1/ Career decisions about your next role/opp are the most impactful decisions you might make in your career. As an operator, all of your eggs are in one basket at a time, and we get a limited number of swings at the plate. So getting good at these decisions is important...
2/ At FB, Bangaly managed Rotational PM's. At the end of a rotation, he'd have the same convo: How are you going to choose your next rotation/role?
As a result, Bangaly got a lot of reps guiding this type of decision and created a framework to help with it...
3/ The framework is Impact = Skills x Environment
The goal is not to try and boil this type of decision down to a spreadsheet of inputs that spits out the answer, but rather it helps with 4 things...
4/ It can help with:
- Identify individual variables that are inputs into the decision.
- Evaluate each individual variable in a structured way.
- Understand the relationship between each variable.
- Narrow the decision down to the most important variable
...
5/ This helps avoid mistakes like
- Choosing to work on the shiny object
- Thinking you just need to improve your skills to progress
- Short-term thinking
- Solving only for brand
- Mixing perception and truth
6/ Impact = Environment x Skills means:
a. Impact fuels career progression. It is the thing you need to solve for.
b. Impact is the product of Environment and Skills
c. If our skills are great, but the environment is wrong (or vice versa), then we aren't set up for success.
7/ Environment = Everything that enables you to do great work that is outside of your direct control. This breaks down into:
a. Your manager
b. Resources
c. Scope
d. Team
e. Compensation
f. Company culture
8/ Skills = things that are within your direct control that enable your success. This breaks down into:
a. Communication
b. Influence/Leadership
c. Strategic Thinking
d. Execution
9/ Bangaly likes to give each of these a score from 0 to 2.
0 = Major Bottleneck
1 = Neutral
2 = Major Amplifier
...
10/ Here is an example of what evaluating your Manager on this spectrum might look like...
11/ Here is another example of what evaluating Resources might look like...
12/ In all of these cases, Bangaly recommends after evaluating each variable, to do a few things:
a. Identify the variable that matters most
b. Evaluate your ability to change each variable
c. Understand the time horizon it will take to change each variable.
13/ Throughout all of this, Bangaly (@iambangaly ) has a few keys. The first is that the most important variable in the equations is your manager. Here is why...
14/ "A great manager can influence your scope, advocate for more resources, help you develop your skills, guide you to better execution, and more. So even in situations where other variables are low if your manager is a major amplifier (1.5 to 2) give them time to figure it out."
15/ Also "Great execution with poor communication limits your impact over time. You could be doing great work, but without great communication then it won't receive the attention that it deserves. Embrace that communication is more influential than the other skill variables."
This is not an exhaustive list by any means, but these are 6 mistakes I see in defining metrics over and over....
1 - Metrics before Strategy
Your metrics are a reflection of your strategy. They help answer, is the strategy working? Metrics without strategy is looking at a bunch of random numbers. Define the strategy before you define your metrics.
2a - Definition Is More Important Than A Dashboard
People focus on "building a dashboard." 10X more important is choosing which metrics are important and defining those metrics well. Defining is more complicated than people think...
Almost every team I talk to says "Our data is mess!"
@crystalwidjaja (Fmr SVP BI & Growth at Gojek and @reforge Partner) wrote an excellent piece on the real root causes of analytics failures, and a step by step process on how she thinks about it: reforge.com/blog/why-most-…
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First, if you don't know @crystalwidjaja and the story of Gojek, it's impressive. Crystal joined at 30 people and helped them scale to complete more daily food orders than Grubhub, Uber Eats, and DoorDash combined, and more trips than Lyft per day 🤯
There are a lot of symptoms of bad analytics/data:
1. Lack of shared language 2. Slow transfer of knowledge 3. Lack of trust 4. Inability to act on data quickly
The Entertainment Value Curve - Awesome post by @ravi_mehta (Former CPO Tinder, FB, TripAdvisor) on product strategy in the social space and why TikTok is on 🔥 and Quibi is 📉
Word of Mouth is critical, but notoriously hard to measure and therefore hard to influence. @ybhaijee (Former VP Growth @ Eaze) wrote an excellent post on @reforge about The Word of Mouth Coefficient with some analysis: reforge.com/blog/word-of-m…
Full Thread 👇👇👇
When @ybhaijee and @tomaspueyo worked at Zynga together, they wanted a metric for Word of Mouth that was:
1. Based on Active Users 2. Stable enough to be used in forecasting 3. Could be influenced with product/marketing initiatives
The result was the Word of Mouth Coefficient
WOM Coefficient: Says that for every X active user, you will bet Y new organic users in that time period.
One key 🔑 is that rather than basing the metric on new users (like K-Factor) they based it on active users. Retention is at the foundation of every growth loop...
All product work is not equal. There is a common issue of over-applying one process, measure of success, and strategy to all product problems. @far33d and @onecaseman wrote a monster post talking that is well worth the read -> reforge.com/blog/product-w…
Full thread 👇
"A common conflict I've seen is when product leaders try to apply a single process to all product work...growth and feature work are different and energy is wasted trying to force-fit into the same process, success metric, and approach." - @far33d
There are four types of product work beyond product-market fit:
1. Feature Work 2. Growth Work 3. Scaling Work 4. Product Market Fit Expansion
"What got you here, won't get you there." @onecaseman and @far33d broke down the transition from Product Manager to Product Leader. Excellent insights from @iambangaly and @ravi_mehta as well.