Weeknotes 478
I did:
Magic number
Three day week for me, which really messed with my sense of time. I thought Wednesday was Friday and next week was the week after. Anyway, this happened…
- Chatted about Domain Driven Design and Opportunity Space Mapping, which seem to work really well together. They give us a way to organise, understand and assess messy, overlapping parts of the organisation.
- Talked about ways product managers can expand their responsibilities and find learning opportunities; across a domain, complementary products and adjacent roles. Product is a generalist role and there are lots ways to get useful skills.
- Started thinking about how to write a business case for some new work. I’ll probably use my usual FOPP metrics (financial, outcomes, performance, and progress) along with our north star metric.
- Joined up three problems to one solution. I like it when that happens. It feels like we’re delivering more value than tackling each problem separately.
- Thought through the things I intend to work on for the rest of the year. I’m reviewing my annual objectives soon so I want to have formed a position on whether I should be measured on outputs, outcomes, behaviours, growth, etc.
I read/listened to:
Product in service
Read Scott Colfer’s new book about what product management looks like in large, often non-commercial, organisations. There’s a lot to agree with. I’m a longstanding believer in the product management role being highly contextual and that applying product thinking is more important than “doing product management.”
Structure and social skills
Interesting podcast challenging Tuckman’s model for forming teams and concluding that it doesn’t really work. Instead, to be successful, teams need the right structure and the social skills to work together.
From Feature Factory to Finance Fluency: How I Learned to Speak CFO
“Executives aren’t against our ideas; they just can’t hear them when we speak in features instead of finance.” I completely agree product managers should be thinking and taking about business objectives such as income and cost, but I can’t help thinking that the other side of the problem is the attitude and approach of leadership towards product managers. When leaders believe their job is to do all the thinking (including understand the financials) and just give product managers features to build, then it’s not surprising that’s the language product managers speak back to them.
Software as signs
“The software your organisation produces is a product of and a reflection of how your organisation operates, as well as its beliefs and values.” I guess that makes software a lagging indicator of culture (just as conversation is leading indicator of culture). I wonder how you’d go about assessing an organisation’s software and what conclusions you’d reach about their culture.
Delivering successful AI after it breaks your existing operational model
I love Sarah’s perspective. She suggests our current product delivery model is outdated as it’s designed for deterministic software not nondeterminisitic, probabilistic systems like GenAI. I’m not sure more controls is the answer but it poses an interesting question to ponder… what would a nondeterminisitic product development process look like?
I thought:
Layers
An architect told me about how they have the idea of Layers. Made me wonder if we can think of products in a similar way, with an interface layer, an action layer, an outcome layer, etc. And that made me think about James Reason’s idea of Swiss cheese layers where failure is because the holes in layers line up.
Do as AI say not as AI do
There are some interesting hypocrisies in organisation’s position on AI. They want to use it to their advantage but don’t want others to use it in ways that disadvantage them.
A few months ago, Shopify CEO Tobi Lütke stated that staff had to prove a job couldn’t be done by AI before it can be filled by a person. This week, Spotify published their position on AI music on their platform and launched tools to stop it because people are using AI in ways that undermine their business model.
And in hiring, organisations don’t want candidates to use AI to apply for jobs, but they’re happy to use AI to screen CV’s and they want their staff to use AI in their day-to-day work.