Rewired: The McKinsey Guide to Outcompeting in the Age of Digital and AI

Summary of Rewired

1. 1

   Digital Transformation: The New Business Imperative

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   In a world where technology evolves at breakneck speed, "Rewired" has emerged as the definitive playbook for business transformation in the digital age. Written by McKinsey veterans Eric Lamarre, Kate Smaje, and Rodney Zemmel, this guide has quickly become required reading in boardrooms worldwide. Elon Musk reportedly keeps a copy on his nightstand, while Microsoft CEO Satya Nadella called it "the most practical digital transformation guide I've encountered." What sets this book apart is its rare combination of strategic vision and tactical implementation-moving beyond the "why" of digital transformation to the critical "how." As companies struggle with the reality that 89% of digital initiatives capture only a fraction of their expected value, "Rewired" offers a comprehensive framework that has already helped organizations like DBS Bank, Freeport-McMoRan, and LEGO Group successfully navigate their digital journeys. With AI acceleration making digital capabilities even more crucial, this book couldn't have arrived at a more pivotal moment.

2. 2

   The Enterprise-Wide Digital Transformation Roadmap

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   Digital transformation isn't a one-time event but an ongoing journey that will define business careers for decades to come. The statistics are sobering: while 89% of companies launch digital initiatives, they typically capture only 31% of expected revenue lift and 25% of expected cost savings. Why? Because successful transformation requires developing hundreds of technology-driven solutions working together, fundamentally rewiring operations, and building entirely new organizational capabilities. The journey begins with creating a comprehensive transformation roadmap-a process that demands far more than superficial planning. True transformation requires vision, alignment, and commitment from leadership teams. Vision serves as the North Star, providing both aspiration and specific goals with quantifiable value. Rather than vague statements like "unmatched customer service," effective visions specify exactly what success looks like: "Deliver personalized, proactive outreach at multiple points during the customer journey." Alignment goes beyond mere agreement-it requires everyone understanding their roles in cross-functional collaboration. Companies with successful transformations are nearly four times more likely to report shared accountability across functions. Leadership teams often begin misaligned, with different priorities and understanding of digital fundamentals. The solution? Create experiential learning journeys through company visits, executive training, and workshops to build pattern recognition before attempting to define a roadmap. Commitment means C-suite leaders making themselves individually and jointly accountable for delivering on the vision through four key elements: a compelling business case with appropriate investments; building foundational enterprise capabilities balanced with specific solutions; CEO-led transformation governance; and executive role modeling of digital leadership behaviors. The domain-based approach provides the right "bite size" for transformation. A domain is a subset of the enterprise encapsulating related activities-defined by customer journeys, business processes, or organizational units. The key is selecting domains large enough to be valuable yet small enough to transform without excessive dependencies. Starting with 2-5 priority domains is recommended, as going bigger requires significant coordination and carries more risk. For each targeted domain, business leaders must identify multiple interrelated solutions that will meaningfully impact performance. This requires a five-step process: defining the business problem through zero-based journey design or end-to-end process mapping; aligning user needs with specific value levers; assessing technology and data requirements; evaluating investments and benefits; and developing an implementation sequence with resourcing and change management plans. The resulting digital roadmap represents the culmination of this business-led planning process, detailing implementation steps and financial requirements. A good roadmap sequences domains to produce meaningful value in both short and medium terms, ties transformations to operational KPIs, accounts for enterprise capability building, includes clear financial metrics, and incorporates comprehensive change management. Limited to a 2-3 year horizon for flexibility, this roadmap becomes a contract that leadership collectively commits to deliver.

3. 3

   Building the Digital Talent Engine

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   Digital excellence requires building your own bench of digital talent working alongside business colleagues. While many executives focus on technology and strategy, the reality is that digital transformations are fundamentally people transformations. Legacy businesses can successfully compete with Silicon Valley for top digital talent through inspiring agendas and genuine commitment to people. The first step is strategic talent planning-translating your digital roadmap into specific talent requirements. Companies that differentiate through digital solutions need 70-80% of digital talent in-house to enable close collaboration between technologists and business counterparts. This proximity drives faster development cycles and gives technologists crucial business context. While specialized capabilities like penetration testing can be contracted, companies should never outsource their way to digital excellence. Assessing existing digital talent requires looking beyond job titles to specific skills and proficiency levels. Organizations need detailed skill mapping that distinguishes between roles like "Java Web Developer" versus generic "developer." One financial services company discovered through testing that only 20% of its 100-person digital team had passing coding grades, explaining why their applications struggled with architectural issues. Rather than transforming entire HR organizations, companies should establish a dedicated Talent Win Room (TWR) to rapidly adapt HR processes for digital talent. This special unit requires C-level sponsorship and a full-time senior HR executive as team leader. The interdisciplinary team combines tech recruiters and HR specialists in talent planning, recruiting, talent management, development, and diversity initiatives. Top digital talent evaluates employers as much as employers evaluate them. Companies must develop a compelling employee value proposition (EVP) that addresses what motivates tech professionals-primarily opportunities to work with modern technology stacks and capable colleagues that will enhance their skills. The recruiting process must shift from step-by-step procedures to creating delightful candidate experiences, with timelines under four weeks to remain competitive. Traditional compensation models often misalign with the value of technical talent, as they reward tenure or management responsibility rather than technical prowess. Digital talent compensation requires benchmarking against Big Tech standards (typically between parity and 30% below), paying for granular skill levels with substantial performance bonuses, and establishing clear technology competency markers. Beyond money, technical talent values meaningful titles like "distinguished engineer," mentorship from respected technical leaders, and thoughtful perks that signal commitment. While some digital colleagues want to progress into general management roles, over two-thirds of developers prefer deepening their technical expertise rather than becoming managers. Successful digital organizations implement dual career tracks-managerial and expert paths-allowing technical specialists to advance without moving into management. This approach relieves promotion pressure and addresses compensation challenges by enabling top technical experts to earn salaries comparable to senior executives.

4. Chapter 4

   Reimagining Work Through Agile Operating Models

   Agility has become almost cliche, yet remains essential for companies operating at the pace of digital transformation. Building an agile operating model is perhaps the most complex aspect of digital transformation as it fundamentally changes how people work together. While any company can successfully implement a few agile pods, scaling to hundreds requires significant organizational changes. True agility isn't just about processes-it requires fundamental changes to objectives, team configuration, and accountability. What truly matters are four defining characteristics: mission-based teams with measurable outcomes; cross-disciplinary pods with dedicated resources; autonomous teams accountable for achieving impact; and fast-moving processes focused on user needs. Simply implementing agile ceremonies without these corresponding organizational changes will inevitably lead to poor outcomes. When implemented properly, agile provides effective performance management through three key ceremonies. First, setting mission and OKRs is where management provides direction and expectations, breaking down a pod's year-long mission into quarterly objectives tied to business outcomes. Second, two-week sprints allow teams to develop solution features with the product owner prioritizing work through a well-organized backlog. Third, quarterly business reviews (QBRs) allow management to assess progress, adjust OKRs, and coordinate across pods. When implemented effectively, QBRs can actually reduce management meetings by up to 75%, streamlining governance rather than adding bureaucracy. Scaling from a handful of agile pods to hundreds requires a formal operating model rather than managing by exception. Three main options exist: digital factory, product and platform, and enterprise-wide agile. The digital factory model is often the starting point, taking 12-18 months to fully implement. It's a self-contained unit typically housed in a physical location separate from the main business, with business units acting as sponsors. The product and platform model represents a more evolved version at much greater scale-managing hundreds or even over a thousand pods rather than 10-50. The enterprise-wide agility model extends agile principles beyond digital/IT to nearly any business or support function. While implementing an agile operating model requires multiple capabilities, product management deserves special attention. Product owners serve as "mini-CEOs" with total accountability for product lifecycles from customer insights to engineering and adoption. They're responsible for delivering specific OKRs, guiding tech-intensive solutions, ensuring pods address the right customer problems, and maintaining product quality including bug fixes to reduce technical debt. Customer experience design is essential to digital transformation success-if users don't adopt your solution, all planning, development and investment is wasted. Design-driven companies show significantly higher revenue and growth than peers, making UX design a "magic ingredient" in digital initiatives. Don't postpone hiring designers in favor of engineering talent. Companies that focus solely on engineers often discover after a year of development that customers won't adopt their clunky solutions.

   Chapter 5

   Building a Modern Technology Foundation

   The fundamental objective of technology in digital transformation is creating an environment where pods can continuously develop and release innovations. This requires building a distributed technology environment giving teams access to data, applications, and development tools needed for rapid, secure innovation. A platform architecture must support both front-end systems of engagement and back-end systems of record, along with the data and analytics needed for digital transformation. The best architectures provide flexibility, stability, and speed for agile pods to build solutions. The key concept is creating a distributed, decoupled architecture that enables teams to assemble modular, reusable components. Decoupling separates connections between systems, enabling applications to evolve independently and improving organizational agility and scalability. The primary technique is adopting API-based interfaces, which allow pods to expose their data and functionality to other teams or external partners. APIs enable breaking down monolithic applications into microservices, letting hundreds of pods innovate without dependencies. Jeff Bezos's famous memo mandated all Amazon teams communicate only through service interfaces, with no direct linking or backdoors allowed. Manual provisioning of infrastructure and software deployment is slow, cumbersome, and error-prone. Leading companies implement automation through infrastructure as code (IaC), enabling agile pods to provision cloud environments, storage, and services in a repeatable, cost-effective manner. All infrastructure specifications should be explicitly coded in configuration files to create a "single source of truth" and track changes. Successful cloud integration requires a value-based approach rather than wholesale migration. The most value comes from increased business agility, innovation, and resilience rather than simply reducing infrastructure costs. Organizations should take a surgical approach by prioritizing business domains and reimagining both the business processes and underlying technology concurrently to exploit cloud benefits fully. The software development landscape has transformed from lengthy, infrequent releases to rapid, iterative deployment. Modern engineering practices enable companies to release software features quickly and continuously-a necessity as every company becomes a software company. At the core of this revolution is the automation of the software development lifecycle (SDLC), allowing teams to make small changes, validate quickly through rapid feedback, test frequently, and iterate continually. DevOps applies lean manufacturing principles to software delivery by integrating development and operations teams. Rather than being just a tool or expert added to existing teams, successful DevOps implementation requires three core principles: Flow (accelerating delivery by mapping and automating the value stream), Feedback (enabling multiple feedback loops for quick issue diagnosis), and Continuous Learning (creating a culture of sharing lessons and improvement). As organizations scale from a handful to hundreds of agile pods, they need self-service development environments that eliminate the burden on IT for provisioning infrastructure. A specialized engineering team implements tools that enforce enterprise architecture standards while streamlining the developer experience. These environments must be flexible, standardized, and rapidly provisioned through infrastructure as code automation.

   Chapter 6

   Data as the New Strategic Asset

   Data often frustrates established companies, with up to 70% of AI development efforts spent wrangling and harmonizing data from legacy systems. Thoughtful data architecture is critical for easy consumption and reuse. The core unit for achieving this is the "data product"-curated data elements packaged for easy consumption across the organization. A data strategy defines what data you need and how to make it ready to deliver on business priorities. Start by identifying data needed for digital solutions in your roadmap, then prioritize data domains based on business importance, risk, and regulatory requirements. Focus on the most critical 10-15% of data elements within each domain. Thoroughly assess data quality across nine dimensions including accuracy, completeness, and timeliness, setting appropriate quality targets that align with business needs. Data products deliver high-quality, ready-to-use data sets that people and systems across an organization can easily access and apply to different business challenges. This product-oriented approach to data management represents a fundamental shift that can deliver new business use cases 90% faster, reduce total cost of ownership by 30%, and substantially decrease risk and governance burden. Building data products requires careful investment decisions based on four key criteria: uniqueness (avoiding duplication of existing data), relevance to end users, clearly defined quality standards, and ability to support multiple high-value use cases. The most valuable data products are distinctive, valuable, and shareable across the organization, like customer-360 products that multiple teams can leverage to develop their own solutions. Data architecture functions as the system of "pipes" that deliver data from storage to usage points. Like a blueprint for a film, good data architecture enables organizations to build reusable, high-quality data products quickly, making data easily accessible for decision-making, customer-facing applications, and internal control. Without sound architecture, data remains trapped in silos across legacy systems, hampering organizational agility. Rather than viewing data architecture as a multiyear waterfall project, organizations should adopt a roadmap-guided approach with reference architectures-proven technology sets that work together effectively. Begin by developing a high-level target of needed data capabilities focused on building a "minimum viable data architecture" for priority digital solutions. To maximize value from data, organizations must establish effective governance structures that balance centralized control with domain-specific flexibility. Leading companies deploy a federated model where a central function sets policies and standards while business units manage day-to-day data activities. This balanced approach distributes responsibilities appropriately across the organization, avoiding the limitations of purely centralized or decentralized models.

   Chapter 7

   From Development to Adoption: Ensuring Digital Impact

   Successfully implementing digital solutions requires not just development but ensuring adoption and scaling. For every dollar spent on development, organizations should budget at least another dollar for adoption activities including process changes, training, and change management. The core challenge is addressing technical, process, and human issues at a granular level to deliver full value. Successful digital transformation requires overcoming "last mile" issues where technically sound solutions fail due to poor user adoption. This requires a two-pronged approach: ensuring solutions meet user needs through iterative design, and implementing structured change management. The change model includes leadership engagement, compelling narratives, performance metrics with incentives, and role-based training. Beyond user adoption, organizations must adapt their business models to support digital solutions, addressing interdependencies across functions like distribution, pricing, and performance management. This cross-functional impact is why CEO involvement is essential in digital transformations. For complex implementations, dedicated adoption teams should work alongside development teams to identify and address adoption challenges early. Scaling requires effectively replicating solutions across different environments-whether production facilities, geographic markets, customer segments, or organizational groups. Successful scaling begins with defining which solutions to scale and where, requiring unit leaders to agree on value, expectations, resources, and accountability. Companies can choose from three scaling archetypes: linear waves (sequential unit-by-unit scaling with a central team), exponential waves (successively larger implementation waves using train-the-trainer models), or big bang (simultaneous enterprise-wide deployment). Effective scaling requires "assetization"-packaging digital solutions as reusable modules to avoid rebuilding from scratch with each deployment. Most proprietary digital solutions can achieve 60-90% reusability. Successful assetization manages three elements: implementation process steps, modular technology components, and solution support people who understand how to deploy, adapt, and train users. Many CEOs lack clear visibility into their digital and AI transformation progress. Effective performance tracking requires measuring the right things with the right supporting tools. Digital transformation KPIs typically fall into three families: value creation metrics, pod health metrics, and change management metrics. Value creation metrics translate into financial or customer benefits that matter to domain leaders and C-suite executives, providing proof points for investors on transformation progress. Digital and AI transformations introduce complex interconnected risks in an environment of increased regulatory scrutiny. Digital trust-confidence that an organization protects data, maintains cybersecurity, offers trustworthy AI products, and provides transparency-has become essential. Companies with strong digital trust are less likely to experience negative incidents and more likely to outperform competitors.

   Chapter 8

   Building a Digital Culture from the Inside Out

   Business leaders often struggle with building a digital culture because they consider it in vague terms. In reality, culture emerges from concrete actions, incentives, skills development, and leadership attributes. The entire digital transformation process-from executive pattern recognition to hiring tech talent, bringing IT closer to business, adopting new work methods, and making technology accessible-collectively builds digital culture. Leaders in digital enterprises must operate differently-they need to be customer-obsessed, understand digital technologies and solution development processes, know how to function in agile environments, embody collaborative leadership, and maintain a "can-do" attitude. Companies like Ping An have expanded their management evaluation criteria beyond traditional hard skills to include softer attributes like adaptability, openness, and collaboration ability, recognizing these are essential for cross-disciplinary innovation. Three specific practices help build these attributes: "Go & see visits" to digital-first companies, "Digital 101" training (at least 10 hours on digital basics), and leadership programs focused on embracing learn-it-all cultures and customer-centricity. Even with upskilling investments, about 30% of top executives typically need to be replaced with leaders better suited for digital transformation. To bring the entire organization along on the digital journey, companies develop scalable training programs through corporate "academies" that build awareness, skills, and behaviors. DBS Bank, aiming to become a "30,000-employee startup," created comprehensive learning infrastructure including data translator curricula, innovation hubs with 300+ hackathons, and peer-to-peer learning programs. They trained over 5,000 employees in digital capabilities, with 1,000+ upskilled for pivotal roles, resulting in 6% higher engagement and 40% better retention. Organizations must focus intensive reskilling efforts on pivotal business roles that will be radically transformed by digital and AI-like merchants in retail, underwriters in insurance, or network planners in logistics. These programs require significant time (3-9 months) and are industry-specific. A US food grocer retrained 400 experienced merchants to use integrated workflow tools, promotion recommendation engines, and real-time vendor portals. Though the transition led to 20-30% turnover over two years, the new technology and training elevated bottom-performing merchants to top-quartile performance.

   Chapter 9

   Transformation Success Stories: From Vision to Reality

   The journey of digital transformation is perhaps best understood through the experiences of companies that have successfully navigated this complex terrain. Three industry-leading organizations-Freeport-McMoRan, DBS Bank, and LEGO Group-demonstrate how integrating the six core digital transformation capabilities can drive remarkable business outcomes. Freeport-McMoRan, a copper mining company, leveraged AI to unlock significant value from existing assets without major capital investment. Facing growth challenges, they turned to AI to extract more from mature copper mines. Their five-year "Americas Concentrator" program achieved the equivalent of an entire new processing facility's production through data, AI and agile methods. Starting with a pilot at Bagdad, Arizona, they achieved a 5% production increase and unprecedented simultaneous improvements in both throughput and recovery. This transformation ultimately delivered 200 million pounds of additional copper annually worth $350-500 million in EBITDA-comparable to a new $2 billion concentrator but without the decade-long wait. DBS Bank built a platform-based operating model with 33 platforms aligned to business segments, each with "2-in-a-box" leadership (business and IT leads jointly responsible for platform goals). Journey teams of 8-10 people worked in agile fashion to improve customer experiences-reducing credit card origination from 21 days to just 4 days. DBS made the strategic decision to bring 70% of tech talent in-house (versus 20% previously), establishing tech hubs and growing to 10,000+ technologists (a third of its workforce). The bank moved 99% of applications to cloud, enabling one administrator to manage 1,200 virtual machines. The impact: 65% of customers now use digital tools, digital customers generate twice the income of traditional ones with half the cost-income ratio, and digital customers deliver 39% ROE (15 points higher than traditional customers). The LEGO Group's digital transformation began with a fundamental question: how to secure their beloved brand's legacy in an increasingly digital era. With children turning to screens and shopping becoming digital, LEGO developed a vision to "own the future of play" by becoming digital to the core. Nearly 100 business leaders and the entire management team formulated a five-year aspiration to become a truly digitally-enabled consumer goods company, identifying over 90 initiatives across 10 capability domains. The company prioritized four key domains-consumers (children), shoppers (direct buyers), customers (retail partners), and colleagues (employees)-and developed a comprehensive roadmap with Board-approved significant investment over five years. These success stories underscore two critical factors: the necessary integration between transformation elements (digital talent needs appropriate operating models; solutions need business adoption), and the importance of baseline capabilities across all dimensions. They also reveal that digital transformation is not a destination but a continuous journey of discovery and reinvention-one that becomes increasingly rewarding as organizations develop their digital muscles and learn to thrive in a technology-driven business landscape.

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