What Should We Measure?

When William Muir set out to study productivity, he used hens as his test subject because measuring their egg-laying productivity was simple. She who lays the most eggs is the most productive. (If you skipped Chapter 9, you'll want to go back and give it a quick scan to learn more about this intriguing experiment.) For much of the Second and Third Industrial Revolutions, we measured human productivity in the same way. Count the number of acres plowed, the cars produced on the line, the barrels of crude pulled from the earth, the new accounts opened, or the clicks and page views on a website, and you get a measure of productivity.

But what if, in the Fourth Industrial Revolution, we are measuring the wrong things? Does optimizing the production of Product A matter as much when market winds shift to Technology B before you can even complete an inventory of the first? What if production output matters far less in the future of work than does production process? What should we measure then?

That's the conundrum for many organizational leaders as they rethink how they construct and lead their teams for greater learning and adaptation.

Fortunately, Dr. Muir's productivity experiments light the way.

Recall that in Muir's experiment the “super chickens”—the hens that were the most productive layers—were also the most caustic. They outperformed their peers by intimidating, abusing, and in some cases even killing them. In short, the super chickens were bullies. They looked good because they made others look bad.

While attempting to foster a breed of high-performing hens, Dr. Muir inadvertently gave us a lesson in the importance of culture. The toxic “work environment” inside those cages didn't just kill chickens, it killed productivity over the long term. Similarly, as Dr. Muir found, the best environments fostered productivity. When Dr. Muir selected all the hens—and not just the top performers—from the best-producing flocks, productivity increased 160%.

As we cross the bridge to a digital economy, we need to shift from measuring output to optimizing throughput. In other words, the conditions in which we create and produce will matter more than the product itself. That may sound like a radical idea, but consider this: the things we produce—because they may be transient—are a product of our organization's capacity to identify and rapidly respond to new opportunity and capture new value. Products and services will be short-lived. Rather than optimizing for specific production, our best work will be in establishing the conditions that enable continuous and continually shifting methods of value creation. These conditions result in an agile, learning, and adaptable company able to thrive in the new realities on the other side of the digital economy bridge.

Those conditions we call culture and capacity.

The Power of the Culture and Capacity Focus

It's a radical but remarkably straightforward concept: companies are nothing more than culture and capacity. Period. Of course, neither culture nor capacity is a simple construct. Still, if you can break apart these two elements to understand them, you can rejoin the ideas to create a framework for highly effective organizational leadership. So, let's break it down.

When we put culture and capacity together, we create a powerful force for transformation of the business, one that shifts the focus from output to input. Culture and capacity are the conditions—the inputs—of an effective business. To the outside world, culture shows up as a brand, an expression of the company's purpose and values. Capacity is evident in the products and services a company puts into the market; these products and services are the outputs of an organization's ability to learn and create (Figure 10.1). Drop culture and capacity into a market context—a market need, an industry, a geography—and you have a business. To put culture and capacity to work in our organizations, then, we need to better understand both. Let's dive deeper.

Culture at the Core

Every organization has a culture. Culture is a sense of purpose and a way of doing things that structure daily life at work. Over three decades of observing culture in early-stage technology companies, Chris developed a theory: culture is either intentional or accidental. An intentional culture is a deliberate construction of organizational leaders, created in collaboration with all those who are led. An accidental culture is an environment that emerges without intention from a collection of experiences. Accidental cultures, Chris has observed, are almost always toxic.

Too often, the trappings of a workplace—onsite daycare, free gourmet meals, dog-friendly offices, and the like—are mistaken for corporate culture. At best, these benefits are evidence of a culture, but they are not the culture itself. In an intentional culture, a company might declare a lofty purpose: to “unlock human creative potential,” for example. Among its operating principles might be a statement like “We believe our employees are at their best when they are at their healthiest.” Dozens of decisions can extend easily from that statement of values, allowing the company to say yes to an onsite gym and no to junk food–stocked vending machines. The workplace benefit reflects the values, rather than the other way around.

If that's not clear, let's try another example. You walk into an office space and notice that every desk is outfitted with a Herman Miller Aeron chair, list price $969. These ultra-comfortable, highly ergonomic chairs were once all the rage with well-funded Silicon Valley startups. What do they say about the company's values? On the one hand, it might project a core belief that employees are most productive when they have a comfortable work environment (intentional). On the other—as is too often the case in the profligate boom cycles—it might just mean “we raised a lot of money and we're spending it on ourselves instead of on our business objectives” (accidental). Like we said, the workplace benefits reflect the company values.

Intentional culture begins with organization's leadership. Frankly, it is organizational leadership. So, where do you start to build a great culture?

Capacity: Culture's Partner

By this point, we hope you are embracing culture as the structure in which to manage change. By nurturing culture with care and intension, you create the conditions that strengthen your adaptation advantage. Throughout the book, we've preached that the future of work is lifelong learning and adaptation. For you, individually, that means taking responsibility and initiative for learning. You'll be able to power through the continuous cycles of change and adaptation by connecting to your own motivational driver, the power source that is your sense of purpose. As a leader, you can tap into that purpose and inspire your team to a collective mission when you make culture the foundation of your operating principles.

But culture alone is not enough for effective adaptation. To get there, you must also nurture culture's partner, capacity. This is where you need to connect the two concepts for effective leadership.

If culture is the heart of a company, capacity is its brain. Simply put, capacity is an organization's ability to respond to opportunity. But it is much more than the available space, time, and talent needed to address a new opportunity. Capacity is how we think about new information and ideas in order to assess and respond to opportunity. In other words, it's not enough to ask whether you have the people—or even the right people. You also need to ask whether your people have the mindset to think about this opportunity in the right way.

Autodesk's Randy Swearer and Mickey McManus talk about this type of capacity in terms of bias. To be clear, we're not talking about the bias—unconscious or implicit—that pigeonholes people into stereotypes. Rather, bias can be a useful tool in thinking. “Humans have to be biased, because the world is a complex place,” Swearer told us recently. “Frankly, our brains are not all that powerful. Biases are a way that we simplify the world and make sense of it but being aware of them is tremendously important.”

McManus makes the point even more clearly with a familiar analogy. “If you have a piece of fabric, like corduroy, it's biased in one direction. You can slide your hand right down the corduroy in one way, but if you slide it 90 degrees, it's really rough and harder to slide. Bias is just a word used for basically creating a shortcut. It requires less energy,” he told us.

For us to channel and leverage biases, however, we need to become mindful of them. “We're very interested in thinking about ways to make people aware of those biases and understand the biases that they use to kind of see the world in the sense of making things, but also beyond making things, because it's so crucial today just to exist and to thrive in an environment,” Swearer says. “We feel like the tool itself needs to be, or I should say, the platform itself needs to be a learning platform that is giving people feedback constantly on the biases, even nudging them aware from their implicit biases.” When we apply this concept to technology, we see that technology, which we once needed to learn to use in order to simply work, now becomes something that we learn with and that we learn from and that, in fact, even learns from us. That's the power of digital transformation when tools and humans learn together.

Capability and Context: The Scissors Metaphor

Nudging people to be aware of their biases, as Swearer puts it, is all about context. Too often, we treat our companies as if they exist without context until something changes in the business environment that upends all our assumptions—our biases. It might be a change in the technology that breaks the business model, a change in the market conditions that shifts customer expectations, or a change in public policy that adds friction to the supply chain, for example. When these changes of context occur, it is helpful to step back and look at the relationships between the company and its environment, the worker and their team, the human and the technology tool.

McManus introduced us to the world of Herbert Simon, an American economist and cognitive psychologist who won the Nobel Prize for his concept of bounded rationality, essentially the idea that humans don't act as perfectly optimizing economic decision makers. Instead, the effectiveness of our decision making must be understood in context. Simon depicted his idea using scissors as a metaphor. One blade is our environment and the other is our capability to respond, what Simon referred to as our “cognitive limitations.”

“It's not like you can look at one blade and understand a pair of scissors,” McManus explains. “The interesting action of a pair of scissors is where the blades push against each other. One blade is the brain running these rules. It's got a limited amount of cognition … but it's pushing against this other blade that is the environment.”

To lighten our cognitive load, we rely on assumptions—biases—about the environment in which we're doing our thinking. “These biases are kind of shaped by the environment we're in, so we can actually help you see the thinking about your thinking,” McManus concludes.

If we keep this interplay in mind, particularly as we experience a whirlwind of change, the necessity of nurturing culture and expanding capacity becomes self-evident. Doing so in harmony becomes essential. Our role as organizational leaders, then, is to expand both human and machine capabilities and collaboration, while celebrating and protecting the organizational culture to optimize environmental conditions—at least internally.

In Accelerated Change, Focus on the Inputs Rather Than the Outputs

In an age when change came slowly and products and brands had long market lifecycles, an executive might be forgiven for conflating culture with brand and capacity with production. It's a mistake that brings a near-sighted focus to the business that often misses shifting context. Consider a classic example. Kodak was really good at silver-halide chemistry, which worked well for decades before digital transformation disrupted the photography industry. Unfortunately, the company had neither the capacity to reimagine how they defined themselves as a business nor the culture to pivot, which is ironic considering that Kodak invented the digital camera. Kodak invented and owned the intellectual property for the very invention that sank a $28 billion business. If Kodak had embraced the purpose in its “Kodak moments” motto and imagined a business beyond (and significantly bigger than) film and print imaging, the company might have endured. Instead the company that invented the digital camera in 1976 reached its pinnacle in 1996 with a $28 billion valuation and 140,000 employees, only to file for bankruptcy 16 years later in 2012.

Kodak, of course, is not alone; dozens of companies, for lack of a culture-capacity dynamic, withered in the face of digital transformation. Barnes & Noble struggles to compete with Amazon. Apple's iTunes sank the record business. Perhaps most famously Blockbuster fell to Netflix, the former plummeting from $6 billion annual revenue to bankruptcy in six short years. Countless retail outlets are failing in Amazon's wake, yet a few—like Target, Walmart, and Kohl's—are running innovative experiments to blend online and in-store shopping and, in the case of Kohl's, a partnership with Amazon for a competitive—dare we say it: adaptation—advantage. It's anyone's guess where those businesses will come out, but it's refreshing to see large organizations leveraging their capacity to evolve.

It is important to understand the distinction between capacity and capability. A focus on capability, rather than capacity, ties a company's success to a workforce hired to execute the specific tasks to produce a specific product. As change accelerates and product life cycles shorten, capabilities-focused businesses will find themselves stuck in the Sisyphean task of firing and hiring for new capabilities to meet the changing market context.

This “spill and fill” model of corporate capability sets companies on an unending chase for talent when they could otherwise be catching opportunity. Worse, it's incredibly disruptive to the workforce and business continuity across three measures: loss of morale and employee engagement among those who remain in the organization, loss of business momentum as new talent is onboarded and existing employees shift roles, and loss of the tacit knowledge often essential to business continuity as employees leave the company.

Tacit knowledge is exemplified by—and embedded in—the rituals of how companies work. It is where the “why” of work informs the “how.” It's the stuff you don't know if you don't work in an organization and it's the stuff that is so embedded in daily work habits that you would be forgiven if you forget to mention it to a new employee. Because tacit knowledge is the unwritten history and habits of a company, it is often impossible to regain once lost.

Whether tacit or explicit, knowledge is nearly impossible to codify and transfer fast enough to stay ahead of the waves of change. Instead, we can build capacity to learn and adapt by making on-demand learning an integral part of organizational culture. How, then, do strong leaders leverage culture and capacity to drive agile and adaptive learning companies?

Curiously, in a scalable learning world, the assets of an organization are measured not in what is produced, but by what an organization can learn. Randy Swearer at Autodesk sums up that idea nicely:

You've got these brains that are created at these companies. Those intelligences change over time, but fundamentally, that's all you have. Autodesk doesn't own any buildings. Autodesk owns very little. We lease everything. We're a 10,000-person company, but we lease everything. What Autodesk has is some computers and furniture. It probably rents a lot of the furniture, but basically what it has is talent.”

Becoming a Learning Company

Transforming any organization is a daunting, and often risky, endeavor. But it's possible. Many companies are putting the building blocks of scalable learning in place as they make their digital transformations, often without even realizing it. Whether it's the product or service you create or the methods and means used to market it, every digital interaction is a learning opportunity.

Few are doing this hard work as clearly as industry analyst Jeremiah Owyang, founding partner at Kaleido Insights. Owyang's consultancy works with Fortune 100 companies to navigate the challenging waters of digital transformation, creating and implementing strategy to make the crossing from the Third to the Fourth Industrial Revolution. Owyang identified seven components of the Digital Directive—modules, he calls them—that measure the maturity of a company's digital transformation. Each of the seven modules—strategy, data, customer experience, organizational alignment, analytics and AI, people and culture, and innovation—measures a series of specific attributes across all departments to arrive at a deep understanding of the company's ability to cross the digital divide.³

“Many companies talk about ‘digital transformation,’” Owyang writes on Kaleido Insights’ blog, “but use it in a limited fashion, such as just turning paper into PDFs or using web tools to communicate to customers, but in the end, the core culture, and even the business model, has changed.” The Digital Directive is a deep dive that provides a thorough diagnosis of the organization's progress toward—and roadblocks to—true digital transformation.

Not surprisingly, Owyang writes, “The most commonly overlooked item is the mindset of workers, managers, and leaders to be a ‘digital-first’ culture.” What's a digital-first culture? Owyang's answer echoes our own. It's a culture that is “making decisions based on data analysis, understanding how to harness information and data as a product, not just physical assets, rapid iteration, acceptance of failure as a means for progress, and developing a culture that is pliable and nimble.”

Most importantly, it is a culture that depends on shared values. “Teams have to be empowered to make decisions based on common vision and common values because in a digital-first company you are making real decisions in real time based on real time data,” Owyang told us. “A hierarchal culture won't work. You need to have the culture that works in real time.”

In some cases, the learning through data is obvious. In others, not so much. When you take a ride with Uber, for example, you are contributing to their mapping of human movement and their learning about traffic patterns and demands. When you use a Roomba robotic vacuum cleaner, you are helping the company create floor maps of homes to better inform smart home design and create better products. When you click on a sponsored story on Facebook, you are refining the algorithm that targets ads to you. When you engage in news stories on curated sites like Apple News and Flipboard, you are refining the type of content pushed to you in the future. When you ask Amazon's Alexa a question, you are building your customer profile for the sale of future products and services. When you drive a Tesla car, you are contributing to their fleet's learning network that seeks to improve future autonomous driving. And on and on.

In each of these cases, the “product” is a means to better understanding of the customer, the market, and future opportunities. The data becomes the basis of learning, which leads to new insights, which leads to new value creation through new products, and the cycle begins again (Figure 10.3).

Data provides transparency in creating information about things we previously could not see or measure—new patterns and insights emerge. As our friend and New York Times columnist Tom Friedman puts it, data allows us to digitize, sensorize, automatize, customize, prophesize, localize, optimize, and, we would add, visualize things we could not comprehend before. More succinctly, data allows us to learn.

The key to staying on top of corporate lists, then, is learning and adapting. And keep in mind that there is a clear distinction between flexibility and adaptability. Arizona State University organizational behavior professor Jeff LePine puts it best: “Flexibility is the ability to pivot from one tool in your toolbox to another or from one approach to another. Adaptability may require you to drop that tool and forge a new one or drop that method, unlearn it, and develop an entirely new one.”

Every company has the unique opportunity to learn from the market experience and the data afforded by their digital offerings. Every user interaction becomes a data point from which to learn. Indeed, the products themselves may be only Trojan horses to collect data from which they can learn.

Consider the Hierarchy Ladder of Business Intelligence, where the more you move up and to the right, the greater the value (Figure 10.4). Insights extracted from data are sufficient and necessary to improve products and services. To create new value by offering new products and services, those data-derived insights must couple with intelligence and wisdom—in other words, culture and capacity.