New manufacturing technology and the move to digital is being embraced globally, because manufacturers realize this is necessary to survive, and thrive.
2018 Predictions for Manufacturing Product & Service Innovation
Jeff Hojlo And Heather Ashton | IDC Manufacturing Insights
There is much discussion about this today: How can manufacturers apply machine learning to their business?
Machine learning technology is in its infancy, but we think there is tremendous potential to apply the technology to improve product and service innovation decision support. The manufacturing process chain is complex, with multiple decisions across product development, supply chain, manufacturing, and service that need to be made throughout the lifecycle of a product. It will become increasingly difficult for humans to process massive amounts of data efficiently and make the optimal decision, especially under time to market constraints and expectations for rapid service.
In our IDC 2017 Product and Service Innovation survey, we asked respondents to rate the importance of new technology areas for their product and service innovation efforts currently and over the next 12 months: IoT and robotics, not surprisingly, were high in the short and longer term – but it was AI and machine learning that showed the largest increase (17%) in interest now vs. 12 months from now. It’s not data deluge itself that is driving this interest, it’s the common challenges and business drivers that manufacturers face every day: enterprise quality, understanding customer needs, improving productivity, ensuring a good customer experience. Machine learning, combined with IoT and cognitive analytics, will become tools for effectively managing these challenges.
I’ve not heard of the concept of innovation blockchains – how could blockchain technology improve product and service innovation?
We are starting to see some promising applications of blockchain technology across business processes for global manufacturers, and the number of inquiries around this emerging technology continues to grow as product and service leaders seek to gain an understanding of how blockchain and distributed ledger technology can assist in the product, customer, and service lifecycles. We expect pilot projects to continue to proliferate in the coming months, as manufacturers become more familiar with blockchain technology and find new uses for it. On the front end of the product lifecycle, using a distributed ledger to assist with product design collaboration could yield shorter product development cycles due to faster design and design team validation, thus improving new product introduction cycles. On the service end, creating the immutable history of an asset, its parts and maintenance records, provides a level of visibility throughout the service lifecycle that enables the creation of new, value-added service offerings that can be monetized.
Is this blockchain concept the same as Bitcoin?
Open innovation is covered in one of your predictions – what’s new about this?
The product failure rate is high across industries, in some cases up to 80%, in large part because manufacturers don’t consistently take the time to understand customer needs at the front end of innovation. Or they presumed what the market wanted. This is a lesson the FMCG industry learned decades ago due to a highly competitive market, and varied product portfolio. These same “fast moving,” dynamic characteristics are making their way into other industries that traditionally have had a longer product lifecycle, such as automotive, heavy equipment, and industrial machinery. Companies in asset intensive industries like chemicals also recognize the need for a proactive, flexible approach to product and process innovation. With the growth and maturation of cloud based platforms, the integration of social media-like capabilities within collaborative innovation systems, and the broader use of simulation and virtualization of product models, or digital twins, the tools are available now for manufacturers in all industries to progress and modernize their approach to ideation, innovation, and new product development.
What is a digital twin and why should manufacturers care?
CAD, simulation, and virtualization of products across engineering domains has been used by automotive manufacturers at increasing levels of sophistication over the past 30+ years. The term “digital twin” was coined by DARPA (Defense Advanced Research Projects Agency) decades ago, but it wasn’t until the past 24 months as 3rd platform technologies (cloud, mobile, big data/analytics, social business) and innovation accelerators like IoT were adopted that the concept of applying visualization and simulation more broadly to the operations of a product or asset became more possible and widespread. Digital twins, or virtual representations, can be used for ideation and early stage design of products and assets, for development of those product/asset models among design, R&D, and engineering, and ultimately, operations of digital twins by engineering and service working in concert. That is, using the digital twin to track performance, usage, and quality so any issues can be addressed quickly, any software or mechatronic updates can be simulated, and the “experience” with said product or asset will be continually optimal. Increasingly, manufacturers in automotive and other industries with connected, complex products, are considering how to leverage the enormous goldmine of information from connected products to be more responsive with service, reduce the cost of quality defects, and improve design and engineering output. Digital twins present a viable way for manufacturers to achieve this.
What is it about today’s market conditions that is sparking the gig economy?
Freelancers, independent consultants, and temporary workers, have been present in our economy for years. This trend has accelerated over the past 20 years through two major periods: the .com bubble burst, and more significantly and recently, the Great Recession of 2008. The gig economy has been defined to include part-time, temporary and freelance jobs. In 2017, it became a significant portion of the workforce in the U.S. and globally in countries that have the digital infrastructure to support it. This digital infrastructure is a core reason the gig economy is so popular, even in a non-recessionary market: it enables talent accessibility.
The benefits to manufacturers include cost savings through a variable workforce that can be more closely tied to customer demand, access to skilled experts who would not be traditional hires (e.g. the personal computer hobbyist with another career), and higher customer service levels. All of this is made possible by the Third Platform — notably the proliferation of personal mobile devices — and Innovation Accelerators like Augmented Reality, which enable guided repairs and remote expert instruction.
How can manufacturers take advantage of augmented service?
Manufacturers continue to increase the connectivity of their installed base of products, leveraging IoT, cloud, and analytics to deliver connected services to customers. Our most recent IDC Product and Service Innovation Survey follows this growth, with 18% of respondents indicating that over one quarter of the products they manufacture are connected. Looking ahead three years, 28% of manufacturers will have more than a quarter of products connected, and 9% of those will have more than half their products connected. This connectivity is essential to enabling connected services and the accompanying revenue increases from services. As part of our Digital Transformation research, we have identified a collection of specific use cases related to connected services that manufacturers are actively pursuing. Among them, remote management and augmented service execution exemplify the opportunities that connected products create for OEMs.
In general, do you think the global manufacturing industry healthy and growing?
If you look at the second half 2017 global manufacturing PMI, overall there is healthy growth. The manufacturing industry is undergoing digital transformation on many levels, change that will enable manufacturers to improve their ability to get to market quickly, ensure product and process quality, as well as sense demand and meet customer needs more effectively. This transformation is challenging of course, and presents opportunity for growth.
Which countries do you see embracing new manufacturing technology and which need to do more to get on board?
New manufacturing technology and the move to digital is being embraced globally, because manufacturers realize this is necessary to survive, and thrive. Although different manufacturers in various countries will adopt these technologies at different rates, our data shows considerable global growth of 3rd platform (cloud, big data/analytics, mobile, social business) and innovation accelerator technology (IoT, cognitive analytics, blockchain, AR/VR, advanced security), with innovation accelerator tech at a 17% CAGR.
About Jeff Hojlo, Program Director, Product Innovation at IDC Manufacturing Insights
As Program Director, Product Innovation, Jeff Hojlo leads IDC research and analysis of the PLM and collaborative innovation market, including topics such as the development of an innovation platform and the intersection of product design, development, and digital manufacturing. Mr. Hojlo is also responsible for research on business and IT issues related to the engineering oriented value chain (EOVC), which includes automotive, aerospace & defense, industrial machinery, and heavy equipment manufacturers, as well as the technology oriented value chain (TOVC), which includes manufacturers in the electronics and semiconductor markets. Mr. Hojlo regularly contributes to the IDC Manufacturing Insights Community (http://idc-insights-community.com/manufacturing) and tweets (@jeffhojlo) about business and IT issues relevant to manufacturers and their product innovation strategy.
About Heather Ashton, Research Manager, Service Innovation, IDC Manufacturing Insights
Heather Ashton is Research Manager for IDC Manufacturing Insights responsible for the service innovation practice. Ms. Ashton's core research coverage includes the customer and service lifecycles in manufacturing, including CX and UX, field service, and warranty, as well as the impact of connected products on customer engagement and service transformation. Based on her coverage of connected products and innovation accelerators like IoT, AR/VR, and artificial intelligence, Ms. Ashton's research also includes an emphasis on operating model transformation in manufacturing, including connected service and product-service systems. In automotive, Ms. Ashton's research focuses on the impact of connected cars and emerging mobility options for Automotive OEMs' business models and service offerings.
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