Business

Are Product Owners set up to fail?

Product Owner choosing postits

I’ve long seen two big problems with Product Owners.

First, Product Owners don’t talk to customers as often as they should.

Second, the Product Owner role is frequently set up to be little more than a Backlog Administrator.

Now these two problems aren’t completely unrelated. If you are simply a Backlog Administrator what is the point of talking to customers?

For a while now I’ve taken a broad interpretation of the Product Owner role. Yes, it was introduced by Scrum, and Scrum defines a very powerful Product Owner (which I agree with). But, the Product Owner role has become a general term for “the one who should decides what needs doing next.” Simultaneously the role has become undermined and very few Product Owners seem to have the power to decide much more than the next couple of items.

The Product Owner role seems to make Product Managers and Business Analysts nervous. It shouldn’t, both Product Managers and Business Analysts are types of Product Owner. After all, while the Scrum definition calls for a powerful PO it says little about how the Product Owner knows what they need to know to make decisions. In my book – and yes, I cover this in Art of Agile Product Ownership – that knowledge usually comes from being a Product Manager or Business Analyst.

Recently I’ve been taking talking to my subscriber base and the issue of Product Owner comes up again and again. While nobody thinks Product Owners should be Backlog Administrators most Product Owners in the wild are just that, Backlog Administrators.

In some cases people think it is because of their situation. “In the public sector Product Owners are not honoured…”, “In Germany, Product Owners are not valued”, “In the outsourced development market the contract ties the PO’s hands.”

Actually, its everywhere. Product Ownership are failing everywhere.

In many cases I’ve seen Product Owners who are “battlefield promotions”. A coder is picked to be Product Owner on the grounds that Scrum demands a product owner and they are “The best coder” (or perhaps the worst), “they understand the system”, “its a technology project” or some other weak criteria. Real power continues to be vested elsewhere.

In other cases the Product Owner comes from “the business side” and has little understanding of the technology, how technology teams work or what is expected of them. Consequently the technology group run circles round the Product Owner.

There is a reoccurring tendency for Product Owners to become the Product Dogsbody and pick up the things that nobody else wants to do. Other times the Product Owner is seen as the team leader by those outside the team, however they hold little real sway inside the team (because they are a Dogsbody, Backlog Administrator, coder who is acting up or new to technology).

But the thing is: we can’t blame the Product Owner for any of this. They have been set up to fail by people who don’t understand or respect the Product Owner role, real power is withheld from the PO. Possibly because giving the PO power can seem like reducing ones own power.

As a result the role as an operational necessity (because Scrum or SAFe say there should be one) rather than the Strategic Role which is should be.

Perhaps one mistake I’m making here is: using the term Product Owner. Perhaps it is too connected with Scrum, and in the same way that Scrum has been devalued maybe Product Owner has too.

So, how do we fix this?

I’m not sure. Perhaps we should dump the title Product Owner, maybe everyone should use Product Manager – although that title too is misunderstood. Product Leader could be an option but I’ve also heard complains about that. Product Expert? Product Analyst? Product Person? – would any other name help?

In the past I’ve run a Strategic Product Owner workshop which aims to give POs the skills to operate more strategically. But for this to happen someone at a more senior level has to ask for the workshop and ask POs to be more strategic.

One option, is for Product Owners to meet customers. This will both inform their decision making and give them the legitimacy that comes from customer contact.

A brave PO can simply start thinking and acting more strategically, they can put themselves in the driving seat and start making decisions. While I think this would often work it requires a brave person who is willing to risk their job. (And please, meet some customers before you grab the controls!)

Ultimately the good, knowledgable, powerful, product people are key to achieving agility, failure to give such leaders power puts limits on success.


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Agility over agile, more than word play

Is it just me or is the world moving away from agile and towards agility?

That may sound like a silly question. I’m prepared to admit it come as much from what I want to happen as to what is happening. Perhaps it is confirmation bias, but it feels like there is a change in the air. It’s a change I’m all for – I was talking about the need for agility over agile over 10 years ago (Objective Agility).

It might seem like a small semantic change to go from “agile” to “agility” but it is a change from “doing agile” to “having agility.” It is a move from “means” to the “end”. From “the way of doing things” to the “outcome.” Rather than emphasis “the way people work” the emphasis is “what is the end result?”

That is a good thing. By definition agile methods, and agile frameworks (Scrum, SAFe, Kanban, even Xanpan) describe how to work. There is an assumption that if one works that way one will achieve agility. In reality there are many different routes to agility. Some look like Scrum, some like Kanban, others don’t. Some people find their own way to agility.

I always introduce agile by asking: “What do you want agile to do for you?” The agile toolkit can be used for many ends.

With agility the answers are pre-defined: agility is both ability to move fast but also the ability change direction and manoeuvre with haste. In order to do that information is needed (learning), and that information needs to be acted on (decision making) – feedback loops again. Maximising agility means pushing that learning and decision making down to the lowest level: giving the people who do the work authority and trusting them. This is where digital tools come in and is why digital transformation demand agility.

Agile Beyond Software

There are two forces driving this change. First off is the expansion of agile beyond software development and into many other fields. As I’ve said before: digital tools spread the agile virus.

As other fields – marketing, law, research, and more – adopt methods which were originally for software engineering some tools need changing. Sure, some tools work just the same – think daily stand-up meetings. Others need rethinking: test first thinking needs a little work when testing is not the norm. And some don’t work at all: Unit testing.

A couple of years ago I saw Scrum forced on people not in software. These people did not always work in teams, they time sliced between different activities and who had to handle a lot of unplanned, urgent, work. The emphasis was on “doing agile” rather than “being agile”. Despite some valiant work it was a mess.

As we apply agile thinking away from software we need to emphasise the outcome rather than the method.

Business Agility demands more

Second, talking about agility, and in particular business agility, puts the emphasis on the whole – the wider context. That is to say: you can have the most agile team ever but the wider organization can stunt agility. The wider organization also needs to hear customers and adjust efforts: budgets, portfolio, governance and other teams also need to work agile so the whole enterprise can have agility.

Summary

Yes: agility over agile might be semantics but it is an opportunity to change the emphasis:

  1. Prioritise outcomes over methods
  2. Seeking agility outside of technologists means embracing more variation in how teams work
  3. It is not enough for teams to be agile, the wider enterprise needs to challenge how it works

Finally, agility is not binary. One might work agile or might not work agile, but agility is measured on a scale. How much agility does your company have? – it might be zero, it might be 10, it can always go higher.

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Software has diseconomies of scale – not economies of scale

“Practical men, who believe themselves to be quite exempt from any intellectual influence, are usually the slaves of some defunct economist.”

John Maynard Keynes

Most of you are not only familiar with the idea of economies of scale but you expect economies of scale even if you don’t know any ecoomics. Much of our market economy operates on the assumption that when you buy/spend more you get more per unit of spending.

At some stage in our education — even if you never studied economics or operational research — you have assimilated the idea that if Henry Ford builds 1,000,000 identical, black, cars and sells 1 million cars, than each car will cost less than if Henry Ford manufactures one car, sells one car, builds another very similar car, sells that car and thus continues. The net result is that Henry Ford produces cars more cheaply and sells more cars more cheaply, so buyers benefit.

(Indeed the idea and history of mass production and economies of scale are intertwined. Today I’m not discussing mass production, I’m talking Economies of Scale.)

Software Milk
Software is cheaper in small cartons, and less risky too

You expect that if you go to your local supermarket to buy milk then buying one large carton of milk — say 4 pints in one go — will be cheaper than buying 4 cartons of milk each holding one pint of milk.

Back in October 2015 I put this theory to a test in my local Sainsbury’s, here is the proof:

Collage of milk prices
Milk is cheaper in larger cartons
  • 1 pint of milk costs 49p (marginal cost of one more pint 49p)
  • 2 pints of milk cost 85p, or 42.5p per pint (marginal cost of one more pint 36p)
  • 4 pints of milk cost £1, or 25p per pint (marginal cost of one more pint 7.5p) (January 2024: the same quantity of milk in the same store now sells for £1.50)

(The UK is a proudly bi-measurement country. Countries like Canada and Switzerland teach their people to speak two languages. In the UK we teach our people to use two systems of measurement!)

So ingrained is this idea that when it supermarkets don’t charge less for buying more complaints are made (see The Guardian.)

Buying milk from Sainsbury’s isn’t just about the milk: Sainsbury’s needs the store, the store needs staffing, it needs products to sell, and they need to get me into the store. All that costs the same for one pint as for four. Thats why the marginal costs fall.

Economies of scale are often cited as the reason for corporate mergers: to extract concessions from suppliers, to manufacture more items for lower overall costs. Purchasing departments expect economies of scale.

But…. and this is a big BUT…. get ready….

Software development does not have economies of scale.

In all sorts of ways software development has diseconomies of scale.

If software was sold by the pint then a four pint carton of software would not just cost four times the price of a one pint carton it would cost far far more.

The diseconomies are all around us:

Small teams frequently outperform large teams, five people working as a tight team will be far more productive per person than a team of 50, or even 15. (The Quattro Pro development team in the early 1990s is probably the best documented example of this.)

The more lines of code a piece of software has the more difficult it is to add an enhancement or fix a bug. Putting is fix into a system with 1 million lines can easily be more than 10 times harder than fixing a system with 100,000 lines.

Projects which set out to be BIG have far higher costs and lower productivity (per unit of deliverable) than small systems. (Capers Jones’ 2008 book contains some tables of productivity per function point which illustrate this. It is worth noting that the biggest systems are usually military and they have an atrocious productivity rate — an F35 or A400 anyone?)

Waiting longer — and probably writing more code — before you ask for feedback or user validation causes more problems than asking for it sooner when the product is smaller.

The examples could go on.

But the other thing is: working in the large increases risk.

Suppose 100ml of milk is off. If the 100ml is in one small carton then you have lost 1 pint of milk. If the 100ml is in a 4 pint carton you have lost 4 pints.

Suppose your developers write one bug a year which will slip through test and crash users’ machines. Suppose you know this, so in an effort to catch the bug you do more testing. In order to keep costs low on testing you need to test more software, so you do a bigger release with more changes — economies of scale thinking. That actually makes the testing harder but…

Suppose you do one release a year. That release blue screens the machine. The user now sees every release you do crashes their machine. 100% of your releases screw up.

If instead you release weekly, one release a year still crashes the machine but the user sees 51 releases a year which don’t. Less than 2% of your releases screw up.

Yes I’m talking about batch size. Software development works best in small batch sizes. (Don Reinertsen has some figures on batch size in The Principles of Product Development Flow which also support the diseconomies of scale argument.)

Ok, there are a few places where software development does exhibit economies of scale but on most occasions diseconomies of scale are the norm.

This happens because each time you add to software work the marginal cost per unit increases:

Add a fourth team member to a team of three and the communication paths increase from 3 to 6.

Add one feature to a release and you have one feature to test, add two features and you have 3 tests to run: two features to test plus the interaction between the two.

In part this is because human minds can only hold so much complexity. As the complexity increases (more changes, more code) our cognitive load increases, we slow down, we make mistakes, we take longer.

(Economies of scope and specialisation are also closely related to economies of scale and again on the whole, software development has diseconomies of scope (be more specific).)

However be careful: once the software is developed then economies of scale are rampant. The world switches. Software which has been built probably exhibits more economies of scale than any other product known to man. (In economic terms the marginal cost of producing the first instance are extremely high but the marginal costs of producing an identical copy (production) is so close to zero as to be zero, Ctrl-C Ctrl-V.)

What does this all mean?

Firstly you need to rewire your brain, almost everyone in the advanced world has been brought up with economies of scale since school. You need to start thinking diseconomies of scale.

Second, whenever faced with a problem where you feel the urge to go bigger run in the opposite direction, go smaller.

Third, take each and every opportunity to go small.

Four, get good at working in the small, optimise your processes, tools, approaches to do lots of small things rather than a few big things.

Fifth, and this is the killer: know that most people don’t get this at all. In fact it’s worse…

In any existing organization, particularly a large corporation, the majority of people who make decisions are out and out economies of scale believers. They expect that going big is cheaper than going small and they force this view on others — especially software technology people. (Hence Large companies trying to be Agile remind me of middle aged men buying sports cars.)

Many of these people got to where they are today because of economies of scale, many of these companies exist because of economies of scale; if they are good at economies of scale they are good at doing what they do.

But in the world of software development this mindset is a recipe for failure and under performance. The conflict between economies of scale thinking and diseconomies of scale working will create tension and conflict.


Originally posted in October 2015 and can also be found in Continuous Digital.

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Fixing agile failure: collaboration over micro-management

I’ve said it before, and I’m sure I’ll say it again: “the agile toolset can be used for good or evil”. Tools such as visual work tracking, work breakdown cards and stand-ups are great for helping teams take more control over their own work (self-organization). But in the hands of someone who doesn’t respect the team, or has micro-management tendencies, those same tools can be weaponised against the team.

Put it this way, what evil pointed-headed boss wouldn’t want the whole team standing up at 9am explaining why they should still be employed?

In fact, I’m starting to suspect that the toolset is being used more often as a team disabler than a team enabler. Why do I suspect this?

Reason 1: the increasing number of voices I hear criticising agile working. Look more closely and you find people don’t like being asked to do micro-tasks, or being asked to detail their work at a really fine-grained level, then having it pinned up on a visual board where their work, or lack of, is public.

Reason 2: someone I know well is pulling their hair out because at their office, far away from software development, one of the managers writes new task cards and inserts them on to the tracking board for others to do, hourly. Those on the receiving end know nothing about these cards until they appear with their name on them.

I think this is another case of “we shape our tools and then our tools shape us.” Many of the electronic work management tools originally built for agile are being marketed and deployed more widely now. The managers buying these tools don’t appreciate the philosophy behind agile and see these tools as simply work assignment and tracking mechanisms. Not only do such people not understand how agile meant these tools to be used they don’t even know the word agile or have a very superficial understanding.

When work happens like this I’m not surprised that workers are upset and demoralised. It isn’t meant to be this way. If I was told this was the way we should work, and then told it was called “agile” I would hate agile too.

So whats missing? How do we fix this?

First, simply looking at small tasks is wrong: there needs to be a sense of the bigger thing. Understand the overall objective and the you might come up with a different set of tasks.

Traditionally in agile we want lots of small work items because a) detailed break down shows we understand what needs to be done, b) creating a breakdown with others harnesses many people’s thinking while building shared understanding, c) we can see work flowing through the system and when it gets stuck collectively help.

So having lots of small work items is a good thing, except, when the bigger thing they are building towards is missing and…

Second, it is essential teams members are involved with creating the work items. Having one superior brain create all the small work items for others to do (and then assign them out) might be efficient in terms of creating all the small work items but it undermines collaboration, it demotivates workers and, worst of all, misses the opportunity to bring many minds to bear on the problem and solution.

The third thing which cuts through both of these is simple collaboration. When workers are given small work items, and not given a say in what those items are, then collaboration is undermined. When all workers are involved in designing the work, and understanding the bigger goals, then everyone is enrolled and collaboration is powerful.

Fixing this is relatively easy but it means making time to do it: get everyone together, talk about the goals for the next period (day, week, sprint, whatever) and collectively decide what needs doing and share these work items. Call it a planning meeting.

The problem is: such a meeting takes time, it might also require you to physically get people together. The payback is that your workers will be more motivated, they will understand the work better and are ready to work, they will be primed to collaborate and ready to help unblock one another. It is another case of a taking time upfront to make later work better.

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Reworking the risk equation

It is hard to argue with the old project management equation:

Risk exposure = Risk impact x Risk probability

Risk impact is often take to be money, say $1,000,000 and probability a percentage, say 50%. So exposure is also in money, $500,000. There is something rather obvious about it. So, while I’ve long disliked the equation I’ve not taken it to task, I never quite put my finger on it, or perhaps, I couldn’t really articular a winning argument.

That changed last week when I took “Papa” Chris Matt’s dog for a walk, or rather, he walked the dog I just tagged along and discussed the state of the world, and the thing we call agile.

Chris has a better equation:

Risk exposure = Money invested x Time to payback

Probability is out, after all, if something fails then it all fails. You were never going to loose $500,000, although you might loose the whole million. Probability is something of a red herring.

Chris’ insight here is that there is risk until the moment when you start seeing payback, i.e. until the investment starts pay is proven. In retrospect I should have realised this before. I read How Big Things Get Done a few months back and Bent Flyberg has the same idea. He points out that the time of biggest risk starts when the big money gets spent and continues until the project is delivered. Flyberg uses this logic to argue that long, detailed, upfront planning is good – because it is cheap and allows problems to be identified and avoided). Once you start the real work then do it as fast as possible; keep moving fast even if it costs you more because until the window is closed everything is as risk. (A highly recommended book by the way.)

The lesson many people take from this is: spend along time in planning and make sure you are certain about what you are doing before you spend the big money. I suggest a more important lesson is: once you start spending the money get to the point of return as fast as possible. Slowing spending does not reduce risk or save money, it increases risk and reduces benefit.

I’ve pointed out before that one way to increase the return on investment (significantly) is to make sure work starts paying back sooner. For example, make sure that the team deliver something every month (which itself reduces risk because something – anything! – is actually being delivered) and have that thing earn some revenue even if it is less than the full amount you want. When you do return on investment calculations correctly (i.e. account for time) then bringing forward the point where some (even a little) money is returned causes ROI calculations to jump.

Although it might seem too good to be true, the same logic will reduce risk. Both on paper and in practice.

Everyone who has ever argued for measuring and reducing cycle time will be happy right now. But Chris has a second point: today’s endeavours often involve multiple teams, and until all those teams deliver there is no return.

Think of it like ships in a convoy: they move at the speed of the slowest ship. None of the ships arrive until they all do, until they do they are all at risk, and since they are moving slow there is more risk. It also means, that reducing risk, speeding delivery, increasing ROI is going to depend on speeding up the slowest ship. If that sounds familiar its because it is what theory of constrains says: the system is constrained by its most significant bottleneck.

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Are you a tailor or an image consultant?

The best tailor

You go to the best tailor in town, and you say: ‘I’m getting married, my betrothed is beautiful, make me look one million dollars, I don’t care what it costs.’

The tailor measures you very carefully then stands back. He rubs his chin, he is clearly troubled by something. ‘Tell me’ you say, ‘Please tell me.’

‘Sir’, he replies, ‘I don’t think it is my place to say’

‘Tell me’ you beg, ‘I must look fantastic on the day’

‘Well Sir, …’ he talks slowly and cautiously, ‘… if you really want to look $1,000,000 can I suggest you lose 5kg?’

What do you say?

Is the tailor a master of clothes who just makes beautiful clothes?
Or are they, because of their long experience making people look beautiful in clothes, an image consultant who can help you look beautiful?

This is the dilemma many a consultant finds themselves in. More importantly it is the dilemma that I find again and again in corporate IT and digital agencies: Is an agency a service which is expected to build what is requested without answering back?

Or, Is an agency a group of experts who know the best way to maximise benefit and gain value from digital investment?

Is your agency a tailor who is expected to produce something brilliant no matter what the request is?

Or are they people who, because they work with technology every day, have experience and knowledge to help their customers maximise their benefit? (Even if that means the original request should be reconsidered.)

I distinctly remember a senior IT manager at an American bank telling me that his department was definitely a service department: it was not his job to answer back to business requests. His job, and that of his team, was to build what was asked for. The implication being that even if his people knew the (internal) client was approaching the issue from the wrong point, and even asking for the wrong system, then his people should not correct them. They should just build what was asked for.

Perhaps this dilemma is most acutely felt by Business Analysts who are sometimes expected to just write down the orders that someone wants to give to IT. Some brave Business Analysts will challenge, and lead their customers to ask different questions.

The original metaphor came from Benjamin Mitchell – who didn’t recall it last time I asked him. As I recall it was part of a very deep conversation we had in Cornwall back in 2011 (the same conversation led to the “Abandon hope all ye who enter Agile” blog post.)

For me the story is about missed opportunities, about frustration and about what you might do to change the position. For Benjamin it is about asking “Do we all expect the same thing? – If you think they consider you a service group how can you confirm this?”

Either way the core problem is about a mismatch of expectations. Your IT department might be a service department, that approach could work and it is how many big corporations operate. For a digital agency the question is more important: do they exist to do what the customer ask? “2kg of WordPress, certainly, sure” Or do they exist to advise the client on to live digitally? – and perhaps build a WordPress site.

I’ve used this story many times since 2011, it comes up again and again. If anything I use it more today than in 2011 or 2014 when I first shared it online.

What has changed since then is not so much the story but the world around it. Digital technology dominates business and requests to “build these 10 features” make less and less sense every year. The best ways of organising and managing work is to work with a tailor who knows what they are talking about and help both sides find the best solutions to meet a goal. Both sides need to respect each other.

I originally published this story in 2014. Nearly 10 years on it is even more relevant than when I first published it.

Are you a tailor or an image consultant? Read More »

Agile Guide podcast with Woody Zuill and Tom Cagley

I’m on a mission to popularise the term Agile Guide. A few weeks ago Wood Zuill (farther of Mob Programming and force behind #NoEstimates) and I recorded a podcast with Tom Cagley – another in his SpamCast series – on the Agile Guide role.

You can download the Agile Guide podcast from libsyn or you can download it from Apple, Sitcher, Google or Spotify.

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The Business Case for Agile in 2020 – video blog

A couple of weeks ago I gave a private presentation to an organization entitled: “The Business Case for Agile in 2020.” Actually, it surprised me a bit that in 2020 people still wondered what the business case for agile was but that probably says more about my arrogance and the agile bubble I live in.

I’ve re-recorded the presentation and it is now on-line: The Business Case for Agile in 2020 is on YouTube and embedded below.

The Business Case for Agile in 2020 – video blog Read More »

Time value profiles – a little tool with big implications

TimeValueProfile-2020-06-23-15-06.jpg

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The picture above is a time-value profile: it shows how value changes with time. It is a graphic illustration of cost of delay.

A fine wine might increase in value over time but most things – think product, project, feature or just story – decay with time. Having something today is worth more than having it next week.

I invented Time-Value profiles – although I’m happy to acknowledge Don Rienertsen’s influence. I’ve included time-value profiles in many presentations and courses (they are a key part of my value workshop) but oddly, while I’ve mentioned them in this blog before I’ve never described them. So here goes…

Imagine we want to build a feature for a product. Naturally we ask: “what is this worth?”

Money is the obvious way to measure value but strictly speaking money is not itself valuable – unless you happen to want small colourful pieces of paper or decorated lumps of metal. Money is a store of value. The value of money is not the money itself but what you can exchange the money for. And because money can be traded for a wide variety of things, which are themselves valuable, money is a useful medium for comparison and measurement.

So the question “what is this worth?” may be answered qualitatively (“a vaccine is valuable because it saves lives”) or quantitatively (“a vaccine is worth $10 trillion because it allows life to return to normal”). In order to compare competing opportunities and valuations, and in order to draw a graph, giving value a numerical quantity helps greatly.

A time-value profile shows quantitive value over time when value is measured numerically: maybe in hard money like dollars or yen, or an abstract measure like business points, wooden dollars or Atlantic shillings (I just invented that but it works).

The graph starts today: we say “If we had feature X today it would be worth 100,000 shillings”. Maybe it is worth 100,000 because that is what a customer would pay for it, or maybe because we could sell 100,000 units at 1 shilling each, or so on.

But we don’t have X today. “If we get feature X next month it will be worth 90,000 shillings.” One month delay, one month late to the customer, one month later on Amazon, costs 10,000 shillings.

“If feature X is 3 months away then it is worth less than 50,000 shillings.” And so on.

Now, the unit of value – dollars, francs, shillings, wood – is of little important. Sure $1,000,000 is very different to 1,000,000 (Russian roubles if you don’t know) but as long as you don’t mix currencies the actual currency is unimportant.

What is important is the shape of the curve and, especially, where abrupt changes happen. Look again at the graph above: between months two and three there is a sudden drop in value. That has scheduling implications.

Once you start to think about time-value profiles then it becomes obvious that value is a function of time and we need to understand what that function looks like for any given work – project, product, initiative, feature, story, just anything in fact.

It should also become clear that the question “how long will it take to build X” needs to be inverted: “how long have we got to build X?”, “how much of X could we build?” or “in the time we have what could create something to satisfy need X”

And then “how much of the available value can we capture?”. Having X might be worth 100,000 but having a half of X might still be worth 50,000 more than not having X.

As I’ve written before: to any given problem there are multiple solutions. Engineering is not about creating the best possible solution, it is about creating a solution within constraints – as my widgets exercise shows.

Add in capacity planning and a whole new paradigm of scheduling opens up.

Not that I wish to ignore costs – and effort estimates – but they are secondary, and the subject of another blog. I’ll write more about this, and perhaps put something into a workshop, in the meantime my value workshop is the best place to find out more.


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Product owner as a homeowner

house-illustration-clipart-free-stock-photo-public-domain-pictures1-2020-05-21-14-50.jpg

For years people have been comparing software construction with building construction. Think about how we talk about “architecture” or foundations, or the cost of change and so on. As I’ve said before, building software is not like building a house. Now it occurs to me that a better metaphor is the ongoing ownership of the building.

Every building requires “maintenance” and over time buildings change – indeed buildings learn. While an Englishman’s home is his castle those of us, even the English, who are lucky enough to own a house don’t have a free hand in the changes we make to our houses

Specifically I’m thinking about the Product Owner. Being a Product Owner is less about deciding what you want your new house to look like, or how the building should be constructed, its not even about deciding how many rooms the house should have. The role of the Product Owner is to ensure the house continues to be liveable, preferably the house is getting nicer to live in, and the house is coping with the requests made on it.

I own a house – a nice one in West London. As the owner I am responsible for the house. I do little jobs myself – like painting the fences. More significantly I have to think about what I want to do with the house: do we want to do a loft conversion? What would that entail and when might I be able to afford that?

I am the Product Owner of my own house. I have to decide on what is to be done, what can wait and what trade-offs I can accept.

When I bought the house the big thing to change was the kitchen and backroom. There was little point in any other works until those rooms were smashed to bits and rebuilt. I had to think though what was needed by my family, what was possible and what the result might be like. I received quotes from several builders – each of whom had their own ideas about what I wanted. I hired an architect for advice. I looked at what neighbours had done. And I had a hard think about how much money I could spend.

An Englishman’s home is his castle – I am the lord of my house and I can decide what I want, except…

My wife and children have a say in what happens to the house. Actually my wife has a pretty big say, while the children have less say there needs are pretty high on my list of priorities.

My local council and even the government have a say because they place certain constraints on what I can do – planning permission, rules and building codes. The insurance company and mortgage bank set some constraints and expectations too.

My neighbours might not own my house but they are stakeholders: I can’t upset them (too much) and they impose some constraints. (In my first flat/apartment the neighbours were a bigger issue because we shared a roof, a garden and the walls.)

So while I may be lord of my own house I am not a completely a free agent. And the same is true with Product Owners.

The secret with Product Owners is: they are Owners. They are more than managers – managers are just hired help. But neither do POs have a free hand, they don’t have unlimited power, the are not dictators, they are not completely free to do what they want and order people around.

Like me, Product Owners have limited resources available: how much money, how many helpers, access to customers and more. I have to balance my desire for a large loft conversion (with shower, balcony and everything else) with the money I can afford to spend on it. That involves trade-off and compromises. I could go into debt – increase my mortgage – but that comes with costs.

Product owners have responsibilities: to customers and users, to the those who fund the work (like the mortgage bank), to team members and peers to name a few. Some decisions they can make on their own, but on other decisions they can only lead a conversation and guide it towards a conclusion.

What the homeowner metaphor misses entirely is the commercial aspect: my house exists for me to live in. I don’t expect to make money out of it. The house next door to mine is owned by a commercial landlord who rents it out: the landlord is actively trying to make money out of that house.

Most Product Owners are trying to further some other agenda: commercial (generating money), or public sector (furthering Government policies), or third sector (e.g. a charity). In other words: Product Owners are seeking to add value for their organization. This adds an additional dimension because the PO has to justify their decisions to a higher authority.


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