By Peter Thorne
Manufacturers can initiate their digital transformation by using enterprise software to develop “digital twins” that mirror their physical assets
By Peter Thorne
September 17, 2019 – “My customers would have asked for faster horses.”
“No amount of development and optimization of candles will deliver electric lighting.”
Most cases are less dramatic, but whatever the situation, there are limitations to both customer-driven strategies and incremental technology development. Sometimes product lifecycle management (PLM) providers must make a big leap in the technology they offer. But their customers want and sometimes need future-development road maps to have a step-by-step feel. Giant leaps are disconcerting.
To bridge this gap, it helps firstly to have a good idea of all the implications of the big leap, and secondly to articulate the road map so that the big leap can be seen in context. One well-known example is in the automotive sector: the road maps for ADAS (advanced driver assistance systems, including autonomous driving) are presented in six levels, from level zero (a human driver controlling everything) to level five (an automatic system that at least matches the performance of a human driver). The big leap comes at level four – no human interaction required.
The wireless communications sector has built the idea of continuous progress with occasional big technology steps into its way of life. The framework from 2G – via 3G and 4G – to 5G has provided the foundation for individual road maps for providers across the entire industry ecosystem. By signalling the steps along the way, everyone involved – the users, the OEMs, the suppliers and the legislators – knows what’s coming and can plan accordingly.
Similarly, the “digital twin” concept is creating an opportunity for PLM companies to define digital transformation road maps for manufacturers.
What is a digital twin?
“Digital twin” is a concept that PLM providers use both as a strategic anchor, and also to communicate the pathway to the future. Their efforts are commendable but have left plenty of space for management consultants to sell “digital transformation” strategies to the top table of management in all the sectors that buy PLM technology.
Digital twin is perceived as a technology – the capability to replicate the characteristics of a physical item in the computer. Digital transformation is something for which management teams must have a vision – a vision for doing more online, a vision that develops and innovates the business model, outflanks fast-moving born-digital start-ups, identifies new revenue streams and defines new competitive advantage.
So how does this fit into a road map? In industrial enterprise software – including PLM – there is no accepted whole-sector framework comparable to 2G-5G in wireless communications, or level zero to five in automotive ADAS. Perhaps the closest contender is Industry 4.0, which describes the concept of connected digitalized industry value chains. Some published material gives maturity-model-type guidance on how to judge the “as-is” and “should-be” Industry 4.0 status of an organization, and these concepts help frame the characteristics a road map should address. However, enterprise software is just one part of an Industry 4.0 vision, so each enterprise software provider must identify how its offer addresses Industry 4.0 objectives.
PLM providers hold an important card: management teams in their target markets believe “PLM” is the owner and source of “digital twin” capabilities. In addition, all industry sectors have an almost unblemished historic record of allocating a higher proportion of their budgets each year for expenditure on engineering software – and forecasts indicate this trend will continue (see figure 1).
This trend is the result of the complex interplay of various aspects of market dynamics. New technologies get the headlines, and these are taken up by early adopters. A combination of new technologies and experience enables users to make better use of software, and grow both the scope and intensity of use of applications.
Also, as time passes, the market lifecycle leads new buyers into the market – the early majority and the late majority of the bell-shaped take-up curve – and overall penetration increases. The result of these factors is the “propensity to spend” curves in figure 1. So market growth within an industry is possible even if the industry itself is not growing.
Responding to market changes
Let’s start with table-stakes. The entry level is that a digital twin road map must make a positive contribution to an overall value proposition. Each PLM provider must show how its road map for digital twin can support and help shape digital transformation in general.
But anyone writing the PEST (political, economic, social, technology) sections for a business plan with global scope will also be asking questions about globalization assumptions and forecasts.
This is fertile ground for discussion with the top management of any organization involved in design, engineering, production, distribution and service. In the manufacturing context, the flow of conversation is broadly:
- Advances in manufacturing technology shift the balance between low-cost labour and highly skilled labour as a source of competitive advantage.
- At some point, new versions of the old spreadsheets that said, “Build factories in low-cost regions” are going to reach a tipping point and will say “Build factories in locations where it is easiest to install, run and maintain advanced production systems.”
- These are complex waters to navigate. Those spreadsheets are just one of many factors that guide manufacturing businesses towards growth and profit. But fluency in the use of connected digital systems is widely seen as vital for survival. This fluency will be key to the ability to “sweat the assets” of an advanced production system and also enable an organization to define and defend its role in the most profitable industry networks.
A change in thinking is needed to enable an organization to achieve the required level of digital fluency. In these days of cloud computing and smart connected products, it is not effective to think in terms of computers, application software and databases. The siloes are changing and the old technology-centric acronyms no longer provide a good guide to the way software should be used.
The best way to plan digital transformation is in terms of digital twins. This is because digital twins will be the nodes that enable communication, automation and optimization for cooperating teams of people and systems. And, crucially, the concept of digital twins empowers non-technical people to see, and help define, the information flow to support their organization’s core value-adding processes.
Digital twins add all the physical assets of an organization and its partners into the scope of online information and operational systems. Business process and business model development can consider the entire business online. This is a big change, because in the past only the parts of the business defined by forms, documents and transactions could be handled this way.
Digital twins allow every status, every action, every command traveling to and from smart connected objects to be handled online and also to be simulated in advance. Whereas Amazon had to invest at a spectacular scale to move retailing online and change market expectations, digital twins offer a step-by-step approach, using the smart connected assets – which are first choices for investment anyway – and integrating smart connected capabilities, which many companies are already adding into their own products.
Business value from digital twins
Everyone needs a proof-point for these claims; technology must deliver business value. One of the easiest examples to explain is predictive maintenance – smart connected assets backed by analytics systems to offer a step-change improvement in uptime for the assets, with lower servicing costs.
But wait – where did this concept come from? It needed a “eureka” moment from the individual or team who first imagined it. Somehow, these people juggled concepts of continuous monitoring, the ability to identify and recognize pre-failure profiles from sensor readings, and insight and belief that this could change the business process of periodic maintenance and fault fixing.
This leads to a question for the management team at a manufacturing operation: where do they (or their management consultants) expect this type of thinking to originate? Digital transformation benefits for their organization will come partly from implementing widely known concepts like predictive maintenance, and partly from seeing unique and proprietary opportunities to innovate, differentiate and improve business processes that impact customers, suppliers and in-house plans and decisions.
The opportunity could be uptime in a production facility, or operational processes to reduce material and energy consumption, or virtual commissioning to reduce the time needed for physical commissioning and start-up of new assets. Who in the organization will see these new capabilities, new efficiencies in working practices, new automation opportunities and new cost reductions?
Making digital twins a core unit of thinking for digital transformation will increase the chance that leaders at all levels of a manufacturing organization can contribute, and make the connections to business value. The IT team is important – but a digital twin discussion is not an IT discussion, it’s a business discussion in which insight into the way assets and products are used will be the catalyst, so the top team themselves will be vital contributors.
In their conversations with manufacturers, PLM providers will need to emphasize how, compared to a no-simulation digital twin, the capability to simulate its physical counterpart enables their digital twins to support a much wider range of possibilities for automation, remote asset management, problem solving and process innovation.
Peter Thorne is managing director of Cambashi, an enterprise software market research company.