Management

OKRs & KPIs

1. Metrics vs KRs - boils down to a starting value.

2. OKRs vs KPIs by filipe castro, 1, 2, 3

Data Science OKR KPI

1. OKR vs KPI, strategic vs tactical

2. Difference between KPI targets and goals

3. Comet ml on medium

by Cecelia Shao Comet ml

1. For the Data Driven manager (not ds)
2. Measuring DS business value
3. Best KPIS for DS - the best is what not to do

Management

1. Important Traits To Help You Become A Better Data-Science Manager, by Dr. Ori Cohen
2. 7 management styles and how to use them
3. 7 leadership styles (similar to the above)

4. The secret sauce of DS management by Shir Meir Lador
5. rework by Google - what makes a great manager

Project Management

1. Data-science? Agile? Cycles? My method for managing data-science projects in the Hi-tech industry, by Dr. Ori Cohen
2. Lessons learned leading AI teams, by Shir Meir Lador
3. How to avoid conflicts and delays in the AI development Part 1, Part 2, by Shir Meir Lador

Building Teams

1. rework by google - understanding team effectiveness
2. Conway's law "Organizations which design systems are constrained to produce designs which are copies of the communication structures of these organizations."

3. team topologies, youtube

   1. key concepts
   2. DS are "Complicated Subsystem team: Phd Level, great expertise, in depth knowledge.

   3. feature teams are "Stream-aligned team"

   4. enabling teams help bridge the gap in knowledge for feature teams, such as architecture

   5. platform team - providing a platform to speed up feature teams.

   6. team topologies article - A complicated-subsystem team is responsible for building and maintaining a part of the system that depends heavily on specialist knowledge, to the extent that most team members must be specialists in that area of knowledge in order to understand and make changes to the subsystem. [1]
   7. team topology for ML
   8. team topologies for data engineering
   9. towards data mesh: data domains and team topologies
4. atlassian - "it's important to understand that not every team shares the same goals, or will use the same practices and tools. Even the way a team is composed shouldn’t be standardized. Different teams require different structures, depending on the greater context of the company and its appetite for change. "
5. good article that talks about conway's law and team topologies by mark mishaev

   1. Quote "The goal of this team is to reduce the cognitive load of stream-aligned teams working on systems that include or use the complicated subsystem. The team handles the subsystem complexity via specific capabilities and expertise that are typically hard to find or grow.

      Examples of complicated subsystems might include face-recognition algorithms, machine learning approaches, real-time devices drivers, digital signal processing, or any other expertise-based capability that would be hard to embed directly within the stream-aligned team"

6. team patterns building an eng team by Kenneth Lange - an alternative to team topologies?

   "In my experience there are four general team patterns that most companies follow. Yes, they have tweaked them to fit their circumstances, but the overall idea behind the pattern remains the same:

   1. Technology Team: The team is formed around a technology, such as Android. For example, a team of mobile developers who build and maintain a mobile app.

   2. Matrix Team: The developers report to a Development Manager, but they are “lend out” to cross-functional product or project teams where they do their daily work.

   3. Product Team: The team is oriented around a product area, such as billing. It’s cross-functional, but all people on the team, regardless of their specialization, report to the same line manager.

   4. Self-Managed Product Team: The team is oriented around a product area. But the management of the team is divided into technical leadership, typically handled by an Engineering Lead on the team, and people management, typically handled by an Engineering Manager outside the team."

7. another good article by Ryan Dawson

   “Organizations not only need to strive for autonomous teams, they also need to continuously think about and evolve themselves in order to deliver value quickly to customers” — Team Topologies

[1] Book: Skelton, Matthew, and Manuel Pais. Team Topologies: Organizing Business and Technology Teams for Fast Flow. IT Revolution Press, 2019.

1. Full cycle DS

Scaling Agile - Agile Approaches

1. The spotify "model" - squads tribes chapters guilds

   1. Scaling agile snapshot 2012
   2. Scaling Agile at Spotify 2014 - Joakim Sunden and Anders Ivarsson
   3. inside Spotify by Andres Ivarsson (spotify) 2016
   4. Spotify eng culture p1 p2 2014 youtube 2017 by Henrik Kniberg
   5. Spotify engineering colture 2017 youtube
   6. how things dont work in spotify and we are trying to solve them 2017 and youtube
   7. you can do better than the spotify model, video - agile 2017 - Joakim Sundén

      "Spotify is used as a framework/model copied by others, but Spotify's model isn't without challenges even for Spotify

      Encouragement that it's always hard AND it's always possible to improve

      It's great to be inspired by others but at the end of the day you need to face your difficulties and solve your problems yourself

      You can succeed with autonomy by never giving up; it comes with challenges and benefits"

   8. failed squad goals 2020, listen on spotify, blowback response
   9. there is no spotify model for scaling agile
   10. spotify model sucks by erwin verweij
   11. how to structure eng team by yotam hadas
   12. spotify model - I dont think it means what you think it means - "Don’t fool yourself and others. The Spotify engineering culture is NOT about their organisational structure. It is how people are allowed to determine what to do. It’s about autonomy. It’s about having a culture of safety. Among others. I advise you to revisit the videos so that you can experience it yourself." - Willem Jan Ageling
   13. balancing autonomy with accountability - edwin dando
2. "shape up" book (under 200)
3. SAFe 5 - scaled agile framework
4. Safe agile principles

Working with partners

Culture building

Psychological Safety

1. (great) has a lot of tips on how to measure - high performing teams need PS
2. high performing teams need psychological safety a summary by microsoft
3. five keys to successful google team, 1st one is PS

Settings standarts

Career development

1. development plan for managers
2. for junior DS

Books

1. People management

   1. (good) the effective manager

   2. radical candor

   3. managing humans

2. Company Management

   1. The CEO within

   2. business without the bullshit

3. Collaborations and influence

   1. (good) crucial conversations, 1, 2, 3
4. Negotiations

   1. never split the difference. TLDR, summary, summary & commentary , summary, 2, 3, 4, youtube, chris voss, 2, 3
5. Manipulations

   1. The prince, 1, 2, 3
   2. The 48 Laws of Power - “Amoral, cunning, ruthless, and instructive, this multi-million-copy New York Times bestseller is the definitive manual for anyone interested in gaining, observing, or defending against ultimate control – from the author of The Laws of Human Nature.
6. Others

   1. (good) High output management

   2. multipliers,

   3. radical candor,

   4. Trillion dollar coach,

   5. The HP way,

   6. How to measure anything,

   7. Mindset,

   8. (good) The hard thing about hard things

   9. principles life & work, summary