Recommendation

McKinsey’s comprehensive and authoritative guide to Digital and AI transformation serves as both playbook and reference. Authors Eric Lamarre, Kate Smaje and Rodney Zemmel draw from five years of McKinsey consultants’ work around the world, advising a bold, integrated approach that emphasizes the organization’s capabilities and people. Written for executives, its recommendations apply to organizations of all sizes – including large multinationals – and reflect current research and emerging best practices. Any executive preparing to lead transformation will find McKinsey’s blueprint essential.

Take-Aways

To remain competitive, businesses will need to undertake constant, never-ending digital and AI transformation.

• A successful transformation depends on foundational work, including a clear, detailed road map.
• To support continuous transformation, the organization will need core digital talent in-house.
• The company’s operating model must enable fast, flexible technology development.
• The enterprise’s technology environment needs seven capabilities to support digital innovation across the organization.
• Digital leaders establish a data architecture that facilitates the flow of data from source to use.
• To ensure the organization benefits from digital and AI transformation, leaders should implement strategies to drive customer or user adoption.

Summary

To remain competitive, businesses will need to undertake constant, never-ending digital and AI transformation.

New technologies are constantly emerging and increasingly permeating every aspect of life. Some, such as cloud and AI, have wide-ranging effects; others bring about new architectures or transform software development. Still others – such as generative AI and edge computing – will exert unforeseeable effects. Businesses will have to evolve along with these technologies. Most leaders understand this: 89% have undertaken some form of digital transformation at their organizations.

“Business leaders will be digitally transforming their companies for the rest of their careers.”

But easier said than done. McKinsey’s 2022 global survey on digital transformation shows companies are reaping only a fraction of the benefits they seek – less than one-third of anticipated revenue lift and only one-quarter of expected cost savings. To gain the potential benefits of digital transformation, leaders must extend their initiatives beyond tech to encompass all organizational capabilities. Transformation favors the bold.

A successful transformation depends on foundational work, including a clear, detailed road map.

An implementation road map and associated financial plan set out the business domains leaders have targeted for transformation, the solutions that will create new value, programs for building enterprise capabilities and key performance indicators that will demonstrate value creation. The road map should incorporate a change management plan and a model for governance. The financial plan should define financial measures and timelines for achieving goals.

Transformations frequently stall because leaders have failed in laying the groundwork. These failures – and the corresponding approaches that will deliver meaningful change and measurable results – fall into several categories:

• Leaders failing to establish a shared conceptual understanding of digital technologies – Leaders need sufficient understanding of digital to know what it can do for the business. Agreement on an ultimate goal serves as the vision for the transformation. To achieve alignment, leaders have to ensure all parties know the role they’ll play and exactly how to deliver on it.
• Setting too broad a scope for the transformation – An overly broad scope makes it impossible to invest adequately in each initiative, causes disruption and poses a daunting level of challenge. A timid scope will deliver too little impact. To right-size the transformation’s scope, leaders should take a domain-based approach. A domain is a portion of the business that comprises related activities; companies typically define domains on the basis of workflows or processes, journeys, or functions. Leaders should prioritize the domains according to the value and feasibility of transforming each, and choose between two and five for initial transformation.
• Leaders becoming distracted by low-value pet projects – Leaders should identify solutions that will have substantial impact on performance, going beyond marginal improvements to reimagine each domain.

“Small thinking leads to small results, often not worth the effort of the transformation. Our rule of thumb is that a robust digital road map should deliver 20%+ EBITDA improvement.”

• Neglecting people and capabilities in favor of tech solutions – By building capabilities across the organization, digital leaders leverage digital and AI solutions to provide great customer experience, cost reductions and continuous improvement. The transformation road map will cover no more than two to three years into the future, but in the process of transformation, the company will be creating capabilities that will serve it much longer. Digital leaders focus on long-term capability building.
• Failure of the CEO to take personal responsibility for the transformation – Every member of the executive team has a role to play in the transformation, as do business line and business function leaders. The chief transformation officer holds responsibility for driving the transformation on a daily basis and serving as its face within the organization, and a transformation office made up of finance, human resources and IT professionals, and subject-matter experts should manage all digital initiatives and the overall digital transformation. However, the CEO has ultimate accountability for the transformation and must remain involved.

To support continuous transformation, the organization will need core digital talent in-house.

Strategic talent planning should receive as much attention as the transformation road map itself. Between 70% and 80% of the organization’s digital talent should reside in-house, including the talent that will provide differentiating digital solutions.

“Digital and AI transformations are, first and foremost, people and talent transformations.”

Rather than attempt to bring an entire HR department up to speed on digital, many organizations have established a specialized team to focus on digital talent, called a Talent Win Room (TWR). The TWR includes an executive sponsor, tech recruiters, HR specialists, and part-time functional specialists such as legal and finance.

Any organization, even a legacy business, can compete for technologists by offering what digital talent demand. The employee value proposition for digital talent should include opportunities to work on a modern technology stack, associate with colleagues who inspire and challenge them, and develop their skills. Digital leaders offer dual career paths that accommodate technologists’ desire to continue developing their expertise, and these organizations align compensation with an employee’s value.

The company’s operating model must enable fast, flexible technology development.

Agility has almost become cliché, but speed and flexibility in tech development remain essential. Digital leaders organize their transformations around agile pods – small cross-disciplinary teams that each own a specific product or service. To support continuous transformation, organizations need to deepen their understanding of agile beyond processes and rituals to ensure agile pods deliver their potential value. Setting objectives and key results keeps pods focused on their impact, and quarterly business reviews give leaders regular opportunities to assess and, if necessary, redirect the pod’s efforts. For each pod, a product owner provides day-to-day guidance and brings solid understanding of the business, the customer and the technology.

“How companies navigate the digital world to achieve sustainable competitive advantage is the defining business challenge of our time.”

Leaders face the task of standing up hundreds or even thousands of agile pods. Here the operating model becomes crucial. Three operating model designs have become dominant; the one that will serve a company best will depend primarily on the role of technology as a competitive differentiator:

• Digital factory – Leaders create a self-contained digital unit comprising 10 to 50 agile pods and typically occupying its own physical facility.
• Product and platform (P&P) – The P&P model deploys the digital factory concept at scale. Leaders modernize the technology stack and realign at least 20% of the organization to exploit that technology.
• Enterprise-wide agile – Leaders extend the agile concept to at least 80% of the organization and embed agile in its culture.

The digital transformation must include the buildup of user experience design capabilities, to ensure the solutions the company delivers meet customers’ needs and wants. Research shows a focus on design contributes to growth in revenues and total returns to shareholders. Agile pods should include design experts, and leaders should understand how customer experience links to value.

The enterprise’s technology environment needs seven capabilities to support digital innovation across the organization.

To function in a digital world, every leader will need to know at least the basics of technology. The enterprise’s technology environment exists to enable pods to create and deliver innovations. That capacity will depend on seven technical capabilities:

1. Decoupled architecture – A distributed, decoupled architecture enables agility and scaling, as it enables pods to work with modular, reusable components. The architecture will make use of application programming interfaces (APIs) for application integration. To reduce costs, the organization should automate infrastructure provisioning and software delivery.
2. Cloud – A decoupled architecture requires a cloud approach to the technology stack and a cloud-based data platform. But leaders should always approach cloud integrations by determining the value to be gained. That value typically stems from boosts to agility, innovation and resilience and not merely from reduced hosting costs.
3. Engineering practices – For all organizations, software development has become a core capability, and agility and quality require the adoption of engineering practices such as automation of the software development lifecycle (SDLC); DevOps, which applies lean principles to software delivery; coding standards to ensure qualities such as maintainability, reliability and portability; and continuous integration/continuous deployment, facilitating code changes and production.
4. Developer tools – To accommodate scaled development pods, organizations will need to provide sandbox environments that offer a full slate of tools and access to data. Internal development platforms simplify the user experience and allow developers to configure their own environments.
5. A reliable production environment – The environments to which developers deploy their applications must be secure, scalable to demand and always available. Automation can support these capabilities.
6. Automated security – Moving to the cloud necessitates new approaches to security. The software industry has begun to embed security throughout the SDLC – by placing security experts on DevOps teams and applying automation.
7. Machine learning operations (MLOps) automation – To exploit AI’s potential requires scaling and embedding it in processes, workflows and customer journeys. MLOps enables this by applying machine learning to meet the needs of AI systems, such as the provision of data and the monitoring of live operations.

Digital leaders establish a data architecture that facilitates the flow of data from source to use.

As organizations increase the number of data use cases from a handful to hundreds or thousands, the data operating model – the overall approach to managing data – becomes pivotal. The data operating model’s components include the organization of data; key roles for talent; DataOps, meaning the application of technology and agile principles to the development of data assets; and approach to data governance and risk.

Data architecture refers to the environment that delivers data from storage to use, including the transformation and analysis of data. The choice of data architecture archetype will depend on the organization’s ability to leverage cloud capabilities and the requirements of its digital road map. Architectures include capabilities such as event streaming, data warehousing, data APIs and analytics.

“Data products are the secret sauce for scaling.”

Data products are cohesive sets of data – for example, complete information about product lines – vetted for quality and presented in a ready-for-use format. Use of data products enables standardization, scaling and speed, and can significantly reduce total cost of ownership as well as the burdens of data governance and risk. Dedicated cross-functional data product pods create, improve and develop use cases for data products.

A data strategy sets out the organization’s data requirements and plans for cleaning and delivering its data. Typically, organizations possess more data than they need, but the data has poor quality. Leaders will need to select data domains to prioritize by referring to the transformation road map. AI tools can assist with data quality assessment and cleanup.

To ensure the organization benefits from digital and AI transformation, leaders should implement strategies to drive customer or user adoption.

Investments in digital won’t generate returns unless leaders also invest in initiatives to drive adoption by customers or in-house users. Leaders must take responsibility for the implementation of solutions beyond development and commit to seeing them through adoption. Adoption depends on two factors: first, people seeing that the solution meets a need and improves their experience – a user experience challenge; second, people also actually choosing to use the solution – a change management challenge.

The following strategies can influence adoption:

• Adapt the business model – Any solution will have implications upstream and downstream. A CEO or division head must take on the task of ensuring alignment across the business.
• Design in replication – Scaling implies implementing a solution in many facilities, organizational groups, markets or customer segments. Leaders should plan a replication approach, including a sequence for deployment and a scaling archetype, rolling it out in linear waves, in exponentially increasing waves, or as a “big bang” – all at once. Assetization – presenting a solution as a package of modules or assets – can facilitate adaptation of the solution to various unit conditions.

“The core challenge in driving both adoption and scaling is addressing at a sufficiently granular level the technical, process and human issues that keep a great solution from delivering its full value.”

• Track progress – Leaders should measure KPIs that reflect value creation, pod health, capability building and organizational mobilization. McKinsey recommends tracking each solution through a stage-gate process consisting of five stages: ideation of the solution; validation; planning; development; and adoption and scaling.
• Establish digital trust – Building solid digital trust – consumers’ or users’ confidence in the organization’s security, ethics and transparency – can reduce the enterprise’s data and AI risks and contribute to higher performance. Leaders should assess risks, review the organization’s digital trust policies and ensure the existence of operational capabilities supporting digital trust.
• Create a digital culture – Implementing a digital transformation will in itself contribute to a digital culture, but leaders also must display attributes that support a digital culture, such as customer-centricity, collaboration and a sense of urgency. Leaders should invest in their own skill development, create scalable learning programs to upskill employees, and establish reskilling programs for critical roles.

About the Authors

Eric Lamarre is a senior partner at McKinsey & Company and the North American leader of its Digital & Analytics practice. Kate Smaje and Rodney Zemmel lead McKinsey Digital.

Review 1

Rewired: The McKinsey Guide to Outcompeting in the Age of Digital and AI is a book by Eric Lamarre, Kate Smaje, and Rodney Zemmel that provides a framework for organizations to successfully transform themselves in the digital age.

The book begins by arguing that the digital age is fundamentally different from previous eras, and that traditional business models and strategies are no longer sufficient to compete. The authors then introduce a six-step framework for digital transformation:

1. Create a transformation roadmap: This step involves defining the organization’s goals for digital transformation and developing a plan to achieve them.
2. Build a talent bench: This step involves identifying the skills and capabilities that the organization needs to succeed in the digital age, and then developing a plan to acquire those skills and capabilities.
3. Adopt a new operating model: This step involves changing the way the organization operates to be more agile and responsive to change.
4. Produce a distributed technology environment: This step involves creating a technology infrastructure that allows teams to innovate and experiment quickly.
5. Embed data and analytics: This step involves using data and analytics to make better decisions and improve performance.
6. Create a culture of continuous learning: This step involves creating an environment where employees are encouraged to learn and grow, and to share their knowledge with others.

The book then provides a number of case studies that illustrate how different organizations have successfully implemented the six-step framework.

Rewired is a comprehensive and well-written book that provides a valuable roadmap for organizations that want to succeed in the digital age. The book is packed with insights and practical advice, and it is sure to be a valuable resource for business leaders and changemakers.

Here are some of the things that I liked about the book:

• The book is well-written and easy to understand.
• The authors provide a clear and concise framework for digital transformation.
• The book is packed with insights and practical advice.
• The book includes a number of case studies that illustrate how different organizations have successfully implemented the six-step framework.

Here are some of the things that I didn’t like about the book:

• The book is a bit long, and it could have been condensed without losing any of the important content.
• The book is a bit US-centric, and it would have been helpful to include more case studies from other countries.

Overall, I thought Rewired was an excellent book. It is a must-read for any organization that wants to succeed in the digital age.