Here's your newsletter, now I'm going back outside
and other useful stuff about product - Apr 2021
April flew by. The weather’s getting warmer, and for the first summer in my life I have a lawn to take care of….well not much of lawn yet, but I’m working on it.
Anyways here’s the best stuff I found on product this past month.
Features vs. Benefits
Customers don’t buy the features of your product, they buy the benefits they get from them. Harry breaks down a communication technique to highlight the benefits.
I’m reminded of the classic “you don’t sell a Fire Flower, you sell the flame-throwing abilities it gives Mario to roast those pesky Goombas.”
Short thread on the strategy questions you need to answer for B2B products: (a strategy primer in 10 tweets)
Shreyas breaks down the questions you need to answer to inform a strategy for B2B products. There’s enough to write a book on this topic as Shreyas references concepts from some best authors on strategy – Michael Porter and Hamilton Helmer.
If you’re a B2B PM without a clearly defined product strategy, this is a must-read.
💻 On the Web
Scaling Data: Data Informed to Data Driven to Data Led
Crystal argues that data needs to be seen as a strategic lever for growth, rather than a team to hire or set of tools to implement.
The right strategy is to match the needs of the business at its current stage with building the appropriate data capabilities in order for the business to scale into its next growth phase.
The prerequisite is key points of leverage that generate enough data for a dedicated data team to have an impact. Scaling a data team can have enormous benefits and she breaks it down into the following stages.
Most companies can fit themselves into one of three stages:
Stage 1: Data Informed. These companies are focused on building the business and getting to product-market-fit (stable user retention rates). The key business need is for data to provide operational visibility.
Stage 2: Data Driven. These companies have reached product-market-fit and are actively optimizing for specific users, behaviors, and experiences in the product at the feature-level. The key business need is for data to support the organization’s growth with scalable tooling, data products, and deep-dive insights.
Stage 3: Data Led. These companies are operationally run by data products, infrastructure, and services. The key business need is the “productization” of data services that unlock Product and Data Science teams, allowing them to automate operational decision-making and user product experiences.
It won’t all happen at once, it’s a continuous cycle of identifying business needs and building the necessary capabilities to help data unlock growth – which creates new business needs. Scaling your data team along the way is necessary to keep the cycle going.
Decision Making vs. Decision Understanding
Decision-making quality can make or break a product team, and getting to the optimal decision is hard. It’s not good to be indecisive, but it’s also not good to rush to a decision when more information would help make a better decision.
Humans are complex – so one of the first steps is to better decision-making is to establish a shared vocabulary around the decision that needs to be made.
Amazing things can happen when people from different disciplines work together. This approach is especially important for complex problems that benefit from diverse perspectives.
There's no magic framework that can instantly solve the problem. People require time to process—alone AND together.
They need safety to challenge their own assumptions and the assumptions of team members. To explore and dig. In our day-to-day, there is so much pressure to decide quickly. The end result is that premature converge makes decisions fall apart.
When a team comes together, with a shared understanding of each other and the problem at hand – decision-making can seem effortless.
Pre-mortems: How a Stripe Product Manager predicts & prevents problems before launch
It’s much better to prevent problems before they occur, as opposed to finding a solution once the problem has already surfaced. Creating shared vocabulary around the types of threats that could derail a product launch is a nice way to get the team thinking about potential scenarios they’d like to avoid.
The way I like to run pre-mortems now is to ask the team to list out their concerns about the project in three different categories:
🐯 Tigers - A clear threat that will hurt us if we don’t do something about it.
📃 Paper Tigers - An ostensible threat that you are personally not worried about (but others might be).
🐘 Elephants - The thing that you’re concerned the team is not talking about.
So after your pre-mortem meeting, you’ll start hearing your teammates mention “the Tiger Bob flagged” or “that Elephant mentioned during yesterday’s standup” when communicating over Slack, email, meetings, and even 1 on 1s.
Shreyas puts together a practical guide to help you run a pre-mortem with your team and explains the process in the video below.
That’s it for this month. Now go outside!
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