"Day 2 is stasis, followed by irrelevance, followed by excruciating painful decline, followed by death. And that is why it is always Day 1." — Jeff Bezos.
Driven by that mental model, it's easy to see why Bezos was so committed to maintaining a Day 1 approach at Amazon. To sustain Day 1, Bezos encouraged a customer-centric obsession, a focus on pioneering, striving towards operational excellence, and the centrality of making high-quality decisions quickly. This model focuses on that final point, drawing on four practical techniques Bezos used to bring it to life.
High-velocity Decisions involve quickly acting on reversible decisions; making decisions with partial information; being okay to disagree and commit anyway; and rapidly escalating misalignment.
FOUR ELEMENTS OF HIGH-VELOCITY DECISION.
Benzos argued that Day 2 companies make high-quality decisions slowly. Instead, he recommended High-Velocity Decisions, which involve:
- Identifying reversible vs irreversible decisions: Bezos called them one-way doors vs two-way doors. Irreversible decisions, or one-way doors, must be considered methodically and slowly. But reversible, or two-way doors, “can and should be made quickly by high judgement individuals or small groups.”
- Making decisions with 70 to 90% of the information: It’s reassuring to see the full picture before making a decision, but that is a rare luxury. Bezos' model involves making decisions with ‘most’ of the information or risk becoming too slow.
- Using the phrase ‘disagree and commit’: Rather than continuing to argue over a point, commit to testing out a hypothesis together.
- Escalating real misalignment: When teams have fundamentally different objectives, the issue should be immediately escalated to a more senior team to make a call.
IN YOUR LATTICEWORK.
The High-Velocity Decision model is a useful decision-making framework for any individual or team wanting to increase their agility and work in a fast, competitive environment. It embraces a Bias to Action, aiming to empower fast decisions and experimentation.
In that sense, it plays well with the iterative nature of Agile Methodology and creating Feedback Loops with further data revealed through fast action. In more complex situations, you might also want to explore combining this model with Prototypes and/or the Cynefin Framework.
For better results, combine this model with the Circle of Competence, to weigh up your expertise (or lack thereof) in a field before you make a decision based on partial information, and Second-Order Thinking, to consider the downstream impact of seemingly reversible decisions.
Explore the Regret Minimisation Framework for another Bezos decision-making model that empowers you to make 'big and brave' decisions. And finally, dive into Entropy, and the universal tendency towards disorder and decay, to fully absorb the difference between Day 1 versus Day 2 companies.
- Choose a bias to action with reversible decisions.
Ask ‘what are the consequences of this decision’ and consider whether it can be undone — does it involve a one way or two-way door. If it is reversible, take action fast to explore the option further and learn more.
- Embrace decision-making in uncertainty.
The more important a decision is, the more time we are tempted to assign to it, which can lead to decision paralysis. Committing to a decision with 70 to 90% of the information is enough, it keeps you in movement and empowers you to discover more information and insights based on your activity.
- Suspend disbelief and experiment.
Differences of opinion on a decision can be reframed as two opposing hypotheses. At a certain point, rather than continuing to argue, commit to an experiment. This might involve setting up parameters to understand what success or failure looks like, and it definitely involves you fully committing to try and make it work even if you disagreed. Simply ‘disagree and commit.’
- Escalate different world views.
If a team of peers has a different world view based on fundamentally different objectives, there’s no point in continuing the debate. Identify these differences quickly and immediately escalate them.
Greenlighting Amazon Prime.
Bezos has said that the decision to greenlight Amazon Prime was ultimately based on intuition because the data did not provide a clear way forward. He explains that this is a common challenge with a new, untested initiative.
Bezos said: “There wasn’t a single financially savvy person who supported the decision to launch Amazon Prime. Zero. Every spreadsheet showed that it was going to be a disaster. So that had to just be made with gut.”
“You collect as much data as you can. You immerse yourself in that data,” said Bezos, “but then make the decision with your heart.”
Even reversible decisions have an Opportunity Cost. The time and effort invested in that choice and then possibly backtracking have a cost in relation to the option forgone.
At the same time, the examples provided by Bezos ‘using his gut’ and intuition are problematic when we consider behavioural economics, Fast and Slow Thinking, and unconscious bias.
It's true that experts have deep, often unconscious pattern recognition within their field of expertise so can often make reliable, fast, gut-based decisions. But it's also true that such gut reactions lack a rational consideration and are prone to be impacted on by countless heuristics, particularly in new and unfamiliar situations.
The high velocity decision model is a useful decision making framework for any individual or team wanting to increase their agility and work in a competitive environment.
Use the following examples of connected and complementary models to weave high velocity decisions into your broader latticework of mental models. Alternatively, discover your own connections by exploring the category list above.
- Agile methodology: sharing the ideas of having a bias to action and testing ideas.
- Lean startup and minimum viable product: again, embracing the idea of quickly testing assumptions rather than discussing them forever.
- Second order thinking: even if it is reversible, will the decision have second order and beyond implications that are irreversible?
- Circle of competence: making fast decisions from your circle of competence.
- Pareto principle: when making a decision based on 70 to 90% of the information, consider whether it includes the critical information.
- Inversion: considering what will be the cost of making the wrong decision in assessing whether it is reversible and what’s at stake.
- Redundancy/ margin of safety: to better make decisions with minimal risk.
- Fast and slow thinking: and the traps of relying on fast thinking.
- Availability heuristic: one of many cognitive biases that might arise from fast decision making.
- Prototypes: supporting a low risk approach to a bias for action.
This approach was described by Jeff Bezos in his 2016 letter to stakeholders. Here's how it starts:
“'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."
The essence of the following 'starter pack' has been summarised into the High-Velocity Decisions model that you've been exploring.
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