Overlooking the potential of new business models for the future could create opportunities for your competitors in the years ahead to 2030.
It’s time for manufacturers to step up their game in the race to be ready for 2030.
That may sound harsh, given all that the manufacturing industry has done in recent years to prepare for the future. Digitization is everywhere as companies embrace the power of technology to meet the ever-evolving demands of the market. The idea that this isn’t the manufacturing industry of earlier generations has never been more true. Manufacturers have learned to connect everything and collaborate with everyone, to reduce complexity, empower the workforce, prioritize innovation and agility at scale, and build a broad, rapidly responsive, inclusive, and unified ecosystem.
And yet, it’s not enough.
The EY CEO Imperative Survey finds 70% of manufacturing sector respondents see technology and digital innovation as a transformation driver for their companies, while only 30% said the same of new business models. Contrast this with the technology sector, which is leading the way with almost twice the focus on business model innovation — and receiving significant investor credit for it. Overlooking the potential for new business models can create opportunities for competitors from adjacent sectors.
Manufacturers are in a powerful position to become leaders in their value chains1. Connected products are generating data rich with potential insights that can drive new services and new business models. Every day, competitors from inside and outside the manufacturing sector are forming ecosystems to manage, and profit from, new ways to deliver customer value. To take their seat at the table, manufacturers must be ready to reinvent their business models, or watch from the sidelines as others take control of their value chains.
Four Ways to Innovate
Manufacturers can thrive in a challenging growth environment by following some key principles to build, launch, and grow innovative business models. If companies want to shift from surviving to thriving, they need to turn their business model innovation intention into action, today. They can do so by building a foundation of innovation on four principles:
1. Strengthen relationships throughout the value chain
Business model innovation begins with bringing a growth mindset to identifying, understanding, and pursuing customers. While most manufacturers are naturally accustomed to considering both direct customers and consumers as key constituencies, leaders should assess all the links in their value chains to establish a comprehensive understanding of who in the chain is creating the most value and how. Doing so helps leaders align strategic decisions and resources to the needs of constituencies that will ultimately drive revenue growth. This also helps leaders broaden their thinking beyond the immediate next link in the value chain to include a wider range of value creation opportunities.
Manufacturing leaders need to transition from a product-delivery mindset to a value-generation mindset. Implementing these shifts within a company may require both structural and cultural adaptations to best generate value. Leaders must bring a fully open mind to the process of understanding their customers better — and be prepared to disrupt their own teams and structures to expand value creation. Reorganization without full knowledge of customer needs, on the other hand, can take a company backwards in the value creation process.
“Connected products are generating data rich with potential insights that can drive new services and new business models.”
2. Establish a presence in the value chain with the strongest market position
As threats from nontraditional competitors rise, manufacturing leaders need to focus their organizations on pursuing and owning value chain positions that offer the greatest opportunities for value creation over time — and embracing the business model innovations required to achieve these goals.
Leaders must assess how their organization’s capabilities and offerings align with the value being generated across the value chain. Reviewing one’s activities through this lens can help identify whether the value being captured by the organization is properly aligned with the value created for consumers or if there are untapped opportunities to create new value — and be recognized for it.
Many manufacturers have succeeded at business model innovation by evolving from a product-based model to a new service- or subscription-based model. These new models frequently draw on existing capabilities (e.g., aftermarket repairs and related ancillary services) while deepening or creating new customer or consumer relationships and providing unparalleled ongoing insights into how these constituencies define value.
3. Shift revenue models from delivery of goods to delivery of value
The first two principles underscore how business model innovation can help firms rethink what value they are delivering and to whom – so focusing on the value case and not the technology. It is also critical for manufacturers to explore changes to the “how” — namely, revenue model shifts and tactics that enable manufacturers to capture their fair share of the additional value delivered to customers.
For companies to succeed at measuring and pricing value, they need access to data, supported by the right technology to capture, analyze and act on it. Connected products provide manufacturers with a prime opportunity to understand customer usage patterns and to build new offerings — and new business models — based on insights from this data. Digital transformation efforts undertaken by many manufacturers may create a foundation, but the insights that may foster real business model innovation require more than just the right toolkit. Leaders must be ready to reimagine all aspects of their business through the lens of what they know, via their own data, that the rest of the market doesn’t.
“If companies want to shift from surviving to thriving, they need to turn their business model innovation intention into action.”
When working with customer data, trust is essential. If manufacturers are to be paid based on value delivered vs. units sold, customers must be willing to trust that data gathered via connected products and services will be used to their benefit as much, if not more so, than that of the manufacturer. Customers should be able to see an accounting of value generated and its alignment with prices or fees, ideally creating a virtuous cycle of openness with the manufacturer. Ongoing transparency makes it easier to identify opportunities that may be addressed by new business models.
4. Build a partner ecosystem to innovate at scale beyond sector boundaries
Business model innovation requires companies to re-examine, and often challenge, their own core competencies. Sometimes a value creation opportunity demands capabilities outside the company’s experience or beyond its sector. In these cases, manufacturing leaders should focus on building or joining an ecosystem2.
To build a high-performing ecosystem, manufacturing leaders need to define where partnerships would best support value creation and delivery by extending capabilities, market presence and innovation more effectively than through organic investment or acquisitions. While ecosystems generally provide value creation opportunities for all participants, leaders seeking to build one should look for ways for their organizations to own it for greater control over how the additional value is allocated.
Through these partnerships, manufacturers should also follow leading practices in sourcing, building and managing ecosystems. Ecosystems work best when regular C-suite reviews, KPIs, dedicated budgets and clear organizational ownership are transparently articulated and followed consistently.
As manufacturing companies seek sustainable, profitable growth, the incentives for laying the internal and external groundwork for business model innovation are clear. It’s not surprising that sector CEOs are prioritizing more tangible and predictable actions (e.g., investments in data and technology) over significant changes in their offerings. But there is risk in delaying more substantive changes that position their companies for manufacturing in 2030 and beyond.
Leaders need to think carefully about the current and future state of their business model and its relationship to the value chain. The answers to the following questions may reveal critical knowledge gaps or risk areas that should be addressed, regardless of the specific solution, before beginning the process:
- Value of offering: Where and how is value created by your company’s products and services?
Value to customers: Where would your customers say your products and services deliver value? How do you know this?
- Pricing of value: How does your company set prices? What is the relationship between your prices and the value delivered to customers?
- Forms of value: What forms of value exchange could you be taking advantage of beyond just fees for products? Would you be better off charging less and receiving additional data, IP rights or access to new types of customers?
- Value from competitors: Where are your competitors creating and delivering value?
- Ecosystem partners: How are partnerships adding to the value of your products and services?
Products, processes, and people: Do you have the right products, processes and people within your organization to maximize value? If not, where is the greatest need for change?
In summary, manufacturers can and should become leaders in their value chains. New business models based on value creation are at the center of successful growth strategies. And when value creation opportunities demand capabilities outside core competencies, manufacturers should consider building or joining an ecosystem.
By adopting this enlightened approach to business model innovation, and understanding both the opportunities and challenges involved, manufacturing companies will be far better prepared to thrive and grow by 2030 and beyond. M
Value Chains: The full range of activities undertaken by companies or individuals to bring a product or service from the concept phase through delivery to the user and beyond. This includes activities such as design, production, marketing, distribution and support to the final consumer.
Ecosystem: An evolution of traditional forms of partnering, ecosystems combine a broad range of skills, technologies, products, services, experiences and data from multiple value chain participants. They allow organizations to innovate at scale, transform their operations, challenge sector boundaries and serve end customers better. Unlike typical supplier relationships, ecosystem partners will frequently go to market together, maintaining individual brand visibility.
About the Authors:
Claudio Knizek is EY-Parthenon Global Advanced Manufacturing and Mobility Leader.
Jerry Gootee is EY Global Advanced Manufacturing Sector Leader.
Greg Sarafin is EY Global Alliance and Ecosystem Leader.
Also contributing to this article was
Julie Buresh, EY Global Advanced Manufacturing Senior Analyst.
The views reflected in this article are the views of the author(s) and do not necessarily reflect the views of Ernst & Young LLP or other members of the global EY organization.
Profitability and sustainability may have once been at odds for process manufacturers, but now, the two are intertwined like never before.
Have you ever thought about the folks who control the Perseverance Mars rover? Driving the rover is one of the most complex and time-consuming activities of the entire exploration mission. The contrast between what it takes these NASA engineers to drive to work each morning — done almost without thinking — and the diligence and collective attention required to navigate the rover with a top speed of under 0.5 mph is remarkable.
So, what does driving the Mars rover have to do with the sustainability and profitability of your business?
Many manufacturing organizations manage their operations in a similar manner to NASA engineers controlling Perseverance. In both circumstances, real-time information alone is insufficient for teams to base their decisions on because it is unreliable and/or untimely. Instead, they work through a process of collecting relevant historical and contextual data, validating it, defining immediate objectives, crafting longer-term plans, and staging these plans for execution without direct oversight or the ability to intervene in the moment if issues arise.
By deploying modern, advanced analytics software, organizations in the process industries can make the shift from interplanetary to in-the-moment business operations.
Given the inherent time-delay and bandwidth challenge associated with interplanetary communications, there is no feasible alternative to Perseverance’s control scheme. But imagine what it would mean to your business if you could drive sustainability the way you drive your car without thinking, rather than treating it like it operates on another planet.
By deploying modern, advanced analytics software, organizations in the process industries can realize the potential of their investments in digitalization, making the shift from interplanetary to in-the-moment business operations. Particularly in the realm of sustainability initiatives, this transition provides a critical step towards more circular production systems, and it also helps innovative manufacturers drive sustainable practices, differentiating themselves from the competition.
Key sustainability initiatives
Modern industrial analytics can help global manufacturers achieve key sustainability milestones, including net-zero pledges, regulatory reporting goals, and energy, water, and materials reduction. By leveraging self-service, advanced analytics applications in process manufacturing, companies can overcome many challenges and barriers to achieving these sorts of measurable gains.
The sustainability-driven activities that support these top initiatives fall into one of three broad categories:
- Measurement and validation: Relevant key performance indicators (KPIs) have primarily been developed around greenhouse gas (GHG) and carbon emissions, but organizations are increasingly adding new ones, such as water usage and NOx emissions, driven by the need to meet regulatory and fiscal requirements.
- Improving existing operations: Increasing operational efficiency and minimizing environmental impact.
- Scope 3 and circular enablement: Fundamental changes to supply chain, sourcing, and manufacturing processes focusing on Scope 3 impact and enabling circularity concepts.
1 Measurement and validation
The notion “you can’t improve what you don’t measure” is highly applicable to sustainability initiatives. Measurement was historically retrospective and infrequent, hampered because calculations, visualization, and validations were performed manually in spreadsheets, often by offsite production accounting groups or corporate sustainability teams with access to few local resources.
By leveraging advanced analytics software, teams gain visibility into current emissions levels at each production facility, helping process manufacturers reverse the old dynamic. This empowers local operational teams to identify excursions and respond in a timely manner to make tangible impacts when issues occur.
For example, advanced analytics applications enable subject matter experts (SMEs) to identify relationships among environmental KPIs and process parameters. When these relationships are understood, entire processes can be continuously monitored to identify and mitigate environmental excursions. This continuous monitoring ensures rapid reaction to events, while facilitating root cause analysis by SMEs.
An ever-widening variety of techniques to validate these runtime measurements and adjust for known disturbances, such as fuel gas composition changes and combustion efficiencies, are under development. This provides the confidence audit trail for the generation of enterprise-level reports through the aggregation of multiple runtime measurements rather than top-down allocations as is common practice today.
Responsible operators want to improve, but they lack the means to track progress without a method of measurement.
More challenging are those emissions that, by their nature, cannot be measured directly — for example, fugitive emissions of storage and transmission systems, which form a significant proportion of total emissions in some sectors. Responsible operators want to improve, but they lack the means to track progress without a method of measurement. With advanced analytics, organizations can overcome this obstacle.
Improving leak detection and mitigation
Oil and gas operators have difficulty pinpointing methane leaks. While methane data is available from a variety of satellite providers, the data is sparse, with measurements typically available just once each day. Additionally, integrating this satellite data with other information of interest — such as weather or process data — poses a challenge. As a result, it is difficult to quantify past events, and nearly impossible to identify events in real-time or detect developing issues.
Using advanced analytics software, SMEs can review satellite, weather, and process data in a single location. The satellite data can pinpoint when an event occurs, and the weather data can help characterize a dispersion model for the event. Meanwhile, an analysis of the process data can pinpoint the source of the leak and quantify the event duration and quantity emitted.
Overlaying data from all sources yields greater insight into emissions events, specifically the duration of an event, amount emitted, and dispersion of the plume. These insights can be leveraged to characterize process conditions leading up to emissions events so users can proactively spot issues as they arise, or even identify early indicators and avert an event altogether.
2 Improve efficiency and impact of existing operations
All the effort expended identifying opportunities for environmental improvement are meaningless unless something changes as a result. Most organizations focus first on existing operations, striving to run optimally as much of the time as possible. This raises two questions: 1) how well can the existing facilities run, and 2) how can this be quantified?
The latter question is the more difficult to answer, as few, if any, sustainability-related KPIs are calculated and monitored with sufficient granularity and timeliness for operations teams to take informed action. Even after runtime visibility issues have been addressed, labelling what “good” looks like can be quite challenging, particularly in operations with variable feedstocks, product slates, and energy sources.
The ability to certify sustainability credentials of individual facilities, product lines, and product deliveries creates opportunities for differentiation and competitive advantage.
Intra- and inter-company benchmarking is invaluable for this identification, and in some cases, performance targets must be derived during runtime from plant models, simulators, and optimizers. Runtime visibility, implemented on a common, enterprise-wide platform, is the only viable way of implementing this.
One of the greatest intangible benefits reported by process manufacturing organizations that use advanced analytics software is the power of a single platform to enable company-wide learning and best practice dissemination. Equipped with live data connectivity, these types of applications provide simplified data-cleansing tools and contextualization, empowering SMEs to derive meaningful and reliable insights across all available data quickly.
Justifying an idle boiler
Wasted energy is one of the largest contributors to carbon emissions, and utilities providers frequently comprise the largest source of energy waste. Manufacturers need ways to identify the time periods of wasteful operation — which come in the forms of vented steam, excessive electricity consumption, and others — and quantify the waste as a financial loss or CO2 emissions equivalent. These quantities provide a common benchmark for comparing alternative operating strategies.
A major U.S. refiner leveraged advanced analytics to justify the idling of a single boiler in a dual boiler operation during the warm months of the year. A team of SMEs configured the software to identify time periods when the dual boiler system was operating at minimum firing rates while venting steam. Then, these time periods were studied to aggregate potential annualized steam savings.
Next, the team analyzed historical data to understand the probability of a boiler trip, which could have a significant financial impact in a single boiler operation, and the potential steam cost and energy savings were weighed against the risk — probability of failure times financial consequence — of running a single boiler.
This analysis provided the data required to make the decision of idling one boiler during prolonged periods of warm ambient weather, saving the refiner an average of $500,000 per year in vented steam costs. This operational change also reduced the operation’s carbon footprint by decreasing energy input to the boiler system.
3 Scope 3 and circular enablement
Analysis can point out significant opportunities for operational optimization, but there will always be inherent limitations imposed by the production systems used today. Every individual plays a role in a larger value chain, and multiple value chains make-up highly integrated and interdependent economic systems. By working together, multiple organizations can keep progress going in the right direction.
This concerted action is underpinned by two key concepts: Scope 3 awareness and reporting, and production system circularization. The practical viability for each of these topics is dependent on the same concept of runtime visibility. Without runtime visibility, process manufacturers are limited to using typical or standard emissions data from suppliers — especially feedstock and energy — in the effort to understand and define Scope 3 performance.
These near real-time carbon intensity estimates provided the organization the opportunity to make data-driven decisions to target carbon reduction on an ongoing basis.
As runtime visibility is improved up and down the value chain, it becomes increasingly straightforward to communicate actual performance metrics in real-time, or on a material-by-material and batch-by-batch basis. This is already commonplace for other quality and compliance-based metrics in many sectors, including polymers, pharmaceuticals, and liquid fuels.
Reducing carbon emissions
A global chemical manufacturer recently pledged to cut its carbon intensity in half by 2030. The first step it took toward reduction was understanding the current state of its operations. Previously, such an analysis was only conducted once per year because it was so cumbersome, but this carbon intensity calculation is critical to understanding the overall carbon footprint of the manufacturer’s process.
Site engineers leveraged an advanced analytics software application to provide near real-time awareness of the carbon intensity of site utility streams. This application converted process sensor data into carbon mass equivalents so SMEs could easily compare the current carbon intensity with a target for a given production quantity. Breaking the carbon footprint into individual utility streams empowered the operations teams to understand the largest contributors, along with the levers to combat them.
These near real-time carbon intensity estimates provided the organization the opportunity to make data-driven decisions to target carbon reduction on an ongoing basis, making measurable progress towards their 2030 reduction goal. Following this approach, Scope 3 measurement simply becomes the addition of individual run-time metrics up and down the value chain. And as more members of the value chain actively participate, this approach will continue to become more accurate, informative, and meaningful.
Economic returns and competitive differentiation
There is no doubt that sustainability initiatives will continue to drive incremental and transformational change. The adoption of runtime measurement and validation facilitates movement toward increasingly proactive production systems, which help establish dynamic mitigation and preemptive detection of emission events.
The actions of individual companies benefit every member of the value chain. Furthermore, the ability to certify sustainability credentials of individual facilities, product lines, and product deliveries creates opportunities for differentiation and competitive advantage — especially in the areas traditionally considered commodity markets.
In a time not long ago, operating a global manufacturing business often felt a bit like trying to maneuver an intricate and complex vehicle by remote control from a planet away, but that no longer must be the narrative. With digital technologies and modern industrial analytics tools, runtime visibility is plausible and common, empowering organizations to drive in runtime, instead of faintly issuing commands with the hope of execution as intended.
Getting organizations behind the wheel is the only way we will collectively impact the sustainability and long-term viability of the industries we work in. As process manufacturers increasingly come on board, we are beginning to achieve levels of efficiency never previously imagined. M
About the authors:
Chris Hamlin is Director, Capability Development at Seeq Corporation
As sustainability pressures mount, manufacturers will benefit by taking a proactive approach.
Manufacturers are increasingly in the hot seat when it comes to sustainability mandates, especially those established by their customers. Understandably, many mandates focus on reducing carbon emissions across value chains. Scope 3 emissions, which come from an organization’s suppliers, are the most difficult to assess and mitigate and can account for 85 to 95 percent of an organization’s carbon footprint, making them a high priority.
So, how can manufacturers take control of sustainability initiatives that include limiting direct and indirect carbon emissions? Customers often have their own corporate commitments with targets and timelines that don’t easily align to value chain processes. And manufacturers typically don’t have the budget or resources to track critical information and make necessary changes.
The answer is to be proactive rather than responding to mandates as they come. Manufacturers that proactively shape sustainability initiatives with their customers can benefit everyone in the supply chain. By so doing, they can avoid or mitigate situations where they’re saddled with complex and costly initiatives that are difficult to implement.
With data insights based on operational baselines, material analysis and regulatory developments, manufacturers can help shape customers’ perspectives.
A case in point is Walmart’s past RFID initiative. Walmart had announced that its top 100 suppliers – and eventually all of their providers – would need to use RFID technology to tag their pallets and cases. The initiative was heralded by the media and closely watched by manufacturers to see how it would improve inventory management. After a few years the RFID initiative was quietly abandoned, due to vendor pushback. Suppliers complained that they were forced to invest in costly technology and experienced increased tagging costs.
In this example, suppliers learned by doing and relayed their feedback to Walmart. If these companies had proactively experimented with RFID ahead of the mandate, they could have shared their findings with the big-box retailer and shaped the initiative from the start. Walmart’s RFID initiative returned in 2019, as processes have now matured. The technology is now used to track certain high-value supplier goods at the item level in stores, rather than all products indiscriminately.
Driving the Sustainability Conversation
As sustainability mandates roll out, how can manufacturers ensure they benefit from these new initiatives? Here are some simple strategies manufacturing teams can use:
- Baseline existing operations: Manufacturers should determine where, how, and what quantity of carbon emissions they are producing at baseline. This data provides invaluable insights into areas to target for sustainability initiatives, as well as baseline metrics that can be shared securely with customers and partners. Customers can then verify aggregated product carbon footprint information, while keeping supplier data confidential.
- Identify materials that contribute to greenhouse gas emissions: Manufacturing teams can break down products into their components, such as metals, plastics and agricultural inputs, to identify opportunities for reducing carbon emissions. By analyzing products for cost, carbon and recyclability simultaneously, manufacturers can identify the best approaches to optimize product design, while avoiding well-intentioned actions that inadvertently increase carbon emissions.
- Stay up to date on regulations: Regulatory teams can track new requirements against their manufacturing companies’ operational locations, inputs and own suppliers. Leaders and teams can use this information to develop holistic strategies, provide their own downstream mandates, and transform products and operations appropriately.
- Explore new business models, products and services: Manufacturers can explore new business models, such as re-commerce initiatives that resell used merchandise and equipment, and programs that collect waste and reuse it in new products. They can also design products for recycling and remanufacturing, implement reusable packaging and more. Levi’s initially launched “wasteless” jeans and denim jackets but learned that mixing polyester and cotton meant the products couldn’t be recycled. The company’s new “circular jean” contains 40 percent post-consumer recycled cotton that can be separated and reused.
- Drive customer conversations with data: Manufacturers are the best experts on their materials, production processes, logistics and more. With data insights based on operational baselines, material analysis and regulatory developments, they can help shape customers’ perspectives. In the case of the Walmart RFID mandate, it was when leading manufacturers provided data on RFID costs that the retailer began walking back its mandate. Manufacturers can’t expect customers to understand the fine-grained details of their operations, so it’s best if they come to the table with this information.
- Team with partners to build a sustainability platform: Manufacturing teams can attend conferences to learn new trends and technologies. They also can partner with research institutes and universities to test new processes and pilot initiatives. Universities benefit by gaining research they can use to share with industry companies and burnish their brand. Manufacturers benefit by getting a first look at a new technology or process that could provide a new source of competitive advantage.
Moving Ahead of Mandates
More than 60 percent of all organizations now have a sustainability strategy, and more are soon to follow. Organizations’ sustainability imperatives and progress are increasingly considered by a wide array of stakeholders. These stakeholders include financial institutions that lend to manufacturers; customers, who use sustainability information to decide whom to partner with; employees, who want to work for a progressive company; and consumers, who want to buy from environmentally friendly brands.
By analyzing products for cost, carbon and recyclability simultaneously, manufacturers can identify the best approaches to optimize product design.
Manufacturers can help shape sustainability conversations with – and mandates from – their buyers by providing insights into operational baselines, material emissions, and regulatory data. They also can create competitive advantages by testing new business models, products and services and exploring new technologies and processes.
Manufacturers can learn and lead with sustainability, ensuring customer mandates are driven by the right priorities and will create value for the entire supply chain. M
About the author:
Shanton Wilcox is Partner, Americas Leader – Manufacturing at PA Consulting.
Software-defined manufacturing is the key to reducing emissions, waste, and resource consumption.
Our world will always rely on manufacturers to produce the goods and materials we need to keep our economies and businesses running. Yet, those same manufacturing operations are severely impacting our planet’s health. Physical industries, including industrial manufacturing, account for 75% of global greenhouse gas submissions, and CO2 emissions released by global fossil fuel combustion and industrial processes rose by roughly 35% over the last 20 years.
It’s abundantly clear that manufacturing has a profound impact on the environment and that it’s time for a significant overhaul of traditional processes now that other options exist. Change is here and now — and the good news is that, when embraced, it will benefit the planet, our economies, and our businesses.
A Worldwide Wake-up Call
There’s been a worldwide wake-up call to do better for our planet, and it’s demanding that organizations implement changes for a healthier, more prosperous future.
For example, businesses now have more focus on environmental, social, and governance (ESG) issues than ever before, across all sectors, with investors, partners, and customers having certain requirements of their vendors to abide by specific ESG protocols. They’re no longer going with the most convenient option but rather sourcing materials and partnering with manufacturers that prioritize sustainability throughout their operations. A PwC survey showed that about half of investors would be willing to divest from companies that didn’t take sufficient action on ESG issues.
Customers aren’t only demanding change in how manufacturers produce but what they produce as well. A survey of C-suite manufacturing leaders showed that more than half of respondents feel that, of all the evolving customer needs, the growing demand for sustainable products is having the largest impact on operations.
Manufacturers that are feeling pressured, even panicked, to evolve their operations quickly need to lean on modern technology to help them navigate the change.
This is a big change for the manufacturing industry, which has negative implications for the environment by its very nature. Take it all into account: Many manufacturers have global operations with a majority of their factories in Asia, where labor is cheaper. Goods are mass-produced, which requires exorbitant amounts of energy and materials, then they’re shipped back to the U.S. and transported by trucks to the customer, who (in many cases) still isn’t the end consumer. The global supply chain is incredibly long and complex, and the last few years have shown us that it’s neither resilient nor sustainable. But it doesn’t have to be this way.
Manufacturers that are feeling pressured, even panicked, to evolve their operations quickly – who are overwhelmed with tackling ESG, supply chain, and digital evolution challenges all at once – need to lean on modern technology to help them navigate the change.
A Sustainable, Software-Defined Future
The manufacturing industry’s impact on the environment is a big problem, and it will take a big shift in production to solve it. That’s where the power of automation comes in. With incredible, fast-paced technological advancements over the last couple of decades, and especially within the last several years, manufacturers have more tools and technologies at their disposal than ever before — many of which help to transform manufacturing from a slow, stiff, resource-intensive industry to one that’s fast, flexible, and eco-friendly.
These tools and technologies (i.e., automation, robotics, virtual reality, digital twins) can and already are helping both established and up-and-coming manufacturing organizations implement new processes and approaches to production that lead to more sustainable operations. But which solutions are the most impactful? There’s a lot of noise in the market, with the global smart manufacturing market size expected to reach a valuation of USD 727 billion by 2030, and it can be difficult to understand which approach is best suited for each organization—even each factory, as needs may differ based on location and/or production requirements.
Manufacturers who move production closer to the end consumer and build or revamp factories with intelligent automation can reduce overproduction.
The North Star for any manufacturer ready to increase efficiency, improve quality, and introduce greater sustainability is a software-defined approach. Software-defined manufacturing combines logic and intelligence in software rather than hardware to create a more flexible environment that can help address decades-old economically and environmentally damaging operational processes. This approach leverages intelligent automation solutions that have cloud, machine vision, and artificial intelligence capabilities built in from the start, which introduce a whole new level of elasticity and resiliency into the production line and onto the factory floor.
Here’s what manufacturers can achieve with a software-defined manufacturing approach:
- Reduced waste and carbon footprint: Intelligent automation regularly assesses areas of production that can be adjusted so that manufacturers can better understand which resources or materials they need more or less of and where maintenance is needed – before it’s needed – to help reduce faulty products that result in waste.
Additionally, manufacturers who move production closer to the end consumer and build or revamp factories with intelligent automation can reduce overproduction. Instead of production based on unreliable forecasting, for example, manufacturers can produce-to-order based on local market demand. This cuts down on wasted, unwanted products, but it also helps to reduce the operation’s carbon footprint. Closer-to-home production and localized supply chains inherently result in less shipping and transportation mileage, reduced waste, and minimized energy consumption.
- Greater flexibility and efficiency: Factories with intelligent automation are more flexible and efficient. These solutions use programmable assembly lines that enable faster product changeovers when the market demands it, and can accommodate multiple types of product SKUs on a single line. Lines are modular, reconfigurable, and reusable over time and can therefore achieve higher utilization. When all of these components come together on the factory floor, manufacturers can better pivot to accommodate increasingly complex demands without overexerting or wasting their resources.
- New revenue streams: Manufacturers searching for new ways to reduce, reuse, and recycle may be able to introduce additional revenue streams in the process. For example, if a manufacturer invests in technology that improves the complex, error-prone disassembly and end-of-life processing of technology solutions such as servers, they could turn around and sell still-viable pieces and components to global technologies that want spares in their inventory. By doing so, they avoid contributing to the 6 million tons of annual e-waste (and rising) that ends up in a landfill. Modern technology helps turn the seemingly impossible disassembly process into a revenue growth opportunity, which happens to benefit the environment as well.
The future of manufacturing will need to include a sustainable, software-defined approach. Organizations that embrace the new tools and technologies that contribute to more efficient, eco-friendly operations will have a smoother, faster pathway to near-term and long-term success. Their businesses will benefit, and our planet will benefit — it’s a win-win. M
About the author:
Sean Murray is VP, Customer Success at Bright Machines, Inc.
Regionally based hubs of value chain participants can help reduce greenhouse gas emissions for so-called “harder-to-abate” industries.
As the push for decarbonization to combat climate change gains momentum, the adoption of readily available low-carbon solutions is accelerating. However, for sectors where efficiency and green electrification are unable to address the majority of emissions, commercially available solutions remain frustratingly out of reach.
For these sectors, often referred to as “harder to abate,” technical and business model gaps compound the challenge of finding cost-effective solutions to address what amounts to be 30 percent of total global greenhouse gas (GHG) emissions.i This share is projected to grow as other sectors decarbonize, increasing the urgency for the harder-to-abate industries of iron and steel, road freight, aviation, chemicals, cement, and shipping to find ways to bring innovations to market in time to mitigate climate impacts.ii
The good news is that there are known technological solutions under development today with the potential to reduce emissions from harder-to-abate sources. Among the most promising are clean hydrogen and carbon capture, utilization, and storage (CCUS).
Combined, these have the potential to abate over 50% of industrial emissions by 2070.iii
However, the current costs of both of these technologies have yet to reach a point low enough to be deployed at scale. Currently, the production cost of clean hydrogen ranges between $1.60 and $12.00 per kilogramiv (depending on the production method) and the cost of carbon capture varies from $25.00 to $120.00v per ton based on stream purity and emission source (Figure 1).
Although they’ve been around for decades, hydrogen and CCUS technologies have faced investment headwinds arising from a persistent chicken or egg problem: companies are reticent to invest in production or capture technology without being confident that there is a market for their product, while downstream customers have not invested in the market infrastructure or technology to utilize captured carbon or clean hydrogen due to the lack of supply. However, for harder-to-abate sectors to decarbonize at the speed needed to keep the planet to less than 1.5-degrees or even 2-degrees of warming, these low-carbon technologies must reach commercial scale in the mid-term as part of the overall solution to achieve net-zero emissions globally by 2050. With investment time horizons of five years or longer, companies need to act now in order to see emissions reduction benefits by 2030 at the latest.
Introducing the Hub Concept
One key pathway to achieving commercially viable low-carbon technologies is by funneling investment to scale up supply in regions with matching, growing demand. By co-locating supply and demand, hubs can bring down infrastructure costs and drive economies of scale. Bound by a specific region, representing a significant level of aggregated point-source emissions, and bringing together actors from across value chains and sectors, hubs sit at the intersection of customers, geography, and collaborators that enable organizations to maximize value. As our analysis will later illustrate, collective action in a hub drives significant cost reduction for collaborators when compared to the costs associated with individual investments.
Through ecosystem collaboration, hubs can accelerate technological development, encourage downstream adoption of clean hydrogen and/or carbon capture for multiple end-uses, and drive long-term decarbonization transformation across industrial value chains. “Co-opetition” amongst hub members creates conditions which may accelerate hub success by both lowering the perceived risk of investment—as participants see others in their industry investing—as well as by creating more tangible competition. For ecosystems to work well, companies will have to give up old notions of competitive advantages in which most moves are exclusively zero-sum and instead think about the value of collaborative advantage and adaptive advantage which comes from working with others—even erstwhile competitors.
Typically centered around geographies with regional advantages (e.g., endemic natural geological storage formations, existing infrastructure, a skilled workforce, favorable regulatory conditions, tax incentives, etc.), successful hubs benefit from solution integration and scale, and reap the rewards of increased innovation, access to human capital, investment flows, and more. Based on these criteria, several low-carbon hub locations have already been identified across the United States, many involving multiple planned or announced projects (Figure 3).
Due to its cost advantages of natural gas, endemic geological storage resources, wind and solar potential, industrial manufacturing capabilities, and existing export and pipeline infrastructure, North America, and in particular the United States, is one of a few regions in the world identified by the International Energy Agency (IEA) as being primed for low-carbon hub development and clean hydrogen export.vi However, with national low-carbon strategies, supportive funding and regulatory regimes, and several announced projects underway, other industrial regions like Australia, Europe, and China have so far led the world in hub development. Though the United States lags behind, recent policy support has signaled that this may not be the case for long.
There are a multitude of hub projects under development globally, each with its own complexities and operating model considerations. At their core, however, we see hubs as being either supply-led or demand-led.
Through ecosystem collaboration, hubs can accelerate technological development and help drive decarbonization transformation.
Supply-led hubs leverage a differentiated supply base to attract customers by establishing supply in areas primed to support it, in the hopes that such actions can create demand. These hubs can either be asset-led in which hub development is focused on acquiring or leveraging a specific asset such as pipelines or salt caverns, or they can be product-led where the hub is stood up with the intention of producing a specific end product – such as hydrogen or carbon black.
Demand-led hubs organize downstream industrial subsectors to aggregate hydrogen and carbon dioxide demand by creating an attractive market for lower emission solutions at scale and emphasizing collaboration. These hubs can either be off-loader led where hub development is driven by high emitting industries looking to off-load captured CO2 and thereby driving demand for capture, utilization, and sequestration services, or they can be off-taker led in which industries look to utilize clean hydrogen and captured CO2 to decarbonize their operations and products (think carbon cured cement, green methanol, or clean hydrogen as a feedstock).
Catalyzing Development: Federal Funding for Hubs
As the United States looks to achieve the emission reductions goals set by the Biden administration, the Department of Energy (DOE) is stepping up support for hubs as a pathway for industrial decarbonization. The Infrastructure Investment and Jobs Act (IIJA), passed in November 2021, vii sets aside over $21 billion in fiscal years 2022-2026 in support of technologies that will be key parts of low-carbon hub value chains (clean hydrogen and CCUS), as well as $8 billion and $3.5 billion in direct funding for individual hydrogen and direct air capture (DAC) hubs, respectively (Figure 4). Several states have also individually announced their intent to form and support regional hydrogen hubs.
Though significant, the DOE funding is estimated to be only a portion of the investment needed to establish U.S. hubs and drive down the cost of clean hydrogen and CCUS on a global scale. By some estimates, the annual global spend on these technologies that will be required to reach net zero by 2050 must exceed $900B in 2026 – up from $24B in 2021.viii While this remaining gap in investment will have to come largely from the private sector, federal funding can serve to de-risk private investment and catalyze hub development.
The Value Proposition of Hubs
Fortunately, even without government support, hubs present a significant value proposition for participating companies seeking to reduce emissions and meet customer demand for low-carbon products and services.
Deploying clean hydrogen and CCUS in the United States at the scale necessary to reach net zero by 2050 will require that a large amount of the CapEx spent by harder-to-abate industries be directed to retrofitting facilities or constructing new greenfield sites for these new technologies. For CCUS, that means growing the U.S. capacity from 25 million metric tons per annum (Mtpa) in 2020ix to over 1 billion tons per annum by 2050.x Companies will need to equip facilities with carbon capture equipment, expand hydrogen production, and build out the necessary pipeline network to aggregate, compress, and move carbon dioxide and hydrogen to downstream consumers or geological storage. Figure 5 illustrates how these pieces may work together within a low-carbon hub, which coordinates and aggregates the infrastructure investment required to maximize efficiency.
To further explore the business case for hubs, Deloitte modeled the cost savings and emissions reduction resulting from two real U.S. hub locations representing the supply-led and demand-led operating models. The full analysis can be found here.
Despite their sizable price tags, when compared to individual companies deploying CCUS by themselves, all companies, regardless of size and industry, see a reduction of up to 95% depending on their industry, emissions contribution, and size. Outside of a hub, a company’s investment in transport infrastructure is governed by the volume of emissions from their own operations, limiting the pipelines they can deploy to smaller diameters with lower annual capacities and significantly less favorable unit economics. By aggregating emissions from other point sources, companies can drive towards more efficient pipelines and lower the per-ton cost of CO2 transported. Hydrogen producers and consumers in the hub can expect similar transportation and storage cost reductions due to economies of scale.
Strategic Considerations for Hubs
The success of different hubs and hub projects will ultimately be driven less by the amount of public funding secured, or the number of participants involved, but more by how well hub organizers are able to navigate the complexity surrounding hub development. This will include sending the right demand signals to ecosystem collaborators, making near-term investment decisions for bottom-line impact down the road, and reorienting mid- and long-term business goals and capital expenditure to meaningfully advance hubs for lower emissions.
To better understand the decisions that hub developers and hub participants will need to make, a series of strategic tensions have been outlined that will influence the hub’s eventual operating model. These are not binary and are not meant to drive towards a single answer. Rather, hub developers and participants should use them to develop a perspective on what would be the most beneficial for their hub and to identify a final hypothesis on how the hub will operate.
Each of these decisions and tensions may not require consensus, but they do need an open and transparent dialogue between civic and corporate leaders, technical experts, governments (federal, state, local), labor unions, community members, and a number of other interested and invested participants.
As a result, hubs will typically encompass a multitude of partners with inherently mismatched capabilities, motivations, and timelines. Where Deloitte has been invited into hub development, it has been to provide the interstitial matter to fill these gaps; convening like- minded partners and providing a third-party perspective to drive towards shared objectives while rounding out hub capabilities with additional services as hub projects evolve. In our experience, hubs that can accelerate alignment across their interdependent and complex stakeholder network will thrive, while those that cannot are unlikely to make it past the planning phases.
As the pressure to reach net zero mounts from investors, regulators, customers, and other stakeholder groups, and the demand for low-carbon products and solutions grows, harder-to-abate sectors are rightfully seeking pathways to achieve meaningful emissions reduction while preserving value for shareholders. Hubs present a relatively accessible option for industry in the near term to make good on emissions reductions pledges and demonstrate action on climate change.
Our analysis shows that while new federal funding has kickstarted hub formation around the country and sparked fierce competition for grants and incentives, there is a considerable business case for cross-sector collaboration within low-carbon industrial hubs even without government support. How a hub is configured—involving the right partners, securing demand amongst diverse end-uses, engaging the complete value chain, structuring agreements governing shared infrastructure, coordinating amongst various stakeholders, and more—will ultimately be important determinants of success.
Facing technical and business model barriers to reducing emissions, harder-to-abate industries must embrace collective ecosystem approaches like low-carbon industrial hubs to accelerate beyond incremental change and to catalyze tipping points in low-carbon innovation. Strategic participation in hubs is a quick win, attainable in this decade, for sectors that don’t have many options—reducing the cost of abatement, enabling further technological innovation, and unlocking emissions reduction benefits now while enabling deep decarbonization down the road. M
ii IEA, “Net-Zero by 2050: A Roadmap for the Global Energy Sector,” May
iii IEA, “The challenge of reaching zero emissions in heavy industry,” September
v IEA, “Is carbon capture too expensive?,” February
vi IEA, “Global Hydrogen Review 2021,” October
vii GOV, H.R. 3684 – The Infrastructure Investment and Jobs Act, November 2021.
viii Bloomberg NEF, “Energy Transition Investment Trends 2022,” January
ix IEA, “A new era for CCUS,” September
x Princeton University, “Net Zero America,” October
xi ACC, “2021 Guide to the Business of Chemistry,” August 12,
This article contains general information only, does not constitute professional advice or services, and should not be used as a basis for any decision or action that may affect your business. The authors shall not be responsible for any loss sustained by any person who relies on this article.
Copyright © 2022 Deloitte Development LLC. All rights reserved.
About the authors:
Stanley Porter, Vice Chair
Porter serves as Deloitte’s US & Global Energy, Resources & Industrials (ER&I) Industry Leader. He oversees and drives the development and execution of the overall ER&I strategy across all geographies and businesses, including more than 44,000 professionals and serving close to 75% of the Global Fortune 500 clients. The ER&I industry practice represents the Industrial Products & Construction; Oil, Gas & Chemicals; Mining & Metals, and Power, Utilities & Renewables sectors.
Geoff Tuff, Principal
Tuff has more than 30 years of experience consulting to some of the world’s top companies on the subjects of growth, innovation, and adapting business models to deal with change. Currently, he is a principal at Deloitte and holds various positions across the firm’s Sustainability, Innovation and Strategy practices. Those include leadership of the US Hydrogen Practice and all Sustainability, Climate and Equity work for clients in the energy and industrials sectors. Prior to this, he led the innovation firm Doblin and was a senior partner at Monitor Group, serving as a member of its global Board of Directors.
Mark Pighini, Principal
Pighini is a principal with Deloitte’s Transactions and Business Analytics LLP and is the US Oil, Gas & Chemicals Risk & Financial Advisory leader. Mark has spent over 25 years of his career delivering professional services related to organizational deployment of capital through capex investments and mergers and acquisitions (M&A). He has worked across a wide variety of asset-intensive industries but focuses mainly on manufacturing, industrial, and healthcare companies.
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.
In his introduction to MLC’s recent Master Class session, Harnessing Digital Technology for a Sustainable Future, Paul Tate laid out the high stakes involved in sustainable manufacturing.
“This is one of the most existential challenges and sources of opportunity for the manufacturing industry over the next decade,” said Tate, MLC’s Co-Founding Executive Editor and Senior Content Director.
To get to a sustainable, net-zero future, application of both data and analytics are critical. During the Master Class, expert speakers Baskar Radhakrishnan of NTT DATA and Rebecca Christiansen of Microsoft defined the challenges and described how digital technology can help manufacturers accelerate decarbonization.
According to Christiansen, Microsoft’s Americas Azure IoT Specialist Director, nearly one-third of the world’s energy consumption and roughly 20% of CO2 emissions are attributable to the manufacturing industry. To help combat climate issues, she pointed to the 5,000 companies that have committed to net zero as part of the United Nations Race to Zero Campaign.
“While a lot of companies have made commitments, building the strategy, backing it with detailed plans and execution methodologies has been really tough,” Christiansen stated. “It’s really up to all of us, collectively, to figure out what technologies and what strategies should be implemented to go after this.”
Further, Baskar Radhakrishnan shared this must be looked at not only through the strategic lens, but also from a tactical, operational technology perspective.
“From a technology perspective, there is a lot of data available coming from the supply chain, coming from your OT systems, coming from all over your networks,” said Radhakrishnan, NTT DATA’s Strategic Advisor for Manufacturing. “But how you derive some meaningful insight out of that is a huge challenge.”
To show how sustainability investments can provide value, NTT DATA and Microsoft have partnered together to demonstrate quick return on investment for their customers. They have designed a production-level pilot that can be set up in a small-scale production environment at a customer site in less than 12 weeks. This allows the implementation team to show its organizational leaders the opportunity, value and positive ROI associated with investing in an energy management or a waste reduction system.
Beyond demonstrating ROI with this pilot, it is important to also look at sustainability from a business objectives perspective.
“There is a gamut of technologies involved,” Radhakrishnan said, “so technology is an enabler. It’s not going to solve your problem unless you have the process straightened out and unless you identify the range of possible options for transitioning towards the net-zero targets.”
In part because organizations cannot improve things they can’t measure, NTT DATA and Microsoft are using the Azure digital twin to help companies meet their sustainability goals.
“We tackle the problem of data by connecting directly to energy data sources – be it power meters, submeters on equipment, or utilizing building management systems. From there we create both real-time visibility to energy usage and provide analytics about the energy usage, trends, and patterns,” said Radhakrishnan.
According to the Master Class speakers, manufacturers shouldn’t be afraid or overwhelmed with the prospect of using digital twins in this process. While they can seem complex, they are simply virtual replicas of physical assets, or “high-fidelity digital representations of the physical world,” as Christiansen called them.
“Once you’ve got [the physical world] modeled, you can garner insights, you can look at consumption, you can look at interaction, you can think about how you can manipulate or even identify fault detection or anomalies in advance, which help you really optimize keeping your manufacturing line healthy, runtime up, and throughput maximized,” she said.
The outcomes from using digital twins are clear, including improved production capacity and inspection efficiency with reduced energy usage and CO2 emissions. Plus, the twin allows the user to look at energy management on many level: at the product, factory, or even supply chain levels. That includes progress toward net-zero goals.
“That’s extremely important because you’re completely taking the guesswork out of this,” said Radhakrishnan. “You need a systematic way of tracking, reporting, recording, and being able to model and show progress not only to your board but also to your external stakeholders as well as investors.”
In fact, he said, if you are not making progress, the digital twin in combination with artificial intelligence allows you to model and fix problems and see how you are progressing toward your vision.
Beyond the technology itself, the final piece to the puzzle is creating an organizational culture with proper funding, training, and resources.
“We’re seeing a lot of organizations hire chief sustainability officers,” said Christiansen. “That’s an incredible start, but that’s a single person. It has to come through the entire culture of a company.”
If the culture is not there, she warns, it will be a challenge to implement these changes.
As the Master Class demonstrated, net-zero goals are challenging, but they are also achievable. Digital technologies like NTT DATA and Microsoft’s production-level pilot can build a case to create sustainability programs that create substantial results. Establishing goals and a strategy, utilizing digital twins, analyzing the data and analytics, and creating an organizational culture where the entire company is behind the mission are all key to accelerating a decarbonization effort.
Visit NTT DATA’s sustainable manufacturing page to learn more about this topic.
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
What do women in manufacturing think about the business they’re in? It’s not something we hear a great deal about, which is perhaps not surprising. Manufacturing is a male-dominated industry, after all. For half a century women have represented around 30% of the U.S. manufacturing workforce, peaking at 33% in 1990, according to the U.S. Census Bureau (USCB).
By number, most female employees are found in production, transportation, and material moving. They are assemblers and fabricators, says the USCB, inspectors and testers, among other roles.
But, proportionately, women enjoy far greater representation in the sales and office-based roles of manufacturing companies, where they are in the majority, holding 51.7% of the roles.
So it’s important to know what they think. Earlier this year we surveyed over 500 manufacturing professionals from a range of industries, including aerospace and defense, automotive, space, electric vehicles, autonomous vehicles, to understand the challenges associated with product-related communication and knowledge transfer.
In line with the USCB data, female employees accounted for 28% of responses. And while we did not set out to measure gender distribution across industries (and so, offer no conclusive insight) there was some interesting variation by sector. For example, women accounted for just 21% of responses in the aerospace and defense sector while in the emerging SpaceTech sector they accounted for 35%, and in the automotive sector 32%.
When it comes to existing product communication workflows – the ways in which documentation describing products and processes is created, shared, and consumed – the data was clear: 71% of female employees believe there is room for improvement in these workflows, and the same proportion believe documentation challenges at their organization are getting harder to manage as the company grows. Ninety-seven percent of female respondents said they had seen products or projects hit by errors or delays as a result of documentation being late, inaccurate or unclear, or outdated.
Digging further into specific elements of the workflows, and perhaps indicating areas where female employees may have greater insight, women were more acutely concerned about bottlenecks associated with the creation of product documentation than their male counterparts. Sixty-five percent of female respondents reported that creation bottlenecks are a frequent problem at their organization compared to just 51% of male respondents.
They also felt more strongly that managing distribution of, and access to, important documentation was a problem, with 43% of women saying this was difficult for their organization to manage, compared to 36% of male respondents.
With documentation creation and consumption routinely involving collaboration between separate departments, we asked respondents how well different disciplines such as engineering and marketing professionals were able to collaborate. Here, female respondents were perhaps more optimistic than their male counterparts, with 30% saying there were no difficulties, compared to only 20% for male respondents.
In terms of the outcomes of these workflow challenges, women again registered somewhat higher levels of concern than men. Forty percent of female respondents said they had witnessed wastage through product defects as a result of product documentation being delayed, inaccurate or unclear, or outdated, compared to 38% of male respondents. And 38% of women said the same problems had led to delayed or missed sales opportunities, compared to 32% of male respondents; interesting considering the USCB data which showed higher numbers of female workers in manufacturing sales roles.
Perhaps more worryingly, one in three female manufacturing employees believe their organization is not actively seeking ways to improve documentation workflows and processes, which suggests a huge opportunity for improvement if the problems these women are identifying can be highlighted and understood at the leadership level.
So what does success look like for women in manufacturing? Well, with 37% of female respondents saying the applications used in documentation workflows are unsuited to the task, 33% saying there are too many applications involved, and 39% saying there are too many people involved, the data suggests women want to see more autonomy and efficiency in these crucial knowledge transfer workflows.
More than 2 in 3 of female respondents said it would be beneficial to use a single application for the creation of all types of product content, while 62% said it would be beneficial if all collaboration were also to happen in one application channel. Meanwhile, 66% said they believed it would be beneficial if the company was able to track and measure document access and usage.
As in any sector, women have an important role to play in manufacturing and it is essential we understand their perspective on the challenges companies face. A clear takeaway from this research is that female employees believe the manufacturing industry faces a defining challenge when it comes to poor communication and product documentation, which is intricately connected to the success of the entire organization. And when the processes in place break down, the result is self-inflicted damage that could – and should – have been avoided.
About the author:
Patricia Hume is Chief Executive Officer of Canvas GFX.
Manufacturers are staying on top of the tech game.
That was among the chief findings of a new polling conducted by the Manufacturing Leadership Council, the NAM’s digital transformation division. The annual Transformative Technologies in Manufacturing research survey aims to reveal data on current realities and expectations for manufacturing in the near future and in the years to come.
Rate of adoption: The most surprising data point was that 89% of respondents said they expect their company’s rate of adoption of disruptive technologies to increase over the next two years. That figure is up from 51% just one year ago.
Why disruptive technology? Reducing costs and improving operational efficiency were the most-cited reasons for investing in digital tech, with 83% of respondents identifying these as important motivations.
- Improving operational visibility and responsiveness came in second, at 61%.
- Other reasons include increasing digitization (40%), creating a competitive advantage (36%) and improving quality (30%).
Top near-future trends: Digital-twin modeling and simulation software, augmented and virtual reality, high-performance computing and further investments in supply chain management software will lead the next wave of investments during the coming year or two.
Not of interest: The survey found that quantum computing and blockchain technology are currently of the least interest to manufacturers.
The role of AI and ML: Artificial intelligence and machine learning usage continues to grow among manufacturers.
- Nearly 50% of respondents indicated that their companies have implemented AI, either on a single-project basis (40%) or in all factories (9%).
- About 75% said they are applying AI and ML to reduce costs and improve productivity and processes.
- Approximately 60% indicated they had used AI and ML for preventative/predictive maintenance or quality improvement.
Misunderstood metaverse: A new topic covered by this year’s survey, the manufacturing metaverse, was perhaps the least understood by respondents.
- About 38% said they were still trying to understand the technology and concept, 20% said they have no plans to adopt a manufacturing metaverse approach and 15% said they didn’t know how to respond to the question.
The last word: “Manufacturers are finding more use cases and business benefits for increasing their use of digital technology, and the pace of adoption is accelerating,” said MLC Co-Founder and Vice President and Executive Director David R. Brousell.
- “The research confirms that manufacturing is headed for an agile, connected and collaborative future driven by technology and fueled by innovation.”