By accelerating digital adoption, the COVID-19 pandemic has widened the gap between the top and bottom companies on the power curve of economic profit,11. Economic profit—the total profit after the cost of capital is subtracted—measures the success of a company in beating the market. Plotting each company’s average economic profit reveals a power curve showing that while most companies effectively earn their cost of capital, only a few companies, all of them in the top quintile of the distribution, generate significant economic value.amplifying winner-takes-most dynamics and further separating digital leaders from also-rans. Competitive differentiation, now more than ever, emerges from superior digital capabilities and technology endowment, more agile delivery, and a progressively more tech-savvy C-suite.
Digital’s ascendancy is visible not only in the dominance of hyperscale tech companies but in the success of non-digital-native companies such as John Deere, Goldman Sachs, BHP, Disney, and Bosch, among others. These companies have invested heavily in new digitally enabled strategies and business models. Not only did they enter the pandemic with bigger technology endowments22. Technology endowment refers to the sum of a company’s overall digital technology capabilities, talent, leadership, and resources. than their peers—they continued to outspend them on digital technology as the pandemic went along.
Legacy companies looking to make comparable performance improvements should start by revisiting the classic strategy moves that, individually and in combination, have been proven to jump companies up the power curve of economic profit.33. Using empirical research, our colleagues described five “big moves” that enabled companies to outperform on the power curve of economic profit; see Chris Bradley, Martin Hirt, and Sven Smit,Strategy Beyond the Hockey Stick: People, Probabilities, and Big Moves to Beat the Odds, Hoboken, NJ: John Wiley & Sons, 2018. Further research since then suggests the shape and magnitude of these moves may be changing in response to a more digital and tech-enabled world.By adapting these classic strategies in sometimes counterintuitive ways, companies can build a winning strategy in an era of digital disruption (Exhibit 1). This article sets out a road map for doing so.
Differentiating through digital technology requires having the right capabilities, culture, and infrastructure. But companies can struggle to build these organically at sufficient scale and speed.
The first of these classic moves describes the business-model innovations and pricing advantages that improve a company’s gross margin. To jump into the top quintile of performance on the power curve of economic profit, your gross margin needs to reach the top 30 percent in your industry over a ten-year period. As digital technology becomes ever more important, the sources of these innovations and advantages are now shifting from traditional sweet spots into less familiar terrain, such as using digital technology to innovate products, services, and business models.
John Deere, for example, now differentiates through an Internet of Things (IoT) ecosystem that provides digital services to customers, enhancing the value delivered to customers by its machinery. Carmakers were previously differentiated, in part, by the quality of their combustion engines. But as cars continue morphing into “computers on wheels,” automakers are looking to differentiate through software, which has traditionally been outside their core competence. No wonder they are looking to quadruple hiring for automotive-software developers.
These new sources of differentiation are not lost on executives, most of whom realize that digital technology is a strategically vital competitive differentiator, not just for business-model innovation but for productivity, cost excellence, and other objectives (Exhibit 2).
In some cases, differentiation will mean getting software into the core of your business model and go-to-market approach. Other times, it will require building new digital platforms inside the confines of traditional legacy corporations, as financial-services giant Allianz succeeded in doing with Allianz Direct—a direct-to-consumer auto and home insurance business served on a single digital platform across multiple European markets.
In still other cases, differentiation may require looking beyond the boundaries of the organization to digitally enabled ecosystems with interconnected services that fulfill a variety of users’ cross-sectoral needs in one integrated experience. For instance, new entrants in the housing market—such as the United Kingdom’s ZPG or Zillow in the United States—are looking to create end-to-end ecosystems spanning search, property comparisons, mortgage shopping, household moving, phone and cable company reconnections, and access to home-improvement professionals. Kakao and WeChat are looking to do the same, in South Korea and China, respectively. We see evidence of both incumbents and tech companies looking to develop ecosystem plays across traditional industry boundaries in a broad range of sectors.
The second classic move relates to productivity. Our 2018 research showed that jumping into the top quintile of performance, or staying there, required a productivity improvement rate in selling, general, and administrative (SG&A) activity in the top 20 percent of the companies in your industry over a ten-year period, and an overall labor productivity improvement rate in the top 30 percent.
Digital disruption—for example, the ability of smaller players to leverage the public cloud and access large-scale data sets—is now changing the math on productivity in many industries. Consider how the data-driven automation of insurance-claim filing has, in some instances, reduced costs by as much as 70 percent in that industry. Across the board, executive teams should now assume the productivity bar has shifted from the leanest of their incumbent peers to that of greenfield, digital-native attackers boasting a high degree of digitization, straight-through processing, and largely variable cost bases.
As they look to meet this new bar, legacy companies may find that remote working and the mass migration to digital channels has helped them discover unexpected savings from cheaper customer interactions and—in some cases—the ability to let go of real estate as they shift toward hybrid working. Companies have also accelerated their tech enablement by moving toward agile operating models across the organization; by automating the cloud-based provisioning of infrastructure and delivery of applications; and by using AI to optimize retail footprints and sales forces, among other examples.
Automation, for example, is becoming increasingly prevalent, with rapid advances since the early days of industrial applications and robotic process automation. For instance, several US grocery stores took advantage of the pandemic-driven surge in sales and the need to decrease the number of people in store at a given time to invest in robots that helped clean floors and shelve inventory—investments that could provide these grocers longer-term cost savings. We see this happening in B2B as well, for example, with Schneider Electric’s acquisition of industrial-automation provider ProLeit, and Microsoft’s acquisition of a software robotic-automation platform.
Of course, productivity gains aren’t all about cutting costs. Productivity improvements from technology investments also arise through innovation. High average productivity, after all, comes about through some combination of producing the same or more output for less input, or higher output from the same or fewer inputs. Digital winners typically rely on hyperscalable software-based business models that can rapidly scale up the number of users and revenue with only minimal changes to the underlying cost structure.
The pandemic has made clear that, while you may still need to out-invest peers to win, where you direct that investment and who you consider “peers” vary according to how you are seeking to differentiate.
Effective capital spending is another of the classic strategies companies have used to jump up (or remain at the top of) the power curve of economic profit. Top-quintile companies on that curve have boasted a ratio of capital expenses to sales in excess of 1.7 times the industry median for at least ten years. But strong capital programs make sense only when companies have the foundations for profitable growth in place, and in the presence of underlying demand for the additional capacity capital programs generate. Absent these, companies risk accelerating projects that destroy value rather than create it.
As technology and digital become increasingly important enablers for business-model innovation and productivity improvement, companies that outperform their peers are focusing more of their capital investment on technology and digital assets. This proved even more true during the pandemic, as further clarity about where and how best to invest in technology also emerged. Top economic performers entered the crisis ahead of their peers on technology spending, and out-invested them during the course of the pandemic—particularly with regard to talent, building new partnerships, and investing in R&D.
The pandemic has made clear that, while you may still need to out-invest peers to win, where you direct that investment and who you consider “peers” when evaluating that level of investment may vary according to how you are seeking to differentiate. For example, one of the biggest differentiators in tech has been the emergence of hyperscale platforms with winner-takes-most economics. It is not surprising, therefore, that the biggest winners during the pandemic (in terms of stock market performance), including both established hyperscale technology players as well as fast-growing players such as Zoom and Square, have invested in these technology platforms.
For most companies, though, aspiring to own a global-scale technology platform may prove a less-than-viable pathway. So while the increasing emphasis of your capital investment should be on digital and technology assets, be sure to focus it on investments that provide not only a clear source of differentiation but also a winnable one. In the world of payments, for example, even large regional banks—which have traditionally enjoyed the resources to out-invest their local peers—are now seeing their investment in payments products and technology dwarfed by global payments platforms like PayPal.
It can still be possible for local or regional incumbents to own critical elements of a future software-enabled business model or technology-platform landscape, but they’ll need to be all the more selective about where to play, focusing on those elements for which local factors are crucial, and which are more difficult for global technology players to replicate. For example, Walmart operates the third largest online marketplace in the United States but still trails more global players (and digital natives), such as Amazon and eBay, by some distance. As it seeks to close the gap, Walmart can leverage its huge physical store network to attract vendors wanting to offer customers in-store pickup and returns and shorter delivery windows. Other local incumbents have shown that partnerships across industry players can enable them to shape key technology platforms to compete with global tech companies. Nordic banks, for example, have partnered to create instant-payment platforms that have helped them defend their share of consumer payments in the face of global tech entrants.
At the same time, the emergence of global-scale technology platforms makes it easier for subscale or local players to compete. A growing number of companies are leveraging these platforms to build and deliver new software-enabled business models of their own by accessing world-class technology solutions via standardized, cloud-based, third-party solutions. For example, cloud computing relieves smaller companies of the need toinvest in the fixed costs of data centers. Now, even the smallest start-up can access the computing power and storage of Google, Microsoft, or Amazon. In so doing, they reduce capital investment in less-differentiating areas and invest instead in the technology assets and capabilities that provide an edge over competitors—and through which they have the ability (and sufficient scale) to be distinctive.
One bank began spending smarter during the pandemic by deploying agile teams to stand up minimum viable solutions to challenges in digitization and technology infrastructure. Rather than shelling out hundreds of millions of dollars to replace core technology systems (such as the systems of record that track loans and other transactions), the bank wrote a bit of code into its new cloud stack to digitize (and automate) data capture around credit risk factors, and combined that minimally viable product with an agile team connecting bankers with risk and compliance specialists. The approach yielded faster, better decisions at a fraction of the cost and time—all while transforming the customer experience. Working smarter avoided (or at least deferred) a massive spend on underlying core systems, enabling the bank to redirect these funds into more productive investments, such as an AI-based credit-decisioning algorithm that lowers credit risk while improving customer experiences.Sidebar
Outperforming through digital requires a high level of tech savvy, not just from technology leaders within the organization but from the entire leadership team. Responsibility cannot fall solely on chief information officers (CIOs) and chief data officers (CDOs). Business-unit leaders and COOs are increasingly being asked to make tough trade-offs between technology and other types of investments. Executive boards, for their part, now need a broader technology fluency across all board-level decisions, rather than simply a single, siloed “tech expert” board member.
Yet, as of today, too few company leaders have engaged deeply with technology, even as it transforms the requirements of nearly every role and becomes part of everyone’s job (exhibit). Without a deeper understanding of the critical intersection points between their business and the promise of new technologies, executives and board members may struggle.
Building a new digital business or fully revolutionizing an existing one is hard, and the pitfalls are many: it can be easy to waste money in digital and technology if leaders are not sufficiently informed regarding their business’ value drivers. A thorough assessment can help companies examine their own technology spending relative to peers, the better to understand where they might need to modernize IT operations to support accelerated digital strategy. A case in point is the cloud. McKinsey analysis shows that almost all industries across the Fortune 500 show potential for an average rise in earnings before interest, taxes, depreciation, and amortization (EBITDA) of more than 20 percent from the cloud, but an overly narrow view of the value the cloud can generate often keeps companies from making decisions that deliver the benefits that are possible. For example, blindly migrating workloads to the cloud in the anticipation of cost savings instead of thoughtfully deploying the cloud to enable innovation and differentiation at pace has contributed to 30 percent of companies reporting that much of their cloud spending currently goes to waste. Paradoxes like this further highlight the importance of achieving technology fluency throughout the top team (see sidebar “Tech-enabled leadership”).
Lastly, given the rapid pace of change, a nimble approach to investment is also important. Agile, stage-gated investment practices help ensure spending gets committed on a performance basis and quickly reallocated if initial hypotheses don’t bear out in the market.
The link between active resource reallocation and value creation is well established: McKinsey research has shown that companies shifting more than 50 percent of their capital spending across their businesses over ten years created 50 percent more value than counterparts that moved resources at a slower clip. Dynamic resource allocation shifts money, talent, and management attention to where they will deliver the most value to your company.
But now companies need to reallocate resources at an even faster pace. What was considered best-in-class speed for most business practices in 2018 is now slower than average—thanks to the massive technology acceleration that has occurred since early 2020. Companies with the strongest technology endowments are moving at an even faster pace.
This effect was visible during the COVID-19 crisis as companies stood up working solutions for big changes, such as remote working, migration to the cloud, or last-mile delivery, all of which required rapid, dynamic resourcing to support innovative changes carried out in a matter of days or weeks rather than the one to two years most companies had previously thought necessary (Exhibit 3). As aptly stated by Microsoft CEO Satya Nadella in a 2020 quarterly earnings call, “We’ve seen two years’ worth of digital transformation in two months.”
At many companies, an effective response to the pandemic required reallocating capital and talent toward digital, even when other parts of the business were seeing broader cost reductions. These trends might not continue at the frenetic pace of the pandemic, but they are unlikely to return to precrisis norms, especially as barriers to improvisation and experimentation fall, along with the associated stigma of “failing fast.” Fortunately, you don’t need to predict the future when shifting resources. You just need to read the present moment better than your competitors and respond dynamically.
Once an incumbent company has acquired and successfully assimilated a digital unicorn, the advantages of taking a more programmatic approach to smaller acquisitions resurface.
Differentiating through digital technology requires having the right capabilities, culture, and infrastructure. But companies can struggle to build these organically at sufficient scale and speed. That’s one reason many companies instead look to acquire digital assets, skills, and talent through digital M&A (defined as the acquisition of a company with predominantly digital capabilities and revenue streams). Companies need broader exposure to the tailwinds of digital technology, and digital is thus often a predominant focus of their M&A activity.
But what is the right approach to digital acquisition? Across most M&A strategies, evidence shows that a programmatic approach (the steady acquisition of multiple smaller targets in a focused fashion over an extended time horizon) is the most effective one for companies hoping to jump up the power curve of economic profit. But programmatic M&A may not always be the best bet for digital leapfrogging—initially, at least. Our research indicates that the early acquisition of a “digital unicorn” (defined as a single deal worth at least $1 billion) has been a significant differentiator for total returns to shareholders (TRS) for big incumbent companies in the past ten years (Exhibit 4), even though this runs counter to what traditional programmatic M&A approaches would suggest.
Why make a big acquisition in the digital space when this strategy has typically been less effective for nondigital acquisitions? Because integrating many smaller tech companies, as would be required by the programmatic approach to M&A, can be much harder than integrating smaller, nondigital companies. The difficulties have to do with culture, talent, and infrastructure. Emulating the culture of a digital native (whether Amazon’s famous “customer obsession,” Netflix’s “no rules rules,” or the rapid product-development cycles typical in a native software company) can be challenging for large incumbent organizations that have strong existing cultures, as well as more structural-process and decision-making barriers to operating like a digital native.
Culture is a sticking point in any postmerger integration, of course, but all the more so when incumbents buy technology companies with the hope of shifting their own culture toward that of a digital native with new talent and ways of working. Typically, there is a mismatch between the incoming talent and the cultural behaviors of the acquirer. This makes the traditional programmatic M&A approach, with its series of smaller deals, more difficult to pull off. If each deal is below critical mass for shifting the culture and ways of working of the combined organization, the smaller acquisitions can have a tendency to die on the vine once they are bought by corporate behemoths. Critical talent can be lost when individuals accustomed to more freewheeling cultures find themselves in more traditional organizations. And when talent walks, the culture the incumbent had hoped might be a transformative catalyst leaves with it.
Furthermore, when it comes to organizational culture, every tech company is different. Incumbents that start off buying many small tech companies often end up with a piecemeal approach to integrating multiple unfamiliar cultures—cultures that may clash with not only the incumbent company culture but also that of the incumbents’ other acquisitions.Sidebar
What about the risks that come with big-bang acquisitions like buying a digital unicorn? Here are some steps to make these large bets less daunting.
Clearly defining your strategic rationale in the context of a specific acquisition target helps ensure your big purchase will prove as relevant to your existing business as possible. Is your acquisition aimed at plugging a capability gap? Expanding your reach and relevance? Changing your company’s DNA, including how and where you compete? Any of these objectives, or some mix of them, might be the primary rationale for a big acquisition.
Some companies, in our experience, perform less technology diligence on acquisitions costing hundreds of millions of dollars than they do on internal pilot programs that cost a fraction of that. Performing deeper and broader technology diligence will help you understand how the acquisition target’s different technology capabilities, systems, and platforms might interact (or not) with one another and those of your own company.
Not only will you want a detailed integration plan with a specific eye toward technical talent retention and existing customer relations, you’ll want to execute against it quickly and thoughtfully. Speed matters with any acquisition but all the more so with digital ones, since their products often sit adjacent to other products in an acquirer’s portfolio. Any significant delay carries increased risk to the synergies built into the purchase price. Furthermore, acquirers that take too long to integrate their purchase sometimes miss the opportunity to transform their organizational culture in time to prevent newly acquired talent from walking out the door. Slow movers also risk migrating too gradually to their new tech stack. Instead, they end up with two parallel stacks operating side by side, at great cost—and with considerable confusion to users.
For both a big initial acquisition and more programmatic ones thereafter, you’ll want an operating model for digital M&A. Your goals are to establish strong governance and accountability; design clear roles and assign them to the right people, along with the right tools; build your capabilities and reputation as an acquirer; and create a compelling narrative for investors.
These pitfalls seem less prevalent when incumbents acquire a large enough source of tech-friendly talent and culture up front. The sheer number of people that arrive with a big acquisition have an easier time protecting their culture—and influencing their new parent company’s established culture and operating model without being suffocated in the process (see sidebar “Making big-bang acquisitions work”).
There’s still another reason it may make sense for legacy companies to consider buying a digital unicorn: the need for well-integrated and coherent technology road maps and fit-for-purpose infrastructure to help transform entire business domains within their companies, not merely deliver individual use cases. To get there quickly, it often makes sense to acquire the needed infrastructure all in one go, rather than trying to integrate smaller acquisitions, each with varying technology platforms that can be made interoperable only after the fact.
Of course, a big acquisition isn’t always the right answer, and a large digital acquisition doesn’t magically modernize your technology function or the tech stack it relies on. The best tech transformations occur in organizations that tackle multiple interdependent elements spanning the technology function’s role, delivery model, and core systems—all with a properly sequenced migration path. In this modernization process, a new acquisition, which might often bring a more cloud-enabled technology stack, sometimes provides a lifeboat, so to speak, that helps companies transition from outdated tech stacks toward the more nimble cloud-enabled stacks they need.
That said, once an incumbent companyhasacquired and successfully assimilated a digital unicorn—and made the necessary shifts in culture, ways of working, and technology architecture—the advantages of taking a more programmatic approach to smaller acquisitions resurface. The organization is now in a fit state to pursue a more traditional M&A approach. In sum, companies looking for a better foothold in digital should consider whether it is best to make a larger acquisition up front to achieve a step change in culture, talent, and technology infrastructure before moving to a more programmatic approach thereafter.
Many companies, stunned by how quickly digital technology moved center stage during the pandemic, have scrambled toward rapid digital transformations. We’d be the last to discourage this urgency. But companies should also step back to reassess their strategies thoroughly and carefully in the light of digital disruption and digital opportunities. The fundamental strategic principles still apply—as do the bold moves proven to boost corporate performance—provided you keep a close eye on how digital is reshaping them.