Tag Archives: Decision Making

A Leader’s Framework for Uncertainty

Decision-Making Under Ambiguity

LAST UPDATED: December 25, 2025 at 10:59AM

A Leader's Framework for Uncertainty

GUEST POST from Chateau G Pato

Ambiguity has become the permanent operating condition for modern leaders. Strategy horizons shrink, assumptions expire quickly, and yesterday’s best practice becomes today’s constraint. In this reality, decision-making is no longer about choosing the optimal path — it is about enabling progress without full visibility.

The leaders who thrive are not those who eliminate uncertainty, but those who design organizations capable of acting intelligently within it.

“Uncertainty does not paralyze organizations; rigid thinking does. The leader’s job is to replace the need for certainty with the capacity to learn and adapt.”

Braden Kelley

From Certainty to Capability

Many leadership models still reward decisiveness as confidence. Under ambiguity, confidence must be redefined. It is no longer about being right; it is about being responsive.

This requires shifting from outcome certainty to capability certainty — confidence that the organization can sense, adapt, and respond effectively.

Understanding the Nature of Ambiguity

Ambiguity emerges when the environment changes faster than meaning can stabilize. Customer needs evolve, technologies converge, and competitive boundaries blur.

In such conditions, leaders must abandon the illusion of control while strengthening alignment around shared intent.

An Updated Framework for Ambiguous Decisions

1. Define Non-Negotiables

Clarify values, purpose, and constraints that will guide decisions regardless of direction. These act as stabilizers when everything else shifts.

2. Sequence Commitments

Avoid all-or-nothing decisions. Break commitments into stages, increasing investment as learning reduces uncertainty.

3. Design for Feedback Speed

The faster feedback arrives, the safer decisions become. Leaders should optimize for learning velocity, not decision finality.

4. Normalize Intelligent Failure

Punishing failure under ambiguity suppresses information. Rewarding thoughtful experimentation accelerates clarity.

Case Study 1: Financial Services Product Innovation

A financial services firm explored new digital offerings amid regulatory and market ambiguity. Leadership framed initiatives as learning journeys rather than launches.

By staging investments and reviewing insights frequently, the organization avoided costly misalignment while building confidence in future opportunities.

Case Study 2: Urban Infrastructure Planning

A city government faced uncertainty around population growth and climate impact. Instead of committing to a single long-term plan, leaders adopted adaptive infrastructure principles.

Projects were designed to evolve over time, allowing the city to respond as conditions changed rather than locking in outdated assumptions.

What Strong Leaders Do Differently

Leaders effective under ambiguity:

  • Ask better questions instead of demanding answers
  • Share uncertainty transparently
  • Focus on learning signals rather than lagging indicators

These behaviors create trust and momentum even when outcomes remain unclear.

Ambiguity as a Strategic Advantage

Organizations comfortable with ambiguity move faster because they are not waiting for permission from the future. They act, learn, and adjust while others hesitate.

In a world defined by uncertainty, this capability is the ultimate competitive advantage.

Frequently Asked Questions

FAQ

How should leaders communicate during uncertainty?
By being honest about what is known, unknown, and being learned.

Does ambiguity mean abandoning strategy?
No. It means holding strategy as a hypothesis, not a fixed plan.

What is the most important leadership skill under ambiguity?
Sensemaking combined with decisive learning.

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

Image credits: Pexels

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Inside the Mind of Jeff Bezos

Amazon's Innovation PhilosophyIt 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!

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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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12 Ways to Make Bad Decisions

GUEST POST from Mitch Ditkoff

There are three things that continue to astound me about most organizations: The cro-magnon way performance reviews are done; the pitiful way brainstorm sessions are run and; the voodoo way decisions are made. What follows is an elaboration of the third — twelve all-too-common phenomena that contribute to funky decision making. (As you read, think about the teams you work most closely with — and which of these behaviors describes them).

  1. Selective Search for Evidence: Gathering facts that support pre-determined conclusions, but disregard other facts that support different conclusions.
  2. Premature Termination of Search for Evidence: Accepting the first alternative that looks like it might work.
  3. Inertia: Being unwilling to change old thought patterns.
  4. Selective Perception: Prematurely screening out information not assumed to be useful.
  5. Wishful Thinking: Wanting to see things in a positive light.
  6. Recency Effect: Putting undue attention on recent information and experience while minimizing the value of information collected in the past.
  7. Repetition Bias: Believing what’s been stated the most often and by the greatest number of sources.
  8. Anchoring and Adjustment: Being unduly influenced by initial information that shapes your view of subsequent information.
  9. Group Think: Conforming to peer pressure or the opinions of the majority.
  10. Source Credibility: Rejecting input from sources prematurely judged to not be credible (or not “cool” or “in sync with the way you do business.”)
  11. Attribution Asymmetry: Attributing success to your team’s abilities and talents, but attributing failures to bad luck and external factors.
  12. Role Fulfillment: Conforming to the decision making expectations others have of someone in your position.

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