This week our data and technology department had a workshop looking at how to be more decisive, led by the fantastic Claire Holmes.

Going away from the meeting we have asked each team to pick two techniques to apply over the next 12 weeks, and then to report back on whether they were effective. It will be interesting to see where we land in a few months' time.

Getting good at decision making is hard, Claire pointed out that you can operate in an underbaked way, making decisions quickly with poor information, and you can also end up in analysis paralysis. How do you get to the Goldilocks zone of having confidence, but not wasting too many cycles of analysis?

I am going to commit to the following for the next three months:

In starting the decision log, it’s already raised questions for me about the distinction between “decisions”, and “actions”.

As I listened to our teams discussing their own experiences around decisions they have been involved in I came away with a few impressions.

It is clear that as our decisions cross over boundaries of control, they become more complex and harder to execute on effectively. It seems teams with good local autonomy feel they are doing pretty well at the moment. Perhaps that means we need to focus on those more difficult areas of where a decision cuts across a boundary. We talked about internal team decisions, decisions across teams in the same department, and decisions that span across varying areas of activity in an org.

Where there is tension of prioritisation between teams, are there things that we can do better as managers to make our strategic priorities clear? There will always be resource constraints, and certainly always time constraints. How do you set up your teams to be able to make good quality decisions. Architecture review groups can play a role here - and there are other ways of organising those kinds of decisions too - https://lethain.com/navigators/.

A puzzle for me is what kinds of tools or frameworks can help with decision making amongst distributed teams? Our TOM work is helping to reduce the number of tools we use, but we are still capturing state in many different places. Our current state of tooling is quite broad, you can get a sense of the tools in play, just in technology in BMJ, by looking at this radar - https://radar.thoughtworks.com/?documentId=https%3A%2F%2Fdocs.google.com%2Fspreadsheets%2Fd%2F1ffJNBxgZpdVp7FxZH5YNWzbXnxtFTLhV0EnWL4ncO-I%2Fedit%3Fusp%3Dsharing.

I really liked the idea of being clear what role folk have in a decision making process - decision maker, advisor, recommender, executor or observer. A strong suggestion was to remove any observers from meetings. Why are those folk even there? Is it for politeness, or is it from habit?

I also really liked the framing of using meetings to actively seek information that will disprove our hypotheses. If you are not getting opposing views, you are probably not uncovering enough data to get to a high quality decision.

Meetings, and meeting culture, are a key engine of how decisions get made. I wanted to share two reads that have been helpful to me over the years in thinking about meetings:

http://www.paulgraham.com/makersschedule.html](http://www.paulgraham.com/makersschedule.html)

https://randsinrepose.com/archives/agenda-detection/](https://randsinrepose.com/archives/agenda-detection/)

It was a great workshop, and Claire has a ton of useful frameworks to pick from.

Classifications from OpenAI: workshop review - management strategies - decision making - teamwork - interdepartmental communication - tools for productivity - meeting organisation - leadership techniques.