Why does fortune favour the focused? It’s the universe’s way of saying,

‘Hey, you actually paid attention, here’s a cookie!’

Why Fortune Favours the Focused

• Why Read:

  • This article provides a compelling framework for founders to ruthlessly prioritize their limited resources and decision-making, grounded in psychological research.

• Featuring:

  • Rick Zullo (@Rick_Zullo), Co-Founder and Managing Partner at Equal Ventures

• Link: 

  • “Hick’s Law – Why Fortune Favors the Focused”

Key Concepts and Tactics:

1. The Importance of Focus and Maximizing Scarce Resources:

   • Point: As a startup, intentional focus on maximizing the reach and impact of scarce resources is critical to success.

   • "For the last 15 years, the economy (and venture world) has been a world of excess, not scarcity. This has created a whole host of challenges, but we often say something that brings us back to center at Equal, 'Fortune favors the focused'."

   • "As a startup, resources are deliberately scarce. Your role as a founder is to maximize the reach of those resources and make your company as valuable as possible on those before you need to raise additional capital. To do this, you need to be incredibly surgical, concentrating your resources behind a concise plan to maximize its chance of success."

2. Understanding Hick's Law and Decision-Making:

   • Point: Hick's Law demonstrates that more options lead to longer, more costly decision-making, so focus is critical.

   • "Hick's Law asserts the more options available to a person, the longer it will take (and the more costly it will be) to decide which option is best. When deciding between more choices, the response time required to come to the right decision is longer given not only the time processing each option (b) and the time between decision making."

   • "Simply by paring the playbook down and reducing the number of decisions you have to make; you can improve both the speed and efficacy of making critical choices for your business."

3. Avoiding the Trap of Optionality:

   • Point: Having too many options can actually reduce the likelihood of achieving any of them, so focus is paramount.

   • "Paradoxically, the more options you leave open for your business, the less likely you are to achieve them. Optionality isn't about establishing a breadth of infinite options, but rather best positioning yourself for the right potential downstream pathways."

   • "Diffusing resources across multiple different options reduces the process power you have in achieving critical mass for any of them."

4. Pursuing Reversible vs. Irreversible Decisions:

   • Point: Make quick, educated bets on "reversible" decisions, rather than getting stuck in analysis paralysis.

   • "Rather than getting lost in analysis paralysis, you are better off make an educated bet of the most advisable path and letting the data guide you. While "irreversible decisions" require greater collaboration and consensus, many of the decisions a business has to make can be made with minimal consequence."

   • "Building a great company requires countless tough decisions. Scoping down that array of choices to make those decisions a bit easier can go a long way in honing focus for the company and alleviating the cognitive exhaustion you might otherwise from deciding and pursuing so many options."

5. The Power of Simplicity and Execution:

   • Point: Focus and simplicity are essential for startup success, even if not a guarantee.

   • "Like many of the best things in life – startup strategies are best when craftly planned, swiftly executed and remarkably simple. Focus isn't going to guarantee your success, but it's certainly going to increase your odds."

Build a World-Class Data Org

Why Read: 

• This article provides actionable insights on building an effective, business-oriented data and analytics function - making it an essential 20-25 minute read for any startup founder looking to maximize the impact of their data capabilities.

Featuring:

• Lenny Rachitsky(@lennysan), Author at Lenny’s Newsletter and Lenny’s Podcast interviews Jessica Lachs(@jesslachs), Global Head of Analytics & Data Science at DoorDash

Link:

• “Building a world-class data org | Jessica Lachs (VP of Analytics and Data Science at DoorDash)”

Key Concepts and Tactics:

1. Build a centralized data/analytics team rather than embedding analysts in different departments

   • Quote: "I believe a central model, a center of excellence is superior and I'm happy to talk about why, but that's something that I feel quite strongly about... we've experimented in the past with the alternative, so putting it into a business unit and it's just much more problematic and I think the value you get from a central model is far greater than some of the things that you might lose."

2. Ensure your data team is proactively finding opportunities and insights, not just answering questions

   • Quote: "For me, analytics is a business impact driving function and not purely a service function, not just answering the why, but answering the, "What do we do now that we know this?" ... I think there are analytics teams at other companies where they are answering people's questions, maybe even through Jira tickets… we're building dashboards."

3. Focus on short-term, measurable metrics that drive long-term outcomes

   • Quote: "Ultimately, you want to find a short-term metric you can measure that drives a long-term output. So people always talk about, "Oh, we want to drive an improvement in retention." Retention is a terrible thing to goal on. It's almost impossible to drive in a meaningful way in the short term, and yet you want to be able to experiment and iterate quickly. So what are the things that drive retention? What are the inputs?"

4. Keep metrics simple and easily understandable

   • Quote: "I think keeping things simple is another thing I've learned over the years, maybe it's data scientists, but they tend to love these composite metrics with a coefficient. "We're going to wait this input at X and this input at X+2." And then you end up with a metric that nobody really understands that doesn't actually mean anything. ... So I always encourage folks, just pick something simple, even if it's not perfect and your composite would be more perfect."

5. Quantify different business levers in terms of a common currency to make trade-off decisions easier

   • Quote: "We spend a lot of time quantifying things in terms of a common currency. So for example, if I were to lower price by a dollar, what would I get in terms of, we'll say, volume? Well, what if I lowered delivery times by a minute? What do I get for that in terms of volume? And so now you can make trade-offs between maybe your marketing team and your logistics team because you have this common currency that everyone can talk about."

6. Focus on edge cases and fail states, not just averages

   • Quote: "With metrics, we are often looking at the average, and I think we talked about this a little bit earlier, but making sure that you're looking at the edge cases and your fail states is also really important. And so we often will set goals actually and create metrics around those edge cases."

7. Foster a culture of extreme ownership

   • Quote: "I think even today I expect of my team that same extreme ownership over the outcomes. And so I'm more interested in our team figuring out how to solve a problem than the box that someone fits in like, "I'm a data scientist and so I only do these things." Right? It's like, "No. I mean, yes, you are a data scientist, but your goal is to figure out what's happening, and if that means that you're going to pick up the phone and call customers, then that is what you're going to do.""

8. Don't be afraid to hire people without traditional backgrounds for your data team

   • Quote: "I think the only thing that I want to reiterate is that you don't necessarily need a formal training in whatever it is you're building. And I think that also goes towards the folks that you hire onto the team. ... I think that that's because my own experience coming over from operations, from being a GM and making that transition into analytics, I find that I'm drawn to other folks who want to make a similar transition."

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