Feature
The industrial sector stands at the brink of a new era where traditional manufacturing and service provision are being transformed by the potent mix of data analytics and generative artificial intelligence. As we look ahead, it's clear that the future of industries is being written by the innovative application of a series of advanced technologies.
The Digital Game-Changer
In their seminal book "Designed for Digital: How to Architect Your Business for Sustained Success," Jeanne Ross, Cynthia Beath and Martin Mocker outline how digital technologies are revolutionizing business. They point to three pivotal capabilities: ubiquitous data, unlimited connectivity and massive processing power. The book suggests the notion of digital offerings and gives examples from industrial companies. However, it's with the release of the book "Fusion Strategy: How Real-Time Data and AI Will Power the Industrial Future" by Vijay Govindarajan and Venkat Venkatraman that we see a comprehensive blueprint for how data and AI specifically empower the industrial future.
Steel Meets Silicon
Govindarajan and Venkatraman's work underscores the critical role of industry in the global economy, contributing to a staggering 75% of GDP across manufacturing, mining, transportation, logistics, construction and health care. They contend that industrial companies must adopt “fusion strategies” to withstand an onslaught from digital-native entities. They claim an inflection point with advances in hardware, software, applications, cloud, data, algorithms and generative AI.
Fusion strategies involve melding the best of physical products with the prowess of AI, leveraging vast data sets to drive business innovation. This means combining what industries do best (physical products) with what digital natives do best (using AI to parse enormous, interconnected, product-in-use data sets to make strategic connections that would otherwise be impossible). One of my favorite examples of a company that has done this is GE — they have used jet engine data to move from selling jet engines to selling a propulsion service to airlines.
The Fusion Approach
An example of fusion from Govindarajan and Venkatraman's is John Deere's See and Spray technology. This solution can differentiate crops from weeds, reducing herbicide use. This approach not only enhances customer value, but also paves the way for novel products and services that address customer needs more effectively.
Datagraphs: Fuel for Fusion Strategies
Datagraphs — a new term for us in the data business — embody an intricate web of interactions and relationships between a company and its products in active use. These encapsulate the myriad connections, links and relationships that are forged between a company and its clientele through the lens of product utilization data.
The term stems from the principles of social networks and graph theory, wherein graph denotes the nature of the connections, pinpointing the pivotal attributes within a networked ecosystem. Govindarajan and Venkatraman tie datagraphs to digital twins — a virtual representation of a product or service that allows for real-time monitoring and analysis. By feeding continuous data back into the product development cycle, digital twins enable products to be perpetually upgraded, ensuring they evolve with the changing demands and expectations of the market.
Govindarajan and Venkatraman claim that datagraph pioneers put themselves at the forefront of data-driven innovation. By collecting and analyzing product usage data, these businesses rapidly integrate insights into their offerings, enhancing the value of their products and services. Additionally, by refining their data and algorithms, this vanguard can constantly improve its customer value propositions, ensuring their solutions are not only valuable, but also remain cutting-edge.
Algorithms at the Helm
Clearly, it is through algorithms that datagraphs are translated into actionable insights, enabling companies to not only respond to current trends, but to anticipate future occurrences.
For this reason, the interplay of datagraphs, AI and algorithms sets the stage for the next generation of industrial innovation. This trio not only interlocks physical and digital business domains, but also enables the creation of digital twins, mixed reality experiences and cross-industry ecosystems that deliver improved products, optimized business processes and enhanced customer service.
See more: Why CIOs and CDOs Need to Work Together on Generative AI
The Industrial Vanguard
Major industrial players, like ABB, Caterpillar and Siemens, say the authors, are countering the threat of digital disruption by digitizing the core of their offerings. These organizations are doing this by digitizing the core of their business — their products. Increasingly this is about multimodal data. To deliver upon this vision, the authors suggest organizations engineer data network effects with tripartite twins — digital representations of the product, process and performance — to facilitate seamless data flows and refine the industrial ontology for better machine performance and customer productivity.
The authors suggest large language models (LLMs) represent a significant advancement in the digital realm — they can uncover previously hidden relationships between concepts, identify underlying root causes more easily, recommend what to do in response and determine how best to redesign the next machine. Only with the emergence of GenAI is it possible to manage the complexity of today’s businesses, according to the authors of the book “Ecosystems Architecture: New Thinking for Practitioners in the Age of AI.” It is interesting to recognize here that Judith Horwitz argues in “Causal AI” for something more — causal AI that can connect cause and effect.
Four Battlegrounds
Fusion strategies delineate four strategic arenas: fusion products, fusion systems, fusion solutions and fusion services. The difference lies in the complexity, ranging from a single product to a network of interconnected solutions. The goal is to ensure interoperability, real-time performance monitoring and the creation of value through services that wrap around products.
Fusion products that interoperate are designed with telemetry to observe their performance in real-time. For example, Rolls Royce analyzes fuel consumption patterns based on product-in-use data. Meanwhile, fusion systems ingest data across tripartite twins in operations and resulting network effects. In terms of ecosystems, every company that is interconnectable can participate in multiple ecosystems.
The value proposition of a fusion products strategy is based not on what happens inside the industrial company, but how products perform in the field with the power of the performance twin unlocking new value.
The Importance of Ecosystems
In the digital age, ecosystems have become critical for businesses seeking to thrive and maintain competitive advantage. Peter Weill and Stephanie Woerner's concept of ecosystems in the book "What’s Your Digital Business Model: Six Questions to Help You Build the Next-Generation Enterprise" delineates two primary roles within ecosystems: modular producers and ecosystem drivers. Modular producers offer plug-and-play products and services that can seamlessly integrate into existing systems, while ecosystem drivers coordinate the network of enterprises, devices and customers, creating a harmonious value exchange for all participants.
This ecosystem thinking aligns well with the perspectives of Govindarajan and Venkatraman. They argue that the next decade will witness a shift where industrial organizations increasingly seek differentiation through fusion strategies. This blend of physical and digital elements is essential to create a more dynamic, responsive and customer-centric business model. By incorporating next-generation technologies, such as the Internet of Things (IoT), robotics and general AI, companies will unlock new levels of efficiency and offer unprecedented value to their customers. In this model, companies will support ecosystem providers or own an open ecosystem.
The Road Ahead
The book outlines a four-step path for industrial organizations to architect and implement fusion strategies. It calls for designing products with an open tech stack, unifying data and processes, accelerating the transition road map and defining mechanisms for monetization.
Delivering
Unlocking business potential at every stage involves merging advanced science and digital tech. This allows innovation to flourish, predict future impacts and foster machine-human collaboration. Upskill current employees and attract future talent.
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Expanding a network occurs by embracing collective intelligence. Strengthen ecosystems through alliances and partnerships. And make ecosystems efficient and adaptable for the future. All of this is powered by developing fusion leaders who embody integrated thinking and instill this mindset from the top down. Finally, these leaders should guide the journey with a strategic scorecard, adjusting tactics based on metrics.
In Conclusion
As we stand on the precipice of this digital transformation, it's evident that a fusion-driven approach is not just advantageous, but necessary. The journey forward requires innovative thinking, strategic alliances and a new breed of leadership capable of navigating the complex landscape of digital and physical integration. The task espoused by Govindarajan and Venkatraman is clear: embrace the fusion of industry and innovation or risk obsolescence in the rapidly evolving industrial future.
Like author Rita McGrath, business leaders must develop the capability to recognize the signals that indicate the relative attractiveness of different battlegrounds, make sense of competitive moves and technology developments and take decisive action. A digital-first architecture will eventually win in the battle of brilliant machines. For this reason, CEOs must address the issues preventing action immediately.
See more: Unveiling the Secrets to Winning in the Age of Digital & AI
