Eric Lamarre, Kate Smaje, Rodney Zemmel — McKinsey & Company
Digital and AI transformation is not a one-off project — it’s a permanent shift in how companies work, innovate, and compete.
In Rewired, McKinsey distils a decade of transformation experience into a six‑capability model that organisations must build in parallel to succeed:
- Business-led Roadmap
- Talent
- Operating Model
- Technology
- Data
- Adoption & Scaling
The book’s central finding? Top performers win not because they have more technology, but because they systematically build these enterprise capabilities — and keep improving them.
Business‑Led Roadmap
Section One
Successful transformations start with alignment, focus, and a C‑suite “contract”.
The roadmap answers what you’re trying to achieve, where you’ll start, and what capabilities you must build.
Core principles from the book:
- Focus initial efforts on 2–5 business domains with the biggest value and feasibility.
- Use a five‑step domain reimagination process: define problems, design solutions, assess tech/data, estimate impact, and plan change management.
- The roadmap is a binding agreement: it commits resources, defines benefits, and spells out enterprise capability build‑out.
Case insight:
A large agricultural firm under competitive pressure devoted its early transformation to the commercial domain, equipping agronomists to better serve growers — building credibility and momentum before scaling.
Self‑check prompts from the book:
Can your C‑suite describe the vision, value at stake, and first domains in under a minute?
Are investments and capabilities aligned to those domains?
Talent
Section Two
“You can’t outsource your way to digital excellence.”
Core competitive differentiation comes from having the right talent in‑house, working directly with business teams.
Key elements from the text:
- 70–80% of core digital talent should be employees, not contractors.
- Build a Talent Win Room — a dedicated agile HR unit to source, onboard, and retain digital talent.
- Professionalise skills assessment: combine manager review, self‑assessment, online testing, and technical interviews.
- Create dual career paths for technologists and managers.
- Foster craftsmanship excellence: clear career architecture, ongoing learning journeys, and expert mentoring.
Case insight:
A global insurer shifted from layers of project managers to full‑stack engineers, boosting throughput by 15% and morale significantly.
Reflection prompts from the book:
Would your best engineers turn down Big Tech offers because their best work is here?
Is there a clear skills map showing who can actually deliver on your roadmap?
Operating Model
Section Three
Agility at scale means choosing an operating model that supports hundreds of cross‑functional pods.
Three proven models:
- Digital Factory – central build hub serving business units.
- Product & Platform (P&P) – integrates business, operations, and tech for domain‑ and platform‑based innovation.
- Enterprise‑Wide Agility – agile principles applied across all functions.
Pod success factors:
- Clear mission & measurable OKRs
- Cross‑disciplinary & dedicated members
- Autonomy & accountability
- Fast user‑centric iteration
Embedded disciplines:
- Quarterly Business Reviews to align funding and priorities
- Product Management as a core capability: POs act as “mini‑CEOs” with customer, market, tech, and leadership skills
- Customer Experience (CX) Design embedded from the start, focusing on a “minimal lovable product” for adoption
Case insight:
Spotify’s Backstage platform gave pods instant access to standard tools and services, accelerating onboarding and productivity.
Book’s readiness checks:
Are control functions (risk, compliance) integrated into pods?
Do your POs have the skill depth to own business outcomes?
Technology
Section Four
Architectural flexibility determines innovation speed.
The goal: a decoupled, distributed tech environment where teams can build and release without central bottlenecks.
Core shifts from the book:
- Point‑to‑point → API‑first, microservices
- Manual → Automated (Infrastructure as Code, CI/CD)
- Fixed → Modular & evolving
- Batch → Real‑time streaming
Other technology mandates:
- Value‑driven cloud adoption: choose migration approach (Retire, Repurchase, Rehost, Replatform, Refactor, Retain) per app/domain
- DevOps/DevSecOps automation from code to deployment
- Internal Developer Platforms for instant, compliant sandbox provisioning
- Production‑grade environments: secure, scalable, monitored
- MLOps to keep AI models accurate, monitored, and retrained
Case insight:
Emirates NBD created 800+ microservices with strong API governance, moving faster across multiple domains.
Book’s questions to leaders:
What’s our average commit‑to‑production time?
Are APIs discoverable, reused, and governed?
Data
Section Five
Scaling AI and analytics hinges on treating data as a product — curated, governed, easy for pods to consume.
Book’s framework:
- Prioritize data products for high‑value domains (e.g., Customer 360)
- Apply 9D Data Quality metrics (accuracy, timeliness, security, etc.)
- Federated data governance with clear ownership
- Modern data architecture (lakes, warehouses, mesh) aligned to business needs
Case insight:
A credit card company consolidated 200+ data stores into 8 governed data products, saving $300M/year and speeding solution delivery.
Self‑diagnostic from the text:
What % of AI/analytics time is spent wrangling data vs. creating value? Over 50% signals a problem.
Adoption & Scaling
Section Six
Even the best digital solutions deliver nothing if not adopted and scaled.
Scaling playbook from the book:
- Design for replication‑by‑default: modular architecture, reusable code, APIs
- Manage adoption as rigorously as development: incentives, change management, training
- Track enterprise KPIs for usage, performance, and business value
- Embed Digital Trust — risk, compliance, AI ethics — from day one
Case insight:
A food producer cut 400 scattered initiatives to focus on 3 high‑value domains, pairing tech with deep change management — netting $150M+ annually within 18 months.
Book’s questions for teams:
Did our last “lighthouse” become a standard across the company — or just an award‑winning pilot?
The Integration Principle
The authors stress: These capabilities cannot be built in isolation.
The roadmap (Section 1) must align with data plans (Section 5), scaling methods (Section 6), talent pipelines (Section 2), operating model (Section 3), and the tech platform (Section 4).
Closing Insight from Rewired
Technology is easy to buy.
Capabilities are hard to build — and they’re what sustain competitive advantage.
Winning organisations weave business, talent, operating model, tech, data, and adoption disciplines into one coherent system — and keep evolving it.
