In his book on habits, Charles Duhigg recalls a now-famous speech Paul O’Neill gave to investors when he took over as CEO of the multibillion-dollar metals company Alcoa. The company, which makes the aluminum that goes into Coke cans and Hershey Kisses wrappers, among other products, had been struggling for some time while competitors stole away market share. Several new product lines had failed. Fifteen thousand workers had recently gone on strike, and the unions were angrily gearing up for another fight with the new CEO, who would surely focus on cutting more costs to fix the declining margins.

When O’Neill stepped to the podium for his first speech as CEO on an October day in New York City, the room was tense. Investors and analysts waited nervously, anxious to hear how the new CEO would fix Alcoa’s flagging profitability. But when O’Neill started talking, he didn’t mention revenue, costs, or profits. He didn’t mention the strikes. He didn’t talk about how he would fix the inventory problems or competitors stealing market share. Instead, he began by saying, “I want to talk to you about worker safety.”¹

The stunned room went silent.

As O’Neill started to elaborate on the dangers workers face, a few investors turned to look at each other quizzically. O’Neill persisted: “Our employees work with metals that are 1,500 degrees and machines that can rip a man’s arm off.”² He continued, talking about how he would make safety his number one priority. At the end of the strange speech, one of the investors asked about capital ratios. Another investor asked about excess inventory in the aerospace division. O’Neill responded, “I’m not certain you heard me … if you want to understand how Alcoa is doing, you need to look at our workplace safety figures.”

As soon as questions ended, the shocked investors rushed to the doors. One broker said he actually ran from the room to get on the phone, telling his twenty largest clients to sell their stock: “The board put a crazy hippie in charge, and he’s going to kill the company.” He now admits it was the worst advice he ever gave. Within a year, profits had hit record levels. By the end of O’Neill’s tenure, the value of an Alcoa investment was impressive: if you had invested $1 million in Alcoa the day O’Neill joined, by the time he left, you would have received another million in dividends, and your stock would have been worth $5 million.

What’s puzzling about the return on investment is why it would be so high when O’Neill seemed to be attacking something so peripheral to performance: safety. But O’Neill’s strategy was brilliant because it attacked the core behavioral bottleneck in the company—its habits and routines—in the language it understood and could accept (taking care of the workers). Alcoa had historically been more of a caretaker organization (see the later section “Tool: Organizational Nomenclature”). It took good care of its workers but, along the way, had developed inefficient processes, waste, and high labor costs. Trying to change these directly by demanding cost cuts, better margins, or labor reductions would be a challenge to the company’s core identity of taking care of its workers. Thus, a direct attack on these values would be like running a battering ram against the castle gate—it would bring the entire organization, tasked with taking care of the people inside the company, out to the proverbial walls to defend it.

Instead of attacking these cherished values, O’Neill subtly spoke in the language—or nomenclature—of these values, emphasizing the importance of safety in taking care of the employees, allowing them to accept the initiative he proposed, precisely because it matched their values. It was a stroke of genius because the safety effort itself was a Trojan horse to discovering and correcting massive inefficiencies that had built up over time. Later, reflecting on his experience, O’Neill describes his intent very clearly: “I knew I had to transform Alcoa. But you can’t order people to change. So I decided I was going to start by focusing on one thing. If I could start disrupting the habits around one thing, it would spread throughout the entire company.” O’Neill’s story illustrates a master stroke in transformational change because it uses a behavioral solution to a primary bottleneck in innovation and change—people’s habits. This chapter describes how you can use behavioral solutions to identify and break similar roadblocks to change in your situation.

The Need: New Tools to Break through Habit and Routine

From the street, the Neurons Building, Thomas’s headquarters, has an impressive eighteenth-century Danish building style. Largely brick, the building is part of an old military barracks where cannons and shells were once manufactured for European wars. But today the barracks hold racks of high-resolution EEG headsets, eye trackers, and servers crunching behavioral data. As one of the leading scientists at the intersection of psychology, neuroscience, and economics, Thomas has already done some of foundational research that helps explain how the brain drives our decisions.

For example, prior theories of the conscious and subconscious mind argued that consciousness operates like a light switch, either on or off. But one evening, as Thomas was reading the writings of the nineteenth-century psychologist William James, he was struck by a passage. James described the peculiar state of consciousness when you try to recall a forgotten name—a state in which there is a gap between remembering and not remembering. Thomas began to wonder, could the dominant view of consciousness be wrong? Could consciousness exist in a halfway state, neither fully conscious nor completely subconscious, and could such a state lead to this gap that James describes?

To test the theory, Thomas designed a series of experiments using functional magnetic resonance imaging (fMRI) brain scanning. In the experiments, Thomas and his coauthors flashed images past people and then examined the participants’ brain responses when they reported being aware, not aware, or partly aware of the image. The team found that, counter to the dominant view, consciousness is not an on-off switch, but rather a continuous process that involves the gradual engagement of different brain regions.³ More important, they found that the transition of a process to consciousness requires the engagement of massive brain resources and expansive regions of the brain.⁴ This huge global brain mobilization helps explain why we so often fall into biases in our thinking. The brain, in an effort to conserve energy, relies on intuition, subconscious feelings, and routines whenever it can, and this reliance often leads to very biased thinking.

Prior research has overwhelmingly shown the dangers of relying on this intuitive, habitual system. This system of thinking, labeled system 1 thinking by Keith Stanovich and Richard West, was popularized by Nobel Prize–winning psychologist Daniel Kahneman. System 1 thinking, which is intuitive and subconscious, while quick and efficient, also regularly leads us to make mistakes in calculation, judgment, decision making, and other important activities.⁵ To illustrate the power of these intuitive, routine, but unexamined judgments, in one experiment, a confederate (someone part of the team running the experiment) tried to cut in the line for a busy copy machine. If the confederate provided an unqualified reason (e.g., “Excuse me, may I use the Xerox machine?”), people in line said no. But if the confederate provided any kind of explanation, even the most silly (e.g., “Excuse me, may I use the Xerox machine because I want to make copies?”), people let the confederate skip the line. Why? Because their intuitive system of thinking is preprogramed to accept explanations for actions without challenging them, even when the reasons are completely illogical.⁶ Similarly, when tested, people almost always give the wrong answer to a simple mathematics question: “A bat and a ball cost $1.10. The bat costs $1.00 more than the ball. How much does the ball cost?” Most people answer $0.10 even though the correct answer is $0.05. Why? Because intuitively $0.10 is one dollar less than the total, and our brains land quickly on the intuitive answer. To think through the problem properly requires some thought, and we must recognize that if the ball costs $0.10 then the bat would cost $1.10, for a total of $1.20, which is more than the total in the question.⁷ These, and hundreds of other clever experiments, demonstrate the pervasiveness and power of the intuitive mental processes that reinforce habit and that can bias many of the decisions in our lives.

Of course, routines in and of themselves aren’t evil. They are created to save time and energy. But we rarely reexamine them, because once they have become so ingrained in our behavior, reexamination is costly. In fact, Thomas once explained to his students that bike riding habits are so ingrained that if you focus too much on turning the pedals, you can actually disable your system 1 thinking (habit) as system 2 thinking (analysis) starts to compete with it. The next day, one of his students came in with scabs on his palms and a bruise on his elbow. He explained, “I went ahead and tried it—paying attention to turning the pedals—and I fell off my bike!”

To make matters worse, the areas of the habitual system 1 thinking have a diabolic dual property that make changing habits even more difficult. Brain regions with obnoxiously difficult names such as the globus pallidus, putamen, and ventral striatum are deeply situated and not accessible through conscious thought or control. This means that we can never directly control our habits but must instead resort to indirect means. Furthermore, the same brain network has a more or less direct connection to the body’s movements, and thus the decisions occurring at this subcortical and subconscious level have a more direct route to action, sometimes circumventing willpower. Breaking habits requires either overcoming both the speed of subconscious choice and the lack of direct access to these processes, or another more subtle approach, like the one O’Neill used when transforming Alcoa.

The Process: How to Break Bottlenecks Using Decision Maps and Archetypes

Recently we worked with a major wholesale distributor of industrial parts (we’ve disguised the company and technology to comply with a nondisclosure agreement). One of the major problems for a distributor is the complexity of stocking and distributing hundreds of thousands of items. The company we worked with got a head start by using the process we described in chapter 2. The wholesaler used science fiction to envision a future in which drones would help workers keep track of inventory and deliver it for packing. Using the tools described in chapter 2, the wholesaler created a compelling narrative and then told the story using a comic book.

Despite the power of the narrative to encourage people to believe, there was still a great deal of work to get everyone mentally and emotionally behind the idea of drones in a closed environment with people. Although drones doing inventory may not sound so radical today, it wasn’t so obvious just a few years ago. For a moment, imagine the risks of being the first wholesaler to put drones into warehouses. What would happen if the drone injured someone, leading to multimillion-dollar settlements and a barrage of negative press? How would staff react to the idea of drones in warehouses potentially threatening their jobs? What would happen if the drone took incorrect inventory of a mission-critical part, causing unacceptable delays for an important customer?

Although our prior work gave the wholesaler some confidence that the transformation process could work, the hurdles for getting people on board with drones in warehouses created a major bottleneck. Resistance started to pop up from every corner, and for good reason. Routines established to protect the company from risks and uncertainty were being activated, threatening to stop the project before it even got off the ground. How, then, did the wholesaler move past these hurdles?

Before we created the narrative and the comic book, we spent some time conducting in-depth interviews. These interviews helped us understand the organizational nomenclature, or the type of organization and the language in which people talk about what they value and do. This understanding helped us to frame the narrative in the organization’s value language so that people could understand it more easily. We also created a decision map of the formal and informal decision structure inside the company. Thus, we had a sense of who sat in the key decision-making roles, especially the hierarchy not on the org chart. Moreover, we analyzed what made these people tick or, more accurately, what made them tick in their role in the organization and how they responded in that role to new things, called their functional archetype (which we will explain later in this chapter). This chapter is organized around the three action steps just described: (1) translate your ideas into the language that your organization speaks; (2) map how decisions are made to focus your efforts on those who matter most; and (3) understand what motivates these key decision makers, and orient your pitches to align with those drivers.

As we sized up the resistance to the drones project, we knew that, despite many potential bottlenecks, we had two priority questions to answer. First, who needs to say yes to get this project into warehouses? Second, how much effort should be expended to get a yes? (You can spend all your effort to win a battle, but still lose a war.) We could see that many key decision makers wanted proof that the drones were safe in the warehouses before authorizing them. But how could we prove that they were safe if we couldn’t get permission to get them in warehouses in the first place? Fortunately, one decision maker in our map was different—the CEO of a recent acquisition running a smaller network of the distribution center. Not only did he have full authority to put the drones in warehouses, but he was also wired a bit differently. He was more of a maverick. When we approached him with the comic book and shared the vision, he grasped it immediately and authorized an initial proof of concept. Breaking this small bottleneck to find an initial launchpoint for the project was the first step toward breaking the bottleneck in the rest of the organization.

Next, we had to figure out how to make the drones, since distributors have not historically been leaders in new technology. We visited every major drone company in North America and Asia. Most companies were so interested in their own projects that no one wanted to take on the project of a paying customer that differed from their own vision. In a classic innovation trap, the firms were so busy creating the solutions they thought customers wanted that they didn’t pay attention to what an actual customer—a major company—wanted to pay them to build. Thus, to get started building drones, the company had to find an uncommon partner, the kind of partner you don’t normally work with and that brings complementary capabilities to help you make a long leap. We found our uncommon partner, a startup working out of a poorly ventilated office space in Silicon Valley.

Before we arrived, the startup had been building high-power consumer drones, an effort that looked like an increasingly hopeless effort in the face of major competitors like DJI. But unlike their colleagues at larger companies, when we showed the comic book to the startup and told them we wanted to partner on commercial drones for distributors, they listened. They were willing to build on the concepts we had introduced in the story. Nine months later, the warehouse drone (WD-1) was flying around warehouses, reading RFID tags, scanning labels, and taking inventory for organized parts (parts that had been broken down out of their larger supply boxes into marked containers). Moreover, workers in the warehouse found that the drones saved them from the tiresome and frustrating task of continuously taking inventory, allowing them to focus on other, often more important tasks they had been putting off.

The speed with which we had made the narrative real, and our early success with the prototype drone, WD-1, enabled us to break a bigger, organization-wide bottleneck. During a trip to Silicon Valley, the executive leadership team visited several tech giants and then came together in a small auditorium at Singularity University (SU)—the Silicon Valley think tank and business incubator—to review the progress on their different innovation projects, including the drone project. SU had long been an important catalyst for many companies, helping them envision how the world is changing. The room was buzzing with energy after the recent visit to Google, just down the road in Mountain View. Everything seemed calm and relaxed on the front stage. But backstage, it was panic and terror. After staying up for two nights in a row, the startup team was desperately patching together the more advanced drone prototype, the WD-2 (capable of taking inventory with both parts broken down into clearly marked bins, assessing bulk packaged parts, and inventorying parts stored on both floor- and storage-shelf levels). At the last minute, the build team was literally duct-taping the drone together while the engineers double-checked the programming. Then, with a half-hearted thumbs-up, they signaled that the drone was ready to go, and the presentation started.

Most of the presentation summarized the progress of various incremental initiatives inside the company. When the time to present the drones project came up, the project’s head, Doug, stepped up and described WD-1’s early success. He presented the initial results, and the other executives began to sit up in their seats and ask questions about its limitations. Always the showman, Doug stopped the questions, saying: “Before we get too far, let me show you the next generation of what we are working on: the WD-2!” The curtains parted, and with a buzz, the drone whirred onto the stage. Doug described how the drone could read both unpacked floor-level inventory in bins and bulk-packed inventory on upper-level storage shelves with a high level of accuracy. The new drone would create radical savings in inventory accuracy and at an incredibly low investment relative to the savings. Moreover, it had multiple redundant systems to make it safe. The room went silent for a full five seconds. Then it exploded with enthusiasm. “Holy smokes,” “This is amazing,” “How did you do this?” ”How does it work?” One executive shouted out, “Why don’t we have this already?” From his chair, the CEO from the recent acquisition, the one who had initially authorized testing the WD-1, turned around, smiling, and defended the decision vigorously: “Because you didn’t want it? Remember?” Everyone laughed. The executive smiled back, “OK, well, I want it now!”

In that moment, with the proof on the table, the barriers big and small began to fall. Everyone was ready to put the drones in warehouses, and the project proceeded with few hang-ups thereafter. Although getting the commitment of the entire executive team may have seemed like haphazard good luck, it actually came about because we followed a very specific process designed to overcome the behavioral obstacles that distort and block decisions and action. The process involves applying the following four tools that help you get past these obstacles inside your organization.

Tool: Organizational Nomenclature

What kind of organization are you? This simple question can be surprisingly hard to answer and incredibly revealing. We recently sat down with a major apparel manufacturer, unrelated to Lowe’s, that had been designing work clothing with technology elements such as fabric that can read gestures to advance a song being played or to provide nudges about the route to follow. The entire team was incredibly proud of the innovation. But initial feedback from users was mixed. Secretly, several team members started to become nervous about whether the new products would be a commercial success. Eventually, they called us in to help them assess their trajectory and see new possibilities.

Given all the talk about science fiction, they had expected us to show up with a quantum computer or neural-network artificial intelligence (AI) on a thumb drive. But the first thing we did was ask a simple question: “What kind of organization are you?” For a moment, the team around the table—senior vice presidents, head of design, head of innovation, and others—hesitated. Then debate ensued. Every comment had an underlying theme of design, but no one said it aloud until we asked, “Are you are a design company?” Everyone nodded. We then asked the follow-up question: “What does that mean about how you make decisions? About what you value?” Everyone agreed that the company valued … well, design—the aesthetics of new apparel, creating new designs, or updating current fashions. Finally, we challenged them: “As you think about this new technology-laced product line, what are customers looking for?” There was another moment of silence, and then looks of recognition spread across their faces. Then we asked, “Do you actually know what customers are looking for?”

Although the team had been building what felt like science fiction—work clothing that could give you directions or let you answer your phone without touching it—when we went out and asked workers what they wanted out of their clothing, they frequently expressed something very different. Most workers found the clothing they wore to work uncomfortable, not durable, and uninspiring. Workers really wanted something simpler—durable comfort with a bit of style.

But changing the views of the team at the clothing retailer wasn’t as simple as returning and reporting that workers wanted something else. Initial conversations with some of the executives, led to typical responses like “They (meaning the customers) don’t get it.” Instead we had to recast the findings in the organization’s nomenclature—design. We went back to the executives and spoke about the design needs of workers and the opportunity to create a new design category—the urban worker design inspired by skate culture. Both recasting the findings in a nomenclature the company could understand and the awareness the leadership team generated when we discussed with them how much they value design helped break down the bottlenecks to a major product reorientation. When we packaged the new insights correctly, the leadership team was able to accept them and get to work designing a new line of work clothing: one focused on comfort and durability on the inside with a bit of hipster and skater on the outside. The new look and the resulting clothing line has been an incredible success.

Thus, the first step in breaking organizational bottlenecks is to recognize the source of the bias so that you can face it head-on, in part, by using the organization’s nomenclature, or the words that organization members use to reflect their values. If you try to persuade the members to see something new, but you are speaking a language they don’t value or use, they won’t hear you.

But as soon as you put the idea in terms they understand (e.g., designing comfortable clothing for workers), almost no matter how off-the-wall it may be, the idea suddenly becomes acceptable. One reason that O’Neill succeeded in transforming Alcoa was that he used organizational nomenclature (the focus on valuing workers) to address how to fix the company, rather than the aggressive language of cost-cutting efficiency. Alternatively, an organization’s nomenclature can reveal overlooked weaknesses that need to be addressed, as was the case for the clothing company we described. In many of the examples throughout the book, you will see the importance of this first tool: identifying and speaking the organization’s language to break up decision bottlenecks. (See “Digital Toolbox: Determining Your Organization’s Type” for more help on this challenge.)

How to Assess and Use the Nomenclature of the Organization

To use an organization’s nomenclature, you need to identify the true focus of an organization by paying close attention to the everyday details of language: job titles, how people explain what they do, how presentations are created, and so forth. The sidebar “Tools to Assess Organizational Nomenclature” lays out in tabular form how you can organize your assessment.

1.   Define what the organization values.   Ask, “What kind of organization are we?”

•   As you ask, “What kind of organization are we,” ask yourself further clarifying questions such as: When making decisions, which arguments are valued? Who gets promoted, and for what? What do our presentations look like (high text or high graphics)? What is emphasized on the earnings call? How do we describe our own jobs? These questions reveal what the organization values. For example, look at the job titles at Microsoft and Adobe. Although the two companies made similar products for decades, the majority of job postings inside Microsoft were described as engineering roles, whereas inside Adobe, they were described as design roles.

2.   Speak in the organization’s language.   Organizations respond to the language, values, and processes that match their archetype. Speak in the value language—the values and words the organization uses—to break through to people inside the company.

•   Conduct in-depth interviews with key people in the organization. Have them tell you stories. Notice the words they use. For example, “charged the mountain” tells you something different from “made the customers happy.” The stories they tell you also say a great deal about what they value and don’t value.

•   Check your nomenclature with someone you trust, someone who can give you honest feedback. For example, did you just use the name of a recently failed project?

In closing, use organizational nomenclature judiciously. Different groups inside, or outside, the organization may have different nomenclatures. Sometimes, the biggest source of resistance is simply aligning the different languages and making the translation between groups.

Tool: Decision Bottleneck Map

In 2017, one of the worst corporate security breaches exposed the personal financial information of millions of households in the United States and Europe. Ironically, although the security breach occurred via third-party software being used inside the company, the software vendor had released a patch to fix the breach the same day it was discovered. But almost four months later, Equifax still had not installed the patch, and the credit-reporting agency was hacked.

Why did it take so long to install a security patch? We can point the finger at Equifax, but we would be failing to see a bigger trend. As Mark Goodman, author of Future Crimes, argues, 95 percent of all cyber security issues are the result of human errors and problems, but only 1 percent of an organization’s security budget focuses on these human factors, with the overwhelming majority of the spending dedicated to mostly ineffective technological “solutions.” Goodman has argued that this very mismatch, between human behavior and technological solutionism, is at the heart of the exponential increase in cybercrime we are seeing around the world today.⁸

Then why did it take so long at Equifax to solve a simple problem? One answer has to do with how decisions are made inside most organizations, where information technology (IT) is seen as a support function or an afterthought rather than a core strategy function. Consequently, not just at Equifax, but at many companies, the investments, the hacks, and the security breaches really reflect how decisions are made.

As you think about your organization’s decision making, ask yourself which office is the most powerful in your organization. Most people would say the corner office or where the CEO sits. But they would be missing something critical. Although the corner office may be where we put the person with the highest rank, it isn’t necessarily where the most powerful person sits. Jeff Pfeffer, a Stanford professor and the author of several books on power in organizations, studied the question. He found that the most powerful locations in a workplace tended to be the offices near the bathroom and the watercooler. Why? Because the people in these offices can see everyone, speak to everyone, and know what is happening inside the organization. Although they may not be central in the formal hierarchy, their position at the center of the informal network provides them crucial information and power advantages.⁹ In a related vein, Tom Allen studied proximity and found that the chances of people in an organization interacting with someone thirty meters outside their habitual paths at work is extremely low.¹⁰ Instead, power in an organization has more to do with informal networks of people, shaped by their location as much as other forces such as formal responsibility.

These informal networks play important roles in decision making. Sometimes, the networks are visible and explicit. Other times, they are hidden and implicit, like whose office is near the bathroom. But you need to understand these networks to lead transformational change. Thus, one of the most important tools we use is nothing particularly special—we simply map the formal and informal decision structure to create awareness of how decisions are made. This tool may sound oversimplified or unworthy of attention, but too often, we assume that we know how decisions are made without understanding the full ecosystem of forces affecting our ability to transform. (The earlier discussion on folk theory gives one example of this lack of understanding.) To help you appreciate these ecosystems of forces, we suggest creating a decision bottleneck map.

How to Use Decision Bottleneck Maps

We call the map of how decisions are made in an organization the decision bottleneck map. To create one and use it, follow these steps outlined below.

1.   Map the explicit, formal decision-making structure. This decision-making structure may be the same as the organization chart, or it may be different. But it is the organization’s stated way of making decisions.

2.   Map the informal decision structure. This map describes how decisions really happen inside an organization. To discover this practice, get out and talk with people inside your organization. Ask them, “How do things get done around here?” or “Who is important in making decisions about X?” You may also ask about a time when a decision wasn’t carried out. Encourage people to elaborate: “Tell me why that didn’t go through as expected.”

3.   Map out the related influences on the key decision. Examine the support functions, like legal, purchasing, IT, or HR. Examine whether they will need to be involved in the decision and how.

As you build the decision bottleneck map, don’t obsess about generating the perfect map. The goal isn’t obsessive completeness. No one is grading you. Just focus on the important pieces and look for the moments of insight, however small, that the map is designed to uncover. For example, you may suddenly realize that “Bob” is the bottleneck on many decisions, even though he sits on the side in IT. When you realize this, you can ask, “What does Bob want?” and start to make progress breaking down this barrier. We have found that this simple tool, combined with the narrative, has incredible power to start and sustain transformation. Understanding the bottlenecks helps you know where to focus, and the narrative can help you win allies and enthusiasm.

But as you work with the decision bottleneck map and pay attention to the individuals in these bottlenecks, an analysis of each individual could become a burdensome chore. Rather, focus on the battles you need to win, and then unpack the functional archetypes of this smaller set of individuals, which will allow you to streamline the analysis to have maximum effect.

Tool: Functional Archetypes

One of the toughest bottlenecks we’ve ever dealt with was convincing a major electronics retailer to put robots in stores (the company and technology have been disguised to comply with a nondisclosure agreement). Although Lowe’s had already successfully tested robots in stores, the head of the innovation lab at the electronics retailer applied the transformation process and discovered a different future: one in which robots could change the face of electronics retailing. For example, robots could assist by guiding customers around the store, giving them advice, helping them make decisions, and potentially even helping them put electronic systems together. (Envision a robot that could potentially assemble a smart home system of compatible products or even build a custom computer on the spot.) This kind of near-omniscient assistant could be both a disruptor of electronics retailing, with the ability to understand how the vast ecosystem of electronics products can work together in an increasingly integrated world, and a defense against low-cost online retailers because the robot would be able to provide deep insight and assistance in assembling systems unattainable from retailers like Amazon. Unfortunately, although executives had been excited about the project and given it a green light to proceed, the legal team had significant reservations that led to persistent delays.

Out of fairness to legal, you can imagine the concerns they might have. What if the robot injured someone in the store? Scared people? Led to resistance from people afraid they might lose their jobs? Gave improper advice to a customer, leading to poor reviews or an improperly functioning system? Assembled hardware that violated a manufacturer’s warranty or patent? The objections were endless. Not surprisingly, both the legal and the risk teams became major bottlenecks to progress.

Meanwhile, in her eagerness, the head of the innovation lab, Natalie, had hired expensive roboticists and coders and begun building robot prototypes. Although the prototypes were under development, more meaningful progress had been held up by the inability to test in stores. At every turn, Natalie tried to push the legal team to approve the robots. But month after month, meeting after meeting, discussions with the legal team went nowhere.

Finally, in a moment of reflection, Natalie realized she hadn’t been following two key steps of the transformation process itself. First, she wasn’t using the strategic narrative to share the company’s vision of the future with the legal team. And second, she hadn’t used the functional archetype tool to identify the legal department’s strategic role in the company’s transformation. As we describe in more detail later in this section, a functional archetype is a quick way to describe people’s motivation for acting the way they do.

To remedy the situation, Natalie first took a closer look at the legal team. Although it was composed of many individuals in a rather tight-knit group, its functional role at the electronics company could be described as the caretaker archetype. Caretakers see their role as protecting the organization from threats and preserving the status quo. For caretakers, the robot in stores represented a massive threat. When Natalie had initially approached them, the legal team had considered her an attacker on the stronghold of their responsibility. Realizing that this adversarial relationship was not the way to persuade people, Natalie called a meeting with the legal team.

Reluctantly, the group assembled, with a few members arriving late. Around the room, the energy was low. People leaned back in chairs or typed away on their phones. Natalie cleared her throat. “I know we’ve been going in circles on this,” she said, “but would you folks humor me a bit? Could we read the story that prompted all this in the first place? It’s in a comic format, which I know isn’t exactly a standard legal document, but it works well for telling the story. Could we read it first, then talk?” Natalie passed around the comic book, and people slowly started to thumb through it. As the team read, she could see people lean forward in their chairs or look more intently at the pages. The mood in the room started to change. As they finished reading, Natalie said, “The comic really just tells a vision of some of the things we could do at this company.”

Then she did something critical—she reframed what she was doing in a language caretakers could appreciate: “But it isn’t the only way. The really important thing is that the world is changing quickly around us, and how do we protect the company in the long run? By keeping up. I want to protect the company—nobody wants a big legal battle—but if we don’t do anything, the company itself is in danger. As retail is changing so quickly, the big risk is doing nothing.” Then she flipped the conversation around. Instead of treating them like service providers, she spoke to them as strategic partners: “I’m not saying that this is the only way to go or the only way to do it, but I need your help to figure out what’s possible. Can you help me work out what we can do and what we can’t do, so we don’t become irrelevant in the future?”

The conversation that ensued totally surprised her. One team member spoke up. “Well, we could do this,” one person said, describing one idea. Another jumped in and said, “This seems like another case that worked. We could draw on the precedent in that case.” Soon other team members chimed in with ideas. The suggestions popping up drew on an impressive breadth of legal knowledge and proved thoughtful, usefully creative, and, quite frankly, brilliant.

The legal team left the meeting discussing how to make the robotics project work. And after months of zero progress, in just a few weeks, the team put together an opinion that paved the way for a groundbreaking perspective on robotics in retail operations. The legal framework proved so valuable that it represents one of their trade secrets.

Moreover, the legal team turned from seeming adversaries to powerful strategic partners. Afterward, the risk team and legal team members became some of the innovation lab’s biggest advocates inside the company. (And when you get risk and legal on your side, that’s really saying something!) Most important, the experience helped the legal team at the electronics company transform as well. Developing the ability to see what is possible, rather than what is impossible, has become part of the legal team culture at the company. In one particularly memorable moment, as Natalie walked past a new recruit being introduced to the legal team, she overheard something that brought joy to her heart. “Rachel,” the legal team member said, “working here is going to feel different than anything you have done before. And that’s a good thing!” It is a good thing. The electronics company was making a profound transformation both in terms of what they offered to customers and how it operated.

How to Use Functional Archetypes

One tool we recommend for breaking bottlenecks is to assess the functional archetypes of the people you are trying to work with. Before we dive into functional archetypes, we have to ask, What drives behavior? The answer is that a thousand things influence human behavior. Sometimes, people simplify these thousand things into nature or nurture, but even this dichotomy starts to break down under the scrutiny of imaging genetics, a new field that lies at the intersection of genetics and neuroscience. The field of imaging genetics explores how your genetic traits combine with your experiences to shape your decisions. For example, about 20 percent of the population has the gene for a particular serotonin transporter that leads to an excess of serotonin, an important neurotransmitter, at the synapse (the place where two neurons meet). Having this gene will lead you to be more anxious and more loss averse. Combine that with a personal history in which unsettling things happened with no warning, and you are likely to become risk-averse.¹¹ This is not to say that you have no choice in becoming risk-averse, but you do have a higher likelihood of becoming risk-averse than does someone without that gene but with the same life experience.

Why share this example? Simply to acknowledge that why and how we make decisions are probably best mapped out as probabilities shaped by complex interactions of genes, history, learning, context, and many other factors. But mapping these complex forces makes for an unwieldy way of understanding the world. Fortunately, in a world before neuroscience, imaging genetics, or personality scales, observers of human nature roughly categorized the roles people play in terms of archetypes. Often forming the backbone of many powerful stories, archetypes underlie some of the most influential early studies in psychology.¹² Although these archetypes are grossly oversimplified, in many ways, modern psychology and neuroscience still support the mechanisms for how these archetypes work (see “Master Class: Neuroscience, Archetypes, and the Real World”).

We use archetypes as shorthand for describing the reasons that some people act the way they do in their functional roles and how to persuade them when change is required. For example, in the story about the legal team at the electronics company, we highlighted several critical elements relevant to breaking bottlenecks. For example, as we examine more closely later in the chapter, we turned insiders into uncommon partners rather than seeing them as a means to an end. More importantly, the story describes how recognizing a core archetype in organizations helped us overcome the bottleneck. In the electronics company case, the people in the legal team weren’t being difficult. They were just doing their jobs. They saw themselves as caretakers, tasked to protect the company from risks.

Whenever you approach a caretaker with a big, risky initiative, the person will, without realizing it, find ways to deflect or reject it. To work with a caretaker, you need to reframe the initiative so that it fulfills the caretaker’s role. Working with the legal team on the robotics proposal, Natalie reframed the situation in the language of a caretaker. She argued that as the retail world faces increasing threats of disruption, the real risk was sitting idle and doing nothing. Finally, she used the strategic narrative to motivate the team members on what was possible and asked them to help us take care of the organization. The bottleneck broke immediately.

Below we describe how to use individual archetypes to break down barriers in your organization.

1.   Identify the functional archetypes of the individuals in your bottleneck map. Classify the individuals who sit in key decision points in the bottleneck map in terms of their primary functional archetype (the role they play in that position). For a list of key archetypes, see table 3-3. Don’t waste time endlessly mapping out every archetype onto every individual in the organization or debating exactly which archetype someone is. Instead, focus on the bottlenecks necessary to do your work and then focus on these.

2.   Classify your own archetype. Be careful about how you are perceived. Often, innovators or transformation leaders are seen as thieves (they steal time, money, focus, or turf from others in the organization) or tricksters (they aren’t really doing anything productive for the organization). If you are seen this way, the image can damage your ability to get things done and you may need to reshape your archetype. When Kyle discovered the utility of functional archetypes, he purposefully reshaped his image as the magician (the magician always delivers some tangible, useful magic). He already looked the part and, most importantly, he always came to every meeting with some magic: a new technology, device, or insight he could pull out of his backpack. The gifts he brought underscored his role as a magician.

3.   Discover what the other archetypes value. Use the language of the archetype you are working with, and work toward their values. For example, when Natalie talked about putting the first drone into a warehouse, the CEO valued boldly carving new territory. This awareness of his functional archetype helped her win his support. Later, when it came time to convince other leaders, her knowledge of their different archetypes helped her break through the decision bottlenecks by delivering the things they valued to them.

Master Class: Neuroscience, Archetypes, and the Real World

Why do some children who are traumatized during childhood go on to become violent offenders whereas others live out peaceful lives? Is it just a matter of choice? As one of us (Thomas) argues in “How Genes Make Up Your Mind,” people need to go beyond the binary nature-nurture debate of the human mind.¹³ Decisions are the result of a mashup between our genes, life history, and learning. With the advent of imaging genetics we are getting much closer to understanding the underlying causes of our behavior.

Today, the age-old answers of who we are and why we have a certain personality trait are becoming more tangible than ever. For example, if one child exposed to a traumatic event has a certain variant of the so-called MAO-A (monoamine oxidase A) gene expressed, then the probability of his or her turning violent is quite high, whereas the child experiencing the same thing with a different version of the MAO-A gene is unlikely to become violent. Likewise, a person who has the “bad” version of the MAO-A gene but is not exposed to trauma is not more likely to develop aggression.

These forces affect major life courses just as much as they affect small decisions. For example, in another study, Thomas and his colleagues used fMRI brain scanning to understand how we are affected by cues when we are making social judgments and decisions.¹⁴ First, they showed that, by framing an exercise a certain way, the researchers could change how people played the famous prisoner’s dilemma game (where people have to decide whether to rat out a colleague in another prison cell in exchange for better treatment). On average, 61 percent of people would collaborate with their coconspirator if they were told it was a cooperative game, compared with a 29 percent cooperation rate if they were told it was a competitive game.

But these figures are just the averages! The real force explaining who cooperates and who does not is actually the relative engagement of the social area of the brain, sometimes referred to as the mentalizing network because it is engaged whenever we are thinking about others’ states of mind. People who scored higher on an empathy test showed faster response times to social cues, were better at predicting what their coconspirators were going to do, and showed increased activity in the brain’s memory and emotional regions. Most important, people with greater empathy scores made up the gap between the competitive and cooperative states—more empathetic people were the ones switching to play collaboratively during a cooperative game. This suggested that individual differences in the level of empathy could explain why some people were faster and more accurate at navigating social decision environments: their brains were more acutely tuned to think and act fast. Participants with greater empathy explained the increase.¹⁵

Although we have used archetypes as shorthand to describe people’s roles in organizations, one could better represent their behavior with scales that show the probability of certain choices. Moreover, although these scales are shaped by people’s genes, they are also deeply affected by life history and learning. For example, Thomas’s research team developed a creative-potential test battery, which is based on a set of creativity scales, and then showed that simply explaining the neuroscience elements of creativity to people increased their creativity by 30 percent on average (a range of 15 to 200 percent).¹⁶ In the future, it will be possible to go beyond creativity and instead develop a set of scales that predict probabilistically how people will respond to forces such as persuasion, framing, and decision making based on their genes, life experience, and related factors. The corollary to these predictors would be a set of scales to understand your own behavior as well as a set of tools to help amplify or counteract these natural tendencies. In other words, we could increase the power you have over the choices you make and your ability to influence others.

Caveats and Alternatives: A Major Rule—Don’t Tell Everyone

Although we talk about becoming aware of the archetypes of the decision makers who become bottlenecks, we do follow one important rule: don’t tell everyone what you are doing. In fact, we encourage you to tell as few people as possible about what you are doing. Why? First, the more people you tell, the greater the number of people who want to get involved, inject their own opinions, and ultimately slow the process down. You will have to involve people and key functions at different points, and later in the book, we’ll share some ideas on how to involve them. But don’t involve everyone from the start. Second, the more people you tell, the greater the likelihood that you start setting high expectations for what you will accomplish (see “Master Class: The Dangers of Setting and Revising Expectations with Narratives” in chapter 2). Setting high expectations among a large group of onlookers can be very dangerous since in anything truly transformational, there will be a great deal of uncertainty and ultimately there will be change. You want to preserve your flexibility to adjust as needed.

Tool: Bottleneck Breakers

Ultimately, breaking bottlenecks comes down to identifying the functional archetypes of the key decision makers and then delivering to these people whatever they need to join you in creating transformational change. This approach may sound a bit jaded, but it isn’t—we just recognize that organizations are made up of people, most of whom are trying their best to play the role they think they should play. So you need both to help them play the role well and to see their role in a new way. There should be nothing inauthentic or deceptive in your attempt to clear roadblocks to a transformation. You should be earnestly trying to help everyone achieve the best collective outcome. To this end, we’ll share a couple of favorite bottleneck breakers. Although the list isn’t exhaustive (some we even share in other chapters), it covers several tools you can use both inside and outside the organization to get past these barriers.

Third-Party Digital Arbiter

Recently a major retailer ran into a perplexing mystery (identities have been disguised). Consumers suddenly seemed to stop buying a major product: oranges. The result was massive overstocks. No one could figure out the sudden change. Had customers changed their preferences? Was it a pricing issue? An advertising issue? The puzzle persisted until a junior manager (nicknamed Kate) at the organization did some simple data analysis comparing sales trends over multiple years with various Google search terms. Kate discovered an obvious phenomenon that everyone had overlooked. When a series of successive flu seasons had led to an increase in orange sales, everyone had assumed the surge in sales was a long-term trend. In fact, it was only the result of a compounding series of flu seasons! Because the data was so self-evident, no one argued with the findings. Instead, leaders just mobilized to take the next step.

The experience with the power of data to uncover behavior patterns and eliminate unproductive politics sparked Kate’s curiosity. The retailer where Kate worked had an area of the store dedicated to new items not sold as part of the regular inventory. She began to wonder if there might be hidden patterns in this area of the store as well. Taking the data on sales, she began to look for patterns, for example, items that few people tried, but that they loyally repurchased (low trial, high repeat purchase). She quickly discovered problems in the way items were displayed, packaged, or sold. Using the data to uncover and then talk about a problem took much of the venom out of potentially contentious debates. Instead, the organization could spend its energy on solving the problem. What Kate discovered was the power of data linked to behavior to generate insight and to arbitrate challenging political debates.

We recently had our own experience using data as a third-party digital arbiter to break bottlenecks in another setting. A major retailer had been trying to optimize its light bulb sales for years. Because powerful suppliers like Philips and GE fought (and sometimes paid) for shelf space, the lighting aisle was arranged by brand. But if you have ever walked into a big store looking for a light bulb, you know by experience how unhelpful this arrangement can be. A $1 light bulb may be sitting next to a $25 light bulb, both of which are different from the actual bulb you are looking for. Although it might make sense to arrange light bulbs differently, doing so was a major political issue. But as customers grew more confused with every increase in choice, we proposed a simple experiment. We tested two alternative arrangements for light bulbs: one with the bulbs arranged by price and the other arranged by type. After gathering the data on sales, we then used a simple machine-learning algorithm (the free software tool TensorFlow) to parse the resulting data and create an optimal model.

Which of the three layouts—brand, price, or type—do you think was the optimal for generating sales? None of them! The algorithm suggested that the optimal layout would draw on a combination of the price and type layouts (and nothing from the brand layout). Using the data and the machine learning led to a productive discussion, with the data as a third-party digital arbiter of the argument. We could discuss whether the model was right, not whether individuals were right. We then retested the new model in stores to continued success.

The experience illustrates the power of data as a bottleneck breaker. Big organizations love data, particularly quantitative data. They love data over time even more, especially data trends (hopefully, improving data trends). But combining data with models that describe how to use the data may be even better. Instead of arguing about who was right, the model becomes a third-party digital intermediary to take the venom and politics out of an issue and instead to encourage a discussion about whether the model is right. If you then combine this data with applied neuroscience (discussed in chapter 4), you can truly understand what the data is saying.

Turn Abundance into Currency

How did Lowe’s, the DIY retailer, get some of the world’s leading tech companies, such as Google, Microsoft, and Lenovo, to work with it? And how did Lowe’s persuade these companies to trade significant development resources in exchange for what they really wanted? The key to getting this kind of access and value was to turn Lowe’s overlooked abundance into currency. Let us explain.

As humans, we tend to overvalue whatever we have little of and undervalue what we have in abundance. Among the many resources Lowe’s had undervalued were the thousands of stores that host millions of customers each week, each person walking in with an unspoken social contract that he or she wants to learn and is willing to engage. The eagerness of abundant customers proved an ideal environment to test ideas with them. The turning point came when Lowe’s learned to take this initial abundance and convert it and other sources of abundance the retailer had created (data, digital-imaging capability, etc.) into currency to build true partnerships that money can’t buy.

Every company has some abundance that could somehow be eventually turned into currency. Look for your sources of abundance—the things you have but possibly undervalue. For example, physical locations can be chances to learn from customers or can become distribution platforms, sales outlets, space for partners, rentable square footage, and more. International locations can provide you greater flexibility in testing new technologies or a space off the radar to explore ideas. Language capabilities can give you local access that partners crave or can never imitate. Other companies have an abundance of customer understanding, and yet others have an abundance of data—a richness that they just don’t recognize. Even companies that think they have no abundance often can find it or create it. For example, when Kyle combined the Lowe’s testing environment with the data generated using applied neuroscience tools, the combination of assets and capabilities multiplied the value of the retailer’s abundance.

Turning Insiders into Uncommon Partners: The Justice League

One good way to handle internal resistance is to find other initiatives in your organization to tag-team with. At the electronics company mentioned earlier, we discovered a way to do just that—ultimately converting a potential source of resistance, IT, into an uncommon partner. Although the head of the innovation lab, Natalie, had received executive approval to scale up the robotics concepts after some very promising proof-of-concept work, she was having trouble connecting with IT to get started on the project.

In one meeting, Natalie explained the robotics and some of the IT needs to scale it up, including the ability to link the robotics systems into the ever-evolving database of products sold and their characteristics.

The IT director just shook his head in silence. Finally, he said, “I can’t do it. It’s not in the road map.”

Natalie paused. “Yes, but at the CEO staff meeting, they approved scaling this up.”

Continuing to shake his head, the director replied, “It’s not in the roadmap. It would take a totally different system and budget that I don’t have.”

By the end of the tense meeting, Natalie and the director were no closer to a resolution, and the director suggested she check with the e-commerce department for available resources. Natalie began to wonder what could be done.

At the same time, the business development organization within the company was continually looking for the right approach to successfully build new initiatives that could scale into the core of the business. The head of the group asked Natalie for a recommendation on how the innovation lab team might approach this problem. Because we had been working with Natalie, we suggested that she form a cross-functional team similar to DC Comics’s Justice League team. In the Justice League series, rotating casts of superheroes come together to solve a single problem. Afterward, they disband and reassemble in different combinations (for one challenge, it may be Wonder Woman and for another it may be Superman). The Justice League would be a team of “superheroes” from each function—people who, working together, could tackle this problem and make more progress, faster?

In the first embodiment of the Justice League, Natalie visited each of the major functions. She shared the robotics story, showed the latest prototypes, and then asked for their help: “This company has the chance to redefine the future of electronics retailing. But we need your help figuring out how to do it. We want to create a team of our best to define a sixty-day sprint to figure out if and how to turn our vision for robotics into reality. Since this is critical to everyone in the company, could you nominate the high potentials who should be part of the team? We are calling the team the Justice League, and just like in the movies, they are the heroes who can define the future. This is an initiative that has support from the top executive team and it is a major honor to participate.”

As recommendations started to trickle in from different parts of the organization, Natalie worked hard to make the Justice League a high-profile, prestigious assignment. She gave out T-shirts, figurines, and “Justice League” bags. In short order, Natalie assembled a team of high potentials from each of the major functions. She then took the newly formed Justice League team for an off-site to define the sprint about what to do next. At the end of the off-site, the high potentials from each function presented their recommendations. Because the Justice League was composed of a cross-functional team of high potentials, suddenly, the initiative was not just an innovation lab project. It was everyone’s project. As the Justice League team stood and presented, the executives in each division took note. These were their best and brightest, and their ideas were quite good and grounded in the realities of each function.

Why did the Justice League program work? It worked, in part, because it created uncommon partners out of internal functions. Sometimes it’s easier to collaborate with the National Aeronautics and Space Administration (NASA) than it is to work with someone you don’t know in another function. The Justice League turned the functions we normally treat like supporting actors into partners and made it easy to collaborate. It also worked because the participants, like the comic-book Justice League, used their special skills in harmony to solve a critical puzzle. The program also created prestige and motivation for the participants. Being on the team was framed as a significant honor and one of the few indicators that someone was a high potential. Moreover, the participants received visible symbols of their participation, so the best people felt highly motivated to be a part of it. Finally, the program worked because, at the end of the week, the high-potential people inside a function recommended to their own function what should be done. The high potentials in accounting were presenting to the accounting executives just as the high potentials in IT were presenting to their own function’s executives. By creating partners out of critical functions, you can break down overwhelming barriers to transformation.

Speak the Value Language

The power of speaking the same language of the group we are trying to influence is worth mentioning again. Too often, we forget to speak in the value language of the resisting group. When O’Neill spoke to Alcoa about taking care of workers, he was speaking in the organization’s value language. When Natalie spoke to the legal team about protecting their company, she was speaking in its value language.

So how can you learn to speak an organization’s or individual’s value language? Try this. First, identify someone who is your adversary or who is in your way. Next, ask yourself, what do people like this want? Ask yourself not what you want them to do, but what their incentives are. What is driving these people? Finally, ask yourself, How do I communicate what I am trying to do in terms of their incentives? In the electronics company legal team case, the team saw its job as protecting and advancing the company’s interests, so we reframed our transformation efforts by helping the team members see that it is a risk not to take risks.

Reframe the Purpose

Framing means recasting an idea or activity with the words you use to describe it, and the choice of framing can completely change how people make decisions. The importance of framing is not new news. We’ve been talking about this already. But rarely do we appreciate how much framing can change our decisions. For example, behavioral economist Daniel Ariely describes how when people are given the choice of purchasing a trip to Rome or to Paris, about half of the people will choose Rome and half will choose Paris. But when the choice is framed as an easy comparison between purchasing a trip to Rome, a trip to Rome with breakfast included, and a trip to Paris, most people will choose Rome because it is easier to compare the value of Rome with breakfast and without breakfast.¹⁷ Not only can framing change the way we make decisions, but framing can also even override deeply held values, such as political beliefs. For example, in a recent experiment by Oberlin professor Paul Thibodeau and his collaborator Lera Boroditsky, participants were told about a crime wave affecting the city and were asked how to deal with it. For half the participants, the crime wave was described as a “beast preying” on the city, and for the other half, it was described as a “virus infecting” the city. Although every other piece of information in the dossier was identical for the two groups, that simple metaphor (beast versus virus) overrode people’s native political views about how to deal with social problems like crime. Those in the “beast” category overwhelmingly prescribed more punishment for crimes, and those in the virus category prescribed more preventative measures.¹⁸ In short, framing has immense power. As you seek to create a transformation, we strongly recommend that you frame your purpose to match the goals of the archetype you are working with.

Making the Transformation Tangible

We are all unduly persuaded by tangible artifacts or small wins. In chapter 4, we will talk about the artifact trail, whose goal is explicitly to make the transformation tangible. But making ideas tangible is so important, it needs to be called out separately from the artifact trail. It is no accident that Elon Musk, who struggled to get NASA’s attention, later won billions of dollars in NASA contracts after he drove the first Space X rocket across the country and parked it in front of FAA headquarters during its centenary celebration of the Wright Brothers. The attendees seeing the rocket with their own eyes made them believers!

We recommend using as many tangible artifacts and small wins as possible—they will help remove barriers. What do we mean by tangible artifacts? Start small, and eventually think big. The comic book is a tangible artifact. So are the prototypes. So are partners signed up to help you. So is progress on the future KPIs you will create in the next chapter. When the three of us are trying to break a decision bottleneck, we are always leaving bits of technology sitting out on our own desks and dropping it off to others to show them what is possible and to make it real. We also try to accumulate small wins—small proof points, bits of positive feedback, connections to prestigious partners, awards, or any other achievement to help the doubters believe what is possible.

Summary

We opened this chapter by describing the power of routine to create bottlenecks in the organization. We then described the tools we use for overcoming these barriers. The tools involved first identifying the organizational nomenclature—what the organization values (although few people probably ever talk about this out loud). With this self-awareness, you then create a decision bottleneck map that describes the formal, informal, and supporting decision-making structure in the organization. Next, you identify the functional archetypes of the individuals who can block the transformation effort so that you can understand how to influence them. Finally, you consider how to apply a bottleneck breaker, of which several were described.

In describing the process we followed, we meant only to provide tools designed to counteract the biasing force of habit. Our list of tools is not exhaustive or fail-proof. Use your own judgment about how and when to best use these tools. For example, in chapter 4, we describe how to use applied neuroscience to generate the kind of data that executives, customers, or partners won’t or can’t tell you. This data can also be fundamental to addressing barriers to transformation. So although we describe our overall transformation process using three discrete steps—strategic narrative, breaking bottlenecks, and using fKPIs for creating the future—don’t be afraid to use the tools in the order that helps you create transformational change.