Beyond the Spotify Model - using Team Topologies for fast flow and organization evolution - DTX Manchester 2024

Organizations worldwide are crippled by slow flow, tangled delivery, and teams waiting on other teams. The cost is $billions per year.

For effective, modern, organizations working with software-enriched services, we need to organize our teams in certain ways to take advantage of technology, human insights, and fast flow. Informed by Conway’s Law, we look to align the team structures to the required software architecture, enabling or restricting communication and collaboration for the best outcomes.

This talk covers the basics of organization design using Team Topologies, exploring a selection of key team types, and how and when to use them in order to make the development and operation of your software systems as effective as possible. The talk is based on the book Team Topologies by Matthew Skelton and Manuel Pais including first-hand experience helping companies around the world with the design of their technology teams.

Key takeaways:

1. Why using the “Spotify Model” of team design is not enough
2. The four fundamental team topologies needed for modern software delivery
3. The three team interaction modes that enable fast flow and rapid learning
4. How to address Conway’s Law, cognitive load, and team evolution with Team Topologies

Transcript

1. Beyond the Spotify model using Team Topologies for fast flow and organization evolution Matthew Skelton, Conflux - co-author of Team Topologies Keynote at DTX Manchester | 2024-05-23 K37
2. Photo goes here Matthew Skelton Founder at Conflux Co-author of Team Topologies “Ecosystem engineering” LinkedIn: linkedin.com/in/matthewskelton Mastodon: mastodon.social/@matthewskelton 2
3. 3 Book signing today Eficode stand D54 @ 13:00
4. 4 Would you like $millions in extra budget without having any lay-offs or offshoring?
5. 5 c.500 people
6. 6 $16 million +
7. 7 Unneeded coupling: c.$30k to $60k+ PPPY
8. 8 Unblock innovation via fast flow
9. 9 We help you to unblock innovation via fast flow and Team Topologies Coaching & consulting | Cohort learning | Community confluxhq.com
10. Team Topologies Organizing business and technology teams for fast flow Matthew Skelton & Manuel Pais IT Revolution Press, September 2019 Order via stores worldwide: teamtopologies.com/book 10 Over 150k copies sold!
11. “...innovative tools and concepts for structuring the next generation digital operating model” Charles T. Betz, Principal Analyst, Forrester Research 11
12. topology the way in which constituent parts are interrelated or arranged Greek: τοπολογία (τόπος == ‘place’) 12
13. Origins - DevOps Topologies 13 CC BY-SA devopstopologies.com confluxhq.com/devops-topologies
14. 14 Philip Fisher-Ogden, Director of Engineering at Netflix: “thanks for your insightful articulations of devops topologies. They inspired many discussions and helped us to think about what model Netflix teams could be/are using.” https://twitter.com/philip_pfo/status/999074792123740160
15. 15 Crystal Hirschorn, Director of Engineering at Condé Nast International “Your topological models resonated extremely well on both the Dev and Ops side btw! I like the balanced arguments, e.g. different perspectives, for each pattern.” https://twitter.com/cfhirschorn/status/1103387659890819073
16. Team Topologies 📗 16 Research over 5 years across multiple industry sectors Informed by 50+ peer-reviewed journal articles 30+ client organizations - consulting and training since 2013 with orgs in CN, EU, IN, US, UK, + Book: 12+ case studies from well-known organizations
17. Team Topologies - since 2019 17 Top 10 ‘Best Product Management Books’ (Book Authority) Adopted by 1000s of organizations worldwide: JP Morgan, ClearBank, Fidelity, Docker, Zalando, NatWest Group, USAF, GOV.UK, … Unlocking $10bn+ extra value in organizations around the world annually
18. Beyond the Spotify model using Team Topologies for fast flow and organisation evolution 18
19. The Spotify Model 19 Limitations of the Spotify Model Team Topologies Getting started
22. The Spotify model of team design for software delivery 22
23. 23 Henrik Kniberg & Anders Ivarsson, 2012 https://blog.crisp.se/wp-content/uploads/2012/11/SpotifyScaling.pdf
24. 24 The Spotify model Squad: semi-autonomous delivery team Tribe: family of Squads - related work Chapter: line management within a Tribe Guild: cross-Tribe interest/specialist group
25. 25 The Spotify model has been hugely helpful to 100s of organizations
26. The Spotify model helps to... 26
27. 27 Encourage flow of value
28. 28 Establish and clarify team responsibilities
29. 29 Promote good kinds of team collaboration
30. 30 Plan and budget for cross-team enablers
31. 31 The Spotify model helps to Encourage flow of value Establish and clarify team responsibilities Promote good kinds of team collaboration Plan and budget for cross-team enablers
32. Limitations of the Spotify model 32
33. “This article is only a snapshot of our current way of working - a journey in progress, not a journey completed. By the time you read this, things have already changed.” - Kniberg & Ivarsson 33
34. There is No Spotify Model 34 Marcin Floryan, 2016 https://www.infoq.com/presentations/spotify-culture-stc
35. 35 What’s missing from the (non-existent) Spotify model?
36. 36 Team-first thinking and cognitive load
37. 37 Heuristics for Conway’s Law
38. 38 Patterns for team interactions
39. 39 Sensing for evolution
40. Team Topologies 📗 40
41. 41 Team Topologies helps with Team-first thinking and cognitive load Heuristics for Conway’s Law Patterns for team interactions Triggers for change and evolution
42. 42 Team-first thinking and cognitive load
43. 43 Team-first thinking
44. 44 Team-first thinking The team is the means of delivery
45. 45 Team-first thinking Design for team cognitive load
46. 46 Team-first thinking Discover boundaries for team ownership
47. 47 Team-first thinking Physical and digital workspace
48. 48 Team-first Thinking The team is the means of delivery Design for team cognitive load Choose boundaries for team ownership Physical and digital workspace
49. 49 Heuristics for Conway’s Law
50. 50 Conway’s Law Any organization that designs a system (defined broadly) will produce a design whose structure is a copy of the organization's communication structure. — Melvin E. Conway
51. 51 Conway’s Law Heuristic for ‘natural’ expected design
52. 52 Conway’s Law Mirroring in tech system + human system
53. 53 Conway’s Law Reverse Conway to mitigate worst effects
54. 54 Conway’s Law Constraint on solution search space
55. 55 Conway’s Law Heuristic for ‘natural’ expected design Mirroring in tech system + human system Reverse Conway to mitigate worst effects Constraint on solution search space
56. 56 Patterns for team interactions
57. 57 Team interactions
58. 58 Team interactions 3 defined Interaction Modes
59. 59 Team interactions Collaboration: 2 teams working together
60. 60 Team interactions X-as-a-Service: 1 provides, 1 consumes
61. 61 Team interactions Facilitating: 1 team helps another
62. 62 Team interactions 3 defined Interaction Modes Collaboration: 2 teams working together X-as-a-Service: 1 provides, 1 consumes Facilitating: 1 team helps another
63. 4 fundamental topologies 63 Stream-aligned team Enabling team Complicated Subsystem team Platform team grouping
64. 4 fundamental topologies 64 Flow of change
65. 3 core interaction modes 65 X-as-a-Service Facilitating Collaboration Flow of change
66. 66 Sensing for evolution
67. 67 Sensing for evolution
68. 68 Sensing for Evolution Not all teams in the org look the same
69. 69 Sensing for evolution Discover, then push to Platform
70. 70 Sensing for evolution Awkward team interactions are signals
71. 71 Sensing for evolution Evolve the org with changing ecosystem
72. 72 Sensing for evolution Not all teams in the org look the same Discover, then push to Platform Awkward team interactions are signals Evolve the org with changing ecosystem
73. Getting started with the Team Topologies approach 73
74. 74 Explicit team cognitive load
75. How well can the team as a unit “grok” the systems they own and develop? Push some things into a Platform? Are skills or capabilities missing? Explicit cognitive load 75
76. 76 Large Conway mismatches
77. Are there major mismatches between the team interactions and the required software / system architecture? What could be easily adjusted? Large Conway mismatches 77
78. 78 Team interactions
79. What would change if we adopted the 3 team interaction patterns? Collaboration, X-as-a-Service, Facilitating How would teams react & behave? Team Interactions 79
80. 80 Thinnest viable platform
81. “A TVP is a careful balance between keeping the platform small and ensuring that the platform is helping to accelerate and simplify software delivery for teams building on the platform.” (p.101, Team Topologies) 81
82. How is your Platform defined? What is the thinnest platform that could work? What’s needed to run an support it? Thinnest Viable Platform 82
83. Review 83
84. Team Topologies helps with… 84
85. 85 Team-first thinking and cognitive load
86. 86 Heuristics for Conway’s Law
87. 87 Patterns for team interactions
88. 88 Sensing for evolution
89. 89 Unblock innovation via fast flow
90. 90 Accelerate your journey today! Join the waitlist: Or sign up via confluxhq.com
91. 91 We help you to unblock innovation via fast flow and Team Topologies Coaching & consulting | Cohort learning | Community confluxhq.com
92. 92 Book signing today Eficode stand D54 @ 13:00
93. thank you confluxhq.com Copyright (c) 2017-2024 Conflux group of companies. All Rights Reserved. The name “Conflux” and the filled C device are Registered Trademarks ® in multiple jurisdictions.