Weeknotes 477
I did:
- Picked up my new laptop.
- Talked about workload management and how we think about what is worth doing.
- Wrote up my thinking on using test and control groups to improve the robustness of financial contribution reporting. I love this kind of critical thinking.
- Chatted about Domain Driven Design, architecture, mapping tech stacks and change implications. Although I’m a firm believer that product management isn’t about the technology, it’s also not much without the technology.
- Got involved in ‘a rock and a hard place’ problem. No viable solutions have presented themselves yet.
Success state roadmap
There is no single roadmap template that covers every part of the product development lifecycle. How weird is that? Now/Next/Later roadmaps are for discovery, and Gannt-type charts are usually used for delivery, and there’s no format for aligning around success.
So I wrote about success state roadmaps and how they show us whether our strategy is leading to a successful product. And I also got a mention in one of Paul Brown’s articles.
I saw:
Look up
I saw the International Space Station and the President of the United States. I’ll let you decide which one was more impressive.
I read/watched:
AI and Product Management: Becoming More Evidence-Guided
“AI’s biggest promise is not in accelerating the way we work today, but in helping us switch to evidence-guided, discovery-driven work.” This is a step forward in the AI as a tool for product managers thinking as it suggests AI can make it easier to do some of the things that are currently hard to do.
The future of product management
Notes on Notes from Ray Wang’s talk at INDUSTRY 2025:
- Companies that build AI-first business models will outperform the market 10 to 1
- The job as a product manager involves collecting data and monetizing that data.
- Realization that there is not enough data to get to a level for stakeholders to trust… and the need to pool data by industry value chains and build partnerships for data.
Digital-era healthcare
I read James Plunkett’s piece on digital-era healthcare and James Higgott’s responses, particularly his point about hierarchical power structures and the ‘do as I say’ culture at the NHS. I’d take what James Higgott says a level deeper and say the big problem with the NHS is that the wrong people have the power.
If digital is about anything, it’s about disrupting power structures. That’s what being user-centred is about. It’s how many of the early Internet products and companies succeeded. So, if the NHS wants to become a digital-era organisation it needs to drastically disrupt its own power structures.
Doctors know they have all the power. They know they are protected from complaint by the patient advice and liaison service. As a carer, I’ve seen it first hand many times. NHS staff making decisions that aren’t in the best interests of their patient and knowing there is nothing patients can do about it.
For the NHS to really change, it needs to fundamentally change the relationship between NHS staff and patients. It needs to put patient power first.
Intentionality FTW
Watched John Cutler describing the journey of how Dotwork figured out mapping product operating systems. Interesting as always. It’s really hard to know how much company operating systems, product operating models, etc., make a difference to the success of the products and organisations. One thing’s for sure, there’s no perfect answer. But I always go back to the question, “What are we optimising for?”
I thought:
Conveyor belts and mazes
Fundamentally conceptually, most products are conveyor belts. Their primary purpose is to take users from one state to another. It’s like I’ve said before, products don’t achieve outcomes, products change user’s behaviours and it’s that change that achieves an outcome (it’s why outcomes are unpredictable). And moving users along the conveyor belt is how those products change behaviour.
The problem with conveyor belt products is they are follow an industrial-age, mechanistic worldview that doesn’t fit our understanding of the world as a complex system.
So far, the only alternative to conveyor belts is mazes. These are products that are designed to keep you in the same state for as long as possible. Their definition of outcome is that user behaviour is changed in more predictable ways and then maintained for as long as possible.
The problem with maze products is they rely on algorithms, and we haven’t yet learned (or don’t want to because capitalism) how to make algorithms that don’t create negative spirals of doom (yeah, I’m talking about social media).
When I see thought-leaders complaining about LinkedIn’s algorithm not showing their super insightful posts to enough people, I think they are confusing a maze product with a conveyor belt product. They expect LinkedIn to help them get somewhere when really LinkedIn just wants to keep them posting.
Fixed and variable value
If you’ve ever done any business cost analysis you’ll know that variable costs change with the amount a business you do and fixed costs stay the same not matter how much business you do. I wonder if the same thinking applies to value. So, legal compliance, security, etc., are fixed value. An organisation needs them whether they have a thousand or a million users. The value (however you might define it) stays the same. Product, on the other hand, is variable value. The more users behaving in ways that drive business results, the more value is created.
Cost calculator for automation
I’ve been wondering how to quantify the question of whether its worth automating a process?
Maybe the calculation looks something like this: (Upfront cost of setting up automation + ongoing cost, e.g., licenses, monitoring, etc.) <> (Time cost of doing it manually x number of times action undertaken – value of what could be done instead) = Yes or no.
The evolution of the digital product
At first, ‘digital product’ meant a product that used technology (software). Then, the Internet came about and a ‘digital product’ became one that used technology and data to create and exchange value. Now, a ‘digital product’ uses technology, data, and artificial intelligence. This gives us a way to think about AI as using data in value-generating ways that weren’t previously possible. Soon enough, technology, data and AI will be the usual for digital products and whatever is next will be at the frontier.