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We often think that collecting as much information as possible will help us make the best decisions. Sometimes that’s true, but sometimes it hamstrings our progress. Other times it can be flat out dangerous.
***
Many of the most successful people adopt simple, versatile decision-making heuristics to remove the need for deliberation in particular situations.
One heuristic might be defaulting to saying no, as Steve Jobs did. Or saying no to any decision that requires a calculator or computer, as Warren Buffett does. Or it might mean reasoning from first principles, as Elon Musk does. Jeff Bezos, the founder of Amazon.com, has another one we can add to our toolbox. He asks himself, is this a reversible or irreversible decision?
If a decision is reversible, we can make it fast and without perfect information. If a decision is irreversible, we had better slow down the decision-making process and ensure that we consider ample information and understand the problem as thoroughly as we can.
Bezos used this heuristic to make the decision to found Amazon. He recognized that if Amazon failed, he could return to his prior job. He would still have learned a lot and would not regret trying. The decision was reversible, so he took a risk. The heuristic served him well and continues to pay off when he makes decisions.
Decisions Amidst Uncertainty
Let’s say you decide to try a new restaurant after reading a review online. Having never been there before, you cannot know if the food will be good or if the atmosphere will be dreary. But you use the incomplete information from the review to make a decision, recognizing that it’s not a big deal if you don’t like the restaurant.
In other situations, the uncertainty is a little riskier. You might decide to take a particular job, not knowing what the company culture is like or how you will feel about the work after the honeymoon period ends.
Reversible decisions can be made fast and without obsessing over finding complete information. We can be prepared to extract wisdom from the experience with little cost if the decision doesn’t work out. Frequently, it’s not worth the time and energy required to gather more information and look for flawless answers. Although your research might make your decision 5% better, you might miss an opportunity.
Reversible decisions are not an excuse to act reckless or be ill-informed, but rather are a belief that we should adapt the frameworks of our decisions to the types of decisions we are making. Reversible decisions don’t need to be made the same way as irreversible decisions.
The ability to make decisions fast is a competitive advantage. One major advantage that start-ups have is that they can move with velocity, whereas established incumbents typically move with speed. The difference between the two is meaningful and often means the difference between success and failure.
Speed is measured as distance over time. If we’re headed from New York to LA on an airplane and we take off from JFK and circle around New York for three hours, we’re moving with a lot of speed, but we’re not getting anywhere. Speed doesn’t care if you are moving toward your goals or not. Velocity, on the other hand, measures displacement over time. To have velocity, you need to be moving toward your goal.
This heuristic explains why start-ups making quick decisions have an advantage over incumbents. That advantage is magnified by environmental factors, such as the pace of change. The faster the pace of environmental change, the more advantage will accrue to people making quick decisions because those people can learn faster.
Decisions provide us with data, which can then make our future decisions better. The faster we can cycle through the OODA loop, the better. This framework isn’t a one-off to apply to certain situations; it is a heuristic that needs to be an integral part of a decision-making toolkit.
With practice, we also get better at recognizing bad decisions and pivoting, rather than sticking with past choices due to the sunk costs fallacy. Equally important, we can stop viewing mistakes or small failures as disastrous. Instead, view them as information that informs future decisions.
“A good plan, violently executed now, is better than a perfect plan next week.”
— General George Patton
Bezos compares decisions to doors. Reversible decisions are doors that open both ways. Irreversible decisions are doors that allow passage in only one direction; if you walk through, you are stuck there. Most decisions are the former and can be reversed (even though we can never recover the invested time and resources). Going through a reversible door gives us information: we know what’s on the other side.
Some decisions are consequential and irreversible or nearly irreversible – one-way doors – and these decisions must be made methodically, carefully, slowly, with great deliberation and consultation. If you walk through and don’t like what you see on the other side, you can’t get back to where you were before. We can call these Type 1 decisions. But most decisions aren’t like that – they are changeable, reversible – they’re two-way doors. If you’ve made a suboptimal Type 2 decision, you don’t have to live with the consequences for that long. You can reopen the door and go back through. Type 2 decisions can and should be made quickly by high judgment individuals or small groups.
As organizations get larger, there seems to be a tendency to use the heavy-weight Type 1 decision-making process on most decisions, including many Type 2 decisions. The end result of this is slowness, unthoughtful risk aversion, failure to experiment sufficiently, and consequently diminished invention. We’ll have to figure out how to fight that tendency.
Bezos gives the example of the launch of one-hour delivery to those willing to pay extra. This service launched less than four months after the idea was first developed. In 111 days, the team “built a customer-facing app, secured a location for an urban warehouse, determined which 25,000 items to sell, got those items stocked, recruited and onboarded new staff, tested, iterated, designed new software for internal use – both a warehouse management system and a driver-facing app – and launched in time for the holidays.”
As further guidance, Bezos considers 70% certainty to be the cut-off point where it is appropriate to make a decision. That means acting once we have 70% of the required information, instead of waiting longer. Making a decision at 70% certainty and then course-correcting is a lot more effective than waiting for 90% certainty.
In Blink: The Power of Thinking Without Thinking, Malcolm Gladwell explains why decision-making under uncertainty can be so effective. We usually assume that more information leads to better decisions — if a doctor proposes additional tests, we tend to believe they will lead to a better outcome. Gladwell disagrees: “In fact, you need to know very little to find the underlying signature of a complex phenomenon. All you need is evidence of the ECG, blood pressure, fluid in the lungs, and an unstable angina. That’s a radical statement.”
In medicine, as in many areas, more information does not necessarily ensure improved outcomes. To illustrate this, Gladwell gives the example of a man arriving at a hospital with intermittent chest pains. His vital signs show no risk factors, yet his lifestyle does and he had heart surgery two years earlier. If a doctor looks at all the available information, it may seem that the man needs admitting to the hospital. But the additional factors, beyond the vital signs, are not important in the short term. In the long run, he is at serious risk of developing heart disease. Gladwell writes,
… the role of those other factors is so small in determining what is happening to the man right now that an accurate diagnosis can be made without them. In fact, … that extra information is more than useless. It’s harmful. It confuses the issues. What screws up doctors when they are trying to predict heart attacks is that they take too much information into account.
We can all learn from Bezos’s approach, which has helped him to build an enormous company while retaining the tempo of a start-up. Bezos uses his heuristic to fight the stasis that sets in within many large organizations. It is about being effective, not about following the norm of slow decisions.
Once you understand that reversible decisions are in fact reversible you can start to see them as opportunities to increase the pace of your learning. At a corporate level, allowing employees to make and learn from reversible decisions helps you move at the pace of a start-up. After all, if someone is moving with speed, you’re going to pass them when you move with velocity.
The biggest risk to irreversible decisions is deciding before you need to. The biggest risk to reversible ones is waiting until the last minute. Make reversible decisions as soon as possible and make irreversible decisions as late as possible.
In today’s fast-paced and data-driven world, organizations are constantly challenged to make smarter decisions at an increasingly rapid rate. As a human-centered design professional, I firmly believe that Artificial Intelligence (AI) holds immense potential in transforming the workplace, enabling decision-makers to unlock unprecedented insights and steer their organizations towards success. In this thought leadership article, we will explore the benefits of leveraging AI in decision-making through two compelling case studies that demonstrate its transformative power.
Case Study 1: Enhancing Customer Experience with AI-powered Insights
One of the key areas where AI is revolutionizing decision-making is in optimizing customer experiences. A leading e-commerce company, “SuperStore,” adopted AI-powered analytics to delve deeper into their customer data and gain actionable insights. By leveraging AI algorithms, they analyzed vast amounts of customer purchase history, preferences, and demographic information. Consequently, they identified customers’ propensity to purchase certain items, enabling them to personalize recommendations and offers dynamically.
SuperStore observed a substantial increase in conversion rates and customer satisfaction as a result of this AI-powered decision-making. With the ability to understand customer behavior patterns and predict preferences, they successfully exceeded their customers’ expectations. Furthermore, the insights obtained from AI algorithms provided valuable guidance in optimizing marketing strategies, product placements, and inventory management decisions, yielding significant business growth.
This case study highlights how AI-driven decision-making tools can harness vast amounts of customer data to create unparalleled customer experiences, boosting sales and establishing a competitive edge.
Case Study 2: Improving Operational Efficiency through AI-powered Automation
Another area where AI is revolutionizing decision-making is in streamlining operational processes. A global manufacturing firm, “SmartCorp,” sought to leverage AI to enhance operational efficiency and reduce costs. They implemented an AI-driven automation system that analyzed real-time production data from various sources and generated real-time alerts for potential anomalies or bottlenecks.
The AI system enabled SmartCorp to detect deviations from standard processes and critical inefficiencies promptly. Production managers were provided with actionable insights that enabled them to make data-driven decisions in real-time, such as adjusting production rates, identifying maintenance needs, and optimizing resource allocation. With the aid of AI, SmartCorp experienced a substantial decrease in downtime, a reduction in errors, and a significant increase in overall productivity.
This case study showcases how AI-powered decision-making supports organizations in transforming their operational landscape. The ability to automate and analyze vast amounts of data in real-time empowers decision-makers to proactively identify and address issues as they arise, optimizing operational efficiency and driving remarkable business outcomes.
Conclusion
AI represents a powerful opportunity for organizations to unlock new levels of productivity, efficiency, and success by harnessing data-driven decision-making. The case studies of SuperStore and SmartCorp demonstrate the profound impact that AI can have on enhancing customer experiences and improving operational efficiency. By leveraging the potential of AI, decision-makers can confidently navigate the complexities of today’s business landscape, ensuring smarter decisions, and ultimately propelling their organizations toward a prosperous future.
Bottom line: Futurology is not fortune telling. Futurists use a scientific approach to create their deliverables, but a methodology and tools like those in FutureHacking™ can empower anyone to engage in futurology themselves.
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Workplace change has never been at a higher rate or faster pace than now. Everything from consumer preferences to product sourcing models is in flux. ‘Reinvention,’ ‘transformation,’ and ‘disruption’ are popular terms to describe how private and public organizations are evolving to accommodate changing operating environments, stakeholder expectations and regulatory requirements. Leaders and their teams must enable multiple, complex changes when most organizational practices are obsolete and the future is at best uncertain.
In today’s dynamic environment, many leaders default to strategies that have worked under very different conditions. Relying on past practices to solve present challenges is often naive and highly risky. Other leaders instinctively select courses of action that feel right or appear credible based on limited or easily available data. In these cases, the speed of response and hope for simple solutions trump rigorous assessment and disciplined evaluation.
Addressing Uncertainty with No Regret Decisions
A pragmatic way to move forward through unknown conditions is to identify ‘no regret’ decisions. A no regret decision provides a net benefit under any future scenario. For example, building awareness of sanitation and hygiene good practices at the beginning of the pandemic was a no regret decision because it benefited people even if the virus didn’t spread through surface contact.
The Benefits of No Regret Decisions
There are four benefits of making no regret decisions. The first is they align stakeholders to a course of action. There is strength in agreement that leads to positive team dynamics and a foundation of success to build upon.
The second is that no regret decisions move a team from a static state to one of motion. Success in change is not about being perfect; it’s about responding to circumstances based on available information, identifying options, and selecting the best way forward. Delaying action is rarely a good strategy during change because issues amplify with time—speed of execution matters; inactivity is harmful. Taking action transitions people from being observers to participants, preparing them to address future time-bound situations and make bigger decisions. Momentum is a source of strength that ignites future efforts.
Creating a fact-base is essential to understanding the interplay of environmental factors that lead to analysis, hypotheses, and action. The third benefit is it provides opportunities to test and learn, to challenge assumptions and modify strategies to deliver the highest value.
The fourth benefit is the building of confidence of individuals and teams. They foster a belief in capabilities, decision-making process, and a high probability of success. Also, taking concrete actions minimizes the “fight, flight, or freeze” effect triggered by uncertainty. It renews people’s belief in their abilities and avoids the emotional responses of self-doubt and fear that come with unknown or vague circumstances.
No Regret Decision Examples
What decisions provide net benefits regardless of future outcomes? Capability development is an enabler of performance. The current focus on resiliency training is an example of equipping people with mindsets, tools, and behaviors, irrespective of the emerging scenarios. Critical thinking, ideation and creativity are other skills that add value when addressing all forms of hyper-change.
Simplifying and standardizing processes is another no regret decision. The decision-making process is a good example of how a consistent framework leads to shared understanding, assessment, and alignment on actions. When people use the same process, they follow the same rules and speak the same language. The symmetry of the approach leads to clarity and agreement.
Soliciting customer feedback to inform strategy development and execution offers benefits regardless of the operating environment. It is easy to skip this step of intelligence gathering when faced with multiple, complex changes requiring quick responses. The risk of doing so is that solutions don’t address client needs, risking relationships and sales.
Leaders and their teams are navigating business environments never seen before. Internal and external realities require them to rethink their operating models and pivot their strategies, initiatives, and resources to achieve their performance goals. Making no regret decisions enables them to align stakeholders on actions that lead to positive outcomes. They also provide the opportunity to test assumptions and hypotheses and refine the understanding of marketplace dynamics. The forward motion and small gains generated by no regret decisions build the confidence of individuals and teams to face challenges head-on to mitigate risks and seize opportunities.
The only regret from this type of decision is not making them. What no regret decisions can you make to help you lead through hyper-change?
In this era of constant digital connectivity, consumers are experiencing an overwhelming fear of missing out (FOMO) on the latest trends, experiences, and opportunities. This fear has a profound effect on consumer decision-making and shapes how they engage with brands, products, and services. To truly understand FOMO’s impact, we must delve into its psychological roots and explore two compelling case studies.
Psychological Roots of FOMO:
Fear of missing out stems from the basic human desire for social connection, the need for validation, and the fear of being left behind. Countless studies have shown that individuals have a fundamental longing to be part of a community, to share experiences, and to feel accepted. FOMO amplifies these desires in the digital age, fueling anxiety-driven decision-making.
Case Study 1: The Influence of FOMO on Buying Behavior
In recent years, the beauty industry witnessed a significant rise in FOMO-driven purchasing behaviors. Brands cleverly utilize social media platforms and influencers to create a sense of scarcity and urgency, inducing FOMO within consumers. A prime example of this phenomenon is the limited-edition makeup collaborations, which generate immense buzz and excitement. By tapping into consumers’ FOMO, brands create a fear of not having the exclusive item, leading to impulsive purchases and even waiting in long queues.
An in-depth analysis conducted by a major cosmetics company revealed that 70% of consumers who bought limited-edition products did so due to FOMO. Furthermore, the study found that consumers were inclined to share their purchases on social media platforms, seeking validation and admiration from their peers. Thus, FOMO not only influences purchase decisions but also contributes to the amplification of social status online.
Case Study 2: The Effect of FOMO on Travel Choices
The travel industry faces a unique challenge in catering to FOMO-driven decision-making. Consumers are bombarded with picturesque imagery of exotic destinations, luxurious resorts, and thrilling experiences. This abundance of options creates a sense of FOMO, as individuals fear missing out on the next best travel experience. Travel companies have capitalized on this psychological state by emphasizing “limited availability” and “exclusivity” in their marketing strategies.
A case study conducted by a prominent travel agency demonstrated the impact of FOMO on consumer behavior. They offered two identical vacation packages: Package A was available without any time restrictions, while Package B was advertised as limited to the first 50 bookings. Despite Package B being slightly more expensive, it received 70% more bookings within 48 hours. The fear of missing out on an exclusive opportunity significantly influenced consumers’ travel choices, even at an increased cost.
Mitigating FOMO:
As human-centered professionals, it is crucial to understand the phenomenon of FOMO and its impact on consumer decision-making. To cater to consumers effectively, brands should consider the following strategies:
1. Transparent Communication: Be open and honest with consumers, providing clear information about product availability or event schedules.
2. Curated Exclusivity: Offer limited-edition products or experiences thoughtfully, but without exploiting consumers’ FOMO. Ensure that exclusivity is based on genuine benefits rather than artificial scarcity.
3. Customer Empowerment: Encourage consumers to make decisions based on their true preferences, rather than succumbing to FOMO. Provide ample information, resources, and reviews to help them make well-informed choices.
Conclusion
Understanding the fear of missing out (FOMO) is essential for human-centered professionals to navigate the ever-changing consumer landscape effectively. By recognizing the psychological roots of FOMO and analyzing case studies, we can see its tangible impact on consumer decision-making. Brands that acknowledge and address FOMO while promoting transparency, curated exclusivity, and customer empowerment are more likely to build trust, loyalty, and meaningful connections with their audience, ultimately shaping a more conscious consumer culture.
SPECIAL BONUS: The very best change planners use a visual, collaborative approach to create their deliverables. A methodology and tools like those in Change Planning Toolkit™ can empower anyone to become great change planners themselves.
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Collaboration is a key driver of innovation, enabling diverse teams to leverage their expertise, perspectives, and skills to solve complex problems. In today’s fast-paced and interconnected world, cross-functional collaboration has become increasingly essential for businesses to stay competitive and drive meaningful change. This article explores the benefits of collaboration in fostering cross-functional innovation through two compelling case studies.
Case Study 1 – Pixar’s Creative Collaboration
Pixar, the renowned animation studio, is celebrated for its consistent delivery of groundbreaking and critically acclaimed films. One of the critical factors contributing to their success is their commitment to cross-functional collaboration. From directors to animators, writers, and technical experts, Pixar brings together diverse talents from different disciplines to create their films.
By fostering an environment of open communication and collaboration, Pixar teams challenge conventions and push boundaries. They encourage cross-pollination of ideas, creating an iterative process where different perspectives enrich the creative process. This cross-functional approach has led to numerous breakthroughs in storytelling, animation techniques, and technological advancements, enabling Pixar to create immersive and emotionally impactful films loved by audiences worldwide.
Case Study 2 – GE’s Global Research Collaboration
General Electric (GE), a multinational conglomerate, places a strong emphasis on collaboration as a catalyst for innovation. GE’s Global Research Center, one of the world’s most extensive and diverse industrial research organizations, brings together scientists, engineers, and experts from various disciplines.
By fostering cross-functional collaboration, GE harnesses the collective knowledge and expertise of its researchers. This collaborative environment has yielded groundbreaking innovations across industries, including advancements in renewable energy sources, healthcare technologies, aerospace, and more. GE’s collaboration efforts not only drive innovation but also contribute to addressing global challenges and improving the world we live in.
Benefits of Cross-Functional Collaboration:
1. Enhanced Problem-Solving: Cross-functional teams bring a range of perspectives and expertise to the table, enabling them to approach problems from different angles. This collaborative approach fosters innovative thinking and generates well-rounded solutions that address diverse needs.
2. Increased Creativity and Innovation: Collaboration sparks creativity by enabling the collision of ideas, encouraging out-of-the-box thinking, and challenging traditional paradigms. The synergy between team members from different backgrounds stimulates new perspectives and innovative solutions.
3. Improved Communication and Knowledge Sharing: Cross-functional collaboration facilitates open communication, breaking down silos and enabling the sharing of expertise and insights. This exchange of knowledge drives continuous learning, enabling teams to stay current with industry trends and leverage emerging opportunities.
4. Enhanced Decision Making: Collaboration encourages collective decision-making processes, leveraging diverse viewpoints and expertise. This approach leads to more informed and well-rounded decisions, reducing the risk of biases and improving overall organizational performance.
Conclusion
Cross-functional collaboration is a powerful tool for driving innovation and achieving organizational success. As demonstrated by the case studies of Pixar and GE, collaboration fosters creativity, problem-solving, knowledge sharing, and effective decision-making. By embracing and promoting cross-functional collaboration, businesses can harness the collective intelligence of their teams and unlock new avenues for growth, ensuring their continued relevance and competitiveness in an ever-evolving world.
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Artificial intelligence (AI) is quickly emerging as a powerful tool for business decision making. Companies of all sizes are realizing the potential of AI to provide insights and automate manual processes that previously served to hinder the decision-making process. In this article, we’ll take a look at some of the benefits that AI-enabled decision making can bring to a business, as well as some examples of successful implementations.
One of the most significant benefits of AI-enabled decision making is the ability to analyze large data sets and identify patterns that inform decisions. By harnessing powerful algorithms, AI can uncover correlations that are otherwise not visible. This can be especially beneficial in customer and market segmentation, where the application of AI-driven analytics can help uncover new growth opportunities. For example, one company used AI to analyze customer data as part of its product segmentation strategy. This enabled the company to develop personalized recommendations that drove increased customer loyalty and revenue growth.
Case Study 1 – Automating Chargeback Calculations
In addition to analyzing data, AI can automate tedious manual tasks for more efficient and accurate decision-making. For example, a global accounting firm used AI to automate chargeback calculations. By eliminating manual human review, AI enabled the company to process thousands of invoices in a fraction of the time. This reduced the cost of processing while improving accuracy and creating an overall better customer experience.
Case Study 2 – AI-Enabled Predictive Logistics
Finally, AI can be used to create predictive models that anticipate future actions, trends, and outcomes. By using AI to develop predictive models, businesses can get a jumpstart on preparing for potential events ahead of time. For example, a logistics firm developed an AI-enabled predictive model that anticipated customer buying patterns and adjusted its shipping routes accordingly. This enabled the company to save time and money through improved deployment of its assets.
Conclusion
AI-enabled decision making offers a range of potential benefits to businesses of all sizes. By leveraging powerful algorithms to analyze data, automate processes, and create predictive models, companies can improve decision making while creating a competitive edge. Through the use of case studies, this article has highlighted some of the key benefits of AI-enabled decision making that can be applied to a variety of organizational contexts.
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Design thinking is a method of problem solving that has been around since the 1970s but has become increasingly popular in business strategy in the last decade. This approach to problem solving relies on creative thinking to find user-centered solutions and has proven to be an effective way to improve customer experience and increase profits. Design thinking has become a key element in crafting business strategy and can help organizations gain a competitive edge. Here are ten ways design thinking can help craft business strategy:
1. Identifying customer needs: Design thinking starts with looking at the user and understanding their needs. Through research and observation, organizations can identify and prioritize customer needs and then use that information to create strategies that are tailored to their customer base.
2. Developing empathy: Design thinking requires organizations to put themselves in the shoes of their customers and understand their motivations, values, and preferences. This helps organizations develop empathy for their customers and design strategies that are tailored to their needs.
3. Improving customer experience: Design thinking helps organizations create a better customer experience by focusing on the user journey and understanding their needs and pain points. This can help organizations create strategies that improve customer experience and increase customer loyalty.
4. Creating innovative solutions: Design thinking encourages organizations to think outside the box and come up with innovative solutions to problems. This can help organizations create strategies that are different from the competition and give them an edge.
5. Enhancing team collaboration: Design thinking encourages collaboration and creativity within teams by encouraging different perspectives and ideas. This helps organizations create strategies that are more effective and efficient.
6. Generating new ideas: Design thinking helps organizations generate new ideas and perspectives that can help them craft better strategies. This can help organizations stay ahead of the competition and create unique solutions.
7. Facilitating decision-making: Design thinking helps organizations make informed decisions by providing them with the data and insights they need to make informed decisions. This can help organizations make decisions that are better for the business and its customers.
8. Improving communication: Design thinking helps organizations communicate more effectively by focusing on the customer and understanding their needs. This can help organizations create strategies that are more effective and better tailored to their customers.
9. Enhancing user-centered design: Design thinking helps organizations create user-centered designs that focus on the user and their needs. This can help organizations create strategies that are more effective and better tailored to their customers.
10. Increasing profits: Design thinking helps organizations create strategies that are more effective and efficient, which can lead to increased profits. This can help organizations increase their competitive edge and stay ahead of the competition.
Design thinking is an effective tool for crafting business strategy and can help organizations gain a competitive edge. Through research and observation, organizations can identify customer needs and then use that information to create strategies that are tailored to their customer base. Design thinking can also help organizations create innovative solutions, improve customer experience, and increase profits. By utilizing design thinking, organizations can create strategies that are more effective and efficient, which can help them gain a competitive edge.
SPECIAL BONUS: Braden Kelley’s Problem Finding Canvas can be a super useful starting point for doing design thinking or human-centered design.
“The Problem Finding Canvas should help you investigate a handful of areas to explore, choose the one most important to you, extract all of the potential challenges and opportunities and choose one to prioritize.”
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It is not too often that the leader of a Fortune 500 gives you an insight into how their company achieves competitive advantage in the marketplace in a letter to shareholders, instead of launching into a page or two of flowery prose written by the Public Relations (PR) team that works for them. The former is what Jeff Bezos tends to deliver year after year. This year’s letter is particularly interesting.
The two key insights in this year’s letter were that:
#1 – Amazon strives to view itself as a startup champion riding to the rescue of customers
#2 – Amazon chooses to be customer-obsessed, not customer-focused or customer-centric, but customer-obsessed
Both of these are crucial to sustaining innovation, and are supported by Jeff’s other main pieces of advice:
– Resisting proxies
– Embracing external trends
– Practicing high velocity decision making
But, I won’t steal Jeff’s thunder. I encourage you to read Jeff’s letter to shareholders in its entirety, check out the bonus video interview at the end, and add comments to share what you find particularly interesting in the letter.
Keep innovating!
—————————————————————- 2016 Letter to Amazon Shareholders
April 12, 2017
“Jeff, what does Day 2 look like?”
That’s a question I just got at our most recent all-hands meeting. I’ve been reminding people that it’s Day 1 for a couple of decades. I work in an Amazon building named Day 1, and when I moved buildings, I took the name with me. I spend time thinking about this topic.
“Day 2 is stasis. Followed by irrelevance. Followed by excruciating, painful decline. Followed by death. And that is why it is always Day 1.”
To be sure, this kind of decline would happen in extreme slow motion. An established company might harvest Day 2 for decades, but the final result would still come.
I’m interested in the question, how do you fend off Day 2? What are the techniques and tactics? How do you keep the vitality of Day 1, even inside a large organization?
Such a question can’t have a simple answer. There will be many elements, multiple paths, and many traps. I don’t know the whole answer, but I may know bits of it. Here’s a starter pack of essentials for Day 1 defense: customer obsession, a skeptical view of proxies, the eager adoption of external trends, and high-velocity decision making.
True Customer Obsession
There are many ways to center a business. You can be competitor focused, you can be product focused, you can be technology focused, you can be business model focused, and there are more. But in my view, obsessive customer focus is by far the most protective of Day 1 vitality.
Why? There are many advantages to a customer-centric approach, but here’s the big one: customers are always beautifully, wonderfully dissatisfied, even when they report being happy and business is great. Even when they don’t yet know it, customers want something better, and your desire to delight customers will drive you to invent on their behalf. No customer ever asked Amazon to create the Prime membership program, but it sure turns out they wanted it, and I could give you many such examples.
Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight. A customer-obsessed culture best creates the conditions where all of that can happen.
Resist Proxies
As companies get larger and more complex, there’s a tendency to manage to proxies. This comes in many shapes and sizes, and it’s dangerous, subtle, and very Day 2.
A common example is process as proxy. Good process serves you so you can serve customers. But if you’re not watchful, the process can become the thing. This can happen very easily in large organizations. The process becomes the proxy for the result you want. You stop looking at outcomes and just make sure you’re doing the process right. Gulp. It’s not that rare to hear a junior leader defend a bad outcome with something like, “Well, we followed the process.” A more experienced leader will use it as an opportunity to investigate and improve the process. The process is not the thing. It’s always worth asking, do we own the process or does the process own us? In a Day 2 company, you might find it’s the second.
Another example: market research and customer surveys can become proxies for customers – something that’s especially dangerous when you’re inventing and designing products. “Fifty-five percent of beta testers report being satisfied with this feature. That is up from 47% in the first survey.” That’s hard to interpret and could unintentionally mislead.
Good inventors and designers deeply understand their customer. They spend tremendous energy developing that intuition. They study and understand many anecdotes rather than only the averages you’ll find on surveys. They live with the design.
I’m not against beta testing or surveys. But you, the product or service owner, must understand the customer, have a vision, and love the offering. Then, beta testing and research can help you find your blind spots. A remarkable customer experience starts with heart, intuition, curiosity, play, guts, taste. You won’t find any of it in a survey.
Embrace External Trends
The outside world can push you into Day 2 if you won’t or can’t embrace powerful trends quickly. If you fight them, you’re probably fighting the future. Embrace them and you have a tailwind.
These big trends are not that hard to spot (they get talked and written about a lot), but they can be strangely hard for large organizations to embrace. We’re in the middle of an obvious one right now: machine learning and artificial intelligence.
Over the past decades computers have broadly automated tasks that programmers could describe with clear rules and algorithms. Modern machine learning techniques now allow us to do the same for tasks where describing the precise rules is much harder.
At Amazon, we’ve been engaged in the practical application of machine learning for many years now. Some of this work is highly visible: our autonomous Prime Air delivery drones; the Amazon Go convenience store that uses machine vision to eliminate checkout lines; and Alexa, our cloud-based AI assistant. (We still struggle to keep Echo in stock, despite our best efforts. A high-quality problem, but a problem. We’re working on it.)
But much of what we do with machine learning happens beneath the surface. Machine learning drives our algorithms for demand forecasting, product search ranking, product and deals recommendations, merchandising placements, fraud detection, translations, and much more. Though less visible, much of the impact of machine learning will be of this type – quietly but meaningfully improving core operations.
Inside AWS, we’re excited to lower the costs and barriers to machine learning and AI so organizations of all sizes can take advantage of these advanced techniques.
Using our pre-packaged versions of popular deep learning frameworks running on P2 compute instances (optimized for this workload), customers are already developing powerful systems ranging everywhere from early disease detection to increasing crop yields. And we’ve also made Amazon’s higher level services available in a convenient form. Amazon Lex (what’s inside Alexa), Amazon Polly, and Amazon Rekognition remove the heavy lifting from natural language understanding, speech generation, and image analysis. They can be accessed with simple API calls – no machine learning expertise required. Watch this space. Much more to come.
High-Velocity Decision Making
Day 2 companies make high-quality decisions, but they make high-quality decisions slowly. To keep the energy and dynamism of Day 1, you have to somehow make high-quality, high-velocity decisions. Easy for start-ups and very challenging for large organizations. The senior team at Amazon is determined to keep our decision-making velocity high. Speed matters in business – plus a high-velocity decision making environment is more fun too. We don’t know all the answers, but here are some thoughts.
First, never use a one-size-fits-all decision-making process. Many decisions are reversible, two-way doors. Those decisions can use a light-weight process. For those, so what if you’re wrong? I wrote about this in more detail in last year’s letter.
Second, most decisions should probably be made with somewhere around 70% of the information you wish you had. If you wait for 90%, in most cases, you’re probably being slow. Plus, either way, you need to be good at quickly recognizing and correcting bad decisions. If you’re good at course correcting, being wrong may be less costly than you think, whereas being slow is going to be expensive for sure.
Third, use the phrase “disagree and commit.” This phrase will save a lot of time. If you have conviction on a particular direction even though there’s no consensus, it’s helpful to say, “Look, I know we disagree on this but will you gamble with me on it? Disagree and commit?” By the time you’re at this point, no one can know the answer for sure, and you’ll probably get a quick yes.
This isn’t one way. If you’re the boss, you should do this too. I disagree and commit all the time. We recently greenlit a particular Amazon Studios original. I told the team my view: debatable whether it would be interesting enough, complicated to produce, the business terms aren’t that good, and we have lots of other opportunities. They had a completely different opinion and wanted to go ahead. I wrote back right away with “I disagree and commit and hope it becomes the most watched thing we’ve ever made.” Consider how much slower this decision cycle would have been if the team had actually had to convince me rather than simply get my commitment.
Note what this example is not: it’s not me thinking to myself “well, these guys are wrong and missing the point, but this isn’t worth me chasing.” It’s a genuine disagreement of opinion, a candid expression of my view, a chance for the team to weigh my view, and a quick, sincere commitment to go their way. And given that this team has already brought home 11 Emmys, 6 Golden Globes, and 3 Oscars, I’m just glad they let me in the room at all!
Fourth, recognize true misalignment issues early and escalate them immediately. Sometimes teams have different objectives and fundamentally different views. They are not aligned. No amount of discussion, no number of meetings will resolve that deep misalignment. Without escalation, the default dispute resolution mechanism for this scenario is exhaustion. Whoever has more stamina carries the decision.
I’ve seen many examples of sincere misalignment at Amazon over the years. When we decided to invite third party sellers to compete directly against us on our own product detail pages – that was a big one. Many smart, well-intentioned Amazonians were simply not at all aligned with the direction. The big decision set up hundreds of smaller decisions, many of which needed to be escalated to the senior team.
“You’ve worn me down” is an awful decision-making process. It’s slow and de-energizing. Go for quick escalation instead – it’s better.
So, have you settled only for decision quality, or are you mindful of decision velocity too? Are the world’s trends tailwinds for you? Are you falling prey to proxies, or do they serve you? And most important of all, are you delighting customers? We can have the scope and capabilities of a large company and the spirit and heart of a small one. But we have to choose it.
A huge thank you to each and every customer for allowing us to serve you, to our shareowners for your support, and to Amazonians everywhere for your hard work, your ingenuity, and your passion.
As always, I attach a copy of our original 1997 letter. It remains Day 1.
Sincerely,
Jeff
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If you’d like dive deeper into the mind of Jeff Bezos, then check out this interview with him conducted by Walt Mossberg of The Verge last year at Code Conference 2016:
And here is another fascinating peek inside the mind of Jeff Bezos from 1997:
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Drum roll please…
It is not too often that the leader of a Fortune 500 gives you an insight into how their company achieves competitive advantage in the marketplace in a letter to shareholders, instead of launching into a page or two of flowery prose written by the Public Relations (PR) team that works for them. The former is what Jeff Bezos tends to deliver year after year. This year’s letter is particularly interesting.