Tag Archives: agility

Feedback Systems That Improve Trust and Agility

Feedback Systems That Improve Trust and Agility

GUEST POST from Art Inteligencia


I. Foundations: The Trust-Agility Flywheel

In the modern business landscape, “agility” has become a ubiquitous buzzword. Organizations pour millions into adopting rigid Agile frameworks, restructuring charts, and mandating daily stand-ups. Yet, many find that despite these mechanical changes, their actual capacity to pivot remains agonizingly slow. The missing link isn’t a lack of process; it is a lack of trust. True organizational agility is not merely about speed — it is about the velocity of safe experimentation.

The Feedback Nexus

To move fast, teams must feel safe enough to fail openly and report friction instantly. High-trust environments utilize transparent, continuous feedback loops that actively reduce the “fear of the friction.” When employees know that flagging a flaw or suggesting an unconventional pivot won’t result in punitive action, the organization gains an early-warning system that traditional, bureaucratic structures completely miss. Feedback becomes the fuel for agility, and trust is the engine that processes it.

Introducing XLMs over SLAs

To truly understand organizational health, leaders must fundamentally rethink how they measure performance. For decades, businesses have relied on Service Level Agreements (SLAs) to track operational efficiency. However, traditional SLAs suffer from a fatal flaw: they measure the transaction, not the human experience. A system can achieve 99% uptime (a green SLA) while the employees using it are utterly frustrated by its clunky workflow (a red human experience).

To bridge this gap, forward-thinking organizations are transitioning to Experience Level Measures (XLMs). Unlike SLAs, XLMs are designed to capture the qualitative, emotional, and practical friction points experienced by the workforce and customers alike. By turning subjective sentiment into actionable data, XLMs allow leadership to optimize for human engagement and well-being. When you improve the human experience, operational excellence and adaptability naturally follow.

II. Anatomy of Human-Centered Feedback Systems

Building a feedback system that people actually trust and use requires moving away from engineering-first or compliance-first mindsets. Instead, we must design the ecosystem through the lens of human-centered design principles. A system is only as good as the psychological safety of the people interacting with it.

Radical Empathy & Agency

Feedback should never feel like surveillance or a trap. Traditional, top-down mechanisms often feel extractive—leadership demands data, but employees see no personal benefit. Human-centered systems prioritize employee agency, giving individuals control over how, when, and contextually where they share insights. By approaching data collection with radical empathy, we design interfaces and touchpoints that respect an individual’s cognitive load and emotional state, transforming feedback from an obligation into an empowering tool.

Bi-Directional Channels

True communication is never a monologue. Organizations often falter by building elaborate systems to funnel bottom-up complaints or top-down mandates, without creating a space for genuine dialogue. A robust feedback ecosystem requires bi-directional channels where information flows fluidly in both directions. Leadership must be just as visible, vulnerable, and accountable in receiving and responding to feedback as they are in soliciting it from the frontline.

Navigating Organizational Personas: The Conscript vs. The Magic Maker

An organization is not a monolith; it is composed of diverse individuals with wildly different motivations and risk tolerances. To design effective feedback loops, we must understand how different organizational personas interact with the innovation ecosystem:

  • The Conscript: These are the individuals who may feel pushed into change initiatives or day-to-day operational shifts without their explicit input. For a Conscript, a poorly designed feedback system feels like a surveillance trap. Human-centered design ensures these channels feel safe enough for them to highlight systemic friction and operational realities without fear of career friction.
  • The Magic Maker: These are your proactive innovators, creatives, and problem solvers who naturally want to push boundaries. If a feedback system is too rigid, slow, or bureaucratic, Magic Makers will disengage entirely. They require dynamic, high-velocity feedback loops that give them the room to offer bold, unvarnished ideas and see them rapidly tested.

By balancing the unique needs of these diverse personas, leadership can design an inclusive ecosystem where every employee feels heard, valued, and safe to contribute to the organization’s collective intelligence.

III. Activating Agility Through Dynamic Loops

Agility cannot survive on an annual schedule. When market dynamics, technology, and customer expectations shift by the week, relying on static, retrospective data is an existential risk. To build a highly adaptive organization, leaders must transition from lag-heavy evaluation cycles to real-time, dynamic feedback loops that fuel immediate action.

From Autopsy to Pulse

Traditional annual or semi-annual employee engagement surveys are organizational autopsies — they tell you why the patient died months after the illness started. By the time the data is cleaned, analyzed, and presented to leadership, the cultural or operational context has entirely changed. Dynamic feedback systems replace these lagging autopsies with continuous, low-friction “pulses.” Integrated seamlessly into the daily digital workflow, these micro-assessments capture real-time sentiment and operational friction without disrupting productivity, allowing leadership to catch systemic issues before they escalate.

Closing the Loop: The Ultimate Trust Builder

The fastest way to breed cynicism and kill employee engagement is to ask for feedback and then offer nothing but silence. When feedback disappears into a corporate black hole, trust evaporates. To prevent this, organizations must adhere to a strict response framework designed to build trust through transparency:

  1. Acknowledge: Instantly validate that the feedback has been received and heard.
  2. Contextualize: Frame the feedback within the larger scope of organizational goals and constraints.
  3. Act: Deploy resources to address the friction point or pilot a solution.
  4. Report: Communicate back to the team what was done, or explicitly explain the why if an action cannot be taken right away.

Showing the workforce that their input directly shapes their environment is the single most powerful way to reinforce psychological safety.

Decentralized Decision-Making

True agility requires shifting power to the edges of the organization. When continuous feedback loops are localized and transparent, frontline teams don’t have to navigate layers of bureaucracy to fix obvious problems. Armed with real-time sentiment and qualitative data, local managers and cross-functional teams are empowered to make autonomous micro-pivots. This decentralized approach ensures that the organization can adapt organically and instantly, keeping pace with change from the ground up.

IV. The Role of the Experience Management Office (XMO)

As organizations scale, feedback mechanisms often become siloed. Human Resources owns employee engagement, Customer Support tracks net promoter scores, and IT monitors system performance. Without a centralized entity to connect these dots, systemic friction remains invisible. To bridge these chasms, forward-thinking organizations are evolving the traditional Project Management Office (PMO) into a centralized Experience Management Office (XMO).

What is an XMO?

While a traditional PMO focuses heavily on timelines, budgets, and compliance, the XMO serves as the custodian of organizational experience, sentiment, and systemic health. The XMO does not replace existing teams; rather, it synthesizes cross-functional data to look at the organization through a holistic, human-centered lens. By monitoring how operational changes ripple across different departments, the XMO ensures that project velocity does not come at the expense of employee burnout or customer frustration.

Operationalizing Friction Reduction

The primary weapon of the XMO is the utilization of Experience Level Measures (XLMs). By tracking qualitative, real-time sentiment alongside traditional quantitative data, the XMO acts as an organizational friction-remover. When XLM data surfaces a bottleneck — such as a clunky procurement tool slowing down a product team — the XMO has the cross-functional authority to intervene. By systematically identifying and clearing these cultural and operational roadblocks, the XMO frees up teams to innovate faster and pivot with minimal drag.

FutureHacking™ the Feedback Landscape

A truly agile organization doesn’t just react to current friction; it anticipates future challenges. Through the lens of FutureHacking™, the XMO combines internal sentiment trends with external market and technological signals. This predictive capability allows leadership to run proactive simulations. By mapping how a future change initiative might impact the workforce *before* implementation, the XMO can design targeted readiness strategies, ensuring the organization handles upcoming disruptions smoothly rather than stumbling into predictable pitfalls.

V. The Agentic AI Frontier: Feedback in the Automated Workspace

We are standing on the precipice of a profound structural shift in how work gets done. The rise of Agentic AI — autonomous systems capable of executing complex, multi-step workflows, making localized decisions, and collaborating with other digital agents — means that the day-to-day reality of the human workforce is being fundamentally rewritten. As routine cognitive tasks are automated, the speed of operations will accelerate exponentially. In this hyper-velocity environment, traditional feedback mechanisms will completely collapse unless they are re-imagined for the automated workspace.

The Human-AI Collaboration

The introduction of autonomous agents will inevitably create a temporary paradox of friction and anxiety within the workforce. When digital agents begin reshaping job descriptions, workflows, and team dynamics, employees will experience rapid shifts in professional identity and psychological safety. To maintain agility during this transition, feedback loops must be engineered to capture the nuances of human-to-AI collaboration. Leaders need real-time data on where AI is empowering employees versus where poorly integrated automation is causing operational drag or cultural alienation.

AI as an Empathetic Listening Tool

While technology is often blamed for creating corporate distance, Agentic AI offers an unprecedented opportunity to scale human empathy. In large enterprises, leadership is routinely buried under massive mountains of qualitative data — thousands of free-form text comments from pulse surveys, Slack channel sentiments, and exit interviews that are impossible for humans to process quickly. AI agents can be deployed not to spy on workers, but to act as empathetic listeners. By synthesizing vast amounts of unstructured, qualitative text in real time, AI can instantly surface hidden systemic patterns, flag brewing cultural friction, and strip away senior leadership’s blind spots without compromising individual anonymity.

The Human-Centered Guardrail

However, leveraging AI to process feedback comes with a strict caveat: technology must never replace the human heart of the organization. AI can aggregate data, identify emotional friction, and predict turnover trends, but it cannot express genuine empathy, build trust, or inspire a team to pivot. The insights generated by AI must serve strictly as a diagnostic tool for human leaders. The ultimate response, the closing of the loop, and the cultural intervention must always remain deeply human. By keeping human-centered design at the core of AI-driven feedback ecosystems, organizations ensure that automation serves to elevate human potential rather than diminish it.

Conclusion: The Ultimate Competitive Advantage

In an era defined by relentless market disruption, shifting workforce dynamics, and the dawn of Agentic AI, organizations can no longer afford to treat feedback as a lagging compliance metric. Trust and agility are not soft, abstract human resources concepts — they are the hard currency of modern business survival. An organization’s capacity to pivot at speed is entirely dependent on the psychological safety of its people and the velocity at which friction is identified and removed.

To thrive in this new landscape, leadership must abandon the static, retrospective tools of the past and commit to building a living, breathing feedback ecosystem. By transitioning from transactional SLAs to human-centered Experience Level Measures (XLMs), and establishing a dedicated Experience Management Office (XMO) to act as the custodian of organizational health, businesses can turn everyday friction into a catalyst for growth.

The call to action for modern leaders is clear: stop asking your people to fill out generic forms that disappear into a corporate black hole. Instead, design transparent, bi-directional, and empathetic loops that honor human agency. When your workforce sees that their voices directly shape their operational environment, trust skyrockets, resistance to change melts away, and true organizational agility becomes second nature. In the final analysis, the ultimate competitive advantage isn’t the technology you deploy; it is the human-centered ecosystem you build around it.

Frequently Asked Questions

1. What is the main difference between an SLA and an XLM?

A Service Level Agreement (SLA) measures the technical or transactional output of a process (e.g., system uptime or response time). An Experience Level Measure (XLM) captures the qualitative human experience and emotional friction associated with that process (e.g., how frustrated or empowered an employee feels using the system).

2. How does an Experience Management Office (XMO) differ from a traditional PMO?

A traditional Project Management Office (PMO) focuses heavily on execution metrics like timelines, budgets, and compliance. An Experience Management Office (XMO) acts as the custodian of organizational sentiment and systemic health, using human-centered data to identify and remove operational friction.

3. Why is trust considered the prerequisite for organizational agility?

Agility requires rapid experimentation, which inherently includes the risk of failure. Without deep trust and psychological safety, employees will hide mistakes and resist taking risks, completely stalling the organization’s ability to pivot quickly.

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.”

Image credit: Gemini

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How to Quantify Cultural Resilience During Transformation

LAST UPDATED: April 21, 2026 at 3:53 PM

How to Quantify Cultural Resilience During Transformation

GUEST POST from Chateau G Pato


The Invisible Infrastructure of Change

In the modern landscape of perpetual disruption, transformation is often treated as a series of technical milestones — software deployments, organizational restructuring, or financial re-forecasting. However, these are merely the surface-level mechanics. The true critical path of any successful evolution is the collective psychological capacity of the workforce to absorb, adapt, and innovate under pressure.

The Resilience Gap

We see it time and again: a high-level strategy is flawlessly designed in the boardroom, only to be dismantled by “cultural friction” on the front lines. This gap exists because organizations focus on readiness (the ability to start) rather than resilience (the ability to endure and evolve). When we fail to quantify the human element, we are essentially flying blind through a storm.

Defining Cultural Resilience

True resilience is not a passive state of “bouncing back” to the status quo. In a human-centered innovation framework, resilience is the ability to bounce forward. It is the organizational muscle memory that allows a team to leverage uncertainty as a catalyst for growth, rather than a reason for retreat.

The Quantitative Shift

To lead effectively in a state of flux, we must move beyond qualitative anecdotes and “gut feelings” about company culture. By identifying the right indicators, we can transform culture from a “soft” concept into a hard asset that can be measured, managed, and mastered.

The Four Pillars of Resilient Culture

To effectively quantify resilience, we must deconstruct it into observable, measurable dimensions. By breaking the “cultural black box” into these four pillars, leaders can move from vague observations to targeted interventions.

1. Psychological Safety

Innovation and change require the courage to fail. This pillar measures the collective belief that the workplace is safe for interpersonal risk-taking. In a resilient culture, employees feel empowered to voice concerns or suggest pivots without fear of career repercussions, ensuring that “red flags” are identified long before they become project-ending disasters.

2. Structural Agility

Resilience is often hampered by rigid hierarchies. This dimension examines how quickly information, decision-making, and resources flow through the organization. A resilient structure is one where the “stable spine” of the company supports flexible “tentacles” that can respond to local shifts in real-time without waiting for permission from the top.

3. Shared Purpose (The North Star)

During the chaos of transformation, individual roles can feel disconnected from the larger goal. Shared purpose is the gravitational force that keeps teams aligned. We quantify this by measuring the degree to which employees understand — and believe in — the “Why” behind the change, ensuring that their daily efforts contribute to a meaningful outcome.

4. Adaptive Capacity

Every human has a finite amount of “cognitive bandwidth.” Adaptive capacity measures the existing skill-buffer and mental energy available within the workforce. By monitoring this, we can avoid the “Agentic Paradox,” where over-burdened employees lose their sense of agency and revert to passive compliance rather than active problem-solving.

Quantitative Metrics: Moving Beyond the Annual Survey

Traditional annual engagement surveys are lagging indicators — they tell you how your culture was months ago, not how it is performing now. To quantify resilience during an active transformation, we must shift our focus to leading indicators that provide real-time signals of cultural health.

The Change Saturation Index

Every organization has a “breaking point” where the volume of concurrent initiatives exceeds the capacity of the workforce to process them. By measuring the success rates of past projects against current workloads, we can calculate a saturation score. This allows leaders to pace the transformation effectively, preventing the fatigue that leads to cultural erosion.

Innovation Velocity

In a resilient culture, ideas move fast. We track the time elapsed from a frontline “pivot suggestion” to its appearance as a prototype or pilot project. A decrease in this velocity is often the first quantitative sign that bureaucracy is stifling adaptive capacity and that the “stable spine” has become too rigid.

The “Silence” Metric

Disengagement often manifests as silence. By utilizing Natural Language Processing (NLP) on anonymized internal communication data, we can track the ratio of constructive friction (healthy debate) versus complete withdrawal. A spike in “silence” or purely transactional communication is a high-probability indicator of declining psychological safety.

Decision Latency

How long does it take for a cross-functional team to resolve a conflict or approve a change-related action? Tracking average decision times provides a hard number for structural agility. High latency suggests that the organization is paralyzed by its own governance, preventing the rapid pivots necessary for a successful transformation.

The Human-Centered Scorecard

Data without a framework is just noise. To make cultural resilience visible to the C-suite and project leaders, we must translate these indicators into a Human-Centered Scorecard. This dashboard moves resilience from a “soft skill” conversation into a strategic business metric that sits alongside ROI and technical milestones.

Category Metric Tracking Method
Trust Peer-to-Peer Recognition Frequency Social Recognition Platforms / Intranet Metadata
Agility Role-Flexibility Ratio Internal Mobility Data / Skills Matrix Evolution
Endurance Burnout Proxy (Stability Metric) Metadata on After-Hours Connectivity & Calendar Density
Alignment Vision Clarity Score Bi-weekly Pulse Surveys (Qualitative to Quantitative)

Interpreting the Scorecard

The goal of the Scorecard is to identify experience level measures (XLMs). Unlike traditional SLAs that focus on technical uptime, XLMs focus on the human uptime. If “Trust” is declining while “Innovation Velocity” is increasing, you aren’t seeing sustainable growth; you’re seeing a team sprinting toward a burnout-driven collapse.

The Value of Visibility

When we put these numbers in front of stakeholders, we change the narrative. We are no longer asking for “patience” with the culture; we are demonstrating the Risk & Revenue Leakage that occurs when cultural resilience is ignored. This scorecard becomes the baseline for designing a better, more human-centric transformation experience.

Analyzing the Data: The Resilience Heatmap

Raw data provides the “what,” but a Resilience Heatmap provides the “where” and “why.” By mapping our scorecard metrics across different departments, geographies, or project teams, we can visualize the cultural health of the entire ecosystem in a single glance.

Identifying Pockets of Resistance

Not all resistance is toxic; often, it is a localized symptom of resource depletion or poor communication. The Heatmap allows leaders to pinpoint exactly where resilience is flagging. If the “Product” team shows high alignment but low psychological safety, we know we don’t have a vision problem — we have a leadership or process problem that is stifling their ability to speak up about risks.

Studying the “Bright Spots”

The most powerful use of quantification is identifying positive outliers. In any transformation, there are teams that thrive despite the pressure. By analyzing the data of these “bright spots,” we can uncover the specific micro-behaviors and local rituals that are sustaining their resilience. This isn’t about copying a “best practice” from a textbook; it’s about scaling what is already working within your own unique cultural DNA.

Data as a Diagnostic Tool

The Heatmap serves as an early-warning system. It allows us to transition from reactive crisis management — fixing things once they break — to proactive experience design. When we see a “cooling” trend in resilience metrics, we can intervene with targeted support, training, or resource reallocation before the friction translates into project delays or talent attrition.

Conclusion: Sustaining the Momentum

Quantifying cultural resilience is not an academic exercise; it is a fundamental shift in how we lead in an era of constant change. Data provides the foundation, but the true impact lies in how that data informs our actions and our empathy as leaders.

Data as Dialogue

Numbers should never be used to “police” culture. Instead, use these metrics to start deeper human conversations. When the data shows a dip in resilience, it is an invitation for leaders to step onto the floor, listen to the frontline, and ask, “How can we better support you through this transition?” The goal is to use data to facilitate connection, not to replace it.

The Futurologist Perspective

As we look toward the 2030s, the primary competitive advantage will not be a superior product or a cheaper supply chain — it will be a superior Resilience Quotient (RQ). Organizations that can measure and master the art of “bouncing forward” will outpace their competitors who are still stuck in the “bounce back” mentality. Developing this capability today is an investment in your organization’s future existence.

Final Call to Action

Stop managing the change as a list of tasks. Start designing the experience of the people navigating it. When you quantify resilience, you make the invisible visible, giving you the power to build a culture that is not just change-ready, but change-proof.

“The speed of your transformation will always be limited by the speed of your culture. Measure what matters, and lead with the heart.” — Braden Kelley

Frequently Asked Questions

What is the primary difference between Readiness and Resilience?

Readiness is the ability to start a transformation (having the tools and plan), whereas Resilience is the ability to endure, adapt, and “bounce forward” during the friction of the actual journey.

Why should we use “Silence” as a metric?

Silence often indicates a drop in psychological safety. When employees stop providing constructive friction or feedback, they have likely shifted from active participation to passive compliance, which is a leading indicator of burnout and project failure.

What is an Experience Level Measure (XLM)?

Unlike an SLA (Service Level Agreement) which measures technical uptime, an XLM measures the qualitative “human uptime”—the sentiment, friction, and engagement levels of the people interacting with a new process or system.

Image credit: Google Gemini

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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!

—————————————————————-
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

———————————

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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