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The Digital Revolution in Your Hands: How Products Are Becoming Smart, Connected, and Alive
What if your refrigerator could not only keep food cold but also track expiration dates, suggest recipes based on its contents, and automatically order groceries when supplies run low? What if your car could learn your driving habits, adapt its performance accordingly, and transform into a mobile office during your commute? This isn't science fiction-it's the near future described in "Reinventing the Product" by Eric Schaeffer and David Sovie. As senior managing directors at Accenture with decades of experience in digital transformation, they've created what The Wall Street Journal called "the essential playbook for product companies navigating the digital age." The book has become required reading at Harvard Business School and has influenced product strategy at companies from Samsung to Schneider Electric, precisely because it maps out the tectonic shift happening in manufacturing: the evolution from traditional mechanical products to intelligent, connected, service-oriented platforms.
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The Great Value Migration: From Hardware to Digital Intelligence
For over two centuries, industrial products followed a predictable pattern: companies designed and manufactured items, sold them through distribution channels, and considered their job complete once the sale was finalized. This linear value chain is now experiencing what Schaeffer and Sovie call a "tectonic tilt" toward a circular model where digitally intelligent products maintain constant communication with manufacturers, users, and other products throughout their lifespan.
The economic implications are staggering. Today's typical product derives about 40% of its value from software, 30% from electronics, 20% from mechanical components, and 10% from digital elements. By 2030, this distribution will flip dramatically-digital components will represent 70% of product value, software will account for 20%, while electronics and mechanical parts will shrink to just 5% each. This value migration explains why seven of the world's ten most valuable companies are now platform businesses rather than traditional manufacturers.
This transformation is happening across industries. HP and Lenovo now offer devices-as-a-service rather than selling computers outright. Medical equipment manufacturers are shifting from selling hardware to managing test data and providing analytics. Automakers are investing heavily in ride-sharing platforms. Even industrial engineering firms are using remote diagnostics and predictive maintenance to service equipment they once simply sold and forgot.
Why is this happening now? The convergence of several technologies has created perfect conditions for smart connected products: unlimited cloud computing power, industrial-scale data analytics, miniaturized processing capabilities, advanced power supplies, and seamless connectivity. But the true breakthrough is artificial intelligence, which forms the intellectual foundation of these new products. As Rajen Sheth from Google Cloud AI explains: "Within the next decade, every product will use AI in some form. The question isn't whether to implement it, but how."
Companies that resist this transition risk seeing their traditional products become commoditized with rapidly shrinking margins. As one executive put it: "You don't go to bed as an industrial company and wake up as a software company." The transformation requires entirely new capabilities and the ability to manage multiple business models simultaneously.
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The Product Reinvention Grid: Mapping the Smart Product Revolution
To help companies navigate this complex transition, Schaeffer and Sovie developed the Product Reinvention Grid, which measures two critical dimensions: a product's Intelligence Quotient (IQ)-its smartness and cognitive independence-and its Experience Quotient (EQ)-the quality of experience it delivers to users. This framework provides organizations with a clear roadmap for product evolution in the digital age, helping them assess where they stand and where they need to go.
Traditional products begin in the bottom-left corner with limited intelligence and transactional relationships. Consider a basic thermostat that simply displays temperature and allows manual adjustment. As products evolve upward on the EQ axis, they progress from basic services to as-a-service models focused on outcomes rather than outputs, and potentially to platform-based ecosystems. For example, a smart thermostat like Nest not only controls temperature but learns from user behavior, integrates with other smart home devices, and provides energy optimization services. Along the IQ axis, products advance from basic connectivity to embedded AI capabilities and potential autonomy, illustrated by self-adjusting HVAC systems that optimize comfort while minimizing energy consumption.
The most valuable position-what the authors call "living products"-combines high intelligence with rich experiences. These products are adaptive (learning from usage patterns), collaborative (working with users and other devices), proactive (anticipating needs), and responsible (maintaining security and privacy). Tesla vehicles exemplify this category, continuously learning from their fleet's driving data, automatically updating features, anticipating maintenance needs, and integrating with broader transportation and energy ecosystems.
Smart connected products differ from traditional ones across ten defining traits. On the intelligence side, they feature always-on connectivity (like smartphones maintaining constant network connections), dense sensor arrays (such as modern vehicles with hundreds of sensors), cognitive capabilities through AI (like smart speakers understanding natural language), and continuous upgrades (exemplified by software updates that add new features). On the experience side, they employ digital-age interfaces (touch screens, voice control, gesture recognition), offer hyper-personalization (adapting to individual preferences and usage patterns), function as platforms for multiple parties (like Apple's App Store ecosystem), become embedded in broader ecosystems (smart home devices working together), and maintain a "digital thread" connecting them to manufacturers throughout their lifecycle (enabling predictive maintenance and performance optimization).
Not all products need to reach the upper-right corner of the grid-different markets require different IQ/EQ combinations. A simple household appliance might need only basic smart features, while a medical device might require sophisticated intelligence but with a straightforward user interface. But virtually every product will require some degree of reinvention in the near future. Companies that delay risk disruption from competitors or even players from entirely different sectors, as demonstrated by Amazon and Google becoming formidable competitors in consumer electronics through products like Echo and Nest. Traditional manufacturers like GE and Philips have had to rapidly evolve their product lines to compete with these tech giants, showing how the smart product revolution is reshaping competitive landscapes across industries.
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From Features to Experiences: The First Major Shift
The first major transformation in product reinvention is the shift from delivering functional features to creating meaningful experiences. Unlike standardized product features that remain external to users, experiences are distinctly personal, adaptive, and subjectively assessed. This fundamental change represents a departure from the traditional product-centric mindset to a user-centric approach that prioritizes emotional connection and contextual relevance.
This represents a fundamental change in how value is created. Traditional products competed on specifications-a car's fuel efficiency, a drill's torque capacity, a speaker's sound quality. Smart products, by contrast, compete on their ability to anticipate user needs and desires, adapting to individual preferences and contexts. For instance, modern smart speakers don't just play music with precise audio specs; they learn listening habits, adjust sound profiles automatically, and integrate with home automation systems to create personalized ambient experiences.
In industrial settings, this transformation creates profitable new markets while delivering massive efficiency gains. Airbus, for example, uses smart glasses to improve accuracy and speed in aircraft assembly, reducing error rates by 40% while increasing productivity. The glasses provide real-time guidance, overlay digital instructions onto physical components, and enable remote expert assistance. Similarly, Boeing has implemented augmented reality solutions in wire harness assembly, resulting in a 25% reduction in production time and virtual elimination of errors.
The business impact of customer experience excellence is substantial. B2C companies that exceed customer expectations achieve better ROI (+14%), cost savings (+6%), and customer loyalty (+17%). Companies like Apple demonstrate this by creating ecosystem experiences that transcend individual product features - their devices work seamlessly together, creating a unified experience that keeps customers within their ecosystem. For B2B companies, failing to deliver excellent experiences means missing opportunities to build relationships with customers who spend more and stay longer. Research shows that B2B customers who report excellent experiences are 34% more likely to repurchase and 32% more likely to renew their contracts.
This shift requires a completely different approach to product development. Traditional product features could be engineered by mechanical specialists working in isolation. Experiences, by contrast, demand interdisciplinary collaboration across hardware, software, and service design teams. Companies like Tesla exemplify this approach, with their vehicles receiving regular software updates that add new features and improve existing ones, transforming the traditional car ownership experience. As Olivier Ribet from Dassault Systemes emphasizes: "Unless you engineer the complete user experience from the beginning, it becomes extremely difficult to create truly connected products later."
The transition to experience-based design also requires new metrics and evaluation methods. While traditional products could be assessed through objective measurements, experiences demand continuous feedback loops, sentiment analysis, and behavioral data to understand and improve user satisfaction. Companies must invest in advanced analytics capabilities to capture and interpret these more nuanced indicators of product success.
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From Hardware to 'As a Service': The Second Major Shift
The second transformation involves moving from selling physical products to offering outcomes as services. This shift was pioneered by the software industry, where SaaS companies have grown at 27% annually compared to just 5% for traditional software companies. Adobe exemplifies this transition-after shifting from one-time purchases to subscription models, their service sales grew from 19% to 83% between 2011-2016, and their market value soared from $12 billion to $122 billion.
This approach is now spreading across industrial sectors. Bill Avey, Global Head of Personal Systems Services at HP Inc, explains how their Device-as-a-Service (DaaS) model evolved from customer demand: "Our clients wanted comprehensive device management throughout the technology lifecycle. They wanted analytics to proactively manage devices-anticipating when batteries need replacement or when an employee's role change requires different computing capabilities."
The typical DaaS customer purchases both the device and a bundle of lifecycle services including analytics, deployment, support, and asset recovery-all for a per-seat-per-month fee, usually over a three-year term. This creates predictable revenue streams for HP while giving customers flexibility and reducing their capital expenditures.
This transition requires fundamental changes to product architecture. Products must be designed to constantly transmit usage data, receive over-the-air updates, handle data securely, and deliver AI-powered services. They need adaptable user interfaces for personalized experiences. The manufacturing process becomes fluid, continuing via updates throughout the product lifecycle.
The shift also demands enterprise-wide changes across five key pillars: business strategy, outcome-focused operations, experience-driven design, integrated business platforms, and cross-functional coordination. Companies must manage the challenging transition from upfront revenue to subscription models while building entirely new capabilities like "customer success" teams that ensure users maximize value from their services.
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From Product to Platform: The Third Major Shift
The third transformation involves products evolving into platforms-the center of ecosystems providing business opportunities for many partners. While smartphones with third-party apps are a common example, platform thinking is now spreading across industrial sectors.
Platform business models have created unprecedented value, with seven of the world's top ten companies by market capitalization being platform businesses as of 2018. Beyond tech giants, companies like Airbnb ($30+ billion valuation) and Netflix ($150+ billion) have achieved remarkable valuations using platform-centric approaches.
Unlike traditional products that follow "supply-side economies of scale" focused on manufacturing efficiency, platforms create "demand-side economies of scale" where value increases with user numbers and usage. Successful platforms share nine critical features: network effects, compelling user experience, strong ecosystem partnerships, clear business models, differentiated data, marketplaces connecting users, scalability, digital trust, and specialized expertise.
Apple serves as the leading role model for hardware companies transitioning to platforms. Beyond hardware, Apple operates multiple successful platforms: the App Store (connecting users with developers), Apple Pay (connecting merchants with consumers), and iOS (a development platform). The App Store alone has created an ecosystem of over 20 million developers who have generated $38 billion for Apple.
Industrial firms making similar transitions include Ford (building the Transport Mobility Cloud), GE (with its Predix IIoT platform), John Deere (developing MyJohnDeere for agricultural data), and Haier (creating an open platform for customized appliances). These companies recognize that platform-driven interactions are expected to create approximately two-thirds of the $100 trillion value from digitization by 2025.
Traditional product businesses must develop clear strategies regarding Internet platform titans like Amazon and Google. For many, partnering will be the logical choice as it would be virtually impossible to catch up technologically or match their investments. Seven of the top ten global R&D spenders are now either Internet platforms or high-tech leaders, with Amazon, Alphabet, and Microsoft in the top five.
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From Mechanical to Artificial Intelligence: The Fourth Major Shift
The fourth transformation involves products evolving from mechanical devices to AI-powered systems capable of sensing, comprehending, acting, and learning with minimal human intervention. This shift represents a quantum leap comparable to the transition from steam to electrical power in the early 20th century.
Voice assistant technology exemplifies this revolution. Starting with Apple's Siri in 2011 and followed by Google Assistant and Amazon Alexa, these systems have achieved remarkable consumer acceptance. Smart speakers represent one of consumer electronics' greatest success stories, with global shipments reaching 56 million units in 2018. Consumer satisfaction is extraordinarily high at 94%, driving product makers across industries to embed this technology in everything from speakers to cameras to smart home systems.
But voice control is just the beginning. Advanced image recognition allows devices like Nest doorbells to identify visitors through facial recognition, while autonomous vehicles combine multiple AI technologies for self-driving capabilities. Following semiconductor trends, processing power continues to increase while costs decrease, with modern IoT chips delivering teraflop-level processing in credit card-sized modules.
Nearly 70% of manufacturers view AI as key to their product innovation and growth, with 73% believing it will transform all industrial products and services. Most manufacturers expect at least 30% of their portfolio to be AI-enabled within three years, and 98% have already begun integrating AI into their products.
The greatest value comes from combining AI with other technologies like mobile computing and big data analytics to drive both operational efficiency and differentiated customer experiences. Vanguard companies like 3M (whose AI-powered healthcare documentation system increased hospital revenues by 19%), Caterpillar (with its CatConnect smart equipment service), and Bosch (developing autonomous farming robots) demonstrate AI's transformative industrial potential.
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From Linear to Agile Engineering: The Fifth Major Shift
The final transformation involves completely reimagining how products are designed, developed, and managed throughout their lifecycle. Traditional product development required mechanical engineers to create physical variants at significant cost, with innovations based on limited user insights and resulting features having multi-year shelf lives.
Now, software is eclipsing hardware in many manufacturing sectors, enabling instant creation of device variants at low cost. Products can change through remote recoding, and the constant data loop from installed products provides engineers with invaluable insights for immediate improvements via software updates.
This requires a major cultural shift from linear approaches to "Exponential Organizations" that systematically implement accelerating technologies. Forward-thinking companies connect contextual information (where, how, and by whom products are being used) with other data through ecosystems to design next-level products with enhanced features.
Internet companies like Amazon and Google offer inspiration with their agile, non-linear approach-launching "minimum viable products" quickly, learning from early market performance, and developing rapid-fire updates. This approach has led to legendary successes like Amazon's recommendation engine, which generates around 35% of platform sales and emerged from experimentation rather than strategic planning.
Agile processes fundamentally conflict with traditional waterfall hierarchies. Self-organizing, product-focused teams are essential for smart connected product development, requiring widespread delegation of decision authority. Team size matters-Amazon's "two pizza rule" ensures teams remain small enough to be nimble.
Smart connected products also require "evergreen design"-continuous editing throughout a product's lifecycle rather than discrete generational versions. This demands platform managers who own every aspect of a product experience from launch through its entire lifespan, interacting with both manufacturing and field services. Tesla exemplifies this approach with its autonomous driving development, using AI to learn from human drivers and deploying improvements via remote updates-a revolutionary shift from traditional product testing.
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The Journey to Product Reinvention: Building New Capabilities
Successfully transitioning to smart connected products requires seven pivotal capabilities. The first is "design flexagility"-combining flexibility (the willingness to change) with agility (the speed of change). This approach embraces quick, non-linear development workflows with multidisciplinary teams that break down organizational silos.
The second capability is agile engineering, which enables continuous product improvement through swift feedback cycles, testing, and architecture upgrades. This approach splits large projects into manageable units, employing rapid prototyping cycles with self-governed cross-functional teams working in two-week development sprints.
The third capability is data augmentation leveraging AI. Smart connected products are fundamentally data-driven devices, requiring organizations to become data-augmented across all functions. This means creating comprehensive data models defining what information is recorded, stored, processed, and accessed.
The fourth capability involves developing as-a-service competencies, including solution configuration, transformed sales approaches, service assurance processes, customer success functions, entitlements management systems, and infrastructure support for monitoring devices.
The fifth capability requires building an experiential workforce with specialized skills focused on outcomes rather than features. This demands a customer-centric organization where employees think along end-to-end experiences rather than product features.
The sixth capability involves ecosystem orchestration-identifying partners who contribute crucial technologies, data, or service elements that enhance product value. Only multilateral partnerships and open collaborative networks will fuel breakthrough innovation and create sufficient value for survival in the new product world.
The final capability is pervasive security. Smart products that impact the physical world make security a major concern. Businesses must define mandatory security standards for all ecosystem partners while leveraging the ecosystem to cross-pollinate security solutions.
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The Roadmap to Success: From Vision to Implementation
Successfully transitioning to smart connected products requires a clear roadmap with seven key markers. The journey begins with defining a vision and identifying value spaces on the Product Reinvention Grid. Companies must decide how fast to move on the IQ axis toward living products, and whether to shift business models up the EQ axis toward services or platforms.
The second marker involves digitizing the core business to fund expansion. The "Rotation to the New" framework provides an effective model, balancing the established core business with new digital offerings. Digitizing core operations can generate massive cost savings (300-700 operational cost basis points)-enough to fund investments in new ventures.
The third marker requires sketching a detailed product roadmap charting both intelligence and experience evolution. This means fundamentally rethinking product architecture to incorporate sensors, voice interfaces, security, and upgrade capabilities. Tesla exemplifies this by including additional sensors and remote update capabilities that enable significant improvements without hardware changes.
The fourth marker involves creating a digital innovation factory to accelerate change. This serves as a product and experience innovation center housing interdisciplinary skills needed for faster innovation cycles. Companies like Schneider Electric have implemented digital services factories that reduce creation and launch time for new digital services by 80 percent.
The fifth marker requires setting up a digitally skilled organization that combines capabilities from three traditionally separate domains: Internet platform companies, software companies, and traditional product manufacturers. This means breaking down silos between product development, manufacturing, and service teams.
The sixth marker involves tracking results to constantly adjust course. Smart connected products enable true closed-loop product lifecycle management where manufacturers can continuously monitor and adjust both products and business models based on real-world usage data.
The final marker emphasizes starting the pivot immediately rather than waiting. Digital disruption threatens to displace around half the S&P 500 companies over the next decade. Being too cautious could lead to failure, as these markets are expanding rapidly with or without your participation.
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The Future Is Already Here: 2030 and Beyond
Looking ahead to 2030, the authors envision a world where reinvented products govern our daily lives. Wyoming farmers will run sophisticated agricultural operations using drone fleets and AI analysis, monitoring crop health in real-time, predicting weather patterns, and optimizing irrigation systems down to individual plants. These smart farming systems will reduce water usage by up to 30% while increasing crop yields by 25%. Urban professionals will rely on AI home assistants that function as personal advocates, managing schedules, transportation, and daily needs - from automatically reordering groceries to adjusting home temperatures based on individual family members' preferences and schedules.
Ownership of physical products will largely be replaced by "lifecycle fulfillment packages" that provide goods exactly when needed. For example, instead of buying a washing machine, consumers will subscribe to "clean clothes as a service," where smart appliances monitor their own performance, schedule maintenance, and even order supplies automatically. Autonomous vehicles will transform commuting into productive time for work or leisure, with customizable interiors that shift from mobile offices to entertainment spaces. Industry experts predict that by 2030, over 40% of urban transportation will be autonomous.
Manufacturing will be dominated by humanoid cobots working in collaborative teams, capable of learning new tasks through demonstration and adapting to changing production needs. These cobots will work alongside human operators, handling repetitive or dangerous tasks while humans focus on strategic decision-making and creative problem-solving. Early adopters are already seeing productivity increases of 50-70% in pilot programs.
While these scenarios might seem futuristic, all the technologies they describe already exist today, though at varying levels of maturity. Companies like Boston Dynamics are perfecting humanoid robots, while Tesla's self-driving technology logs millions of miles weekly. Agricultural drones from companies like DJI are already monitoring thousands of acres of farmland, and smart home platforms from Amazon and Google are becoming increasingly sophisticated.
By 2030, these innovations will have evolved from prototypes to mass-market realities, transforming our lives as workers, consumers, and businesses. The integration of 5G networks, edge computing, and advanced AI will enable real-time coordination between devices and systems at an unprecedented scale. Early adopters in industries from healthcare to retail are already seeing 30-40% improvements in operational efficiency.
The transition to smart connected products promises greater productivity, personalization, value, and leisure time. Studies suggest that smart product adoption could reduce household energy consumption by 25% and increase personal productivity by up to 2 hours per day. It will fundamentally change how we relate to our communities, economies, and each other, creating new forms of social interaction and economic opportunity. For product companies, the choice is clear: embrace this transformation or risk becoming irrelevant in a world where products are increasingly smart, connected, and alive. Those who fail to adapt could lose up to 50% of their market share to more innovative competitors within just five years.
