Ever think that something's slowing down your process but can't put your finger on it? Losing candidates in your hiring pipeline but can't spot the leak? Or maybe you know the problem but you're having trouble quantifying it and getting buy in to solve it? This session will serve as an introduction to systems thinking using real world engineering examples. You'll leave understanding what systems thinking is and how it can help you diagnose, quantify, and iteratively improve your processes to gain efficiency no matter which flavor of Agile (or whatever else) you happen to follow.

1. Systems Thinking
FOR ENGINEERING LEADERS

2. About Me
Hey! I’m Stacy Vicknair.
I’ve been in software development for 18
years, and in engineering leadership the
last 9 years
Microsoft MVP, 2009 – 2015
This year I went solo, focusing on
helping SaaS social enterprise founders
unclog their software development
processes.
https://stacyvicknair.com

3. Help! I need your feedback!
stacy@stacyvicknair.com

4. Agenda
The Basics
Deriving Metrics
Optimizing Flow
Broader Applications
Additional Resources

5. The Basics

6. The Basics: What is it?
“A system is a set of things – people, cells, molecules, or
whatever – interconnected in such a way that they produce
their own pattern of behavior over time.”
– Systems Thinking: A Primer by Donella Meadows

7. The Basics: A Caveat
• Everything we think we know about the world is a model.
• Our models do have a strong congruence with the world.
• Our models fall far short of representing the real world
fully.
- Systems Thinking: A Primer by Donella Meadows

8. The Basics: Stocks and Flows

9. The Basics: Stocks and Flows

10. The Basics: Variables and Links

11. The Basics: Variables and Links

12. An Example Process

13. Deriving Metrics

14. The DORA Metrics
•Deployment Frequency
•Lead Time for Changes (Cycle Time)
•Change Failure Rate (CFR)
•Time to Restore Service (Mean Time to Recover or MTTR)

15. Deriving Metrics: Flow Rates
Deployment
Frequency

16. Deriving Metrics: Cycle Times
Lead Time for Change

17. Deriving Metrics: Cycle Times (Again)
Mean Time to Recover

18. Deriving Metrics: Inflow vs Outflow
Change Fail
Rate

19. Deriving Metrics: A Note
“When a measure becomes a target, it ceases to be a good measure.”
– Goodhart’s Law
• Incentivized metrics become sub-optimal real quick.
• In addition to avoiding perverse incentives, balance metrics.

20. Optimizing Flow

21. OptimizingFlow: Bottlenecks

22. OptimizingFlow: Unavoidableloops

23. OptimizingFlow: Avoidableloops

24. OptimizingFlow: Avoidableloops

25. Broader
Applications

26. Broader Applications: Hiring

28. Resources: Books
Systems Thinking: A Primer by Donella Meadows
An Elegant Puzzle by Will Larson
Accelerate by Nicole Forsgren PhD, Jez Humble, and
Gene Kim

29. Resources: Links
https://lethain.com/systems-thinking/
https://insightmaker.com/
https://cloud.google.com/blog/products/devops-sre/using-the-four-
keys-to-measure-your-devops-performance
https://queue.acm.org/detail.cfm?id=3454124
https://medium.com/serious-scrum/how-late-integration-inflicts-
wicked-problems-on-your-scrum-teams-364dcc62bcc0

30. Questions?
Please email me your feedback!
stacy@stacyvicknair.com
https://stacyvicknair.com