“Show me the money!” Cuba Gooding Jr., playing Rod Tidwell, made those words a cultural touchstone in the movie Jerry McGuire. He was not just voicing his concerns about committing to a sports agent, played by Tom Cruise in this case; he was also questioning Cruise’s commitment.
Business leaders, shareholders, and board members have increasingly been saying the same thing — albeit using different words — when it comes to their company’s digital and AI transformations. While 89% of large companies globally have a digital and AI transformation underway, they have only captured 31% of the expected revenue lift and 25% of expected cost savings from the effort.
That track record begs some tough questions: Is all this digital effort worth it? Do I really need to lead my industry or is being a fast-follower a smarter strategy? Can I create digital and AI capabilities that give me a lasting competitive advantage or is this just the price of doing business in the modern age?
Until business leaders are convinced of the value and confident in how to get it, they are unlikely to do the difficult, hands-in-the-dirt changes needed to improve their success rate, as we argue in our book Rewired: How to Outcompete in the Age of Digital and AI. But using proprietary data, we’ve found just how and where digital transformations create value — and what businesses can do to beat the competition.
Hard Evidence, Real Value
Hard evidence that directly ties digital and AI transformation to improvements in operational KPIs and financial performance is scant.
To redress this issue, we turned to banking, a sector that has enough of a history with digital transformations to produce meaningful findings and where we own a unique longitudinal dataset.
First, we used McKinsey’s Finalta benchmark, which tracked the performance of 80 global banks every year from 2018 to 2022 against a set of 50 normalized metrics, such as digital/mobile adoption, digital sales by banking product, number of people in contact centers, and number of branches. We then isolated performance in two metrics — the percentage of mobile adoption by their customer base and the percentage of sales originated in digital channels — to define 20 digital leaders and 20 digital laggards. These two metrics are broadly recognized in the industry as core indicators of a digital retail banking model.
Next, we combined this data with McKinsey’s Corporate Performance Analytics to see how banks ultimately perform against financial metrics (e.g., total shareholder return, growth, expenses). We then ran a blind assessment (i.e., the identity of the banks was hidden) of the maturity of digital and AI capabilities of the leading and lagging banks.
The findings have been striking: Digital leaders are creating much more shareholder value than laggards. Between 2018 and 2022, digital leaders achieved average annual total shareholder returns of 8.1% vs. 4.9% for laggards. Leaders also had significantly better return on pre-tax tangible equity (ROTE), growing it from 15.5% in 2018 to 19.3% in 2022, vs. a more modest growth from 13.6% to 15.3% for laggards.
This financial outperformance is a result of leaders’ success in growing revenue and better containing expense growth. Between 2018 and 2022, digital leaders have grown their active customer base at 0.5% and their retail revenues at 0.8% annually, while digital laggards saw zero growth in their active customer base and a decline of 1.4% per year on retail revenues. During the same period, leaders’ operating expenses grew at 1.3% per year, while laggards grew at almost twice that (2.3% per year). So, how are leaders able to outcompete so demonstrably?
Creating Value That’s Hard to Copy
Where does value come from? Let’s look under the “digital hood.” Both digital leaders and laggards are growing adoption of their mobile app at the same rate, with a gap of 14 to 15 percentage points between them staying constant over time. (See below chart.) This is not surprising. As soon as a bank introduces a new mobile app feature, others see it and follow suit relatively quickly. The mobile app is table stakes.
Turning to digital sales provides a much more insightful answer. Here, the gap between leaders and laggards is growing fast, with leaders almost doubling their advantage over laggards over the five-year period. In fact, digital leaders grew digital sales from 40% to 70%, while digital laggards grew from 8% to 17%.
The reason for this large differential is that to drive digital sales, leading banks go well beyond the mobile app to digitally transform what’s hard to see and hard to copy: the end-to-end process from origination to fulfillment to servicing. To do this, they must orchestrate hundreds of teams capable of developing digital and AI innovations, day-in, day-out, across all their customer journeys and core business processes.
At the front end of this process, for example, leading digital banks deploy personalization analytics and digital marketing campaigns to bring relevant offers to (potential) customers. In the middle of this process, they create an omnichannel experience where branch and contact center professionals have the tools and data to support customers at any stage of the sales journey, even if that journey was started online. These leading banks also provide customer approvals in real time, thanks to automated credit-risk decisioning. At the back end of the process, they drive customer self-servicing through well-designed digital workflows enabled by a modern data architecture.
The value of this approach to transformation is also revealed in contact center staffing. Laggards saw an increase of 20% over the past five years, as they were unable to contain inbound calls from customers that enter digital channels. In contrast, digital leaders were able to decrease contact center staffing by 11% as they benefited from their ability to fully fulfill customer demand online and provide effective self-servicing capabilities.
Knowing what to do is important, but executing on the “how” is what makes the difference. Let’s see how a U.S. bank did it for its secured lending business. Traditionally, the bank took about 45 days for a customer to secure a loan, on average. The process involved multiple documentation requests to customers (e.g., pay stubs, W2s, letters of explanation), and back-end processes (e.g., initial file review, file assignment, ad hoc reports) were highly manual.
To transform this journey, the bank’s leadership team reinvented the entire process. To speed pre-approvals, they developed a database of tens of millions of U.S. households combining credit, property and income attributes using internal and external data sources. This data allowed them to generate personalized pre-approved offers that customers could accept with one click. They built a mobile-first customer experience, where customers could personalize their offers based on real-time data and finalize a pre-filled application, either on mobile or with the assistance of a bank employee. They redesigned key processes (e.g., specialized loan “assembly lines”), automated key tasks (e.g., initial file scrub), and developed digital tools for operators to drive productivity (e.g., daily workflow management). And they modernized credit policy execution to enable greater use of data in underwriting (e.g., using direct deposit data for income), while maintaining or increasing risk controls for the bank.
To enable all these innovations, they implemented key technology and data capabilities, including a customer data platform, AI/ML models (e.g., propensity models), data products (e.g., income), a digital app for customers and a workflow tool for the fulfillment center, all deployed on a cloud-based platform-as-a-service infrastructure.
All in all, this transformation required more than a dozen use-cases across the entire journey and massive change management programs (e.g., training, retooling) for agents in branches, contact centers, and operations. But, only 18 months after the initial launch, the approval process was shortened from 28 to 7 days. This leap allowed the bank to become a leading secured lending originator and increase originations by 35%, while reducing origination cost by 20%.
The Capabilities Needed to Outcompete
A company that aspires to outperform needs to do the kind of end-to-end changes the bank above did across dozens of customer journeys and core business processes. That’s only possible when it is rewired with differentiated capabilities. Our study of more than 200 large-scale digital and AI transformations isolated the six core capabilities rewired companies develop:
Creating ambitious and focused transformation roadmaps. This requires business leaders to align their efforts on specific domains (e.g., journeys or processes) that matter to customers and generate significant value.
Building a quality digital talent bench. Leaders prioritize creating an environment that attracts top-notch engineers and allows them to thrive (e.g., tailored career tracks, autonomy).
An operating model where hundreds of small cross-functional “pods” made up of business, engineering, and resources from control functions are mobilized against priority solutions. A single journey (or product) owner responsible for the end-to-end experience.
A distributed technology environment and modern software engineering practices to allow the entire organization — not just IT — to develop digital and AI-based solutions.
Data products and modern data architecture that make it easy for different parts of the organization to consume data for their own applications.
Change management to ensures digital solutions are adopted and can scale by making them easy to use and reuse across the enterprise.
In our blind assessment of these capabilities for the leaders and laggards, we found that leaders stand out across the board on these capabilities. No single one explains their success. All are needed. With that baseline, the most differentiated capabilities are talent and operating model, not technology. Over time, these capabilities create ever-improving customer experiences and drive lower unit cost. Financial rewards follow.
While our research has focused on banking, our experience reflects similar lessons and patterns in every industry, whether B2B or B2C, products, or services. A digital and AI transformation, however, cannot be done in “special project” mode. To pull this off, the entire organization must be able to deliver constant digital innovation, which requires a holistic set of capabilities. The effort is significant, but so is the reward.
This content was originally published here.