Weeknotes 323

Photo of the week:

Sunset over the sea


Continuous improvement

I did some work on one version of what continuous improvement could look like for some of our products. In part, it’s about establishing a good practice that tackles some of the issues we uncovered in retros. It provides predictability to help people plan their time, aligns to goals and uses more data to inform decision-making so we understand why doing the work, and embeds ownership and responsibility. It’s only one way of approaching CI, and I still have lots of work to do on figuring out other approaches for other contexts, but its good progress.

Why make a humanoid robot?

This week’s Irregular Ideas newsletter was about the humanoid robot announced by Tesla and how making robots that look like an able-bodied man reinforces how society isn’t designed for everyone.


Chaos surfing

We tend to think of chaos as a bad thing, but in nature it’s just how things are. Perhaps if we can drop the value judgement, we can view chaos as system behaviour and accept, even in organisations for example, that too much stability creates a risk of not being able to adapt, self-organisation will always emerge regardless of hierarchy, and trying to be directive towards a linear path creates tension and is likely to fail.

Innovation and not-knowing

If, at its simplest, innovation is about ‘creating new value’, then the ‘new’ part has to start as unknown. Vaughn Tan’s point, “not-knowing creates room for new things to emerge”, means accepting uncertainty. The question is, how do you stay with uncertainty when creating new value. This is part of the product management question I’ve been working through over the past few weeks, trying to find methods for dealing with uncertainty to go along side those that try to create certainty.

Trial and Error

Jerry Neumann’s post about uncertainty and using trial-and-error as a fundamental building block of knowledge is useful for thinking about how we apply the scientific method. He says, “The naive view of trial and error is: you try random things until something works (“blind variation…”.) In reality, we try things that seem most likely to succeed. Science does this, but also tries things most likely to generate more knowledge, knowledge that might help future trials. Understanding why things happen, rather than what happens, is more general and more valuable. After a trial’s results are in, deduction and induction are used to help decide what to try next.” Also, interesting that we call it ‘trial and error’ rather than ‘trial and result’ or ‘trial and feedback’.

What does radical collaboration really mean?

I know I tend to get caught up in semantics, so my definitions of competitive (not working together, but trying to achieve the same goal), cooperative (working together but trying to achieve different goals) and collaborative (working together and trying to achieve the same goals) aren’t as helpful to others as they are to me, but Collective Change labs’ post on radical collaboration provides a different focus. It talks about taking the transactional nature of collaboration and changing it to be transformational. In my definition, that means shifting away for ‘working’ and ‘to achieve’ (the transactional parts of the definition) to ‘together’ and ‘same goals’ (the transformational).


Open ideas

Tom Watson’s open ideas is brilliant. This is good compost. It prompted me to update my ideas list, and to ask myself about the difference between a question and an idea; is an idea an answer is search of a question?

Kipling questions

How do we ask better questions? That is the question. It might not be the best question, or the right question, but we wouldn’t know because we’re not very good at asking good questions. What makes a good question needs more definition. From the poem, ‘I Keep Six Honest Serving Men’ by Kipling, we can say that every question should contain only one ‘who’, ‘what’, ‘where’, ‘when’, ‘why’ or ‘how’, and we could start to say that ‘who’ questions are about people, ‘when’ questions are about time, etc. And we could add logic tests to questions, such as is the question ‘concise’, ‘answerable’, etc. Needs a lot more work, but I think a framework for asking better questions could be really useful.

My problem with Think big, start small

I have a problem with the statement and idea of ‘Think big, start small’. I think my problem with it stems from a lack connection between the two parts. Think big with the vision. Start small is the practical actions. But there is nothing to connection the actions to the vision. So, at the moment, I prefer ‘Think deep, start small, encourage emergence’. It says, considering deeply what you understand of the situation, take small steps in that situation, and allow the direction and destination to emerge as you take the steps. No grand vision to head towards.

Trainers or socks

My old trainers wear holes in my socks. Should I replace the trainers or the socks? This is a problem-solving thought experiment as well as my current dilemma. Do you buy more socks, and implement a cheaper, quicker fix but know that the problem will continue to happen? Or do you buy new trainers, a more expensive solution with greater risk of getting it wrong? And more importantly, how do you choose between different solutions, how do you know when it’s best to go with quick fixes or more expensive bigger solutions?