1. Complex environments

Key message: complexity thinking is the understanding that some systems are unpredictable because their boundaries only partially constrain the agents that act within the system, and the agents modify the boundaries

Complex adaptive systems:

• System: a set of parts which, when combined, have qualities that are not present in any of the parts themselves
• Complex: behaviour of the whole isn’t predicted by the behaviour of the parts
• Adaptive: system can learn and change
• Examples: stock market, biosphere, city, any human social group‐based activity, many things in high velocity IT environments

Complex adaptive systems in HVIT:

• Inherently unpredictable
• A challenge to people who are used to working with processes
• Behaviour arises through interactions between many agents
• Boundaries can be affected by the agents, increasing unpredictability
• Experimental approach is needed to both development and support:
  • Many independent experiments in parallel
  • Deal with negative side‐effects of experiments that fail
  • Continue and broaden experiments that succeed
  • Remember that circumstances and results will change

Some work is more predictable, and some is less

Cynefin is a sense-making framework to deal with complexity:

Domain	Description	Action
Complex	Unclear, unknowable, causality	Safe to fail experimentation (emergent practice)
Complicated	Unclear, knowable, causality	Analysis/expertise then apply good practice
Obvious	Clear causality	Apply predetermined best practice
Chaos	Extreme complexity	Take immediate action (novel practice)
Disorder	Not knowing which domain applies	Check you’re not assuming the domain you know best

 

Recognising complexity can be a big help to engineers:

• Often used to think in if-then-else ways
• Rethink belief (or confirm doubt) that rigid processes and plans always work
• How to troubleshoot a complex failure:
  • Identify multiple hypotheses for what might be happening
  • In parallel, test each plausible hypothesis, using small, safe‐to‐fail experiments
  • Observe the impact of the experiments
  • Try to amplify any positive outcomes, and dampen any negative effects

Unpredictability is not always a bad thing, research and development often benefits from high variability

Antifragility: complex adaptive systems that increase in capability, resilience, or robustness, as a result of stress or failure (example: evolution of a plant, or an animal, or a social media platform)

Challenge of complexity thinking:

• You have to think for yourself, and face your own difficulties
• Can no longer simply apply best practice

2. Lean culture

Key message: a Lean culture is characterized as a work environment where trust, respect, curiosity, inquiry, playfulness and intensity all co-exist to support learning and discovery

HVIT needs to be based on Lean culture to be effective, resilient and adaptable

Leaders set norms and expectations and they explain the goal and support the people

Lean creates social patterns that inspire engagement (what we do matters, so let’s act that way)

Lean has many really good tools:

• Lean culture is needed to achieve results
• We have tools but need focussed attention

Elements of a Lean culture:

Trust	The assured reliance on the character, ability, strength, or truth of someone or something including a team, a work process and, most importantly, process
Respect	The act of giving particular attention, consideration, special regard and esteem to another
Curiosity	A relentless desire to know how and why things work, what makes things work better, and what better looks like after things have been made better
Inquiry	A systematic search for the facts about the nature of things: their origins, their causes, their interdependencies, their lifecycles and their nature
Playfulness	A fresh, fun way of viewing ideas and their relationship to other ideas while simultaneously maintaining serious focus
Intensity	A deep focus on the topic at hand and the persistence not to become distracted or lose the path

3. Toyota Kata Key message: Toyota Kata is a pattern for scientific thinking and routines for practice and coaching Orgs need to continually improve: With varying and changeable market conditions, difficult to follow predetermined plans Improvements are incremental Requires: Scientific thinking with disciplined execution Practice unlearning old habits Confidence and competence to improve Practice and coaching

Four step improvement process...	...based on five questions
1. Understand the direction: improvement should be aimed at specific goals, not just random	1. What are we trying to achieve ?
2. Grasp the current condition: a direction is not useful unless we know where we are right now	2. Where are we now ?
3. Establish the next target condition and identify obstacles: describes both the outcome we desire next and the expected condition of the process to generate that outcome	3. What obstacle is now in our way ?
4. Experiment toward the next target condition: come up with ideas to overcome an obstacle and run experiments with that idea. If possible, test only one hypothesis at a time	4. What’s our next step, and what do we expect ? 5. When can we see what we’ve learned from taking that step ?

 

Go back to Principles, models, and concepts to finish this section or to the main chapter ITIL 4 Managing Professional Certification Course: High Velocity IT (HVIT).