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Tech leadership: lessons learnt

Tech leadership: lessons learnt

As engineers we often prefer hard facts over the fluffy stuff. As a manager most of our impact is through soft skills. How does an engineering manager find balance the between the worlds of data-driven team metrics and the people skills required to get the best from their team.

In this talk, Dale shares some of his hard-won lessons managing an ever growing engineering team using a variety of processes like kanban and lean product development, and tools like metrics, coaching, autonomy and guard-rails.

Dale is co-founder and CTO of Nomanini, a local fintech startup that helps informal merchants across Africa thrive.

Dale Humby

March 03, 2020
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  1. Dale Humby, Nomanini
    [email protected]
    Tech leadership
    Lessons growing a dev team

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  2. Dale Humby
    CTO
    co-founder
    Nomanini
    Cash payments
    In Africa

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  3. About this talk

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  4. What is a start-up?
    “A startup is a human institution designed to
    deliver a new product or service under
    conditions of extreme uncertainty.
    Eric Ries
    http://www.startuplessonslearned.com/2010/06/what-is-startup.html

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  5. Why have an engineering team?

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  6. Goals of an engineering team
    Respond to rapidly
    changing competitive
    landscape
    Provide a stable,
    reliable, secure service
    to our customers

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  7. What is the output of a manager?

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  8. What is the output of a manager?
    Output of their team
    +
    Output of the
    teams they influence

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  9. How do you increase output?
    + Motivation + Skill

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  10. The 1st lever: Motivation

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  11. The 1st lever: Motivation

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  12. Scrum: 1 month sprints

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  13. Scrum: 2 – 1 week sprints

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  14. Scrum (2011)

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  15. 1 story sprints…?

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  16. Feedback loops

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  17. Kanban
    Dev team promise (SLA)
    Work will be deployed to production
    within 1 week of starting

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  18. Importance of Work in
    Progress (WIP) limits

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  19. Maslow's Hierarchy of Needs

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  20. The 2nd lever: Increasing skills

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  21. Task relevant maturity
    Low
    Task oriented
    ● What
    ● When
    ● How
    Medium High
    Individual oriented
    ● Emotional support
    ● Encouragement
    Objective oriented
    ● With monitoring

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  22. Complexity, Uncertainty, Ambiguity
    Time
    Complexity, Uncertainty,
    Ambiguity
    “Junior”

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  23. Complexity, Uncertainty, Ambiguity
    Time
    Complexity, Uncertainty,
    Ambiguity
    “Junior”
    “Mid”

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  24. Complexity, Uncertainty, Ambiguity
    Time
    Complexity, Uncertainty,
    Ambiguity
    “Junior”
    “Mid”
    “Senior”

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  25. Complexity, Uncertainty, Ambiguity
    Time
    Complexity, Uncertainty,
    Ambiguity
    “Junior”
    “Mid”
    “Senior”

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  26. Complexity, Uncertainty, Ambiguity
    Time
    Complexity, Uncertainty,
    Ambiguity
    “Junior”
    “Mid”
    “Senior”

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  27. Complexity, Uncertainty, Ambiguity
    Time
    Complexity, Uncertainty,
    Ambiguity
    “Junior”
    “Mid”
    “Senior”

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  28. Complexity, Uncertainty, Ambiguity
    Time
    Complexity, Uncertainty,
    Ambiguity
    “Junior”
    “Mid”
    “Senior”

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  29. Complexity, Uncertainty, Ambiguity
    Time
    Complexity, Uncertainty,
    Ambiguity
    “Junior”
    “Mid”
    “Senior”

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  30. Complexity, Uncertainty, Ambiguity
    Time
    Complexity, Uncertainty,
    Ambiguity
    “Junior”
    “Mid”
    “Senior”

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  31. Increasing skills
    ● Pair programming, Code reviews
    ● Self study
    ● Coaching, 1-on-1’s
    ● 360’s / peer review
    ● Skills assessment
    ● Medium-term career development
    ● Formal courses

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  32. 3rd lever: Decentralised control
    Rapid
    response

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  33. 3rd lever: Decentralised control
    Rapid
    response
    Alignment
    more difficult

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  34. 3rd lever: Decentralised control
    Rapid
    response
    Alignment
    more difficult
    ● Focus on the outcome: Why not how/what
    ● One main effort
    ● Consistency of decision making
    ● Trust through experience

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  35. Key takeaways
    ● Output of a manager
    = Output of their team
    + output of neighbouring teams
    ● Tools
    ○ Increase motivation: Build a racetrack: Metrics
    ○ Increase skills: Tailored mentorship program
    ● Decentralised control works well for extreme
    uncertainty

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  36. Books worth reading
    Thank you
    [email protected]

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  37. Innovation
    http://web.mit.edu/6.933/www/Fall2000/teradyne/clay.html

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  38. Complexity, Uncertainty, Ambiguity
    Time
    Complexity, Uncertainty,
    Ambiguity
    “Junior”
    “Mid”
    “Senior”

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