Category: Blog

Takeaways

Product management is becoming more responsible for business success and revenue. 

The Product School CEO shared The Value Stick and talked about how product management is involved in protecting margin by increasing willingness-to-pay and reducing cost. Vinay Ramani, CPO at Tide, shared his playbook for market-first innovation and how they expanded into new markets by relying on local knowledge and separating from their established approaches before bring successful things into their core business later. 

AI in product management, products and organisations 

AI was definitely a theme, as you might expect. Lots of organisations are trying to figure out how they should use it. The trend seems to be in using AI behind-the-scenes to make organisations more efficient than creating new opportunities or value by building it into products. The Financial Times considered whether AI would change their core mission or support elements of their existing business and landed on the latter, with journalists using AI to make their research more efficient. 

Everyone is modernising, migrating or replatforming 

Ok, maybe not everyone but organisations you might expect to have a modern tech stack still struggle with how the tech keeps pace with the rate of change in the business. It was interesting to hear how TIER Dott, a company that rents electric bikes and scooters, managed bringing together two platforms and apps into one following a merger, and how Mastercard introducing SAFe to help them manage legacy tech platforms failed. 

Talks

Videos of the talks.

• Augmenting Your Product’s Value Proposition with AI by Debbie McMahon, CPO at Financial Times 

• The Future of Product in 2025 by Carlos González De Villaumbrosia, Founder & CEO at Product School 

• Product Localisation Playbooks for International Expansion by Vinay Ramani, CPO at Tide, Ex-Meta, Google, Uber 

• Product & Culture Integration After M&A by Pénélope Carlier, VP of Product at TIER Dott 

• Killing SAFe, Safely: Breaking Bureaucracy to Unlock True Agility by Simone Paul Tamussin, CPO at Mastercard Gateway 

• Partnering with AI Agents to build Stronger Teams and Smarter Products by Christine Itwaru, VP of Product at Beamer Userflow; Sally Fuller, Head of Mobility Products at BT; Susanne Jones, Senior Partner & Customer Transformation Leader at IBM and Sang Ha Park, AI Agent Workforce Leader at Sendbird 

• Scaling & Monetising Marketplaces by Carlos González De Villaumbrosia, Founder & CEO at Product School and Tanya Cordrey, CPO at Motorway. 

• Practical AI Use Cases for Product Leaders to 10x Impact Today by Dave Killeen, VP of Product at Pendo 

• Don’t Leave Money on the Table: Optimising Payments to Reduce Churn by Chetan Pandya, SVP of Product at DAZN 

• Streamlining Product Operations for Category Expansion by Sam Hancock, VP of Product at Deliveroo 

As a product manager, I think about AI in three ways: AI in the market, AI as a tool, AI in products.

AI in the market

Understanding how AI is affecting the market you operate in is essential. It’s a must. As with an emerging tech, product managers need to be watching how the tech is developing, what use cases come out and how organisations use it to meet those needs.

The introduction of AI is mostly ‘technology push’ which means it’s a solution in search of a problem, but also means that it’s widely applicable to lots of problems. If we believe even a small part of the hype, we can expect AI to change every industry and so affect every person’s life in some way. It’s more of a question of when and by how much, rather than if. So as a product manager, even if you don’t work in ecommerce or healthcare or fintech, your users are being affected by AI used in those sectors, and it will change their behaviour and expectations (just like the internet and mobile devices did) for your sector and product. Understanding and getting ahead of the trends is part of the job.

AI as a tool

Using AI as a tool means using it to be more efficient in what product managers already do. I’ve heard it said that “AI won’t replace you, but someone using AI will”. Again, when, not if. Can you imagine working as a product manager and not using that new-fangled email for communicating? It won’t be long until we think of AI in the same way.

Product managers can (and increasingly, should) use AI to write user stories or create prototypes or summarise workshop notes. Current thinking seems to be that AI isn’t reliable enough to be used without a human-in-the-loop, so as that human, products managers have to exercise the kind of critical thinking they would is other areas of their work. Its AI as a tool, not AI as an avatar/assistant (yet, but it’s coming), and a bad worker blames their tools.

AI in products

Using AI in products relies on product managers asking, “does it solve a worthwhile problem?” In the rush to find the problems technology push allows, adding AI into a product without that problem being worth solving could be wasteful but there are advantages to exploring ambiguous spaces and building an organisation’s capability for the future.

Product managers could be discovering worthwhile problems in two complimentary ways at the same time.

Firstly, testing hypotheses about user adoption, even if that is done quite bluntly by plugging an LLM into the product to see if anyone uses it is a completely viable approach given the state of the market mentioned above. There are other ways to understand user adoption, of course, but it’s important to understand that what doesn’t work today might work next year because of how user expectations will be quickly changed by other organisations using AI.

At the same, story-telling about the possibilities, building the case for investment, and creating longer-term technical capability for using AI as part of the product tech stack are all good things for productbmanagers to be doing. As well as, or instead of, surfacing AI to the user as part of the interface, it can include using AI to make predictions, analyse images, automate proceses with uncertain outputs, etc., etc.

It is also for product managers to balance the opportunity with the risks.

Product managers could be doing supplier due diligence, data protection and information rights assessment, figuring out an IP protection stance, analysing the total cost to run, assessing the risks, understanding ethical concerns about privacy and bias, and environmental impact of AI’s use of energy and water, and all the other things that come with introducing an emerging technology to an organisation, their product and their users.

That’s my current thinking on how product managers can think about AI. It’ll probably change, but for now I’d say product managers must be understanding AI in the market, should be using AI as a tool, and could be introducing AI to their products.

Thanks for the inspiration, Olu.

In 2025, I hope to:

1. Run more
2. Learn something new
3. Change my mind
4. Support my colleagues better
5. Keeping blogging
6. Give blood
7. Spend less time on social media
8. Read lots more books
9. Set myself some fun challenges
10. Talk to more people
11. Eat better
12. Help the right people get the recognition they deserve
13. Ask for help
14. Get even more organised and better at tracking, reviewing and improving my productivity
15. Have more focus on fewer things
16. See positive progress through the permacrisis
17. Get rid of more possessions
18. Maintain a twelve month runway
19. Care more, but attach less
20. Lead better, not more
21. Get stronger
22. Understand responsibility
23. Donate to charities
24. Fix a few things
25. Have more impact on the things that matter to me

Most interesting ideas I explored

Is it a product or service?

Had a few chats and thought quite a bit about the definitions of product and service, mostly on the assumption that they are different things. In the past, products and services definitely had different definitions, but nowadays the differences are often hairsplitting. So, until anyone can provide a robust definition for how products and services are different things, I’m saying they are the same thing seen from different perspectives.

Product or service

Who defines things in organisations matters. In my experience, if service designers do the defining, they tend to create a hierarchy where ‘the service’ is the big thing that spans the entire user experience and ‘products’ are the pieces of tech a user interacts with at each step as they go through the service. This implicit organisational power dynamic (kind of Conway’s Law) and misunderstanding that product doesn’t equate to tech, doesn’t lead to good, equitable, or useful definitions.

I’ve written before about how I think product managers and service designers can work together, so in a world where a service and a product are mostly the same thing, it doesn’t make sense for these roles to have mutually exclusive responsibilities, but instead to have complimentary perspectives that define and create better products/services.

Product or project

A product is a product if an organisation chooses to treat it as a product, and the best way to decide is to look at the problems it’s tackling. If the problems are well-defined, stable, and have predictable solutions, you don’t need product thinking or the skills a product team brings in tackle uncertain problems, and so don’t treat it as a product, treat it as a project. If the problems are new, unknown and the potential solutions are uncertain, then a product team with the skills to apply product thinking are a good way to tackle those problems, and so the organisation should treat those problems as a product.

Product or tech implementation

Differentiating between a product and technology implementation is much easier. If you’re working with hypotheses, discovering user problems, and delivering solutions iteratively, then you’re probably treating the work as a product. If you’re working with an accepted business case, stakeholder requirements and delivering features, then you’re probably implementing some tech.

Either way is fine, the important thing is to pick the right approach.

The future of product management

There have been so many boringly mediocre social posts about the future of product management being all about AI this year. I mean, look around. If that’s the best future you can envision, you clearly aren’t paying attention and probably shouldn’t be working in a role that involves having a wide perspective.

If product management is about navigating uncertainty and ambiguity, then the future of product management should consider the largest and most pressing cause of uncertainty; the state of the global economy (how it’s affecting organisations and what it means for the value product managers provide), climate crisis (how product management can help organisations stay within planetary and societal boundaries), the aging population, wars, energy and food insecurity, etc., etc. All of these create a permacrisis that should inform the future of product management.

And if anyone thinks that such big things are outside the scope of product managers, consider that how we think about disruptive innovation and growth now is a result of Schumpeter, Keynes, etc., and economic policies from the 1930’s that attempted to tackle the great depression and effects of World War I.

Cross-functional teams

I’ve explored a few different thoughts about cross-functional teams.

Truly cross-functional teams need wider remit

Truly cross-functional teams need the influence, authority and remit to affect goals, people, process, structure, technology and products/services. This idea comes from reading more about socio-technical theory, which introduced the idea of cross-functional teams and basically says you can’t treat the people side of an organisation differently than the technology side, they have to be designed to work together.

Unfortunately, most cross-functional teams usually only have the remit to make changes to tech, not as aspects of a socio-technical organisation. Maybe it’s a problem of focusing more on the ‘team’ part of ‘cross-functional teams’ and less on the ‘cross-functional’ part that makes us think it only needs to be within the boundaries of the team. Or maybe it’s another case of an idea that was designed to disrupt the status quo being co-opted into reinforcing existing power structures. Who knows.

Cross-functional teams should have regular contact with users

Internet-era cross-functional product teams work in an open system that is constantly changing and they have to respond to those changes. Industrial-era teams work in a closed system, meaning they aren’t affected by things changing out there in the world. One of the best ways for cross-functional product teams to know about changes is to have regular contact people who’s behaviour shows the change. Things like insight reports on customer behaviour, whilst useful, distance the team from the changes users are going through. They make an open system behave like a closed system, which reduces a team’s ability to respond to change and achieve outcomes for users.

The problem with professions

But cross-functional teams aren’t perfect. Professions exist to tackle a gap created by the move to cross-functional teams, but they in turn create a coherence problem for people facing different approaches that result. There must be a better way to provide a complete employee experience within cross-functional teams.

Decision stack

Spent some time understanding and critiquing the decision stack. The stack has Vision at the top and Strategy the second step down. Strategy breaks out into a number of Objectives, each of which in turn break down into Opportunities to explore to find ways to achieve the Objectives. At the bottom of the stack is Principles.

The different layers interact in two ways; the how and the why. How flows downwards, so Strategy says how to achieve the Vision and Objectives show how to achieve the Strategy. Why goes upwards, so Opportunities are selected because of the Objectives, which were chosen because of the Strategy.

The decision stack is a useful way to bring more coherence to the often vague and amorphous product work, but like every other framework, it says nothing about the environment necessary to make it a success.

Onto some thoughts from this year…

Logic model

A product logic model explains inputs, activities, outputs, outcomes and impact with if/then reasoning to show how changing one thing affects another. It depicts the hypotheses product manager’s use in their work, for example, how adding a different output (feature) is expected to affect an outcomes (user behaviour). Should the logic model be in the decision stack, and if so where?

I think it should, and goes either between vision and strategy, if we want to order things by longevity, or between opportunities and principles, if we think it’s more important to show that it’s foundational and supporting of how all the things above will work.

Whether we show the logic model using north star metrics or impact mapping (a favourite of mine) or theory of change, the point is to help understand and show others which aspects of the product that are within our ability to change and how the change will lead to what outcomes and impact. It shows whether our Objectives are the right ones to be working on, it validates our Strategy, it’s the feedback that tells us if we’re achieving our vision.

Principles

Principles are funny things. They can be really useful in solid decision-making or be useless talk about nothing much.

If you think of your principles as foundational, then you’ll be deontological about them. That means you consider them universally applicable rules or guiding boundaries that you don’t cross. Whereas if your principles are nice ideas that you might talk about occasionally, then you’re more utilitarian about them. You think that the ends justify the means, so you apply a principle when it suits and not when it doesn’t.

Given that centuries of moral philosophy hasn’t been able to decide between the two, I think we can accept that neither of these approaches is wrong, and the placing principles at the bottom of the stack doesn’t give us an answer about how to choose. It visually suggests either approach; a foundation to build upon (deontological) or less important than the opportunities above them (utilitarian).

I guess the interplay between applying universally applicable rules or using principles when they suit is another of those things product managers juggle.

Product ontology

I tried to think about the ontology and epistemology of product thinking to give it some robust theoretical foundations. I didn’t get very far other than the idea that product work might be better approached as constructivist rather than positivist.

User research is constructivist

I think user research uses a constructivist ontology. So, rather than trying to reveal an objective reality, it seeks to show how people create and interpret their own reality. I’ve never heard user researchers talk about this (except this guy) or even cover an ontological position in a research report. That seems a bit of a shame as it sets out a position that counters the criticism of user research not being robust enough because of population size.

Product attribution

Product attribution models usually take a positivist ontological stance, assuming there is a single objective truth to be revealed and show how this feature lead to that increase in metrics. But, given that product work is about affecting user behaviour, and an outcome is a change in user behaviour, wouldn’t a constructivist ontology make more sense? It also fits better with user research. I need to think about what a constructivist log model and metrics would look like, but that’s for next year.

Things I changed my mind about

Talking to people

I’m a big believer in asynchronous communications, and talking to people never comes easy for me, but I pushed myself to talk more to team members and to meet people outside the org. Now I think conversation is the unit of culture change. The more people talk to each other, the more knowledge is shared. And in modern knowledge work, sharing knowledge is a competitive advantage.

AI

I used to think GenAI was going to lead to big changes in people’s lives and new business models for organisations. Now I think it’ll have a similar scale of impact on content creation as email did on communication, and that in most cases it probably isn’t worth the environmental impact. Machine learning analysis, on the other hand, has much more potential (if you have the data).

OKRs

I used to think OKRs were a rubbish. Now I think they’re a good technique for teams to align with strategy and a tool for organisational change. I even did a short intro training session for some colleagues.

Stuff I wrote

What’s the difference between a delivery manager, a project manager and a scrum master, because they often get confused.

Against the standardisation of product management, because it’s a bad idea for a discipline that is going through so much change.

How product managers and service designers work together, because it’s better to bring complimentary perspectives than opposite opinions.

Uncovering better ways… of being agile.

Team objectives and fast feedback: a better way to improve individual performance, because individual performance objectives make no sense in a socio-technical organisation.

Three reflections on ten years in charity product management.

Goals

I have three longstanding goals that I’ve used for many years to focus my roadmap. Here are some of the things I did this year to contribute to my goals.

Contributing to digital transformation for social good

Work

Joined the Open University as a lead product manager.

Went to UKEduCamp.

Joined the Product Leader’s group.

Continually developing my knowledge, skills and practice

Reading

Books I read:

• Wiring the winning organisation
• The service organisation
• The agile manager
• Design for how people think

Learning

I didn’t do much formal learning this year but learned and practiced a lot about working with people. I’m really grateful to those who helped me learn.

Writing

764 posts (including 52 weeknotes and 25 blog posts, the rest were notes and links).

68.4k words.

33.5k views.

Most viewed post written in 2024: What’s the difference between a delivery manager, a project manager and a scrum master with 255 views.

82.3% of visitors came via search engines, 8.2% from other websites, 5.7% from social media, and 1.5% via AI.

Leading an intentional life

Travel

My coastline trip was on hold for this year because I had more important things to do.

Finances

Runway isn’t as healthy as I’d like but I spent money on worthy things so I’m ok with that.

Health

Didn’t walk, run or swim much this year.

How to decide if you’re building a product or building a technology system:

• Are you creating something that will validate hypotheses about how to enable the organisation to move in an agreed direction?
• Are you deciding what to build based on dedicated discovery work to understand what problems users are facing?
• Are you delivering small, frequent, reliable releases to users and getting feedback on whether you’re solving their problems?

If the answers are No, then you aren’t building a product, you’re implementing technology. There’s nothing wrong with that. Implementing technology is necessary, but it’s better to be clear about what you’re doing and why, and treat it accordingly.

I’ve been thinking about how mental models relate to definitions (like ‘product’) which relate to artefacts (like roadmaps). It’s confusing and dissonance-creating to define a product one way and then create a roadmap in a different way. So, if an organisation defines it’s products as pieces of tech, then an outcomes-based roadmap is going to make no sense. Lining up artefacts, to definitions, to mental models might help create more coherence and understanding. So, I thought I’d start with mental model based definitions of products.

By tech

This is the usual thinking in lots of organisations: a piece of tech equals a product. ¯\(ツ)/¯

Pros – Intuitive mental model because it’s fairly easy to see the boundaries of the tech and what that means for user experience, etc. Aligns the capability of the tech with the expertise of those working on it. Features roadmap makes sense because it expresses changes to the tech.

Cons – It makes it almost impossible for a product team to be outcome-focused as a user hardly achieves their outcomes by interacting with a single piece of tech. It falls into Conway’s law, which means users across multiple products often don’t get the consistent experience they’d expect when going from one tech to another.

By outcome

A product is all the things necessary for a user to achieve an outcome, including tech, team capabilities, policies, processes, etc.

Pros – Most user focused way to think about a product. Offers greater flexibility in how to achieve an outcome as a change could be in policy, user interface, etc.

Cons – Limits how to structure teams to work on a product as there aren’t going to be that many outcomes. Measuring outcomes is hard, so teams have to rely on proxy measures.

By activity

I’m not sure activity is the right word but it fits well enough. I mean product managers being responsible for things users do like Payment, Notifications, Search or Onboarding.

Pros – Allows for a great deal of flexibility in how the activities are defined which makes it easier to add, merge and disband teams aligned with activities.

Cons – It can be a bit feature-led, which means teams need to communicate and coordinate to create a coherent product experience.

By goal

The goals would usually be metrics based, e.g., Increasing Daily Active Users or improving retention.

Pros – Product teams can experiment and implement across any tech or user experience to achieve their goal.

Cons – Requires coordination across teams to prevent one team from negatively impacting another team’s goal.

It’s easy to get confused about prioritisation. We often use that word when we mean other things. We should mean ordering things by relative importance, but sometimes we also mean the sequencing of those things. One word, used to mean different things to different people. And that’s where it causes confusion.

I think it’s clearer to separate how important something is from when you’re going to do it. And to make that separation even cleaner, we could prioritise the problems we want to tackle, and sequence the solutions we want to create.

Prioritising problems

Like all good product managers, we want to start by understanding the problems we want to tackle or opportunities we want to go after.

We want to know which are the most important problems, and to figure that out we might look at how many people have the problem, how affected they are, how much they need a new solution, etc. All this information helps us pick which problems to tackle and which not to. And that’s the point of prioritisation; choosing what to work on, not when to work on it. It’s the logic of ‘this, not that’, whereas sequencing is ‘this, then that’.

Sequencing solutions

Once we have the problems prioritised by importance, we can then sequence the solutions.

We want to sequence the solutions separately from prioritising the problems because there are different factors to consider. Now we need to think about team capacity, technical skills, dependencies on other systems, budgets and other organisational constraints, etc. These things don’t affect what problems we’ve prioritised but they make a difference to when we’ll be able to tackle them.

By thinking about problems and solutions differently we can avoid confusing how important a problem is from when we want to solve it. It helps us make better decisions about whether to tackle more important problems sooner or when to solve easier problems.

Delivery manager, project manager and scrum master are three quite distinct roles, but with a lot in common. Although each role is a valuable in it’s own right, for either of the roles to provide value, and for a person in a role to be successful, it’s important that the right role is selected for the circumstances. Exploring the commonalities and differences can help with matching the role to the working environment.

What the roles have in common

Delivery manager, project manager and scrum master are all non-authoritative. They don’t direct people or assign work. They exist to support teams to focus on the value-driving work by taking on the meta-work – the work that makes work possible – including things like planning, coaching and reporting. With so much overlap between the three, a Venn diagram helps us see some of the activities and responsibilities the roles take on.

What makes the roles unique

Delivery manager

Purpose: Enabling team health.

Responsibility: Creating an enabling environment by removing impediments, facilitation and coaching.

Method: Agnostic. Delivery management doesn’t follow any specific methodologies and can work equally well whatever methodology a team is using.

Best environment: Cross-functional teams tackling ambiguous problems.

Success measures: Individual’s purpose, autonomy and mastery.

Project manager

Purpose: Monitoring unplanned deviations.

Responsibility: Managing the day-to-day progress of a project to ensure it follows the plan.

Method: Predictive. Project methodologies (sometimes called waterfall) that involve upfront planning, reporting against the plan, and triggering corrective actions.

Best environment: Established project teams working on delivering known solutions.

Success measures: Project scope, schedule, budget.

Scrum master

Purpose: Improving team workflow.

Responsibility: Establishing Scrum and helping the team inspect and adapt their practice to become more effective.

Method: Adaptive, and Scrum specifically.

Best environment: Scrum team.

Success measures: Team velocity, throughput, sprint burndown.

Which role fits where

A delivery manager fits best as a part of a multi-disciplinary team tackling novel and ambiguous problems, where the organisational environment contains challenges for the team, and the team is open to being supported to tackling the challenges and removing impediments.

A project manager fits well in a team and organisation that is working on things that can be well-defined upfront, usually because they’ve been done many times before. Although project management has started to adopt adaptive methodologies, it still works best with pre-defined scope, budget and schedule.

A scrum master only works in a scrum team. That’s the only setting where a scrum master can be successful. Scrum master isn’t a profession in the same way delivery management and project management are, in that there is no career progression path of scrum master, senior scrum master, head of scrum mastery.

References

Association for project management. What does a project manager do?

Atlassian. What is a project manager? Responsibilities and best practices explained.

Everyday Agile. 2023. What Is Agile Delivery Management?

Government Digital and Data Profession Capability Framework. 2022. Delivery manager.

Project management institute. What is a Project Manager?

Metz, T. The 10 Most Helpful Agile Metrics According to Experts.

The 2020 Scrum Guide. 2020. Scrum master.

Webber, E. 2016. Explaining the role of a Delivery Manager.

Williams. J. 2021. What’s wrong with delivery management?

Matt Ballantine mentioned lots of little theories. Little theories are a great way of holding onto a questions while you look for signals to prove or disprove them, so I thought I’d make a note of some of mine.

• The number of conversations leaders have with people below their pay grade and outside their reporting line is a leading indicator of organisational culture change.
• Organisational self-image explains culture better than the behaviours of individuals.
• Four day working weeks reverses Brook’s Law. It isn’t (only) less time at work that creates the benefits, it’s that everyone spending less time reduces the coordination challenge by 20% which is a massive efficiency/effectiveness gain.

Product managers should champion user needs within the team and within the organisation. They aren’t the only ones, of course, everyone should, but product managers can bring together multiple perspectives on meeting user needs because they don’t represent a specialist discipline.

User needs can be general and specific. So, whilst the specific user needs might be for a user researcher to discover and champion, it’s for a product manager to champion the general user needs. These are the kinds of things user’s need but a user researcher wouldn’t find out; things like making a product accessibility, making it work on various devices, how secure their account should be, etc., etc. In old money, they used to call these Non Functional Requirements, but for modern, user-centred product teams that term is too loaded with tech-first organisational needs, so better that we remind ourselves that it’s our users that need these things by calling them user needs.

Because product managers often think at scale, these general user needs have to be expressed in more generalisable terms. This is where standards, concepts and theories such as cognitive load theory, WCAG, COM-B behaviour change model, OWASP top ten, etc., become an important part of meeting those general user needs.

Championing these general user needs means working with the team to internalise them to the point where they are a given. When the team designs and builds accessibility, security, etc., in from the start, then they are meeting those general user needs. Then they are being user-centred. Then the product manager knows they’ve done the job of championing user needs.