A Digital transformation involves the fundamental rewiring of an organization's operations. The primary objective of a digital transformation, as highlighted in the latest McKinsey book, Rewired: A McKinsey Guide to Outcompeting in the Age of Digital and AI (Wiley, June 20, 2023), is to establish a competitive advantage by consistently implementing technology at a large scale to enhance customer experience and reduce costs.
As many commonly used phrases go, "digital transformation" has become a vague term that holds different meanings for different individuals. This presents a problem. The truth is, digital transformation is not just important for organizations to compete, but it is crucial for their survival. Without a clear understanding of what a digital transformation entails and without aligning the entire organization around a specific program, leaders cannot expect to achieve success.
Digital transformations differ from regular business transformations in both small and significant ways. While business transformations usually conclude once a new behavior is established, digital transformations are ongoing efforts to rewire an organization's continuous improvement and change processes. In fact, they are long-term journeys that most executives will embark on for the rest of their careers. This is because technology is not only increasingly integrated into businesses, but it is also constantly evolving. For instance, considering the growing significance of AI in generating business insights and enabling decision-making logic, any digital transformation should also encompass an AI transformation.
As we will demonstrate, the success of digital transformations relies less on how companies use digital and more on how they become digital.
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What are the essential capabilities required to drive significant progress in digital transformation?
To achieve a successful digital transformation, it is essential to implement a range of coordinated actions. Rewired outlines six critical capabilities for digital transformation success:
1. Crafting a clear strategy focused on business value:
Companies should prioritize specific domains, such as customer journeys, processes, or functions, that generate significant value for the business. A roadmap should guide the transformation, outlining the necessary solutions and resources for change.
2. Building a strong talent bench with in-house engineers:
Outsourcing alone cannot lead to digital excellence. Having a dedicated team of digital talent working alongside business colleagues is crucial. Effective digital talent programs go beyond hiring and include employee value propositions, agile and digital HR processes, and a supportive environment that fosters the best talent.
3. Establishing a scalable operating model:
Cross-functional teams are integral to digital transformations, bringing people from different areas of the company together. While many companies have a few of these teams, scaling to support hundreds or thousands of them requires a new operating model. Three primary models to consider are the digital factory, the product and platform model, and the enterprise-wide agility model.
4. Implementing distributed technology for independent innovation:
Technology should facilitate continuous development and release of digital innovations by teams. To achieve this, organizations should foster a distributed technology environment, granting every team access to necessary data, applications, and software development tools. Recent technology advancements, such as the use of APIs, developer tooling, cloud migration, and infrastructure automation, contribute to this distributed environment.
5. Ensuring access to data as needed:
Reliable and up-to-date data are crucial for successful digital transformations. Data architecture should enable easy access for teams across the organization and be regularly assessed and updated. Strong governance is necessary to support this capability, with the core element being the data product that structures various data pieces for consumption by different teams and applications.
6. Prioritizing strong adoption and change management:
Unlike the linear process of the past, digital transformations follow an iterative approach that involves designing, prototyping, collecting feedback, and improving solutions to maximize their value potential. It is important to allocate resources for process changes, user training, and change management initiatives, with a general rule of spending at least an additional dollar on implementation for every dollar spent on developing a digital solution. Companies should consider adoption and scaling at the beginning of their transformation journey to ensure the necessary resources for successful change delivery.
Coordinated action across all these areas is essential for a successful digital transformation.
Understanding the concept of a domain and its significance
Digital transformations have a significantly higher chance of success when teams focus on transforming entire domains, such as customer journeys, processes, or functional areas, rather than just individual use cases. By concentrating on domains, companies can bring about effective change by encompassing all related activities needed to deliver a complete solution. For example, instead of solely focusing on one step of a process, such as creating an app for customers to open a bank account, the domain would also include other crucial activities like account setup, verification, and workflow automation. It is essential to consider all these activities to ensure the solution delivers its value. A domain should be large enough to be valuable and noticeable to the company, yet small enough to be transformed without excessive reliance on other parts of the business. Managing the interconnectivity of use cases and solutions within a domain is a key factor in achieving successful transformation.
How can AI contribute to the success of a digital transformation?
AI, especially generative AI, is revolutionizing the way companies operate and create value, offering tremendous opportunities in content generation, new discoveries (especially in industries like pharmaceuticals and chemicals), and coding.
However, it's crucial not to get distracted by flashy new technologies. The lessons learned from past technological innovations still hold true: value is derived from having a clear understanding of business objectives and how technology can help achieve them. While it's important to experiment and learn quickly, it's equally important to resist the temptation of developing use cases with exciting new technology that ultimately fails to create value for the business.
Generating value with generative AI requires the same core competencies necessary for a successful digital transformation, including a well-defined strategy, a pool of talented in-house digital professionals, and a flexible and scalable operating model. Moreover, it's not a one-time endeavor: companies looking to incorporate generative AI into their value propositions must continually reassess their digital transformation roadmaps and evaluate prioritized solutions to determine how new iterations of generative AI models can support their objectives.
What roles are critical for leading a successful digital transformation?
A successful digital transformation impacts various functions within an organization, enabling them to collaborate in innovative ways. This necessitates substantial and coordinated investments. The individual with the authority to drive this level of sustained change is the CEO. One of the CEO's pivotal responsibilities is to ensure alignment, dedication, and accountability among the leadership team. Without these elements, progress in digital transformations can quickly come to a halt.
Leaders at the C-suite and business unit levels also have critical roles to play. In terms of technology, the chief information officer typically focuses on enhancing the company's internal operations with technology. The chief technology officer typically concentrates on improving customer offerings using technology. Chief digital officers often collaborate as co-leaders of the transformation, leveraging digital and AI technologies to create new digital experiences for users. The chief human resources officer plays a crucial early role in securing digital talent and implementing talent management practices that foster the development and retention of digital talent. The CFO oversees the transformation business case and tracks the realization of value. Lastly, the chief risk officer needs to guide the integration of risk assessments into the development process and understand how to address new risks, such as data privacy and cybersecurity, that may arise from a digital and AI transformation.
How do you know if a digital transformation is working?
Determining the progress of a digital transformation can be surprisingly challenging. Without proper tracking and measurement of outcomes, leaders may struggle to effectively manage performance and ensure that the changes being made are truly valuable.
Understanding what to measure is a crucial aspect of this challenge. In the context of digital transformations, key performance indicators (KPIs) generally fall into three main categories:
1. Value creation:
Digital solutions typically focus on specific operational KPIs that can ultimately translate into financial benefits.
2. Team health:
Many digital transformations encounter delays due to factors such as understaffed teams, outdated work methods, or a lack of critical capabilities like product management and user-experience design. Our experience shows that high-performing teams can be up to five times more productive than their low-performing counterparts.
3. Change-management progress:
These metrics assess the advancement of new capabilities and the overall health of the transformation itself. Are teams being mobilized as planned? Are individuals engaged? Are capabilities and talent being developed? Are people seamlessly adopting the technology, tools, and products being created? We have found that, when managing change, it is important to remember that perfection can often hinder progress.
By focusing on these areas and effectively measuring the outcomes, leaders can gain valuable insights into the success of their digital transformation efforts.
Which companies are excelling in these areas?
Becoming a digital company requires a complete rewiring of how businesses operate. Even industry leaders like Amazon started as startups and had to invest in technology, data, performance management, and talent practices over time. The great news is that successful digital transformations are not limited to tech giants. Companies of all types can achieve success on their digital transformation journeys. Here are three inspiring examples:
Freeport-McMoRan, a prominent copper-mining company, achieved remarkable performance improvements by implementing an AI model at their ore-concentrating mill in Bagdad, Arizona. Their leadership aimed to increase copper output without significant capital investments. They formed cross-functional teams to develop, test, and refine the AI model, fostering a culture of rapid iterations and continuous improvement. To ensure effective coordination and resource allocation, Freeport-McMoRan appointed a senior product manager and a finance director. They also established a quarterly planning system, bringing top leaders together to set objectives and focus resources on high-priority areas.
Vistra, one of the largest power producers in the United States, enhanced overall efficiency, reliability, and emissions reduction through a multilayered neural network model. By analyzing two years' worth of plant data, the model learned how to optimize efficiency in real-time, generating recommendations every 30 minutes. The success of this approach relied on building scalable solutions that could be tailored to each station in Vistra's network. A cross-functional team, consisting of plant operators, data scientists, analytics translators, and power process experts, played a crucial role in rapid development, high-quality models, and widespread adoption.
Emirates Team New Zealand utilized an AI bot, trained through deep reinforcement learning, to secure their fourth America's Cup victory in 2021. By collaborating with sailors and data scientists, the team developed and trained the bot to dynamically learn and improve accuracy through continuous feedback. Extensive effort went into designing effective learning models, coaching the bot, and establishing proper guardrails. The team leveraged cloud hosting to accommodate the computational scale required for their success.
These examples demonstrate that digital transformations can be accomplished by companies across various industries, provided they invest in the right strategies and embrace the power of technology and data.