Reinventing the Product

You are entering the era of Product X.0, where products are no longer static objects but living systems. This transformation—powered by sensors, connectivity, compute, cloud, and artificial intelligence—redefines what it means to design, sell, and support products. The authors argue that companies that fail to adapt will lose margin and relevance to digital-native competitors and platform giants. To succeed, you must shift your mindset from making products to managing ongoing relationships throughout the product’s lifecycle.

From Transaction to Relationship

In the traditional model, you sell a product once and hand over responsibility. In Product X.0, ownership is continuous. Your devices send telemetry back to you, helping improve performance, anticipate failures, and deliver ongoing upgrades. This drives a pivot from one-off revenue to recurring, outcome-based models—mirroring how companies like Rolls-Royce (Power-by-the-Hour) and Michelin (Effifuel) transitioned from selling equipment to guaranteeing performance over time.

Why It Matters Now

The book recognizes a major economic shift: value migration from physical components to digital ones. Mechanical and electronic elements are shrinking as a share of total product value, while software, analytics, and experience layers dominate the pie. If you neglect this, platform players will capture what was once your margin. The World Economic Forum and Accenture estimate up to $100 trillion in potential unlocked value from digitization by 2030—a generational opportunity for those who reinvent early.

Six Imperatives for Reinvention

• Transform the core: Digitize engineering, manufacturing, and services to enable the pivot.
• Focus on experiences and outcomes: Build measurable customer value rather than features.
• Join or lead ecosystems: You can’t provide everything yourself—collaboration is mandatory.
• Work new business models: Move toward as-a-service and subscription pricing.
• Build a digital-ready workforce: Incorporate data scientists, UX designers, and platform engineers alongside traditional roles.
• Manage multiple pivots: Balance digitizing the core with exploring new platforms and AI-enabled products.

Core insight

The product is no longer an endpoint. It becomes a living system with customers and data at the center. You move from isolated transactions to continuous relationships built on insight, adaptation, and shared outcomes.

This first idea sets the stage for everything that follows: redefining the product’s intelligence, experience, business model, design process, and ecosystem. Reinvention is not optional—it’s the foundation for survival and competitive advantage in a connected world.

To guide reinvention, the authors introduce the Product Reinvention Grid. It maps two dimensions: Intelligence Quotient (IQ) and Experience Quotient (EQ). IQ measures how smart, connected, and autonomous your product is. EQ measures how rich, satisfying, and outcome-oriented your customer experience has become. Together, these determine your Product Reinvention Quotient (PRQ)—a composite score indicating the depth of change required.

Raising Product IQ

IQ grows through sensors, embedded compute, connectivity, and AI-enabled autonomy. A basic connected appliance may have modest IQ, while Tesla’s continuously learning fleet demonstrates the high end. You can move step-by-step: from connected devices to intelligent ones and eventually autonomous systems. Airbus engines brimming with sensors show how telemetry drives smarter maintenance and autonomy potential.

Evolving Product EQ

EQ starts with raw features, matures into services, then becomes as-a-service models, and finally platform-led experiences. Apple’s App Store exemplifies maximum EQ—where third parties build value around your product. For industrial firms, rising EQ means shifting from hardware reliability to measurable outcomes such as efficiency or uptime. Michelin and Haier demonstrate how even industrial goods can become experience engines.

Using the PRQ

Plot your product on the grid. Identify your current IQ and EQ, then define the desired state that matches customer expectations. A high PRQ means deep transformation: new architectures, data models, and business processes. A mid-range PRQ may only require adding services or connectivity. Use the PRQ as a shared language across R&D, marketing, and operations to prioritize investments and avoid chasing every shiny technology.

Implementation principle

Success isn’t limited to the upper-right corner of the grid. Choose the quadrant that fits your customers and capabilities—focus on business relevance, not just technological ambition.

By quantifying IQ and EQ, you can make concrete plans: upgrade connectivity, embed analytics, introduce as-a-service pricing, or build ecosystems. Treat the grid as your navigational map to Product X.0 maturity.

One of the biggest mindset changes is moving from selling features to delivering experiences. Products succeed not by having more features but by generating simple, emotional, outcome-oriented interactions. In B2B, this means performance, uptime, and total cost; in B2C, it means convenience and delight. Either way, your customers expect ease, speed, and personalization.

What Constitutes a Product Experience

An experience blends functionality, user interface, support, analytics, and emotion. It’s judged by how relevant and effortless it feels. Design experiences around moments that matter: the touchpoints that define satisfaction or frustration. Then measure them—through uptime, loyalty, renewal rates, or Net Promoter Score—rather than counting features used. The book highlights Schneider Electric, which redefined equipment reliability as an experience outcome using predictive analytics.

Engineering Experiences

Building experiences demands new collaboration. Designers, engineers, and data scientists must work in cross-functional teams using design thinking and iterative testing. You prototype, test with real users, and continuously refine. Airbus used augmented reality tools to improve assembly experiences for technicians; Faurecia built voice-centric smart cockpits for personalized in-car engagement; Biesse simplified its machine interface based on operator feedback.

Design principle

Great experiences are easy, fast, and convenient. Make these three tangible and customers will stay loyal—even in markets once defined by price.

By turning your product into an experience engine—instrumented, data-rich, and human-centered—you unlock recurring revenue and defensible differentiation. (Compare this focus with Pine & Gilmore’s concept of the Experience Economy—it applies equally to industrial and consumer markets when done systematically.)

Reinvention eventually transforms your business model. You move from selling hardware to providing Product-as-a-Service. This transition converts one-time transactions into recurring revenue streams, but it also reshapes finance, operations, and sales incentives.

New Commercial Foundations

As-a-Service economics turn capital expenditure into predictable operating expense. While attractive, this requires upfront investment in telemetry, support, and analytics. Finance teams must adjust for slower cash inflows and longer customer lifetime value. You’ll need new tools: CPQ systems for complex subscription bundles, entitlement management for feature access, SLA monitoring for uptime, and Customer Success organizations focused on adoption and retention.

Examples and Lessons

HP’s Device-as-a-Service and Michelin’s Effifuel show different as-a-service archetypes—hardware plus analytics bundled into monthly fees that guarantee outcomes. Adobe’s pivot to subscriptions transformed its valuation, a signal that even traditional suppliers can make the transition if they integrate data, billing, and lifecycle management. Rolls-Royce pioneered this in industrial settings decades ago, proving the model’s durability.

Operational Alignment

Sales, accounting, and field service must all realign. Commissions shift from one-time sales to usage-based retention rewards. Warranty design becomes SLA management. Finance needs metrics that capture customer success rather than inventory turnover. The Rotation to the New approach—digitizing older processes to fund the pivot—helps balance the transition without wrecking short-term cash flow.

Core insight

Product-as-a-Service is not just pricing innovation; it’s the operating model for intelligent, connected offerings. You win not by selling ownership but by ensuring outcomes.

Moving to as-a-service defines how Product X.0 generates future cash flow and maintains customer intimacy through data and trust. It marks the point where your product becomes both service and platform.

Product X.0 demands a complete rethinking of engineering. You shift from long, waterfall cycles to agile, model-based, data-driven development. Instead of freezing designs months ahead, you release prototypes, collect feedback, and iterate continuously. This concept—called Engineering in the New—combines agile hardware methods, digital twins, and unified lifecycle management.

Agile Hardware and AutoScrum

AutoScrum adapts agile software principles for complex systems. You synchronize cross-functional teams on sprints, develop on cadence, and release when ready. Tesla’s least-path engineer-to-engineer communication model exemplifies this—autonomy and speed replace managerial bottlenecks. Haier’s networked micro-enterprises illustrate agile organization at scale for manufacturing.

Digital Twin and Digital Thread

Your twin is the virtual replica of your product—geometry, materials, software, and field telemetry. The thread connects design, production, and service data across the lifecycle. Together, they enable predictive maintenance, remote updates, and rapid feature refinement. Airbus, Faurecia, and Caterpillar use twins to optimize performance and shorten development loops.

Integrated Engineering Toolchain

ALM (Application Lifecycle Management) merges with PLM (Product Lifecycle Management). This integration ensures traceability between software patches and hardware configuration—a necessity for over-the-air updates. Digital innovation factories (Schneider Electric, Nytec, Faurecia CoF labs) host multidisciplinary teams that iterate rapidly using simulation and prototype tools.

Performance insight

Engineering in the New delivers up to a 10X productivity gain by connecting data, teams, and development cadence. It transforms hardware design from a linear sequence into a continuous, living process.

In short, your engineering function becomes the heartbeat of product learning and evolution. By adopting agile, model-based methods and a connected engineering stack, you move from designing products to orchestrating their ongoing performance and intelligence.

Data and artificial intelligence are now the foundational forces of product reinvention. Data fuels the learning loop; AI interprets, predicts, and adapts behavior in real time. The authors frame AI as the new mechatronics—where sensing, comprehension, action, and learning converge to make products proactive rather than reactive.

The Four AI Capabilities

• Sense: Gather inputs through image, audio, or environmental sensors.
• Comprehend: Use NLP and contextual analytics to interpret meaning.
• Act: Drive real-time autonomy, as seen in robotics and self-driving systems.
• Learn: Apply machine learning to improve performance over time.

Data Architectures for Smart Products

Legacy SKU-and-BOM systems hinder learning. You must shift to unified data models that combine hardware, software, and experiential attributes. Attribute-based data allows real-time updates and analytics across design, manufacturing, and support. Paired with digital twins and threads, this data architecture becomes the nervous system of your living products.

Voice and Experience Interfaces

Voice-driven UIs transform experiences through natural interaction. Smart speakers (Echo, Google Home) exemplify widespread adoption and satisfaction. Faurecia’s integration of Alexa into its intelligent cockpit demonstrates how voice embeds AI into the everyday driving experience.

From Data to Insight

The authors note that most manufacturers are early on this journey. Around 70% appreciate AI’s potential, but fewer than 20% have funded strategies. You must invest in data quality, governance, and AI talent. Whether you partner with cloud giants or build internal capabilities, treating data as a first-class product is non-negotiable.

Core insight

Data is the sensor, AI is the brain, and together they create intelligent systems capable of continuous evolution. Treat them as product features, not back-office tools.

By mastering the combined flow of data and intelligence, you build adaptive, evergreen products that learn from their users and environments—closing the loop between design, experience, and service.

As your products become smart and connected, they inevitably evolve into platforms and ecosystems. Value multiplies when external developers, partners, and customers co-create around your offerings. But openness brings new challenges: governance, revenue sharing, and security.

Platform Dynamics

Apple, Amazon, and Google demonstrate how multi-sided platforms dominate market capitalization through network effects. Product companies can emulate this at scale: Apple’s iPhone platform, John Deere’s MyJohnDeere, and Haier’s Cosmoplat all create data-driven ecosystems rooted in domain expertise. You must decide whether to orchestrate your own or join existing ones—it’s not a neutral choice because someone else might platformize your products.

Building and Orchestrating Ecosystems

Ecosystems hinge on clear partner incentives, IP rules, and governance. Faurecia’s partnerships with ZF, Mahle, and Parrot show how collaboration across hardware, AI, and UX can accelerate innovation. Haier’s wine cabinet example illustrates how hardware can seed a commerce ecosystem connecting wineries and logistics partners. The managerial implication: your company needs a dedicated ecosystem office to manage alliances and data-sharing agreements.

Security Across the Lifecycle

Security becomes existential. Your products control physical systems—failures can threaten safety. You must design secure update mechanisms (FOTA), strong machine identity, encryption, and partner-verified standards. The Jeep exploit and IoT botnet incidents underline the stakes. Build security into your development thread, define partner SLAs, and treat resilience as a core experience dimension.

Final insight

Your future competitiveness depends on orchestrating ecosystems safely and intelligently. In Product X.0, platforms generate scale, ecosystems generate innovation, and security sustains trust.

Together, these elements complete the reinvention mandate. Your product becomes a living hub—intelligent, experiential, service-based, agile, data-rich, networked, and secure. Reinvention is not a single project; it’s the new operating system for modern industry.