From a talk at Tech.Rocks 2020 For effective, modern, cloud-connected software systems we need to organize our teams in certain ways. Taking account of Conway’s Law, we look to match the team structures to the required software architecture, enabling or restricting communication and collaboration for the best outcomes. This talk will cover 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

1. TeamTopologies.com
@TeamTopologies
Beyond the Spotify model
using Team Topologies for
fast flow and organisation evolution
Matthew Skelton, Conflux
co-author of Team Topologies - @matthewpskelton
Tech.Rocks - 10 December 2020

2. Matthew Skelton
2
Co-author of the book Team Topologies
Founder at Conflux - confluxdigital.net
Experience as: software developer,
system architect, technical director,
change enabler, conference organizer...
Twitter: @matthewpskelton

3. 3
The Spotify Model
Limitations
Team Topologies
Getting started

4. 4

5. 5

6. The Spotify model of
team design for
software delivery
6

7. 7
Henrik Kniberg & Anders Ivarsson, 2012
https://blog.crisp.se/wp-content/uploads/2012/11/SpotifyScaling.pdf

8. 8
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

9. 9
The Spotify model has
been hugely helpful to
100s of organizations

10. The Spotify model
helps to...
10

11. 11
Encourage flow
of change

12. 12
Establish and
clarify team
responsibilities

13. 13
Promote good
kinds of team
collaboration

14. 14
Plan and budget
for cross-team
enablers

15. 15
The Spotify model helps to
Encourage flow of change
Establish and clarify team responsibilities
Promote good kinds of team collaboration
Plan and budget for cross-team enablers
@matthewpskelton / @TeamTopologies

16. Limitations of the
Spotify model
16

17. “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
17

18. There is No Spotify Model
18
Marcin Floryan, 2016
https://www.infoq.com/presentations/spotify-culture-stc

19. 19
Software sizing
and cognitive
load

20. 20
Heuristics for
Conway’s Law

21. 21
Patterns for
team
interactions

22. 22
Triggers for
change and
evolution

23. 23
We also need to address
Software sizing and cognitive load
Heuristics for Conway’s Law
Patterns for team interactions
Triggers for change and evolution
@matthewpskelton / @TeamTopologies

24. Team Topologies
24

25. topology
the way in which constituent parts are
interrelated or arranged
Greek: τοπολογία (τόπος == ‘place’)
25

26. Team Topologies
26
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

27. Origins - DevOps Topologies
27
CC BY-SA devopstopologies.com
@matthewpskelton / @TeamTopologies

28. 28
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

29. 29
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

30. Team Topologies
30
Organizing business and
technology teams for fast flow
Matthew Skelton & Manuel Pais
Publication date: Sept 2019
IT Revolution Press
Pre-order from Amazon:
https://teamtopologies.com/book

31. 💥#1 on Amazon
Business and Organizational Learning
31

32. “innovative tools and concepts for
structuring the next generation
digital operating model”
Charles T. Betz, Principal Analyst, Forrester Research
32

33. Team Topologies for fast flow
Conway’s Law
Team-first
Thinking
Team
Interactions
Sensing for
Evolution
33

34. 34
Software sizing
and cognitive
load

35. 35
Team-first Thinking

36. 36
Team-first Thinking
The team is the means of delivery

37. 37
Team-first Thinking
Design for team cognitive load

38. 38
Team-first Thinking
Choose boundaries for team ownership

39. 39
Team-first Thinking
Physical and digital workspace

40. 40
Team-first Thinking
The team is the means of delivery
Design for team cognitive load
Choose boundaries for team ownership
Physical and digital workspace
@matthewpskelton / @TeamTopologies

41. 41
Heuristics for
Conway’s Law

42. 42
Conway’s Law

43. 43
Conway’s Law
Heuristic for ‘natural’ expected design

44. 44
Conway’s Law
Mirroring in tech system + human system

45. 45
Conway’s Law
Reverse Conway to mitigate worst effects

46. 46
Conway’s Law
Constraint on solution search space

47. 47
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
@matthewpskelton / @TeamTopologies

48. 48
Patterns for
team
interactions

49. 49
Team Interactions

50. 50
Team Interactions
3 defined Interaction Modes

51. 51
Team Interactions
Collaboration: 2 teams working together

52. 52
Team Interactions
X-as-a-Service: 1 provides, 1 consumes

53. 53
Team Interactions
Facilitating: 1 team helps another

54. 54
Team Interactions
3 defined Interaction Modes
Collaboration: 2 teams working together
X-as-a-Service: 1 provides, 1 consumes
Facilitating: 1 team helps another
@matthewpskelton / @TeamTopologies

55. 4 fundamental topologies
55
Stream-aligned team
Enabling team
Complicated Subsystem team
Platform team

56. 4 fundamental topologies
56
Flow of change

57. 3 core interaction modes
57
Flow of change
X-as-a-Service
Facilitating
Collaboration

58. 58
Triggers for
change and
evolution

59. 59
Sensing for Evolution

60. 60
Sensing for Evolution
Not all teams in the org look the same

61. 61
Sensing for Evolution
Discover, then push to Platform

62. 62
Sensing for Evolution
Awkward team interactions are signals

63. 63
Sensing for Evolution
Evolve the org with changing ecosystem

64. 64
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
@matthewpskelton / @TeamTopologies

65. Getting started with
the Team Topologies
approach
65

66. Getting started
66
Explicit cognitive load
Large Conway mismatches
Team Interactions
Thinnest Viable Platform

67. 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
67

68. Getting started
68
Explicit cognitive load
Large Conway mismatches
Team Interactions
Thinnest Viable Platform

69. Are there major mismatches between
the team interactions and the required
software / system architecture?
What could be easily adjusted?
Large Conway mismatches
69

70. Getting started
70
Explicit cognitive load
Large Conway mismatches
Team Interactions
Thinnest Viable Platform

71. What would change if we adopted the
3 team interaction patterns?
Collaboration, X-as-a-Service, Facilitating
How would teams react & behave?
Team Interactions
71

72. Getting started
72
Explicit cognitive load
Large Conway mismatches
Team Interactions
Thinnest Viable Platform

73. How is your Platform defined?
What is the thinnest platform that
could work?
What’s needed to run an support it?
Thinnest Viable Platform
73

74. Getting started
74
Explicit cognitive load
Large Conway mismatches
Team Interactions
Thinnest Viable Platform

75. Review
75

76. 76
The Spotify model helps to
Encourage flow of change
Establish and clarify team responsibilities
Promote good kinds of team collaboration
Plan and budget for cross-team enablers
@matthewpskelton / @TeamTopologies

77. 77
We also need to address
Software sizing and cognitive load
Heuristics for Conway’s Law
Patterns for team interactions
Triggers for change and evolution
@matthewpskelton / @TeamTopologies

78. Team Topologies for fast flow
Conway’s Law
Team-first
Thinking
Team
Interactions
Sensing for
Evolution
78

79. Getting started
79
Explicit cognitive load
Large Conway mismatches
Team Interactions
Thinnest Viable Platform

80. Team Topologies
80
Organizing business and
technology teams for fast flow
Matthew Skelton & Manuel Pais
Publication date: Sept 2019
IT Revolution Press
Pre-order from Amazon.com:
https://teamtopologies.com/book

81. Sign up for news and tips:
TeamTopologies.com
81

82. Remote-
Friendly
Training
teamtopologies.com/training
82

83. Free Resources
83
Resources
teamtopologies.com/resources
Free tools & templates
github.com/teamtopologies

84. 84
🠊 teamtopologies.com/shop

85. TeamTopologies.com
@TeamTopologies
Feedback:
info@teamtopologies.com
@TeamTopologies

86. Thank you!
info@teamtopologies.com
Matthew Skelton, Conflux
@matthewpskelton
Manuel Pais, Independent
@manupaisable
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