What Makes a Company “Future Ready”?

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What makes a company “future ready”? The author analyzed top companies by revenue across four sectors, measuring seven equally weighted factors, then analyzed what leading companies were doing differently. They discovered industry specific insights, which also informed more universal lessons. First, don’t play zero-sum games with disruptors. Looking at the financial industry, companies that explored new tech early were able to develop partnerships and exploit that tech more quickly. Second, when everyone is digitizing, only going deep sets you apart. Learning aggressively, with a strong viewpoint, helped retail companies find opportunities to differentiate. Third, in a high-speed sector, you have to branch out fast. Looking at the tech sector, the author saw the importance of knowing what kind of decision you’re making, so you can make it quickly.

The pandemic put companies under a tremendous amount of stress. It revealed who is ready for the many changes the near future will bring — and who is not. In times of crisis, this type readiness doubles as a source of resilience. It reflects how companies can adapt, the robustness of their internal capabilities, and how capable of finding new sources of growth they really are. And the more uncertain the world seems to be, the more important for companies to become future ready.

Consider how fashion brands and retailers have navigated the past two years. Executives have been talking for more than a decade now about how retail is moving toward direct-to-consumer, omnichannel, and personalized offerings. Then the pandemic hit. The winners have been the ones who have scaled such capabilities ahead of their competition. Stock prices at Hermes, Nike, and Target have hit all-time highs as they have pivoted to e-commerce, in stark contrast to the parade of bankruptcies among some of retail’s most iconic names: Brooks Brothers, J. Crew, and JC Penny.

The automotive industry offers another example of the importance of becoming future ready — specifically, in cultivating mastery of software and electronics. While major carmakers have made strides to pivot to electric vehicles, the ongoing semiconductor shortage has forced companies like VW and GM to halt their production lines. Tesla, on the other hand, was able to “substitute alternative chips, and then write the firmware in a matter of weeks,” explained Elon Musk. This process required quickly rewriting the car’s software, which was possible because of Tesla’s in-house mastery, and helped Tesla deliver 308,600 vehicles in the fourth quarter — up from 180,667 the previous year — achieving a “trophy-case” performance.

Becoming future ready means scaling up capabilities relevant to future competition. In previous research, we found that a company must make regular shifts in its know-how in order to stay ahead of competitors over the long run. If a company’s know-how stagnates, it will face competition from copycats, fall behind in advancements, and eventually fail.

At IMD, we’ve compiled a future-readiness indicator, which measures a company’s preparedness. We ranked the top players in each industry based on seven equally weighted factors. We evaluated the financial fundamentals of a company’s ongoing business, as investing in the future requires a healthy cash flow; we also looked at cash and debts. We measured a company’s growth prospects, looking at investors’ expectations and the intensity of a company’s investment in startups or new ventures. Because executive teams need to see beyond their day-to-day operations, we also looked for diversity in the management board, taking note of gender and nationality as well as the industry backgrounds of a company’s top leadership. When possible, we gauge a company’s productivity by measures such as operating revenue per employee. Finally, we monitor the trajectory of new product rollouts — openness to new ideas and the early results of innovation.

The resulting industry rankings are based on hard data. They include financial reporting, investors’ calls, LinkedIn profiles of the management team, CrunchBase, Factiva, and other publicly available reporting, all of which we used to produce a balanced composite score. Our measures are selected based on prior management literature. Using more than a decade of data (2010 to 2021), we also compared the choices and outlooks between the top- and bottom-ranking companies to highlight how top-ranking companies behave.

The rankings analyze 86 top companies (as measured by revenue) across four industries. What we found is that, while each industry has its own playbook, there are universal managerial behaviors and cognitive outlooks that are common across top-performing companies. For each, we’ve identified an industry-specific insight and a universal behavior that can help guide other companies to become more future ready. 

Two thousand twenty-one was a year for fintech innovation. Electronic payments took off as people shopped online. Many managed their finances online rather than going to bank branches. These have permanently shifted consumer behavior. While fintech disruptors PayPal and Block (formerly Square) were near the head of the pack, the leading incumbents are the legacy infrastructure builders: Mastercard and Visa.

How did these companies prosper when Apple Pay and Google Wallet seemed poised to make plastic cards obsolete? Instead of trying to outrun fintech disruptors and tech giants, Mastercard and Visa partnered with their rivals, to the benefit of all involved. Specifically, they invested heavily in a wide range of application programming interfaces (APIs). An API is a set of official rules and guidelines that lets software exchange information with one another. This allows third parties to tap into Visa and Mastercard’s infrastructure in a way that is both secure and easily accessible.

This strategy helped protect Mastercard and Visa from disruption. Not only do Apple and Google work with the two credit card companies; so do PayPal, Block, Samsung Pay, Facebook Credits, Stripe, and even Coinbase, a cryptocurrency exchange.

The major insight here, then, is that a product’s best feature may not be invented in-house. Visa and Mastercard realized that killer apps were being invented by third parties, who are closer to their customers. Sometimes you compete, sometimes you cooperate, but it’s never a zero-sum game. That’s the new playbook.

The success of Mastercard and Visa wasn’t predetermined. A decade ago, American Express was the largest payment company (now ranked 20) and had several major advantages: It issues credit and processes its own transactions, earns both interests and transaction fees, and has a closed-loop operation. Unlike Mastercard and Visa, it doesn’t need the backing of JP Morgan Chase or HSBC to underwrite cards. What happened to produce such a reversal for these companies?

By our analysis, American Express’s digital operation had improved over the last decade. But, when compared with its main rivals, Amex’s relativeposition fell behind. Where Visa and Mastercard surpassed American Express was in exploring new areas while exploiting existing opportunities; American Express, on the other hand, focused largely on short-term exploitation. As a result, it got trapped in its legacy business model, trying to get customers to spend more and stay loyal.

In the pursuit of a new business model, the opportunity to learn is fleeting. Once your competitors explore enough, they will pivot to exploit that new knowledge base to their advantage. So, at all times, you must maintain a healthy portion of activities dedicated to exploring the new, even when early evidence remains unclear, and commit yourself to difficult choices and tough tradeoffs guided by a vision about the future when evidence becomes compelling.

For a consumer brand, digitalization is not merely about the front-end, online experience — there are a lot of make-or-break technologies to master behind the scenes. Consumers today want to personalize their goods online and have them shipped in days. To make this happen, and to do it profitably at scale, a company must digitalize its entire supply chain. It must automate all the tracking and coordination with external partners. All these facets require new learning.

To keep up with fickle consumer demands, Nike, for instance, leverages advanced data analytics to gather insights around the clock. A cross-channel prediction at the local level allows the company to make markdown and promotion decisions instantly and to move inventories across the country. That’s how consumers can find what they’re most interested in wherever they are.

Meanwhile, Nike’s retail stores increasingly resemble an immersive gallery. Shoes are displayed like art pieces. But far beyond a mere luxury boutique, customers can use the Nike App in the store to gain access to limited release items, fun facts, and reward schemes. This is a prime example of a future-ready brand in sportswear. It employs a digital, direct-to-consumer, and data-driven approach, which annihilates the boundary between the online and physical world.

Companies like Nike, Lululemon, and Hermes rely on a strong viewpoint about the future to guide their learning, exhibiting a high degree of certainty. This set of behaviors — high learning and high certainty — may sound paradoxical, but that’s how visionary leaders update their mental model when new data emerge. These are strong opinions loosely held. We find such outlook associates with a high level of shareholders’ return over the last ten years. These are companies open to experimentation. If pivoting is required, they pivot. And, based on evidence, they commit at scale.

As for Lululemon, its robust digital channel is built upon innovation beyond apparel design. The company holds patents in well-being metrics, a biometric sensor belt, and a three-dimensional texture for the surface of a yoga mat. Then there’s the acquisition of Mirror in 2020: Lululemon bought the startup that sells a $1,500 tech-enabled mirror with a camera and speakers so people can tune into live yoga and fitness classes at home. All the direct-to-consumer relationships helps the company better discern consumer taste and detect new behaviors.

These are big bets that are difficult to commit to — unless, of course, you have a high learning attitude and a top management team aligned with a shared viewpoint about the future.

It’s an understatement that technology companies are the “fruit flies” of the modern economy. The tech sector operates at a rapid velocity, and executives must pivot quickly to avoid being left behind. Top-ranking technology companies don’t only invest in new technologies; they are biased toward action in branching out to new offerings or entering new verticals. They are willing to acquire new capabilities and wade into the unknown. The subsector of semiconductors in technology illustrates this.

Intel doesn’t rank well at 16. It has got stuck making microprocessors for PCs, laptops, and servers while its competitors, most notably Nvidia, have capitalized on the surging demands in chipsets for applications in machine learning, autonomous driving, natural language processing, and other A.I. applications.

Intel’s conservatism is understandable; it is the only player in the semiconductor sector that has an enormous footprint of factories, but with that comes the baggage of risk avoidance. It can’t branch out into new businesses without the worry that its factories might stand idle if new products aren’t blockbusters.

Asset-heavy companies are always more conservative, and, paradoxically, when others are asset-light and you are not, you end up being disadvantaged.

Meanwhile, Nvidia has evolved beyond deploying graphic processors only in the gaming sector. AMD, which used to be an underdog on the brink of bankruptcy in 2014, now provides the industry with some of the most powerful processors. Nvidia and AMD both rely heavily on Taiwan’s TSMC to manufacture their leading-edge products. And, because they don’t have factories or fabs, they don’t inherit any sunk cost. They are asset-light compared with Intel and can therefore afford to be agile.

Knowing how to make decisions quickly is essential to surviving in a fast-paced industry. But, to do so, you need to identify which decisions are reversible. Amazon’s Jeff Bezos calls such decisions “two-way doors.” You can back out later if you don’t like what you see, so you can go fast on them. The trouble is, as an organization grows bigger, managers tend to uniformly use a heavy-handed approach to scrutinize every decision and slow down the company.

Having a clear distinction in which kind of decision you’re making is the key when change is constant. This distinction is what separates the successful turnaround of Microsoft from the less successful one at IBM when both companies were pursuing cloud computing and A.I. on their enterprise client base.

Microsoft won the day because it harbored a healthy bias for action but remained unfailingly realistic. Its executives focused on preventing catastrophe while they were scaling new businesses, such as cloud computing, augmented reality, and its own line of tablets. A healthy paranoia of what could go wrong guided its decision making, and yet it didn’t stop the company from trying new things. It kept learning in the face of uncertainty. Conversely, IBM was less able to make fast decisions among managers across all levels than Microsoft. That meant that well-intentioned initiatives got prematurely scaled, resulting in offerings ahead of the market or before the underlying technology became robust enough.

At the Palo Alto headquarters, visitors at Tesla can marvel the dramatic use of vertical integration. Tesla has used integration in places where the automotive ecosystem has underperformed. In the battery technologies, for example, Tesla designed and produced battery suitable for super-charging vehicles with coolant running throughout the entire pack.

More critically, Tesla uses the software muscle to take over more functionalities that used to be located in purpose-built hardware. Elon Musk seeks to work directly with TSMC and Samsung instead of outsourcing electronic components to the conventional Tier 1 suppliers. It tackles technical problems that the existing ecosystem cannot resolve fast enough. It goes beyond the conventional role of an automaker to integrate the hardest problem that needs to get solved.

Little wonder why automotive possesses the least optimism as a sector. It’s an industry unaccustomed to exploration and experimentation, a conservative sector filled with managers with similar backgrounds. That’s how companies become fixated with keeping pace with the competitor next to them and lose sight of what’s on the horizon.

A good number of automakers still possess a healthy balance sheet to fund new investment. But to move away from mechanical engineering as the dominant know-how and to replace it with knowledge in software and electronics requires a shared viewpoint at the highest level. It also requires experts coming from very different backgrounds. Nike has succeeded in doing this, and so have Visa and Mastercard.

The fear of losing in the near term is very real. But the threat of losing relevance looms even larger. That’s why becoming future ready is straightforward. But it takes courage to drive it.

Editor’s note: Every ranking or index is just one way to analyze and compare companies or places, based on a specific methodology and data set. At HBR, we believe that a well-designed index can provide useful insights, even though by definition it is a snapshot of a bigger picture. We always urge you to read the methodology carefully.