An antipattern that I see in startups constantly is Senioritis. This normally happens when the startup finds some success and wants to upgrade its product and engineering teams. Typically at this stage, new leaders are hired and there is a we need to grow up vibe. These new leaders typically are hired from established companies/startups and bring with them their approaches. Continue reading “Premature optimization is the root of all evil”→
Accountability is one of those topics that sounds super easy but is the hardest to get right in practice. A recurring pattern in organizations is
The top of the totem pole (exec team, org VP’s) get together and decide the strategy for the year
It gets broken down into priorities and goals for the year
Its gets documented and passed downwards via some process
The entire organization references the document and should have visibility into priorities and be completely aligned
Starting from the top every node in the hierarchy points to the document and downward and says I hold you accountable to this. This process continues until you reach the individual contributor at the bottom of the tree.
The organization achieves 30% of what’s on the priority list
The accountability stack unwinds upwards with the feedback that either
The goals were not clear
Stuff changed midstream
Reasons why the goal was missed
Go back to Step 1
This loop repeats like clockwork. Welcome to accountability theatre.
My current obsession is the topic of signaling. Julie Zhou posted an interesting newsletter last week about team dynamics and feedback. The central theme in her post was about creating a document called the user guide to you and how it helped her level set with her team.
Something about that post didn’t sit right with me. It made it to hacker-news and the comment section gave me a few clues on why I had such an allergic reaction to the post. I have had to a few times in my career, write a user guide like Julie described. I’ve always found it uncomfortable, but never dug deeper. I wrote the document and carried on, treating it as a piece of paperwork that I have to get out of the way.
Tell me if this sounds familiar. It always begins with a workshop. We all gather in a room and talk about the mission of the company. We talk about who we want to be when we grow up as a company. We discuss how we want our customers to feel when they interact with us, we talk about how we want to feel. There are brainstorming exercises, discussions with word-clouds, and visceral debates on logo design. What is our brand identity? what is our company identity? – deep deep discussions. This culminates with a big fat book with detailed instructions on how the logo should look, what type of font you should use, what type of words to use, and the approved color palette.
In the last few weeks, the tech world has been abuzz with GPT3. There has been a Cambrian explosion in demos that look super cool. A16Z has a great podcast that goes through the details that is a must-listen.
How GPT3 works. A visual thread.
A trained language model generates text.
We can optionally pass it some text as input, which influences its output.
The output is generated from what the model "learned" during its training period where it scanned vast amounts of text.
Every business will eventually have to get into the financing business. Financing is a fancy word for lending and it has been around since the dawn of civilization. In this post, I will attempt to describe a simplified mental model for lending.
What is lending at its core?
Lending is a contractual relationship between two parties. One of them has something that the other needs. The lender, who has the thing and the borrower, who wants the thing. Since the dawn of mankind, the thing to want is productive assets. You start with borrowing a plow, borrowing some land, borrowing some seeds – you get the idea. As mankind progressed and the next abstraction of money came into being, money is the asset that everybody wants. Money is the path to get to productive assets. The lender of money wants to get compensated for giving his asset to the borrower. He is giving up the use of the asset and needs an incentive to compensate for the lost opportunity cost – this is the interest. Every contractual relationship has to have a time frame specified. In lending, this construct is described by the repayment term i.e over what period of time does the lender get their money back.
For our last 10K club we discussed Shopify ($SHOP). Giorgio has a fantastic post going into the 10k details. The bull case for Shopify is all over the interwebs but to truly understand the company, it’s useful to formulate the other side of the argument. In this post lets deep dive into Shopify’s business model and strategy and work out the bear case. Standard disclaimer: this is not investment advice and I do not hold any positions in $SHOP. This is a thought experiment using the good business/bad business framework.
When a management with a reputation for brilliance tackles a business with a reputation for poor fundamental economics, it is the reputation of the business that remains intact. – Warren Buffet
As I age in the business world, I have internalized this buffet quote. I superficially understood it early on in my career, but now I understand it! With fintech as the backdrop, this post is a view of my mental model on business models and gross margins in general. What makes a good high gross margin business?
Let’s start with a 30,000 ft view of what forms a business. Businesses exist to provide value to a set of customers via the products they create. A firm solves a need and customers pay them to solve that need. At its core, a company is a machine that takes raw ingredients (physical widgets, human capital, and intellectual capital) and transforms them into products that customers pay for. Raw ingredients cost money (cost centers) and customers pay money (revenue centers) for the finished product. A good business, in the long run, generates a consistent profit i.e (revenue – cost) is a positive number. Profit takes various forms such as free cash flow, EBIT or EBITDA – but the simple model holds, value creation only happens when what you get for the product is higher than what it costs to make it.
A question I wonder a lot about is, What is the long-run curve of a direct response paid marketing channel? The intuitive theory is that in the beginning, you expect your cost to be high relative to your LTV. The starting curve looks like the below
In this post lets delve deeper into the mechanics of channels. As mentioned in my previous post, do not start this exercise before you have locked down your product value proposition and positioning.
Think deeply about LTV and set guardrails
What does the economics of your business look like? The most important thing is to align on is the value of your customer to you. What is the long term value of the customer (LTV)? Don’t be confused by the term “Long”. It’s up to you on how long you consider a customer to be using your product. Early on in a startup, it is better to have shorter periods. The more mature you are, you will have actual data on how long users use your service. You have to start by nailing down the exact equation on how you calculate LTV. This also forces you to think about the unit economics of the business. The biggest issue isn’t in creating the equation for LTV rather it’ getting a broad agreement with the team on the equation. Everybody has to believe in the assumptions and understand the specifics of how LTV is calculated. Continue reading “Shouting from the rooftops, Channels 101 for Product Managers”→
Subscribe to Monetary Musings and get regular updates