Digital Transformation (DX) is a broad business strategy to solve traditional business challenges and create new disruptive opportunities using digital technology – such as maximize revenue, reduce cost, improve quality, and increase flexibility. Use cases range from asset optimization to workforce productivity to industrialization.
Why Manufacturers Need Digital Transformation
To remain competitive, DX for manufacturers is a necessity. Global market intelligence firm IDC predicts that in 2025 global DX spend among manufacturing industry companies will total more than $816 billion. Forrester Consulting found that more than 90% of manufacturing leaders believe that DX is important for their success. Clearly there is a lot at stake and developing a DX strategy is critical to capturing the most value.
The range of opportunities for DX in manufacturing is both a positive and negative. On the one hand, for whatever challenges facing an organization, there is likely a solution out there to address it. But manufacturers are faced with dozens of challenges. Such initiatives are usually driven by a scattergun, technology-driven approach. Ultimately, this results in resources being misdirected and just a small set of initiatives driving true transformation. Instead, companies must employ a laser-focused approach, that emphasizes impact, speed, and scale.
Manufacturers that have successfully adopted DX strategies are more efficient than their competition. That efficiency may be generated by greater worker productivity, asset uptime, better cross-organizational collaboration, or other DX opportunities. Ultimately, regardless of how efficiency is gained, it can be leveraged to increase revenue and/or reduce costs.
Achieving Transformation with Impact, Speed, and Scale
Regardless of the many different challenges an organization faces and the many different solutions on the market, there are fundamentally four objectives for manufacturers that have not changed: maximize revenue, reduce cost, improve quality, and increase flexibility. Impact, speed, and scale are the three key success factors for delivering transformational outcomes, and each must be tied to at least one of the objectives. Here’s how:
Impact – Focus resources on the most important constraints to drive P&L. Based on the dynamics of an industry and strategic roadmap, manufacturers should determine which of the fundamental goals are most important to improve upon and which are most likely to impact these goals in order of their criticality to the business.
Speed – With impactful opportunities identified, attention should turn to speed and scale. Quick wins can make or break a good initiative by building early, positive momentum. A quick win will generate team buy-in and can be leveraged for greater executive support. This rapid time to initial value is best achieved with proven off-the-shelf solutions.
Scale – Scalability must be considered early. No initiative should take place without a comprehensive and actionable scaling plan. If a project is slow to scale it is more likely to lose support and fold. If it cannot scale, then it is not delivering transformational value. The most reliable way to build a scalable plan is to model it after approaches that have already proven to be successful. The key here is finding repeatable use cases, that check off the high impact requirement and can be deployed with off-the-shelf solutions.
A recent PTC survey found that there is a stark difference between the companies that succeed in DX and those that do not. Companies that meet ROI goals expectations beat them by an average of 50%; those that fail miss expectations by an average of 30%.
This insight underscores the requirement for strategic DX for manufacturing organizations, and the PTC Impact, Speed, and Value Framework described here creates a foundation for DX success.
Will Hastings is Director of Product Marketing, PLM for PTC.
The Manufacturing Leadership Council recently partnered with EY for a two-day event focused on preparing for the future of manufacturing. Hosted at MxD in Chicago, Ill., the event focused on data-driven manufacturing and included a tour of EY’s Digital Operations Hub, several discussion panels and presentations, and a collaborative workshop.
Diving deep into manufacturing at EY’s Digital Operations Hub: Day one featured a round-robin visit to a selection of experience modules within the EY Digital Operations Hub. Participants had the option to visit five of the hub’s 31 modules where they heard about topics including workforce upskilling, intelligent demand forecasting and planning, digital performance management, digital worker enablement, edge computing, and more.
As participants made their way around the Digital Operations Hub, led by EY’s Mark Heidenreich, who leads the Digital Operations Hub, EY’s expert team and partners shared a deep dive into each topic, demonstrating the latest technologies and thinking on this important array of manufacturing topics.
Focusing on the future: The second day of programming kicked off with a conversation between David Brousell, MLC’s Co-Founder and Executive Director, and Scott Dixon, EY’s Managing Director – Advanced Manufacturing Technology Leader. The topic at hand was MLC’s latest white paper, The Next Phase of Digital Evolution and what it tells us about the future of manufacturing.
The two focused on data and its important role in manufacturing. While data may be difficult to get to – particularly on-demand – it is an important driver of decisions and value. However, they cautioned that data collection doesn’t equal success. Instead, Brousell and Dixon urged organizations to balance resilience while adding complexity. Brousell recommended that organizations not focus on data’s ability to “knock down silos.” That phrase, he warned, can be scary for subject matter experts. Instead, he recommended weaving silos together so that systems are integrated and domain expertise can be maintained.
Becoming data-driven: Next up, the event covered the top challenges for data-driven manufacturing with a presentation by EY’s Sachin Lulla and Amy Burke, the Americas Consulting Sector Leader – Advanced Manufacturing & Mobility and Advanced Manufacturing & Mobility Markets Leader, respectively. With a survey of 400 manufacturing companies as its basis, the presenters shared how only 10% were experimenting with digital, while only six percent were tackling digital at scale.
Throughout the conversation Lulla and Burke emphasized the need to put humans at the center of any transformation, building digitization and operational excellence around that core. For Lulla, the purpose of technology is to augment human intelligence. The pair agreed that starting with an end goal in mind is important when formulating a data strategy. The organization and employees need to know “the why” behind the data collection and use.
Further, Burke and Lulla recommended that organizations should not just look at gaps in their current workforce, but at what employee skills exist on the team and how upskilling and a learning environment can cultivate a fertile ground for data to be used successfully.
Driving digital with data: Pfizer’s Vice President of Digital Manufacturing, Mike Tomasco, was on hand to share how the pharmaceutical and biotechnology company uses data-driven decision making to create value. Tomasco shared how the company’s initial failures with capturing and using data led to significant successes and allowed Pfizer to move beyond pilot purgatory to large-scale transformation.
Moving beyond: The idea of moving beyond pilot purgatory was explored further to start the final panel discussion moderated by Brousell. Panelist Jim Fledderjohn, Dell’s Manufacturing Vertical Field Director, advised organizations to align pilots to the bigger strategic vision and fail fast. According to fellow panelist Terry Davenport, Rheem’s Executive Vice President, Global Operations, leaders should use the scientific method to learn from pilot projects and prove the value before scaling. From a collaboration standpoint, Microsoft’s Americas Regional Business Lead – Manufacturing, David Breaugh suggests that cross-functional teams help keep an eye on the big picture and unlock insights faster. Meanwhile, James Zhan, PTC’s Vice President, Market Development, IoT Solutions cautioned the audience not to focus solely on pilot purgatory and to be sure to keep an eye on workforce skills purgatory.
The panel also tackled the topic of data measurement, with Fledderjohn urging organizations to be selective about what data they collect – a proactive strategy that will help ensure the data is used and useful. Any process should have a metric that makes things faster, safer, eases worker burden, and offers higher quality and cheaper outputs, added Davenport. To that end, panelist Steve Pavlosky, GE Digital’s Vice President of Product Management, shared that GE shifted its technology roadmap to help customers move data into a single system so operators could make decisions quicker.
Capping it off with idea sharing: The event was capped off by a series of collaborative breakout sessions during which participants brainstormed go-forward ideas and feedback around the topics covered throughout the course of the entire event. Beyond the content that participants absorbed throughout the event, the breakouts gave them a chance to add their own two cents to the discussion, share their own experiences, and take away new perspectives that can be applied to their organizations.
Visit https://www.mxdusa.org/partners/ey/ to learn more.
All photos courtesy of EY.
If you were looking for a dose of optimism to counter the troubling reality of the post-pandemic world, you could do a lot worse than turn to the start-up community. Even in the best of times, the odds are stacked ruthlessly against anyone considering starting a business. And these are hardly the best of times. Yet new ideas and the magic combination of hope and conviction that supports them, continue to pour forth in a torrent. According to the U.S. Census Bureau, Americans started 4.3 million businesses in 2020, a 24% increase from 2019, and by far the biggest number in a calendar year in the previous decade and a half.
As an investor, and a mentor for Creative Destruction Labs (CDL) I meet a lot of founders, and I watch a lot of introductory pitches. And while the enthusiasm is ever-present, it is not uncommon, after the founder has left the room, for those who have just watched the pitch to turn to one another and say something like: “I still don’t know what they actually do.”
The effective communication of a new product’s value and function is, I believe, the biggest challenge facing any start-up founder. This is about knowledge transfer. It is a prerequisite of every progressive step the company hopes to take. And it is particularly difficult for companies that are bringing to market – either as a core product or as part of a wider service or solution – a complex mechanical object (CDL focuses on science and technology start-ups).
These founders have to convince investors to fund their project; they have to explain defensible intellectual property to patent attorneys and granting authorities; they have to communicate requirements to sub-component suppliers and manufacturing partners; they need to convince buyers and users that the product can deliver; they must ensure anyone responsible for maintenance and repair knows exactly what’s required to keep it operational.
That is a broad audience, each with a specific set of knowledge transfer needs. So to be effective, communication needs to be highly versatile, and to deliver absolute clarity through the most efficient processes. If this capability isn’t baked into the organization from the outset, the best case scenario is that the challenge scales as the company becomes successful, creating a much bigger problem which can have a direct impact on operational KPIs.
As products come to market they bring with them a host of documentation and content requirements associated with that knowledge transfer. Creating and maintaining this content is a huge task and one that can easily become a bottleneck. If the content isn’t ready, the product can’t be promoted or sold. If it isn’t completely accurate, if it’s hard to access, if doesn’t tell the full story, you could be looking at fabrication or maintenance errors and costly downtime.
Advances in manufacturing technology – the adoption of agile workflows and additive manufacturing – actually make things worse. These processes accelerate product development and iteration, making the documentation and content bottleneck even more damaging.
Macro realities compound the problem yet further. Once upon a time a new company would start by bringing a core team together at a new premises. However, full-time, on-site work looks like a thing of the past. Studies suggest 70% of the workforce will remain working remotely five days per month by 2025 with others opting to work part-time on-site and part-time at home. And, in any case, start-ups tend to rely on a distributed ecosystem of product and service suppliers from the outset, for obvious reasons.
And according to a 2020 McKinsey report, Unlocking growth in small and medium-size enterprises, SMEs have innate productivity challenges, exacerbated by lack of access to high-cost enterprise software solutions. So, to ensure effective communication – to give themselves the best possible chance of success – start-ups today must find a way to drive effective teamwork and collaboration among a distributed workforce and ecosystem, at an affordable price point, all while driving productivity, in order to become competitive.
But start-ups have an advantage. Their primary strength in addressing these challenges is their capacity for continuous innovation, not just in terms of products and services but also – crucially – in terms of processes. This owes a huge amount to that optimism which got them started on the journey in the first place. According to McKinsey, “Because they are unhindered by legacy systems and outdated strategies, new market entrants are often able to rethink established practices and cut through traditional industry boundaries.”
Here’s a great example: Impossible Sensing is a CDL alumnus that develops and manufactures autonomous exploration tools designed to function in extreme environments from deep ocean to deep space. Their products are used to detect valuable minerals in off-planet environments. Prior to the pandemic, Impossible Sensing’s founder used 3D-printed models to enable prospective buyers – a Mars scientist at NASA, for example – to get a tangible sense of the firm’s products.
Restrictions on face-to-face meetings put an end to that, leaving this CEO suddenly missing a key part of his sales pitch. He overcame this by using interactive 3D communication which allows customers to play with the 3D models of his product (the closest thing to handling that 3D-printed object) wherever they were located. Video calling is great for replicating the conversation, but there are a number of critical communication experiences that it simply cannot deliver.
Many people might have focused on the frustration of being unable to continue to operate as they had before. But the start-up’s optimism will always find another way.
A start-up’s Big Idea is only as good as the extent to which it can be understood by everyone whose participation is required to make it successful. Get in front of that effective communication challenge as early as possible – solve that knowledge transfer problem across the board – and not only will you be giving yourself the best possible shot at success, you’ll be future-proofing your business against problems which can undermine you as you grow.
About the author:
Patricia Hume is Chief Executive Officer of Canvas GFX.
About 100 Manufacturing Leadership Council members, associate members, guests, and staff descended on Lexington, Ky., in November for a tour of Schneider Electric’s smart factory – a 65-year-old brownfield facility that showcases artificial intelligence, augmented reality, remote monitoring, and predictive maintenance.
The factory was recognized in 2020 as a Fourth Industrial Revolution Advanced Lighthouse by the World Economic Forum (WEF) and later as a Sustainability Lighthouse, one of only ten globally and the first of two for Schneider Electric. It is one of several Schneider Electric factories to achieve this designation, and the company’s first on U.S. soil. Schneider Electric, a 180-year-old company, had E28.9 billion in revenues in its 2021 fiscal year. The company provides industrial automation and control, energy management, and building automation and control products and services.
What They Saw: During the 11-stop tour, participants experienced the complete breadth of Schneider Electric’s manufacturing process. The Lexington smart factory houses a complete, vertically integrated process including a typical assembly line, conveyance, fabrication center, paint room, and more – all connected through Schneider Electric’s Industrial Internet of Things-based (IIoT) EcoStruxure platform.
The tour showcased how Schneider Electric’s digital transformation increased energy efficiency and reduced downtime. AVEVA and Schneider Electric partner on integrated digital transformation solutions that bring together energy management and automation tools with industrial software. In Lexington, the company utilizes both its EcoStructure and AVEVA platforms throughout the facility. For example, at tour stop nine participants saw how the EcoStructure Lean Digitization System calculates true labor efficiency with e-performance and e-andon — digital data-sharing and production monitoring of performance and defects for immediate response. Meanwhile at stop seven in the paint room, the group learned how AVEVA Edge processes data and populates the company’s dashboards in real-time.
In a fascinating application of AI and machine learning, the company has set up a 5G networked camera to photograph and analyze every link in the mile-long conveyer chain. The photos are then automatically compared to thousands of images of broken and unbroken chain links, and the AI-powered system identifies broken and breaking links that need to be repaired and relays this information to the operator.
Insights from Digital Subject Matter Experts: Beyond the smart factory tour, participants joined breakout sessions where they heard directly from Schneider Electric experts about hardware and software tools used in the company’s digital transformation journey to help breakdown data silos and empower employees to make effective decisions at the gemba – the real place where they do their work. Breakout topics included Smart Factory Execution, EcoStruxure Deep Dive, EcoStruxure & Industry Automation, Cybersecurity and Operations, Advanced Analytics in Supply Chain, and Supply Chain Sustainability.
Unfettered Access to Company Leaders: The day ended with a discussion panel during which Schneider Electric leaders answered questions from both the audience and moderator, Jeff Puma, MLC’s Content Director. The panel featured Greg McManaway, Business Process Leader; Fabrice Meunier, Vice President, Industrial End User, System Integrator and Software Business; Anand Varahala, Environment and Sustainability Manager; and Bharat Virmani, Vice President, Supply Chain Performance and MTS/MTO Cluster. The panelists shared their insights on topics including the factory’s digital transformation journey, the WEF Lighthouse process, setting priorities, and scaling digital advances.
A Chance to Rub Elbows: In addition to witnessing the innovations and smart factory implementation at Schneider Electric’s Lexington facility, the tour offered an opportunity to interact with nearly 100 industry leaders in attendance including digital pioneers from both the host company and other MLC member companies. Like all MLC tours, the formal and informal networking opportunities allowed participants to ask questions, discuss hurdles, and seek solutions from other participants on the digital transformation journey. These relationships are invaluable to members’ efforts to expand their connections and Manufacturing 4.0 understanding.
All photos by Ian Wagreich; Copyright: capitolhillphoto.com
When toddlers learn to stack blocks, they learn by trial and error — often with immediate feedback from a parent or other adult. It is a model-free learning process, or reinforcement learning, that does not require them to learn Newton’s equation to figure out how to stack the blocks.
For Dr. Hiroaki Kanokogi, Yokogawa Digital Corporation’s President and CEO, reinforcement learning (RL) in artificial intelligence (AI) has direct uses in a manufacturing environment. In fact, as Kanokogi shared during the Manufacturing Leadership Council’s Manufacturing in 2030 Project: Let’s Talk About AI event, RL was a building block when Yokogawa used AI to autonomously control a Japanese chemical plant for 35 days earlier this year.
In his presentation at Let’s Talk About AI, Kanokogi shared that there are serious challenges to applying RL to real world manufacturing. First, he said, traditional RL takes 1 million to 1 billion trials to go beyond human learning, and second, manufacturers must include safety assurances.
To overcome the first of these challenges, Yokogawa and the Nara Institute of Science and Technology developed scalable reinforcement learning called Factorial Kernel Dynamic Policy Programming (FKDPP) specifically for plant control. FKDPP allows for faster learning (typically in about 30 trials) and robust protection against disturbances. Yokogawa was able to demonstrate that FKDPP can autonomously stabilize water levels in a fundamental three tank level control experiment significantly quicker than traditional proportional-integral-derivative (PID) control.
At Let’s Talk About AI, Kanokogi shared four videos that chronicled FKDPP’s iterative attempts to stabilize the water. In the first iteration, AI does not know anything yet, so when the valve is opened the water level goes all the way up. In the 20th iteration, AI can control the water in a somewhat stable manner, but it varies and resembles a human’s performance on the task. For the 25th iteration, AI learns how to regulate the variation. By the 30th iteration, the FKDPP perfects the process. Kanokogi pointed out that this final iteration demonstrated that once AI finds a good way, optimization of this process is AI’s strength.
For the second challenge around safety assurance, Yokogawa was able to prove AI can satisfy this need during this year’s 35-day autonomous factory operation. The company first built a good simulation model by using domain knowledge in a digital twin so the AI could learn. Step two called for simulation and evaluation using both past and live data. Finally, the company ensured safety and control in the actual plant using Yokogawa’s integrated process control system, CENTUM™ VP DCS.
For Yokogawa and its autonomous operation, Kanokogi reported that he and his team continue to look at problems in the factory where AI can be applied. While the first-of-its-kind, 35-day automation demonstration is truly impressive, he sees manufacturing working in an autonomous plan-do-check-act (PDCA) loop by 2030. This loop will run continuously, and AI will help the plant improve itself. While there is no need for human intervention during this loop, Kanokogi pointed out that AI cannot add new sensors or integrate new technologies, so human experts will maintain a defined role in manufacturing.
Like a toddler with blocks, autonomous factory operation might be in its nascent years, but with the help of AI and Yokogawa’s FKDPP technology, maturation by 2030 is possible.
Manufacturing in 2030 Project: Let’s Talk About AI was held Dec. 7-8, 2022 in Nashville, Tenn. The event was part of MLC’s Manufacturing in 2030 Project.
AI will become a key player in driving manufacturing competitiveness in the years ahead.
David R. Brousell, Co-founder of the NAM’s Manufacturing Leadership Council, called on all manufacturers to accelerate their understanding and use of new Artificial Intelligence (AI) technologies in his opening speech at the MLC’s latest Manufacturing in 2030 event, Let’s Talk About AI, in Nashville, Tenn., this morning.
“The stakes for our industry and our country couldn’t be greater as our economy becomes increasingly digital,” asserted Brousell. “Global competition for dominance in AI is underway, with manufacturing as a key player in the race. Our competitiveness as an industry at home and abroad will increasingly be defined by AI expertise, application, and experience – and in a trusted and responsible way.”
Technologically, he noted, AI is finally coming into its own after a long development period and researchers now estimate that the value of the global AI industry will rise rapidly from $93.5 billion in 2021, to a substantial $1.8 trillion by 2030.
AI is also a pervasive technology, he continued, meaning that it will be incorporated into many other technologies including semiconductors, software applications and platforms, and communications equipment. It will increasingly power the operation of front-office applications, ERP, PLM, MES, CRM and other key operational applications. Robotic systems, too, will increasingly be guided by AI.
And although only 9% of respondents to a recent MLC study said that they saw AI and ML as a game-changer for the industry today, by 2030, 53% said that they believed it would indeed become a game-changing transformative force.
Citing a U.S. Patent Office report from October 2020 that stated, “AI is poised to revolutionize the world on the scale of the steam engine and electricity”, Brousell stressed that’s why manufacturers now need to better understand how AI may shape how they run their factories and plants, how it will influence their workforce strategies, what business benefits may attend AI use, and what challenges the industry must overcome to realize its potential in the years ahead.
However, “as with any important technology,” he added, “let alone one as unique as AI, there will be a learning curve replete with twists and turns.”
One of those twists is the fact that AI remains a controversial technology. Some see it as an existential threat to humanity; others see it unleashing a new wave of productivity and efficiency and enabling people to have better and more rewarding business lives.
Brousell also believes that AI’s unique ability to learn, and what that ability implies for predicting machine and operational patterns and behavior, qualifies it to be “in a special place among all of the technologies associated with digital transformation.”
“I can’t think of another technology that we have employed in our factories and plants,” he added, “that requires us to ask the question: do we need a code of ethics for AI use?” According to recent MLC research, he noted, 75% of manufacturing executives already believe a code of ethics will be needed in the years ahead.
Nevertheless, predicted Brousell “AI is here to stay”, and that its influence will only grow in operations, in the workforce, in the interactions across supply chains, and with customers and partners in the years ahead.
“AI”, he concluded, “is truly a force to be reckoned with” for the future of manufacturing, and manufacturers now need to act with urgency to accelerate its adoption to drive competitiveness in the years ahead.
With the recent release of the Manufacturing in 2030 Project survey A Lens on the Future, MLC assembled an expert panel of speakers to discuss the results and bring context to the survey findings.
Moderated by David R. Brousell, the MLC’s Co-Founder, Vice President and Executive Director, the panel included Dennis McRae of West Monroe, Greg Wagner of EY, Chirag Rathi of Infor, and Joe Zakutney of NTT DATA.
Here are ten key takeaways from the discussion:
1. 84% of survey respondents expect an increased pace of digital adoption in the next decade
Dennis McRae, West Monroe’s Senior Partner and Practice Leader, Consumer & Industrial Products, noted that the acceleration rate depends on the size of the company, but he said the biggest thing is if you haven’t started your Manufacturing 4.0 journey in a meaningful way, now is the time to do it to maintain competitiveness.
“One of the first things you can do is really establish a team focused on digital with the right leaders, the right innovators, and also the right disruptors who can really challenge and do what leadership needs to get done,” McRae said.
2. 58% of survey respondents have autonomous factory operations on their radar by 2030
Chirag Rathi, Senior Director, Industry and Solution Strategy at Infor, pointed out that the desire for autonomous operations is not new and that General Motors was talking about this in the 1980s. Citing deep-learning and self-learning algorithms in machine learning, digital twins, blockchain, and autonomous transportation, he sees autonomous operation as a game changer, but he cautioned that full autonomy is unlikely in many circumstances.
“The cost of doing full autonomy in most industrial manufacturing processes might be too high,” he said. “So you will have part autonomy in several manufacturing arenas where the business case makes sense, but it will be a decision made on a case-by-case basis.”
3. 76% believe manufacturing should adopt an AI code of ethics
For Joseph Zakutney, NTT DATA’s Vice President, Manufacturing Industry Consulting and Digital Transformation, thinking about AI’s future means protecting against biases and cyberattacks, while accounting for safety.
“Procedures will need to be put in place to make sure that we’re complying to [a code],” he said. “We need to make sure that the software that we are releasing is fair, reliable, explainable, takes data protection and government regulations into consideration, and is focused on the well-being of society.”
4. Almost half of respondents indicated they expect workforce shortages to continue through 2030
Traditionally, manufacturing doesn’t have the best image according to Greg Wagner, EY’s Data Driven Manufacturing Leader. It is considered dirty, loud, and can be physically intense at times, but Wagner pointed out that those seeking purpose-based work should be attracted to manufacturing. The old adage of “being a cathedral maker and not a bricklayer” fits here, according to Wagner.
“If we change the paradigm and what we’re looking for, the types of job experiences we can give people, and use automation to get rid of some of those menial tasks that people don’t enjoy and free up their capacity to focus on bigger problem solving, it will mean more impactful types of roles,” Wagner said. “That’s going to really start to attract people and start to soften some of that gap we see right now in hiring.”
5. 81% of manufacturers are looking for greater speed and flexibility
When we think about speed and flexibility, what people really want is responsiveness, according to Wagner.
“If we really want to be able to respond quicker, we need to know what’s going on and we need to invest in better end-to-end visibility of what’s happening within our factories and what’s happening across our network so that we can be more adaptive and have the right insights to drive that change,” he said.
McRae added, “There’s a big opportunity for manufacturers in terms of connecting with their customers, building that client experience, and really monetizing a lot of the data that’s already in the business.”
6. By 2030, 50% of respondents believe digital adoption will be a game changer.
For Rathi, we’ll be closer to Industry 5.0 by 2030 with hyper-customization, responsive and distributed supply chains, and business model innovations. In fact, Rathi said we already have the building blocks to make this a reality.
“We have certainly got a lot of the raw materials to make that transformation happen,” he said. “So we will have a lot of transformative changes by that time period.”
7. Digital acumen is important across functions and at various leadership levels
One challenge McRae sees is getting everyone on the same page using the same language so that data assets are understood across company levels by all who manage data and products in the business.
“It’s not just around different levels, but also across functions,” added Wagner, noting that there is a wide array of digital understanding and how those technologies can be applied.
8. Hiring for a digital background versus a subject matter expert depends on the project
“I think we’re seeing the rise of data scientists and citizen data scientists at some organizations. At the same time a lot of data DIY products are becoming available, and they will become more prevalent by 2030, meaning that people with subject matter expertise will be able to basically design and develop their own data science projects,” Rathi said. Because of that, he believes subject matter experts will be in higher demand in most cases vs. data scientists.
9. For companies slowing down their digital projects due to the economy, focusing on specific things can help prevent losing ground
“Digital adoption is really a people play right now,” said Zakutney. “I’d stay focused on people and process, because ultimately, that’s what you’re going to end up automating [when funding comes back].”
“You can’t quit your digital investments,” added McRae. “If you don’t become digital, you’re going to be left behind. At the same time, prioritizing those digital investments specifically around areas that are going to improve your customer experience and take costs out over the next few years are going to help you win.”
10. Beyond the panel discussion, the survey report provides insightful data about the future of manufacturing
The MLC’s Manufacturing in 2030: A Lens on the Future research survey includes front-line insights from over 260 senior manufacturing industry executives, spanning multiple functional roles, and representing large-, medium-, and small-sized manufacturing companies from multiple industry sectors. Armed with this rich combination of real-world predictions and forward-thinking understandings, the MLC hopes that manufacturers can better plan their longer-term future and find ways to enhance their value, competitiveness, and contribution to society. Download the complete survey data and report.
The manufacturing industry has spent a lot of time, effort and money on making its processes more efficient over time. And now the industry is investing in the Industry 4.0 philosophy to minimize wastage and downtime, leveraging technologies including 3D printing, digital twins, and predictive maintenance. Powering all of these investments is data.
Late last year I had a number of conversations with manufacturing professionals who manage products throughout their lifecycles – from the 3D CAD design phase, through review, fabrication, sales and marketing, and even further into customer usage and after-sales. They each told similar stories of breakdowns in the processes for creating, distributing, and consuming content that transfers vital knowledge about their products. In addition, they all identified significant negative impacts stemming from these problems. Errors, delays, and missed sales opportunities were frequent complaints.
I came away wanting to know more about these problems, their outcomes, and the underlying causes. What is driving ineffective product documentation workflows and processes at organizations that otherwise appear to be investing heavily in efficiency-based initiatives and cutting-edge tech?
In a bid to find out, my company, Canvas GFX, surveyed over 500 manufacturing professionals across a broad range of verticals, including automotive and electric vehicles, aerospace and defense, new space tech, industrial machinery, and more. The results showed these challenges exist widely across the manufacturing sector, suggesting an endemic and interconnected problem.
We’ve dubbed this problem Product Communication Disorder. For many companies, Product Communication Disorder is perceived, managed – and often tolerated – as a series of departmental workflow challenges. The data suggests the problem cannot be solved unless assessed and addressed with a company-wide perspective.
Where have manufacturers gone wrong?
There are three distinct stages within documentation and knowledge transfer where problems arise, the first being the creation of product content.
As it stands, creating product communication content is time-consuming and complicated, requiring input from multiple team members across an organization. Our research highlighted how critically deficient current workflows are, with clear room for improvement. The stats lay the issue bare, with over 95% of manufacturing industry professionals reporting that projects or products at their company had suffered errors or delays as a result of inefficient workflows for the creation of product communication.
But the problem runs deeper than content simply being late or too time-consuming to create. While the data says these are both true, our survey also suggested that the processes underpinning the creation of content are themselves flawed. For more than one in three respondents (36%) workflow bottlenecks stemmed from too many people being involved in content creation. Meanwhile, the lack of skills or software needed to be able to properly visualize 3D models, the basis for many documentation illustrations, was cited by one third of respondents.
Collaboration is another area fraught with challenges. In fact, 73% of respondents in our survey said they had experienced product or project errors or delays in the past two years as a result of difficulty collaborating on content.
Just as content creation at manufacturing companies is fragmented in terms of departments, skills and software, the collaborative process also appears to want for some kind of central management. According to almost three quarters of survey respondents, a primary problem appears to be too many channels (including email, Microsoft Teams, Slack, and other voice and video calling solutions) being used to manage collaboration, review and feedback on product content. The result of this vital communication happening across a range of channels according to 3 in 4 respondents is that it is easy to miss feedback on important documentation and content.
Lastly, the survey revealed serious concerns around the ability of workers to access the most up-to-date documentation materials. For many organizations this appears to be a struggle, while the problem is aggravated by managing a range of different content formats. It’s vital to remember that consuming content is what this entire process is about.
Worryingly, 85% of respondents said that outdated documentation in circulation had resulted in errors and delays over the last four years, and over a third (36%) said their company struggled to manage the rate at which content becomes outdated. More alarming still is the large proportion of respondents who conceded that their company has difficulty ensuring everyone who needs access to content is able to access the most up-to-date version of each document (54%).
Solidifying Industry 4.0 gains
The overarching issue is that manufacturers spend heavily to update their processes to reduce defects and ensure products make it to market on time, documentation issues are continually undercutting those investments.
Perhaps the starkest illustration of the problem lies in the fact that 73% of respondents felt that inefficiencies in their product communication processes were undermining gains made through other technology initiatives.
But it’s not all doom and gloom, and there is a silver lining here. The findings pointed to evidence that manufacturing companies are looking to cure the problem, rather than simply manage the pain. While the data is clear, so are the actions companies can take.
By addressing their problems in product documentation, companies can take a huge leap in realizing the full potential that Industry 4.0 offers and maximize their investments in it.
About the author:
Patricia Hume is Chief Executive Officer of Canvas GFX.
Though once considered a radical concept in the eyes of some, the necessity of digital transformation is now embraced by most organizations. The question is no longer whether to digitally transform — it’s now how to do it. But often, those discussions focus myopically upon the technologies involved.
That’s a mistake.
People, after all, are the ones driving change. Technology is the tool they use to do so. If the attitudes, behaviors and goals of your organization’s people — your culture — are not on board with your digital transformation goals, your transformation will likely fail even if you have the right technology in place. Having clear alignment between your technical objectives and your company’s culture is essential for success — in fact, organizations that take a human-centric approach to digital transformation are 2.6 times more likely to see success.1
Five common business blockers to cultural change
There are several common stumbling blocks that may significantly impede your progress along the path to digital transformation. The most vexing challenges revolve around five key cultural issues:
- Organizational data isolated in functional or hierarchical silos.
- A lack of the skills needed to enable digital transformation.
- The breakdown of inter-team communication and collaboration.
- Cultural resistance to change rooted in lack of understanding of transformation goals.
- Fear and worry about job insecurity, or a lack of psychological safety, among employees.
Any one of these cultural barriers presents a significant speed bump to the transformation process. The presence of all five within a single organization — not an uncommon scenario — wreaks havoc upon an organization’s efforts to transform.
Stepping over those stumbling blocks
Transformation undeniably involves change — and change and human nature often have a stormy relationship. People tend to resist change, particularly when it makes them feel isolated or left behind. How can companies overcome these stumbling blocks to enable and encourage cultural change in support of digital transformation? The answer involves a mix of technology and people-centric management.
To eliminate data and skillset silos without disrupting your key business processes, you need to gradually build cross-functionality across teams. Consider using tools and techniques such as Kaizen (a management strategy that supports ongoing, incremental change), which many organizations have found to be crucial for success. A top-down commitment to opening silos is equally important; however, the true key to breaking down silos is about understanding, engaging and promoting collaboration across both the formal structures and the informal networks that exist across the organization.
Recently, research has found that the key to identifying and engaging these informal networks is by identifying influencers across an organization and engaging with them. Each silo represents a comfort zone for the group of employees that operates within that silo, and employees may be reluctant to move away from those comfort zones. By activating networks across the organization, company leadership can promote collaboration without incentivization.
Similarly, it’s essential to nurture teamwide collaboration and communication in ways that are nonthreatening to individuals and team cultures. While specialized skillsets and knowledge specific to a team (or even a single task) is valuable to the entire organization, individuals who hold that knowledge often consider themselves the owners of that knowledge — an ownership that they may be reluctant to surrender for fear of diminishing their own value. Commending employees for exceptional knowledge sharing and skill development creates a culture of collaboration while promoting candid communication.
Innovation culture and success factors for digital transformation
Leadership should also be sensitive to the language used in communicating transformation initiatives. Phrases such as “breaking down silos” can feel threatening to people working in those so-called silos. Functional areas with their own domains of expertise and knowledge exist for important reasons — and will continue to exist — so leaders should instead talk about “weaving silos together” to achieve cross-functional integration while preserving the benefits of domain expertise.
Adopting agile approaches serves to foster the evolution of cultural shifts across teams, enabling them to be more cross functional. Another tool that can be highly effective in breaking down a range of barriers to collaboration and communication — including differences in age, gender and ethnicity — is reverse mentoring, where younger employees are paired with executive team members to help those executives connect with a younger demographic. Creativity, too, is important when it comes to breaking down cultural cliques. Even discouraging teams from keeping to themselves in settings like company cafeterias can be effective.
Finally, executive leadership, like all other members of the organization, must also evolve. They must embrace the goals of transformation and become comfortable with the higher levels of ambiguity that characterize today’s marketplace.
That said, technology does play a major role in supporting digital transformation initiatives. The right technology can make all the difference in fostering the cultural shift necessary for successful digital transformation. Today’s digital tools can guide effective collaboration, enhance efficiencies, enable standardization and encourage innovation. For example, Hitachi designed a cross-functional 2-day Smart Manufacturing Solution Envisioning Workshop for Logan Aluminum that helped key employees better understand the benefits of specific digital transformation initiatives.
Transformation is really about people
Business organizations are often perceived as lifeless, faceless entities. But in truth, each organization is a collection of people — people who must work together to make the business successful. That’s why it’s so important that everyone in your organization is on board with both the processes and goals of transformation.
Ultimately, fostering positive cultural shifts among your people is the best way — and, realistically, the only way — to ensure that your digital transformation goals can be achieved. Because, in the end, digital transformation is all about your people; a journey begun for your people and achieved by your people.
Hitachi’s Social Innovation imperative is all about unlocking value for society through the power of technology and people. For more tips about getting ahead by thinking ahead, visit our Social Innovation page.
About the authors:
John Brinegar, Director, IoT Solution Architecture, Hitachi Vantara
John Brinegar leads the Solution Architecture team at Hitachi Vantara, and has been leading IIoT projects at Hitachi customer sites for eight years. In addition, Brinegar led the architecture, development, and launch of Lumada Manufacturing Insights, an analytics platform for optimizing performance, maintenance and quality operations. He has extensive background deploying analytics systems into a variety of manufacturing sub-verticals, including electronics, pharma/biotech, metals, automotive, and others, along with IIoT software development and integration in telecommunications, health care, and enterprise markets.
David R. Brousell, Co-Founder, Vice President and Executive Director Manufacturing Leadership Council
David R. Brousell is the Co-Founder, Vice President and Executive Director of the Manufacturing Leadership Council, the digital manufacturing arm of the National Association of Manufacturing, the largest association of manufacturers in the United States.
In his role as head of the MLC, Brousell sets the strategic direction of the organization and oversees day-to-day activities across the MLC’s portfolio of live and virtual events and thought-leadership content generation. Brousell is a member of the NAM Leadership Team and is also a member of the MLC’s Board of Governors. In his more than 40-year career, Brousell has served in numerous leadership positions in companies large and small.
1Errol Gardner, Norman Lonergan, Liz Fealy, “How transformations with humans at the center can double your success,” EY, June 24, 2022, https://www.ey.com/en_gl/consulting/how-transformations-with-humans-at-the-center-can-double-your-success.
Data mastery and AI are key drivers for the future of manufacturing, say industry experts during a discussion of the MLC’s new Manufacturing in 2030 Project white paper.
“Manufacturing is poised to unleash the next engine of production,” declared Manufacturing Leadership Council (MLC) Co-Founder David R. Brousell, in his opening remarks at the recent launch of the MLC’s white paper on the future of the industry, Manufacturing in 2030: The Next Phase of Digital Evolution.
The pandemic taught us, noted Brousell, that manufacturing needs to be able to act with greater agility and be better prepared for future disruptions, whatever form they may take. The MLC recognized the urgent need for manufacturers to take a longer view of things to come, he explained. The Manufacturing in 2030 Project has been created to help enable those companies to envision what manufacturing might look like by the year 2030, to better plan their future, and to help their leaders find new ways to enhance value, competitiveness, and their contribution to society.
Brousell was joined by a panel of industry experts from Manufacturing in 2030 Project partners EY, Infor, NTT DATA, and West Monroe, plus MLC Board Vice Chair, Dan Dwight, CEO of the Cooley Group. They went on discuss key highlights from the forward-looking 52-page white paper, which explores the multiple megatrends and industry themes that will dominate the manufacturing world by 2030, from demographic shifts and global economic trends to rapid advances in technology, new approaches to workforce development, and the importance of greater sustainability.
Optimism for the Future
“For me, there are three reasons for optimism about manufacturing’s future,” commented Randal Kenworthy, Senior Partner and Consumer and Industrial Products Practice Leader at West Monroe. “The levels of investment in digital solutions that we are already seeing in manufacturing, the widespread recognition that manufacturing is essential to the future of the U.S. economy, and the opportunity to address one of the most existential challenges facing mankind: climate change. We have to solve this. Failure is not an option.”
“I certainly think digital is going to be the way of operation for survival in the future,” added Baskar Radhakrishnan, Senior Director, Manufacturing Industry Solutions at NTT DATA. Many of today’s factories are almost unrecognizable from the way they were 10 years ago, he observed. “And the industry is only going to continue to evolve. So, I envision future manufacturing organizations to be data driven digital enterprises, fully hyperconnected, with more distributed, agile, and value-driven ecosystems.”
Highlighting the impact of the numerous disruptive forces at play today, Brad Newman, Advanced Manufacturing & Mobility Industry Market Leader, Americas, at EY, noted that, “The collective sum of all those forces is creating a bias for action and a need for change.” The industry already has the building blocks and the technology tools in place today, he continued, “which will help business models to evolve to ensure functions are more connected and help build better and smarter products for people in more sustainable ways. All of this will make the manufacturing industry much more rewarding for all the workers and stakeholders involved.”
The Challenge of Complexity
While the accelerated adoption of ever-more powerful and intelligent digital technologies over the next few years will underpin many of those transformational changes, the huge increase in the volumes of data generated by those technologies will have its own challenges.
“It may take another 10 years to get to real maturity with AI, but that’s the technology we can see being highly important for the future,” commented Andrew Kinder, Senior Vice President International Strategy at Infor. “There are fantastic opportunities around AI and it’s only just beginning. But I think one of the challenges of that transition is that we have to pay more attention to data.”
Traditionally, noted KInder, manufacturing has always talked about people, processes, and technology, but he believes that companies now need to add data to that essential mix. “We’re already good at getting data, at streaming it into data lakes, and we’re getting better at turning it into actionable insights,” he added. “But now we need to focus much more on how we mature our data mastery for the years ahead.”
“But before you get to data mastery,” argued MLC Board Vice Chair, Dwight, “you first have to go from legacy to smart tech. The next phase then gets more complicated as the amount of data compounds and we start to adopt new AI approaches with complex algorithms. To make that work, we first need to develop confidence that the data we are gathering is telling us the right story and that becomes more complex as data volumes increase and spread across the enterprise. To cope with that, manufacturers need to be constantly rethinking their business model.”
And it’s not just about rising complexity within the four walls of the company, added EY’s Newman. “The bigger picture is looking at the end-to-end value chain,” he said. “For example, digitizing the supply chain with more accurate forecasting and optimized planning puts pressure on companies along the chain to catch up. As supply chains become more intelligent and complex, companies will need to be more flexible and agile to create more scalable and responsive digital platforms.”
New Business Models
However, warned Radhakrishnan at NTT DATA, “digital will become yesterday’s advantage if organizations are not thinking about moving to the next level. They must think differently about their transformation initiatives so that the traditional ways of operating become a thing of the past. So, with the people, processes, and digital infrastructures they create using new digital technologies, manufacturers should think about reinventing their business models with outcome-based business models, or usage-based business models, or product as a service, and offering their customers more customized products and services.”
Yet that’s a big step for many manufacturers, noted the MLC’s Brousell, and for some it may be a little scary.
“But to me,” added Cooley’s Dwight, “all manufacturing companies, regardless of their relationship to M4.0, demand reinvention. To rest too firmly on last year’s expectations and commitments, prevents your ability to evolve. As I say all the time, the only constant is change – and I don’t mean incremental change.”
“At Cooley,” he continued, “we went through a deep cultural transformation to break down silos to drive collaboration with the objective to become more adaptive and more agile. But for companies who are not change driven, who have not been investing in digitization, who are not rethinking and reinventing, they are the ones who are failing to see the power of digitization and the power of transforming on a constant basis.”
Leadership Advice for the Future
Brousell concluded the discussion by asking the panel: ”What’s your most important piece of advice for manufacturing leaders as they head to 2030?”
“Put together your strategic vision and plan,” responded Kenworthy at West Monroe, “If you don’t have that strategic vision for 2030, you need to start thinking about it now. That will set your roadmap for your digital roll out and plan for the future.”
“I think there a number of dimensions,“ added NTT DATA’s Radhakrishnan, “Develop a fully integrated strategy with very clear transformation goals; leadership commitment all the way from the Board and CEO to middle management; having the right team of high caliber tech talent and subject matter experts; adopt an agile mindset that will drive the broader adoption of digital technology; track progress and measure well-defined success; and, finally ensure there are business-led, modular, technology and data platforms to enable the real transformation”.
“Leaders also need to focus on people,” suggested Infor’s Kinder. “The talent shortage is global and it’s not going to go away. Technology will help, of course, and there is already a change from location centric, to human centric, so leaders need to focus on the reduction or elimination of any non-value-added tasks when intelligent equipment can do that and leave humans to do the high value decision making work. Focus on the people and bring the people with you.”
“Building a digital business ecosystem is only going to reach its full potential when the entire organization is digitally driven, and driven seamlessly across traditional functional lines,” said Dwight. “As the white paper says: ‘Digital is agnostic about functional boundaries.’ I believe this transformation is going to be the most difficult piece of digital evolution that leaders are going to have to grapple with.”
EY’s Newman also added his final thoughts: “While the future will be centered on cross-industry collaboration,” he observed, “I look forward to seeing the manufacturing industry take the lead when it comes to innovating new business models and engaging ecosystems. I think our ability to do this will wildly change the trajectory of the industry, driving better investments across safety, sustainability, technology, and most importantly, the development of our people.”
* Download the full MLC White Paper, Manufacturing in 2030: The Next Phase of Digital Evolution
* Listen to the insights shared during the Manufacturing in 2030 White Paper Panel Discussion