Table of Contents
- Executive Overview
- Digitization Targets and Outcomes
- Strategy and Management
Over the last several years, industrial and municipal leaders have become increasingly interested in digital transformation. Most organizations recognize that they need to do something about it and many have some kind of transformation program under way. We see this across all industries and among companies of all sizes.
This is not surprising, since many potentially disruptive digital technologies have emerged in recent years, carrying with them the implied promise of significant change. Many of these technologies have moved beyond hype and, while not quite yet mainstream, use cases, practices, and solutions are becoming known and available. Vendors have moved through the usual stages, first largely dismissing the technologies, then adding them to their roadmaps (and marketing materials), before finally incorporating them in products and solutions. This adds pressure for organizations to “do something” about digitization. Unfortunately, it also tends to add to the confusion.
We have only begun to glimpse the potential value to our businesses. In some cases, we can also see alarming potential threats. This is true in discrete industries like automotive, manufacturing, aerospace, and heavy machinery. It’s true in continuous processing industries like chemicals, power generation, and oil & gas. It’s true in utilities, buildings, and smart cities. And it’s true across our transportation and other infrastructure. Clearly, this widespread digital transformation will continue to accelerate and evolve for some time. It’s equally clear that every organization will need to innovate, change, and adapt. The question is, how can organizations take best advantage of this disruptive transformation?
So, where to begin? How can organizations determine which technologies and techniques to consider, which to prioritize, and which to reject? The answer will certainly be different for each organization. A good starting point is to gain an understanding of the critical dimensions of the problem, which can serve as the basis for planning. This report addresses the four dimensions that any organization must consider when developing a digital transformation strategy: targets & outcomes, technologies, change & impacts, and management issues.
Pilots, Strategic Planning, or Both?
Rather than just “dipping their toes in the water” with half-hearted pilots, companies must start and pursue digital transformation plans and programs with determination. They need to effect change quickly, and it must be the right change. The dilemma for many is, where to start?
A holistic plan will work on all four dimensions and changes in each dimension will impact the others. A plan will incorporate emerging technologies, but focus on desired results or outcomes. It will consider the areas that will either need to change to achieve those outcomes – or will be changed as a result. And it will proactively address subjects such as strategic planning, business processes, organization, innovation, and change management. Pilots remain useful, but only as part of a larger, well-thought-out plan.
It’s not too late to begin, but once again, a sense of urgency is mandatory.
Digitization Targets and Outcomes
Digital transformation involves a host of interrelated things that need to be considered. It involves disruptive/transformational technologies, but also affects how products are designed, sourced, manufactured, sold, delivered, and serviced. New business processes, value chains, management practices, information systems, and customer relationships will have to be cultivated, implemented, and optimized. Unlike many other recent technology trends, digital transformation could have “life or death” implications for companies that fail to address it successfully in time. It is not sufficient to pay lip service and wait for a solution to manifest itself. It’s time to act.
ARC has identified six focus areas that are likely to be transformed for the better:
- Operations (both operate and maintain)
- Design and construct
- Supply chain, and
- Business processes
These functional areas are all subject to disruption or transformation from technologies such as IoT platforms and IoT edge, AI and analytics, and cybersecurity.
Smart products, or smart, connected “things,” are often the first thing that come to mind. These products typically have onboard sensors and embedded compute and communications capabilities. They can run analytics and other applications. Designing the smart product demands knowledge of these new capabilities, but also an understanding of how the products, ecosystem, and surrounding business models will operate. Who will own the product? Who will have access to the machine health data generated? How will it be operated and serviced? How will parts and supplies be sourced? What’s the expected lifetime? All may impact the design, materials, process, and production equipment; but they also have organizational implications.
New business models, service organizations, monitoring teams, pricing models, and financing and warranty support may be required. Some might warrant being finalized before design commitments are made.
Adding a smart, connected product to your portfolio can be an important step on the path to digital transformation – but it is not a trivial one.
Many organizations will target production operations, rather than products, for their digital transformation plans. These organizations can choose to focus on asset performance (improving uptime and reducing risk to optimize the asset value over its lifecycle), operations performance (improving responsiveness, changeovers, throughput, quality, safety, sustainability, etc.), or both.
Other organizations will focus primarily on transforming their supply chains or service offerings. Innovations in service offerings could be based on enhanced connectivity and monitoring machine health data, or could represent a new class of service offering centered around the customers’ use of the products. For example, monitoring a farmer’s field conditions and recommending which crops to plant or which fertilizers to apply and when. These digitally enabled services bring the company much closer to the customer, while improving the customer’s results. This improved customer relationship can lead to additional innovations and business opportunities and encourage an ongoing business relationship instead of a series of one-off sales.
Since we live in an age in which so many emerging technologies have enormous disruptive potential, it would be easy to get too caught up in the technologies themselves. However, technology is an important dimension of digital transformation, so it’s worth taking a few moments to highlight some of the technologies that organizations should be considering.
Artificial Intelligence, Machine Learning, Cognitive Computing
AI is the primary enabler and driving force behind digital transformation. With connectivity and execution, AI is already transforming industrial processes in operations, maintenance, engineering design, and supply chain. AI also powers a multitude of other transformative technologies that will drive industrial efficiency. Examples include augmented reality, autonomous machines, smart voice interface, and remote sensing.
The materials used to make smart products are also becoming “smarter.” Materials science; advanced processing, forming and machining; and advanced digital modeling and design techniques all help increase the performance of the materials that make up all components in the value chain. This can contribute to products that are smaller, stronger, lighter, more flexible/stiffer, more wear- and/or stain-resistant, have better resistance to heat or cold, or have smart capabilities such as changing colors or contracting or expanding based on temperature or other environmental changes.
Engineering science is progressing at a fast pace assisted by digital modeling and engineering techniques. This enables new approaches for industrial production that will bring about a step change in performance and a profound transformation of industry. New approaches to interfacing modular equipment and automation have improved interoperability between units and dramatically decreased engineering, commissioning, and integration times to reduce overall time-to-market. This approach started in packaging lines, but is now gaining traction for production equipment in the hybrid industry. Here, modular production can help reduce the time and effort needed to produce different products or product grades.
At the same time, we’re seeing increased intensification, an engineering approach to miniaturize production equipment and improve heat and mass transfer characteristics. With increased modularization and intensification, production lines can be “lined up” instead of “scaled up” to attain the desired production levels. In addition, by interchanging a few modules, the same production lines can be quickly transformed to produce a totally different intermediate or finished product. This can increase both return on assets and production flexibility, particularly when compared to traditional scale-up approaches.
The overall trend is towards highly sustainable, high-quality, high-precision, and highly flexible production that can adapt quickly to changing customer demands and economic circumstances.
Additive manufacturing, perhaps the greatest disruptor in discrete manufacturing today, requires manufacturers to rethink a large swath of their manufacturing processes, methods, and techniques. Additive manufacturing could make decades of tribal knowledge based largely on traditional machining obsolete. In addition, industry is already learning how to “print” wear sensors directly into parts as they are made. This could radically change maintenance models by enabling these smart parts to order their own replacements, when needed.
While still in its infancy, immersive augmented reality (AR) will eventually become standard practice for maintenance and assembly operations. This technology will commonly support and enhance work instructions, assembly/disassembly visualization, parts and tools identification, specifications, training, and more.
IoT Platforms and Solutions
Many different varieties of IoT platforms and/or solutions will undoubtedly play a significant role for most companies on their respective digital transformation journeys. These platforms or solutions may include functionalities such as an application platform, network communications, support for connected products, analytics and algorithms, a rules engine, cloud infrastructure, edge or gateway hardware, and/or off-the-shelf apps.
In many cases, digital transformation will require companies to build out the technology infrastructure located at or near operations to be able to efficiently collect, analyze, process, and store edge data. While operating at the edge can create unique security challenges, it also enables:
- Remote operations
- Reduced requirements for local IT skills
- Multiple applications to run at the edge, such as AI/analytics, field service, etc.
- Access to often-critical and time-sensitive locally generated data
- Autonomous operations
Blockchain decentralized database technology offers the potential to create a permanent, public, secure, transparent ledger system for tracking operations, components, and parts throughout manufacturing and across the supply chain. This will have applications for traceability, anti-counterfeiting, quality enforcement, product pedigree, carbon footprint, and more. In addition, expect to see blockchain technology used in commodity trading, production verification, and many other applications.
Robotics, Autonomous Machines
We are facing the imminent “rise of the machines.” While not in the ominous sense made famous in the “Terminator” movie series (at least not yet), it’s likely that autonomous machines in warehouses, loading docks, or factories for moving inventory, parts, and products will be part of many different companies’ digital transformations. Smarter, safer robots will supplement and/or displace human workers in logistics, assembly, and other operations, freeing those humans for more value-adding activities. And we are seeing telepresence robots, security robots, and other specialized robotics applications emerge.
Digital Twin, Digital Thread
Products, production systems, buildings, and the like need to become smarter and more connected, which places new requirements on design systems. Smart, connected products need sensors, embedded hardware and software, network communications, pedigree, and other system design and modeling requirements and constraints. Increasingly, this will utilize a “digital twin” or digital model of an asset with design specifications and engineering models that describe its geometry, materials, components and behavior, as well as a “digital thread,” a communication framework that allows a connected data flow and integrated view of an asset’s data throughout its lifecycle.
Implementing and maintaining a thorough approach to cybersecurity is a requirement for digital transformation. The Industrial Internet Security Framework, created by the Industrial Internet Consortium, is an example of a comprehensive approach to cybersecurity that can support the needed vigilance. This framework identifies at least 15 threats and vulnerabilities to IIoT endpoints.
While by no means comprehensive, the above list illustrates the point that companies will need to consider and evaluate many disruptive technologies on their digital transformation journeys. Digital transformation projects could also potentially include additional disruptive technologies such as drones, software, cloud, Big Data, or others. In all cases, it is important to think beyond the technologies themselves, to consider the changes or impacts the technologies will usher in, the management challenges, and the results or business outcomes desired.
Transformative initiatives change the organization. Some changes are necessary to drive the transformation; others may result from it. The main levers of change include people and culture; business processes; and production, IT, software, and information systems. These levers should be considered in terms of the functional areas they are intended to impact, such as production operations, as well as other affected areas – such as the broader ecosystem.
Business Process Automation
The shift from manual and/or paper-based business processes to fully or partially automated digitized processes can happen within the organization, across disciplines, across departments and/or across enterprise borders within the value chain network.
One example is automating production analysis. While engineers occasionally perform these analyses, they can never do so with the frequency and consistency that an automated application can. Automated production analysis results in operational analytics dashboards that provide operators with actionable intelligence about desirable process outcomes and the appropriate actions needed to achieve these. Digital transformation also supports improved corporate governance, risk management and compliance, and can introduce more flexibility and faster control to enable businesses to capture often-fleeting opportunities and protect them against associated risks.
Relationships and Ecosystems
Introducing new, more complex and intense relationships and processes often requires new skills. For example, it may be necessary to align goals, roles, and responsibilities and strengthen leadership skills and communication and negotiation abilities. Digital transformation ecosystems tend to be complex. They often need attention, methodologies, and management to work well. As a result, digital transformation triggers renewed interest in communication, interpersonal skills, change management (in the sense of supporting people and organizations to change) and leadership. This is already an integral part of several “smart field” initiatives in the oil & gas industry. Shell upstream, for example, has created a collaborative work environment (CWE) to increase collaboration effectiveness with external parties as well as between people in the company’s own office and production operations.
Norms and Culture
In addition to the new skills required, digital transformation also typically requires individuals, teams, and often entire companies to identify new values that may change or replace the vast amount of habits, norms, and culture deeply embedded in many established companies. This requires change leaders to know how to surface these rules and habits, create trust and cooperation, encourage mutual awareness of each other’s goals, and make the teams and organizations agree on, and commit to a new, commonly defined set of rules.
It can be helpful to use a maturity model (like the one shown below for Plant Performance) to help plan the transformation from a current state to a desired future state.
Strategy and Management
Perhaps the biggest challenge relative to digital transformation is the management challenge. Digital transformation is part of strategy execution. In addition to finding new solutions to known problems, transformation may also involve finding new problems to solve and then solving them in a strategic way. The organization’s strategy must also change. Until recently, basic economic calculations often dominated the approach to strategy, with a focus on commodity, performance, or client intimacy. Now, we find that the potential scope for optimization has increased because systems can be larger and span more entities inside and outside the organization. At the same time, industrial organizations face increasing pressure to develop alternative metrics such as environmental footprint or social sustainability.
The promises of disruption can justify high-risk investments. But this makes risk management and governance even more important, typically requiring more accurate and frequent reporting, performance and risk management, and careful attention to human factors and change management. Often, a change in attitudes and behaviors will be required to successfully change the organization and introduce new processes, relationships, and operating expectations. During the transformation, sufficient attention must also be paid to ensuring both process safety and cybersecurity programs and policies.
Innovation and Speed of Implementation
It can be difficult to find the right balance between creativity and innovation on the one hand, and control and predictability on the other. But if the world is changing around us, we must push beyond our respective comfort zones. We can anticipate the need for new ecosystems, relationships, and ways to collaborate. A premium will be placed on innovation, particularly as it relates to services, business processes, and strategies.
Innovation involves research and development but goes further because it aims to create a marketable and applicable result. Innovation should lead to future-oriented products with high added value that are designed to improve economic, social, and environmental sustainability.
Existing agile manufacturing methods allow companies to adapt to market or user feedback during the product development process. To make innovation even more effective, many companies are turning to the discipline of design thinking, a methodology that draws upon logic, imagination, intuition, subjective experience, and systemic reasoning to explore possibilities of what could be, and create desired outcomes.
Innovations will need to be implemented rapidly, and the innovation process itself will need to be ongoing and iterative. This has implications for technology implementations, which will need to be fast, agile, and iterative.
Innovation must not only be limited to products, production, technology, and business processes. It should also contribute to creating human-centered work designs in which humans and machines work interactively and share tasks through appropriate and adjustable levels of physical and cognitive automation.
In addition to wholesale disruption, effective digital transformation will require evolution and continuous improvement, depending on specific needs and priorities.
Enhanced collaboration among disciplines may also require new organizational forms. Departments may have to be merged and/or collaborative “labs” created. Often, in situations where innovation or intense collaboration is required, it can be helpful to detach people or change from a hierarchical, technical or support organization to small units within development or operations, supported by a centralized pool of experts. More important than formal organizational structure is that people understand their roles and that business processes perform well.
Worker skill profiles will likely need to be redefined to include improving interpersonal skills, developing more IT and IoT skills for all trades, and developing more OT skills for IT and vice versa. This could help facilitate a fast-track approach to application and service development, with successive adaptation cycles following the changes in economics, raw material prices, and consumer trends. Not everyone can diversify his or her skills, so there is room for different, more-or-less focused skills profiles. Lifelong learning and development will not only be desirable, but necessary.
Digital transformation will bring increased data, powerful AI to process and interpret that data, and new business networks. This will almost certainly disrupt organizations and possibly entire value chains.
For organizations to leverage this disruption in a positive manner, digital transformation requires:
- Support from the CEO and top management
- Programs to identify potential new business opportunities and specific goals for digitization
- Innovation expertise
- An expectation that digital transformation will involve substantial changes that will impact people, sacrosanct metrics, organizational structures, and relationships with customers and partners
Nevertheless, it is still important to plan and execute a measured rollout program. This typically involves:
- Putting a team together and creating a lab
- Scanning for challenges and opportunities in all domains
- Listing technical solutions
- Performing continuous value assessment
- Starting small (to minimize initial risk) and then moving fast to roll out what works (to increase ultimate impact)
- Kicking off sustainable change projects and adapting strategy at the corporate level
- Planning and assessing skills; developing business processes, roles and responsibilities; and safety, security, and privacy mechanisms at the technical organizational level
- Addressing the skills gap, engagement, and attitude levels; goals, norms, and culture; and systematic approach and coaching at the human organizational level
An Invitation to Join the Digital Transformation Council
Readers who belong to organizations that are users of software, hardware, or automation systems - such as chemical companies, food & beverage companies, municipalities, utilities, oil and gas companies, automotive companies, mining companies, metals companies, and other similar organizations - may wish to join the Digital Transformation Council. The Council, created at the request of many of ARC’s end user clients, is a member-driven community for professionals who are interested in keeping abreast of the many emerging technologies and business trends, learning from others on similar journeys, and leveraging trends and technologies to achieve transformational growth. There is no fee to participate. Join at https://digitaltransformationcouncil.com/
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