Month: April 2025

Year one

This week was my one year workiversary. It’s been a pretty amazing year of learning and planting seeds that I’ll hope to grow in my second year. But this week I:

• Chatted about what it takes to create a high-performing team.
• Started chatting to user-centred design people (because I’ve met all the product people).
• Wrote up some thoughts a product strategy. I really need to find some time to blog about this.
• Helped plan a prioritisation workshop.
• Learned a bit more about how unit finance works.
• Got some early feedback on my opportunities presentation. I’m looking forward to encouraging product managers to spend more time looking outside the building and discovering worthwhile problems.
• Reflected on my first year doing product in higher education (which may become a blog post if I get the time).

The numbers

Tasks completed: 25

Minutes spent in meetings: 495

(Four day week.)

AI horizon scanner

Added more entries to my AI horizon scanner and added a Type column to make it easier to see what kind of resource it is. Still adding stuff as and when I find it and don’t yet have a system in place, so I need to figure that out, but it’s on the roadmap.

I read:

Making Better Product Decisions: Approaches and AI Prompts for Product Managers

I think critical thinking is a fundamental product skill, and good decision-making technique is built on top of that. In my experience, most product decisions aren’t made with robust logic because organisations and people are messy, but it’s still really good practice to be able to show your working out.

Sludge

“If you make things harder, I call that sludge. Kind of a fun word for stuff that’s the opposite of fun” – Richard Thaler on the Freakonomics podcast episodes about sludge, friction and administrative burden have been doing the rounds in some product circles.

Sludge, Part 1: The World Is Drowning in It

Sludge, Part 2: Is Government the Problem, or the Solution?

Trilly Chatterjee, head of product management at NHSE, has thoughts about it too.

Disruption

Doug Shapio’s talk at FutureWeek Forum is exactly the kind of analysis product manager’s should be looking at to think about how AI is going to disrupt their industry.

He talks about how the last great disruption to the media industry was the internet, which removed the distribution moat media companies used to have, and how Gen AI is the next great disruption which will remove the production moat. The disruption isn’t Hollywood using Gen AI to replace writers, it’s Gen AI replacing Hollywood.

There’s also an interesting point that if you are monetising attention and engagement, you are a media company. So does that make universities media companies? Education is more complex than entertainment, there’s more to unpack and disintermediate, because education provides knowledge, credibility, connections, etc., and arguably the institutions have far greater control over the status quo, but maybe the disruption isn’t universities using Gen AI to replace lecturers, it’s Gen AI replacing universities.

I thought:

There’s a prompt for that

Had a 5am thought about making Gen AI prompts part of documents, presentations and workshops to help people learn more about a topic. I might try it with the work I’m doing on opportunity assessment.

I haven’t tested it yet, but it would really help if a short prompt could tell the AI to go to a web page to get the full prompt. It would make for a better user experience between document and browser.

Pot holes

I vaguely remember hearing something on a podcast about using AI to improve road repairs. The point was that AI image detection can speed up identifying pot holes but that was never the slow part to fixing pot holes, it’s all other stuff of having enough budget to have enough teams with enough equipment to go out and fix the pot holes. So, yeah, it’s great that no-code and AI had a baby and now you can build a standalone application on your mobile just by sending a few chat messages. But building stuff was never the bottleneck to great products, so it’ll be interesting to see how AI changes all the other parts of product management (beyond summarising information). Maybe I should spend some time imagining that myself.

I did:

Opportunity knocks

This week has seen all kinds of opportunities coming up, some panning out and some not. Long may it continue, I say. I’m always up for doing something new.

Among lots of other things, I…

• Started talking about how we improve our testing capabilities.
• Worked on a training session for retros.
• Went to the product community of practice (it usually clashes with another meeting) about the craft of product management.
• Talked through some feedback on group product strategy and identifying the levers that allow us to achieve the change we want.
• Wrote a presentation on how product managers can look for new opportunities.
• Did data protection training.
• Signed up for AI product management training.

The numbers

• Completed 39 tasks, 12 of which contributed to my objectives.
• Spent 930 minutes in meetings.

I read:

How not to transform

It always amuses me when product people think product approaches are generalisable outside of managing products, especially for organisational change. Product management is not change management. It doesn’t work as a change methodology because it carries the inherent assumption that changes made, stay made. It has no mental model for understanding that in organisations things slip back to old ways, change gets undone.

If you want to change an organisation there is an entire body of knowledge with a long history about organisational design and change management. So, at the risk of stating the obvious, if you want to transform an organisation, or even just how it does product, turn to the disciplines that already know this stuff.

Opportunities

Brushed up on Opportunity Solution Trees and Assessing Product Opportunities, partly because I’m working on how we improve our ability to spot opportunities, and partly because they were mentioned in the Product Leaders group discussion on training. One of the things I’m puzzling is whether the deductive reasoning of OST is right for us as it starts with the outcome you want to achieve, which limits the opportunities you’ll come up with. Maybe it’s useful for analysis and grouping opportunities after you’ve understood them but I need something that is more about how to bring multiple diverse observations together into an idea for an opportunity.

Online and Distance Education for a Connected World

This book goes into a lot. But I’m interested in how distance and online learning meets product management, so hopefully it’ll help improve my knowledge and thinking.

I thought:

Pace layers

Brand’s idea of pace layers describes how change happens at different rates, with fashion being fastest and nature being slowest. I wonder if, actually all change is happening at the same speed but appears different because things like fashion have a simpler, clearer path to follow, whilst culture change follows more routes, has twists and turns and dead-ends, has more ground to cover. Does this change anything about how we approach change? Probably not, but it might be nice to get away from the sense of blame that comes with slow change.

Being clearer

I’ve been thinking about how to frame conversations around deciding what we want to achieve, and that includes defining my terms, recognising that unintentional things also occur

My definitions:

• Goals are general. They can be measurable and specific or vague and qualitative.
• Objectives are specific, measurable, intentional, and upfront subset of goals.
• Outcomes (a change in user behaviour that achieves business results (Seddon)) are a subset of goals that can be objectives (if they meet definition, particularly being intentional) but can also not be objectives if they occur unintentionally.

So, maybe it looks like this:

It gives me three ways to talk about the things we want to achieve to different audiences. Goals fit nicely when story-telling and showing how product work fits into bigger pictures. Objectives are used to talk about the effect we’re having and benefits we’re delivering. And Outcomes give us a way to bring the user into the discussion and show what we’re achieving for them.