacturers’ outlook for the U.S. economy in 2023 is a mixed bag, with 38% expecting a recession to occur later this year. But 23% expect moderate growth in the economy and no recession, while 16% expect inflation to ease and growth to rebound in the second half (Chart 1).
The economic context, however, does not appear to be constraining Manufacturing 4.0 investments. Fully one-third of survey respondents said they expect M4.0 investments to increase this year, while another 51% said they expect investments to continue unchanged (Chart 2).

Status of Digital Adoption

The focus of M4.0 efforts has shifted to broader deployments, with 33% reporting that they are currently implementing M4.0 company-wide, compared with 24% last year. There was also a slight uptick in those implementing single M4.0 projects, to 17% this year from 15% last year (Chart 4).
The shift to more significant deployments is also reflected in the stage of digital adoption by functional area. For example, the percentage of those reporting an advanced stage of digital adoption in production and assembly operations rose to 16%, from 9% last year. Those reporting they had reached an advanced stage in equipment maintenance operations rose to 13%, from 8% in 2022 (Chart 5).

Measuring Digitization

End-to-end or extensive digitization of a variety of factory-related operations is still aspirational at most companies, but intentions over the next couple of years are very strong, with some areas anticipated to experience exponential progress.
By 2025, for example, nearly 10% of respondents expect to have their full factory operations completely digitized end-to-end, compared with none reporting so today. Even more pronounced in terms of intentions is plant floor equipment maintenance and service operations. By 2025, 42% expect to have extensive digitization of this process in place, compared with only about 5% today (Chart 7).
Similar anticipations of extensive digitization – rising to double digits by 2025 from single digits today – are evidenced in production/assembly (45% in 2025, compared with 9% today; Chart 8), IP-enabled plant floor networking (60%/25%), integration of plant floor equipment data with quality systems (39%/4%), and integration of design and production processes (32%/9%).
Outside the four walls, integration with suppliers and customers is also slated for significant adoption. Today, only 4% say they have extensively integrated production functions with customers and suppliers, but by 2025, 26% expect to have done so (Chart 9).

Factory Organization and Management

Very few manufacturers, only 3% according to the survey, expect their factory operations to be run autonomously. The overwhelming sentiment, by 88% of respondents, is that the future state of factory models will be a hybrid of humans and machines, incorporating elements such as robotics, digital production systems, and digital processes (Chart 10).
Nevertheless, there is considerable agreement that future factories, with the aid of AI and machine learning technologies, will be self-managing and self-learning facilities. Sixty-three percent of respondents partially agree with this characterization, and another 14% fully agree with it (Chart 11).
In assessing their technical security level against potential cyberattacks, 57% of respondents said they felt partially secure, while 30% said totally secure. Only 9% indicated they felt vulnerable to attack (Chart 12).

M4.0 Technology Usage

The survey assessed the current and planned usage of 21 technologies, all of which are in use to some degree today by respondents. The five technologies which garnered the highest percentages of those saying they planned to use them by 2025 are smart planning and scheduling tools (54%), digital twins (53%), adaptive process control technologies (50%), digital threads (47%), and machine learning and AR/VR technologies (both at 49%).
AI also had a strong showing in terms of planned usage by 2025, with nearly 36% of respondents expecting to use the technology within the next two years. By 2025, the most desired applications of AI are in production optimization, equipment maintenance and service, and in distribution, logistics, and inventory management (Chart 13).

M4.0 Opportunities and Challenges

The chief challenges manufacturers identified in implementing their M4.0 plans remain largely the same as they have been over the past handful of years. Top of the list this year were data and systems integration (49%), the need to upgrade legacy equipment (at 48%), and the lack of skilled employees (38%) (Chart 14).
The most sought-after benefits from M4.0 are also repeats this year. Better operational efficiency topped the list this year (59%) followed by better decision making (51%) and cost reduction (50%) (Chart 15).
Just over half of respondents (50.5%, down from 53% last year) opined that M4.0 would provide their companies with a unique competitive advantage, as opposed to just table stakes (46%), but a notable increase occurred in the number of respondents saying that M4.0 would be a game-changer for the industry (61%, up from 56%) in 2022 (Charts 16,17). M

Part 1: STATUS OF DIGITAL INVESTMENT AND ADOPTION

1. Mixed Bag on Economic Outlook for 2023

Q: What is your company’s outlook for the economy in 2023?

2. Majority Sees M4.0 Investments Continuing Despite Economy

Q: How does your company’s outlook for the economy translate into M4.0 technology investments for 2023?

3. The State of Digital Maturity

Q: How would you assess the Manufacturing 4.0 digital maturity level of your manufacturing enterprise? (Scale of 1-10, with 10 being the highest level of digital maturity)

4. Companywide M4.0 Implementations Increase

Q: Which activity best describes the primary focus of your company’s M4.0 digital efforts today?

5. Production/Assembly Most Advanced with M4.0

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

6. Level of M4.0 Integration With Business Strategy

Q: How far has your company’s Manufacturing 4.0 strategy been integrated with the overall company business and manufacturing strategy? (Scale of 1-10, where 10 is fully integrated)

Part 2: MEASURING DIGITIZATION

7. Only a Fraction See Full Operational Digitization by 2025

Q: To what extent are your factory operations fully digitized end to end today, and what do you anticipate they will be by 2025?

8. Big Gains Seen in Production/Assembly Digitization by 2025

Q: To what extent are your production/assembly processes digitized today and what do you anticipate they will be by 2025?

9. Much Progress Foreseen in Integrating with Customers by 2025

Q: To what extent are your production functions electronically integrated with customers and suppliers today and what do you anticipate they will be by 2025?

Part 3: FACTORY ORGANIZATION AND MANAGEMENT

10. Hybrid Human/Machine Factory Model Expected

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

11. But Self-Learning/Managing Facilities Also 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-managing and self-learning facility.”

12. Cyber Defenses Seen as Secure by Strong Majority

Q: As factories become increasingly networked and digitized, how would you rank your company’s technical security level against potential cyberattack/disruption to plant floor systems and assets?

Part 4: M4.0 TECHNOLOGY USAGE

13. Smart Tools, Digital Twins Highest on 2025 Plans

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

Part 5: M4.0 OPPORTUNITIES AND CHALLENGES

14. Data Issues, Legacy Equipment Are Top Challenges

Q: What do you feel are your company’s primary roadblocks to implementing your M4.0 strategy in your production operations? (Select top 3)

15. Better Operational Efficiency, Decision Making Are Chief Benefits

Q: What are the most important benefits and opportunities your company hopes to realize from embracing M4.0 in your production operations? (Select top 3)

16. Slight Majority See M4.0 Conferring Unique Advantage

Q: Do you believe that M4.0 digital adoption will create a unique competitive advantage for your company or is it merely table stakes to remain in the game?

17. Strong Majority Sees M4.0 as Game-Changer for Industry

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

About the author:

David R. Brousell is the Co-Founder, Vice President and Executive Director of the Manufacturing Leadership Council,

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

Manufacturing Leadership Journal content and MLC resources are exclusively available to MLC members. Please sign up for an account or log in to view this content.

Manufacturers see data’s massive potential to improve operations, predict disruptions, and bring about new revenue streams, but realizing that promise continues to be a work in progress.

Data could be described as the lifeblood that enables the digital enterprise. In the 18-plus months that the COVID-19 pandemic has been roiling supply chains, forcing once-live interactions to go virtual, and necessitating remote work and collaboration, manufacturers have seen the immense value of using data to keep operations going and make better-informed decisions. It isn’t hard to imagine a far worse scenario if this once-in-a-generation disruption had happened in a time of less (or no) digital maturity.

But while former IBM CEO Ginni Rometty once said that big data is the new oil, a more apt comparison might be that data is like sunlight – in infinite supply, unyielding, quite often blinding. But it can also be illuminating, shedding light on former dark spots by improving transparency and visibility, enabling businesses to grow and thrive.

Manufacturing data mastery is in its tween years for most enterprises – certainly past its infancy, but still awkward and gawky and not quite fully formed. It is often unclear who is responsible for data strategy, what the data strategy is, or what data is actually worth to an organization. But manufacturers also say data has helped them to grow their productivity, lower their costs, boost efficiency, and improve quality.

These findings and others from the MLC’s new M4.0 Data Mastery Survey provide insights on where manufacturers are on their journey to harness the power of data and its revolutionary promise.

Where Improvement is Needed

Most manufacturers rate themselves as just average at their organizational data skills, and they struggle not only to collect the right data but also to interpret it. Fifty-eight percent said that their company had just a moderate ability to collect data that is meaningful and impactful for their business needs (Chart 11). More than a quarter ranked themselves as low in this area.

It is often unclear who is responsible for data strategy, what that strategy is, or what organizational data is actually worth.

But data collection is not the greatest struggle. Even more respondents said they had room for improvement in terms of finding insights from that data, with 75% ranking their organizations as only somewhat capable in their ability to analyze their manufacturing operations data (Chart 12). In this area, 11% of respondents said their organizations were not capable of this type of analysis.

Furthermore, a gap remains between the effort to collect and sort data and the effort to apply insights and create value from that data. Almost a third said they expend greater than 80% effort in gathering and organizing data vs. the effort expended to analyze and apply insights from the data (Chart 8).

Other stumbling blocks to utilizing data to a greater extent speak to the unwieldy tangle that manufacturers often find when undertaking data projects. This includes a lack of systems to capture the data (46%), followed by data inaccessibility (43%) and a lack of skills to effectively analyze data (39%) (Chart 16).

However, for what they are able to collect and analyze, more often than not organizations are leveraging that data to make informed decisions. Forty-eight percent say that their organization makes data-driven decisions frequently, while 18% say that they make data-driven decisions constantly (Chart 13).

Tools of Collection and Analysis

Digging a bit deeper into organizational data tactics, 79% said their shop floor systems are the primary source of manufacturing data, followed closely by ERP systems at 77% (Chart 6). This may not be surprising given the near-ubiquitous nature of those technologies within many manufacturing facilities.

What could be a trend to watch, though, is the growing use of edge computing systems (18%) and even embedded systems in products (12%). The former shows that manufacturers are taking advantage of faster networking technologies to process and store data closer to where it is produced and consumed, while the latter could hold promise for monitoring product lifecycle and performance, in addition to sustainability by making products more efficient and reducing materials usage and waste.

“Manufacturing organizations have serious governance issues to address, such as having a formal plan and somebody ultimately in charge of data management.

But among those emerging technologies lie some old faithful ones. CPA favorite Microsoft Excel is still the leader as the manufacturing data analysis tool of choice 34 years after its initial release, with 71% of respondents saying they use it (Chart 9). Meanwhile, AI is making inroads in its use for analysis, with nearly a third saying they are using in-house AI systems (28%), and others using cloud AI systems (12%) or an external AI partner (8%).

The Fundamental Flaws

Assigning value to data is an elusive undertaking for many manufacturers. Of those who do, most measure it by impact on operational performance (44%), as it is likely the easiest way to see the results of manufacturing data projects (Chart 1). But nearly as many admitted that their organization has no measure for data value (42%), a somewhat troublesome finding given the time, resources, and effort that go into data collection and analysis.

It’s difficult to determine if this is merely an oversight, or if reliable models just haven’t yet been developed to assess ROI, but this will be an important and necessary undertaking for manufacturers to make impactful data-led decisions. The good news is, though, that executives appear motivated to take on this pursuit, as 40% of respondents said data collection, management, and analysis were included as part of annual objectives for company executives (Chart 3).

But manufacturing organizations have other serious governance issues that also must be addressed, such as having no formal plan for data management or having nobody ultimately in charge. Four out of 10 respondents said that their company had no corporate plan, strategy, or formal guidelines for how data is collected and organized across the enterprise (Chart 2), an almost-astonishing number at a time when manufacturers are making significant investments in digital technologies to build connected operations.

“In today’s algorithm-driven world, manufacturers must pay heed to data accuracy, quality, and fidelity.

Manufacturers continue to take a scattered approach to governance and control over data, though many have a head of IT or combined IT/OT team ultimately in charge of data governance and strategy (Chart 4). However, 12% said that no one has data governance responsibility at their organization, a glaring issue that must be addressed at any company that wants to stay competitive in the long run.

Trusting the Data

One of the oldest idioms in computer science lexicon is garbage in, garbage out, meaning that flawed input data will result in flawed output data. In today’s algorithm-driven world, manufacturers must pay heed to the accuracy, quality, and fidelity of the data they are using for all-important business decisions. But it’s nearly an even split between manufacturers who check for that accuracy – 49% saying they do vs. 46% saying they complete no such checks (Chart 10).

Whatever leads those manufacturers to believe they can trust their data, there is no question that data is driving much-improved decisions – 94% said the use of data has helped their company make better decisions, though just 35% say it has helped them to make faster decisions (Chart 15).

To underscore the views that manufacturers have on data’s value for competitiveness, there is little room for debate that most see it as a requirement. Seventy-five percent said that data mastery will be essential for future competitiveness, with 25% saying it will be supportive for competitiveness – and not one single respondent saying that it will have no impact at all (Chart 17).

There is little question that manufacturers see the immense value that data can bring to their businesses. As organizations grow their data competency, they will seek to move past simply monitoring and collecting data to unlocking the insights and predictive ability that will be essential to future competitiveness. But until those organizations address the fundamentals of data mastery, they are likely to feel more growing pains along the road to that promising tomorrow. M

Part 1: CORPORATE DATA GOVERNANCE & ORGANIZATION

1. Many Organizations Have No Measure for Data Value

Q: How do you measure the value of the data in your organization? (Select one)

2. Many Organizations Lack Formal Data Collection Guidelines

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? (Select one)

3. For Many, Data Mastery is an Executive Objective

Q: Is data collection / management / analysis included in some way as part of the annual objectives for company executives? (Select one)

4. CIOs, IT Teams Largely Responsible for Data Governance

Q: Who is responsible for data governance and strategy in your organization? (Select one)

5. Cost Savings, Quality Top List of Business Objectives

Q: What are your key business outcome objectives for embarking on manufacturing data projects today and what do you expect your primary objectives to be in 2 years’ time? (Check top three for Now and top three in 2 years)

Part 2: DATA COLLECTION & ANALYSIS TACTICS

6. Shop Floor Systems, ERPs are Primary Data Sources

Q: What are the primary sources of your manufacturing data today? (Check all that apply)

7. Pandemic Makes Supply Chain Analytics a Priority

Q: Has capturing and analyzing certain types of data become more important to your organization in the wake of the COVID-19 pandemic? (Check all that apply)

8. Gap Lies Between Data Collection and Application

Q: What is your estimate of percent effort to gather and organize data relative to the percent effort to analyze, derive insights, and apply those insights to creating value from that data? (Select one)

9. MS Excel Still Leads as Data Analysis Tool

Q: What systems do you use to analyze the manufacturing data you collect? (Check all that apply)

10. Checking Up on Data Accuracy, Quality

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

Part 3: ORGANIZATIONAL DATA MASTERY

11. Matching Data Collection to Business Needs

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

12. Data Analysis Sees Room for Improvement

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

13. Data Leads More Decisions, More Often

Q:How often would you say your organization makes data-driven decisions? (Select one)

Part 2: DATA-DRIVEN OUTCOMES & CHALLENGES

14. Data Boosts Productivity, Lowers Costs

Q: How has the increase in manufacturing data
helped you to improve your manufacturing organization? (Check all that apply)

15. Quality, Speed of Decision-Making Improves

Q: How has the use of data affected your
company’s decision-making? (Check all that apply)

16. Data Capture, AccessRemains an Obstacle

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

17. Most See Data Mastery as Essential to Competitiveness

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

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

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.