One of the trends I have observed over the last decade is that industrial products continue to be designed and built with greater complexity. My interactions with the industry analyst community have revealed that the Internet of Things (IoT) and a growing reliance on software to execute “smart” capabilities have contributed to this challenge. At the same time, the importance of maintaining operational resilience and agility escalated as companies were forced to adapt quickly during the global pandemic. Change happens faster today. So too must innovation to keep up. These pressures have created an urgent need to improve product design.
Manufacturers have long sought to accelerate and improve innovation. Regardless of the strategy, looking at the data is a great place to start. Today, based on what I hear from the analyst community, manufacturers are increasingly looking at asset service data for insights. Recent technological advances, new digital business models, and industry changes are making this vision increasingly possible.
Three trends are now playing a critical role in easing access to industrial asset service data. This intelligence can now be used to improve product design.
Manufacturing Innovation and Digitalization
It wasn’t long ago when manufacturing innovation was seen as lowering costs. This could be achieved by outsourcing production to developing nations or adopting Lean manufacturing principles. Technology-led innovation ushered in a new era of how products are designed. 3D printing, PLM/CAD software, and Digital Twins have helped to achieve greater efficiency, quality, and performance while enabling higher customer satisfaction.
Manufacturers have also applied innovation to the production process. According to McKinsey, the pace of innovation in manufacturing techniques has skyrocketed by more than 150 percent, as measured by the number of new patents registered in the United States alone over the past two decades.
These changes have been made possible by investing in digital transformation initiatives. Digital Twins and Digital Threads now provide agile blueprints on how processes are executed, designs are optimized, and quality is continuously improved. These digital assets are continually being updated to keep up with today’s pace of change. Organizations that have adopted a “digital-first” perspective are performing with greater effectiveness, including the process taken to improve product design.
Manufacturers are now expanding these digital programs to better understand how their products are used and maintained. Wear patterns can be evaluated. Artificial intelligence can be applied to identify improvements. Features seldom used can be discontinued or provided instead as an optional add-on. This valuable knowledge is now being collected, so makes sense to apply it to new product design. This knowledge has the potential to streamline innovation, improve adoption and customer value, reduce design costs, and ease how new products are serviced and maintained.
[More on the digitization of Field Service Management: Five Foundational Areas for Digital Transformation]
The Transition to Product Servitization
According to Gartner®, “product servitization is the manufacturers’ evolution of their product offerings from a product-oriented service support model to a service-centric operational model through IoT-enabled solutions.” [1] This report suggests that IoT-connected products coupled with modern Field Service Management programs are making product servitization an eventual reality – at least from a technology perspective.
This is a concept now gaining market traction. Manufacturers are transforming their business models from selling products to selling the outcomes delivered by a combination of products and services. Examples often cited by the analyst community of manufacturers that have already adopted this strategy include Caterpillar, Michelin, and Rolls-Royce.
Products delivered as an output-based service place the responsibility on how a product operates on the manufacturer instead of the customer. This means that the manufacturer is now responsible for absorbing the cost of poor quality, service, and maintenance. The ability to access this information quickly and then act upon it has the potential to greatly impact the future profitability of this business model.
The growth of the Internet of Things (IoT) has played an important role in “unlocking” data traditionally trapped within equipment running inside the four walls of a plant. This helps explain the growth in analytics, Artificial Intelligence, and Machine Learning investment. A wealth of data can now be converted into actionable intelligence, helping to make this business model a reality. The only remaining challenge is how to best understand and act upon the wealth of data now visible!
[More on the benefits of aligning product design with outcomes: Design for Outcomes: A Critical Step to Unlocking As-a-Service Models]
The Circular Economy
The value of industrial asset service data has increased as the world grows increasingly sustainability-focused. For example, if a certain type of industrial asset service model is shown to extend an asset’s lifecycle by an additional five years, then the cost to recycle and complete the end-of-life process can be amortized over a longer period for a lower monthly cost of ownership. Alternatively, these assets could be refurbished to further extend the lifecycle and reduce the disposal impact. McKinsey points out that this intelligence can be incorporated into product engineering and design to help reduce a manufacturer’s carbon footprint while driving greater value from ESG initiatives.
According to IDC Research, worldwide spending on ESG business services is forecast to reach $158 Billion in 2025. Note this figure includes just the cost paid to the consultants to understand what should be done – it doesn’t include the cost of implementation!
As raw materials, environmental regulations, and growing corporate governance mandates continue to increase pressure on how products are designed and manufactured, organizations will seek any way possible to improve efficiency and operate with greater precision to avoid waste. Those manufacturers with a viable digital business model and visibility to all aspects of their product lifecycles – including service and support – will have a better opportunity to operate more holistically and positively impact our environment.
[More on the circular economy: Service Is at the Heart of the Circular Economy]
These factors are just a few now impacting the value and criticality of gaining access to asset service data. With this focus, data will be increasingly available and play a greater role in new product design. Firms that invest in digitalization programs that extend to remote field service recognize this increasing importance. An enterprise strategy to capture and harness this data is a great start to being well-positioned to drive innovation, market share, and profitability. I expect more research to be published on this concept in the next 6-12 months.
[More on the asset data thread: The Evolving Role of Field Service]
[1] Now Is the Time to Deliver IoT-Enabled Product Servitization to Manufacturers, Gartner®, by Scot Kim, Eric Goodness, published May 13, 2022.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.
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