#NoProjects: Project Myopia is published

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Project Myopia – the original case for #NoProjects – has been a long time in the works but it is now done. Published. For sale on Amazon.

Projects fail. Some say 40% of all IT projects fail, some say 70%. And it has been that way for years. Each project fails for its own reasons but they all share one thing in common: the Project Model. Could it be the project model itself which creates failure?

Projects end. Successful software continues. Twenty-first century digital businesses want to continue and grow.

Project Myopia is available to buy on Amazon today – the physical version should joined the eBook in a few days.

Project Myopia gives the case against projects – the hard core #NoProjects arguments. A second book, Continuous Digital will join Project Myopia in a few weeks on Amazon. Right now copyediting isn’t finished on Continuous Digital, plus the physical copy needs to be worked out. In the meantime late drafts of Continuous Digital are available on LeanPub.

Release or be damned

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Back when I was still paid to code I had a simple question I posed to troubled development efforts:

“Why can’t we release tomorrow?”

This short simple question turns out to be amazingly powerful. I remember one effort I was involved with in California where a new CEO took over and started cutting jobs. I posed this question to the team and in a week or two we did a “beta release” – we did those sort of things back then. Asking this question was the key that allows us to question everything, to cut the feature list – or rather push work back, it stayed on the to-do list but we didn’t let it stop us from pushing to release.

We rethought what we were trying to achieve: we didn’t need the whole product, we just needed enough of the product to work to show to one specific target customer. Even if they signed there and then we had weeks before they used it in anger. But until we released something, until we had something “done” our team, our product, look like just another “maybe.” We had to draw a line under it so the new CEO wouldn’t draw a line under us.

Saying “only do the essential” is easy and come up again and again, whether it is Minimal Viable Product, Minimal Subset, Must haves in Moscow rules, but it is far easier said than done. One persons “essential” is so often another persons “optional extra.” In this context, when I say “essential” I mean “the parts needed to make the system work end to end” – I’m far closer to the old walking skeleton idea.

I was reminded of this question by a couple of endeavours that came to my attention during the summer. Well, I say came to my attention, I feel a bit responsible. Both endeavours are happening at clients; clients who I had fallen out of touch with. My style of working is to help clients who want help, I don’t like selling myself. These clients didn’t ask for more help so I didn’t jam my foot in the door, in retrospect maybe I should have.

In one case the team were doing very well. They were iterating, they were TDD/BDD’ing, they were demoing, they were working with the client, they were doing everything … except releasing. Then one day the client asked “when will it be done?”

Now think for a moment: What if you could release your product tomorrow?

The thing is, without actual products those around the team look for signs that the team can be trusted, that they team will deliver, that the team are thinking about what is to be done. People ask for proxy-products: plans, schedules, risk-logs, budget forecasts and so on. When stakeholders can’t see progress they look for things to assure them that there is (or will be) progress (soon).

Who needs plans and predictions about the future when the future is here tomorrow?

Actual releases are they key to reaching the new world, they change everything.

So I feel guilty: I should have inflicted myself on these teams, I should have been there again and again bugging them “Go to release”, “Remove that barrier”, “Force it through”.

Being able to ship an update of your product has a transformative effect.

It demonstrates the team have the ability to do the job in hand.
It demonstrates you have quality. It obliterates the need for a test-fix-test-fix aka stabilisation aka hardening phase.
It blows away sunk costs because something has been delivered.
It removes “maybe” and “ready but…”
It is probably the greatest risk mitigation strategy possible.
It creates trust and provides a platform for solid conversations.

Most of all, a released product is a far better statement of progress than any number of plans or forecasts.

This does not mean everything is done. Sure there are things left undone but there will be things left undone when I’m on my deathbed, that is the nature of life. As much as we (especially men) love to collect entire sets there are few prizes in life for completing everything on your bucket list.

Having a released product utterly changes the nature of the conversation. Conversations are no longer full of “ifs” “maybes” “shoulds” “how long will it take?” “what are the quick wins?”. Those questions can go away. In its place you can have serious conversations about prioritisation and “what do you want tomorrow?”

This is all part of the reason I love continuous delivery. Teams can focus on real priorities and stop wasting time on conjecture.

In my book if you don’t have a releasable product at least every two weeks – say every second Thursday – you are not Agile. And if you haven’t released a product to live in the last two weeks you are probably not Agile.

I don’t care how close you get to a releasable product: it isn’t a release if it isn’t released to a live environment – close but no cigar as they say. (OK, I’ll accept the live environment may not be publicly know, or might be called a beta, but it has to be the real thing.)

Nor should you rest on your laurels once you have regular releases (to live) every second week. That is but first base. You have opened the door, now go further. There are at least 13 opportunities to improve.

If you cannot do that now then ask yourself: Why can’t we release tomorrow?

And start working to remove those obstacles:

  • Reduce the number of work items you are aiming to put in the release.
  • Fix show-stopper defects now.
  • Running tests now.
  • Get those people who need to sign-off to sign-off.

Software development has diseconomies of scale: many small is cheaper than few large.

And once you have your release you can turn your attention to making sure these things don’t happen again:

  • Reduce the amount of work you accept into development at one time.
  • Fix every defects as soon as they are found.
  • Automate tests so they can run more often. (Automate anything that moves, and if it doesn’t move, automate it in case.)
  • Find a way to reduce the time it takes to get sign-offs: remove the sign-off, make sure the signer prioritises signing or delegate someone else to sign (or automate the signature.)

If there are essential processes, activities, third-parties (or anything else) that has limited bandwidth which need to be done before release but inject delay then re-orientate your process around that bottleneck. For example, if your code needs to pass a security audit before release (an audit you can’t automate that is) then, downsize all the other activities so that the audit process is 100% utilised. (OK, 100% is wrong, 76% might be better, but thats a long conversation about queuing theory.)

Again and again I seem condemned to learn the lesson: nothing counts but working software which is used.

As for my team, and my job in California, it didn’t save me. I regret not asking the question sooner.

Agile is the process digital technology needs

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In my presentation at Agile on the Beach last week I continued my discussion of Agile and Digital. It is increasingly clear that digital and agile are intrinsically linked. Specifically, business need agile processes to get the most out of digital technology. My “Agile, Digital & the new management paradigms” presentation is online but let me give you the argument here.

There is a long standing model of technology change – so widespread I can’t find the original source – which says change comes in three steps:

  1. First new technology allows the same processes and activities to be done better, faster, cheaper, more efficiently. In this stage new technology is used to do the same things, the processes and practices change little.
  2. Next new technology allows process and practices to be reconsidered and changed to make the most of new technology. Work becomes even better – whether that be faster, cheaper, higher efficiency, superior products, whatever.
  3. Finally new innovations appear because of the technology and new processes. One can see opportunities for new businesses, new business models, the next round of technology innovation and more.

So the whole thing repeats.

Look at the photo above. According to WikiCommons this is a picture of a factory at Woolwich Arsenal sometime in the 1800s. Notice the belts stretching from the ceiling to the workstations. These carried power, or to be more precise motion. Above the workers is the line shaft which turns. The shaft is driven by a central power (motion) source somewhere, probably a water wheel or a steam engine.

This is before electricity. The line shaft and the belts carry the power the factory needs to work. And they break, the longer they are the more prone to breaking they are. Factory design is constrained by the need to have straight lines for the line shaft and short distances between the shaft and the workstation. And factory design dictates layout and processes.

Then came electricity.

Electricity allowed each workstation to have its own motion generator. At first factory owners used electricity to do the same things faster and more reliably. They could dispense with the steam engine and thus the stokers and coal it needed. But at first they didn’t seize all the advantages electricity brought.

It took time to understand how a factory could be laid out more efficiently and how processes could be changed. When they did factories got even more efficient and faster. Some might argue that it took the coming of Lean manufacturing to complete these process changes.

The same story has played out in industry after industry with technology after technology. Think of Word processors: first they helped secretaries do their job faster, then processes changed and everyone wrote themselves, goodbye secretaries. Containerisation in the shipping industry is another. First ships loaded and unloaded faster. Then the shipping companies innovated but more importantly world trade innovated. Some observers claim containerisation was a more significant factor in trade globalisation than free-trade agreements.

Digital technology is like electricity. It changes business, it creates new opportunities for doing things differently. To get the most from digital technology you need new processes. Right now most companies are stuck – even happy – doing things faster. Only when they change processes will they get the full benefits.

Agile processes are that change.

Agile ways of working help companies get more from digital technologies. Without Agile companies using digital technologies are just doing the same old thing faster.

Agile started in software development for two reasons. First software developers had a lot of problems, they had the need to change. Second, programmers had the first access to digital technologies.

Ray Tomlinson, a programmer, was the first person with e-mail. Tim Berners-Lee, a programmer, had the first web-browser. Ward Cunningham, a programmer, had the first Wiki. I could continue.

Software developers created Agile because they needed to and they could.

This is why Agile is taking off in marketing.

Outside of technology itself marketing has probably been more exposed to digital technology than any other part of business. First with digital publishing then with social media. At first digital helped marketing departments do the same work faster. Next it changed what you could do entirely. Marketing is adopting agile because those processes allow marketeers to do a better job when working with new digital technology.

So forget all those arguments about agile being a better way of working (it is but never mind).

Forget all those stories of agile like processes and practices before 1998 (yes they existed but that doesn’t change things).

Forget the debate about waterfall and upfront planning versus agile and just-in-time (that is history).

All you need to know is:

  1. Digital technology is helping you do things faster/better/cheaper.
  2. Agile ways of working allow you to get more from digital tools.
  3. More innovation is coming.

Agile is the process for digital businesses.

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Image of Woolwich Arsenal factory taken from WikiCommons, no known copyright.

Organizational structure in the Digital and Agile age

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Someone asked the other day: how should an organisation be designed?

There are two potential answers, which actually aren’t as contradictory as they look at first sight.

The first is very simple: Don’t.

That is, don’t design your organization, don’t set out an organizational chart, don’t set out a plan and aim to restructure your organization to that plan. Rather create the conditions to let a structure emerge.

I suppose its the difference between “design” meaning “create a plan for the way you want things to be” and “design” meaning “the way things are arranged.” To differentiate them the first might be called “intentional design” and the latter “emergent design.”

That does not necessarily imply all emergent structures are good. As we see in code sometimes emergent designs are not always the best and over time they need refactoring. Which implies at some point there needs to be intentional design.

Put it like this: I’d rather your organization pulls the design rather than you push a design on the organization.

Organizational structure is itself a function of business strategy. And both need to be part emergent and part intentional. Although you might have noticed I tend towards emergent while most of the world tends towards intentional!

Thus it helps to have a reference model of how you think the organization should be, maybe something to steer the organization towards.

So the second answer to the question would be longer:

  • Create standing delivery teams which are embedded in the business line itself. This is sometimes call stream teams, or stream based development, or “teams aligned to the value stream”, or several other names I can’t think of just now.
  • Each business line is itself a stream of work and digital delivery teams support that work.
  • Teams contain all the skills and authority to do the work that is required for that business stream.
  • The team is part of the stream so the business/technical divide should dissolve. Something I call BusTech.
  • Teams are value seeking and value creating: the team seeks opportunities to create value for the business and delivers on the most valuable ones.
  • Devolve authority to the teams whenever you can. Teams are mini-businesses. (Notice I deliberately don’t use the word empowerment.)
  • Teams grow when the business is successful and more digital capability is needed. And teams shrink when money is tight or less capability is needed.
  • Teams may split (Amoeba style) from time to time. New teams may be in the same business line (addressing another question) or part of another, possibly new, business line.
  • Active – or Agile – Portfolio Management sits on top to monitor progress, provide extra resources, remove resources, etc. There may even be multiple portfolio processes, one at the business line level and perhaps one above multiple business lines.
  • Minimally Viable Teams are started to explore new initiatives, sometimes these go on to be full standing teams but they may also be dissolved if the idea doesn’t validate.
  • Seek to minimise common services between teams because these create bottlenecks, conflicts and delays. Each team should stand alone. This may mean some duplication, and therefore some extra costs, but accept that. Once you have your model working you can fine tune such things later.
  • Don’t worry about planning and synchronisation between teams to much, worry more about getting the teams to release more often and deal with synchronisation issues when they become a problem.

They are the main points at any rate. If you’d like to know more Continuous Digital contains a longer discussion of the topic. (Continuous Digital actually builds on Xanpan in this regard, and the (never finished) Xanpan Appendix discusses the same idea.)

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#NoProject #NoEstimates workshop

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In August I’m running a 1-day workshop in Zurich with Vasco Duarte on the bleeding edge of Agile: #NoProjects and #NoEstimates for Digital First companies.

This is a pre-conference event for the ALE 2018 conference which is happening the same week in Zurich. Everyone is welcome, you don’t need to attend the conference.

If you book in the next two weeks you get it for cheap, after July 20 the price goes up – although its still only a few hundred euros.

Book now, save money and secure your place – places are limited!

For those ho can’t get to Zurich in August I’ve got a Continuous Digital workshop of my own and a half-day management briefing. Right now you can book either of these for private in-house delivery. I’m looking at offering these as public courses here in London, if you are interested get in touch and help me fix a date.

(I have a love hate relationship with #NoProjects, I’d love to retire the name but it resonates with so many people. So I tend to use #NoProjects when I’m discussing my critique of the project model and Continuous Digital when I’m setting out my preferred alternative.)

Best practices considered harmfull

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I’ve long worried about “Best Practices”. Sure I usually play along at the time but lurking in the back of my mind, waiting for a suitable opportunity are two questions:

  • Who decided this was best practice?
  • Who says this practice can’t be bettered?

I was once told by someone from the oil industry that it was common for contracts to specify “best practice” should be used. But seldom was the actual practice specified. Instead each party to the contract would interpret best practice as they wished, until something went wrong. At that point, after an accident, after money was lost they would go to court and a judge would decide what was best practice.

Sure practice X might be the best know way of doing things at the moment but how much better could it be? By declaring something “best practice” you can be self limiting and potentially preventing innovation.

Now a piece in MIT Sloan Management Review (Why Best Practices Often Fall Short, Jérôme Barthélemy, February 2018) adds to the debate and highlights a few more problems.

Just for openers, sometimes people mistakenly identify the practice creating the benefits. Apparently some people looked at Pixar animation and decided that having rest rooms (toilets to us English speakers) in the centre of an office floor enhances creativity. They might do, but there is so much else happening at Pixar that moving all the toilets in your organization will probably make no difference at all.

But it is worse than that.

Adopting best practice from elsewhere does not mean it will be best practice in your environment but adopting that “best practice” will be disruptive. Think of all the money you will need to spend relocating the toilets, all the people who will be upset by a desk move they don’t want, all the lost productivity while the work is going on.

The author suggests that in some cases that disruption costs are so high the “best practice” will never cover the costs of the change. Organizations are better shunning the best practice and carrying on as they are. (ERP anyone?)

It gets worse.

There is risk in those best practices. Risk that they will cost more, risk that they won’t be implemented correctly and risk that they will backfire. What was best practice at one organization might not be best practice in yours. (Which might imply you need even more change, even more disruption at even more cost.)

In fact, some best practices – like stock options for executives – can go horrendously wrong and induce behaviours you most definitely don’t want.

So what is a poor company to do?

Well, the author suggests something that does work: copying good practices. Not best but “just OK”. That works. Copy the mundane stuff, the proven stuff. The costs and risks of a big change are avoided. (This sounds a bit like In Search of Mediocracy.)

In my world that means you want to be getting better at doing Agile instead of trying to leapfrog Agile and move to DevOps in one bound.

The author also suggests that where your competitive advantage is concerned keep your cards close to your chest. Do thinks yourself. Work out what your best practice is, work out how you can improve yourself.

I’ve long argued that I want teams to learn and learn for themselves rather than have change done to them. But I also want teams to steal. When they see other teams – at home or elsewhere – doing good things they should steal practices. The important thing from my point of view is for the teams to decide for themselves.

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Free books and other news

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Many of you are reading this because you signed-up for a free copy of my Xanpan book.

Thank you so much! – I hope you are enjoying my thoughts, reflections and tips.

Now, can I ask a favour, please? – a few minutes of your time.

If you have a copy of Xanpan would you mind writing me an Amazon review? (thats .com, Amazon UK has a separate list of reviews – yes, it is a pain).

Please, please, please 🙂

Amazon reviews make a big difference to sales and I’d be most grateful. (Even more so for 5-star reviews!)

And I will happily give a free review copy of “Little Book of Requirements and User Stories” to anyone who would like to review that book too – mail me, allan@allankelly.net. (And if you already have a copy of Little Book please suggest some other way I can thank you for your review.)

I’m also working on getting Continuous Digital and Project Myopia onto Amazon. Both will get new professional covers and a proper copy edit

Finally, as some of you know, I’ve started writing a companion to Little Book: Product Ownership. Again I’m using the LeanPub system so you can buy the book now and get free updates as I add to the book and edit it. And I am most grateful to those of you who have already bought Product Ownership.

Dialogue sheets update – translation & Amazon

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It is six years now since I introduced Retrospective Dialogue sheets to the world and I continue to get great feedback about the sheets. Now I’m running a little MVP with the sheets via Amazon, but first…

In the last few months Alan Baldo has translated the planning sheet to Portuguese and Sun Yuan-Yuan, with help from David Tanzer, has translated two of the retrospective sheets to German.

Thank you very much Alan, Sun and David!

I also updated the Sprint Retrospective sheet (above): version 5 has removed all references to software development. While can still be used by software teams it is more general. Actually, the sheet was largely domain neutral already which explains why it has been used in a Swedish kindergarten for retrospectives.

In the meantime I’ve been busy with an MVP experiment of my own – which has taken a surprising amount of work to get up and running – and you can help with.

I have made printed versions of the latest Sprint Retrospective sheet available on Amazon to buy. The sheets are still available as a free download to print yourself but I want to see if I can reach a broader audience by offering the sheets on Amazon. Plus I know some teams have trouble getting the sheets printed.

Right now this is market test, the printed sheets are only available in the UK I only have a few sheets in stock so this is a “Buy now while stocks last” offer.

If you are outside the UK (sorry) and want a printed sheet, or find stocks have run out, or want a different printed sheets please contact me and I’ll do my best.

Assuming this is a success then I’ll get more sheets printed, arrange to sell outside the UK, add more of the sheets to Amazon and make a renewed effort on translations. Pheww!

So now I need to ask for your help.

If you have used the sheets and find them good please write a review on Amazon – there are a few but there cannot be too many.

Conversely, if you have never tried a Dialogue Sheet retrospective please do so and let me know how it goes: I am always seeking feedback. Download and print for yourself or go over to Amazon and buy today – you could be the first buyer!

Estimation, planning, teams and money, some data

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When I deliver Agile training for teams I run an exercise called “The Extended XP Game”. It is based on the old “XP Game” but over the years I’ve enhanced it and added to it. We have a lot of fun, people are laughing and they still talk about it years later. The game illustrates a lot of agile concepts: iteration, business value, velocity, learning by doing, specification by example, quality is free, risk, the role of probability and some more.

When I run the exercise I divide the trainees into several teams, usually three or four people to a team. I show them I have some tasks written on cards which they will do in a two minute iteration. They do two minutes or work, review, retrospect then do another two minutes of work – and possibly repeat a third time.

The first thing is for teams to Get Ready: I hand out the tasks and ask them to estimate, in seconds how long it will take to do each task: fold a paper airplane that will fly, inflate a balloon, deflate a balloon, roll a single six on a dice, roll a double six on two dice, find a two in a pack of cards and find all the twos in the pack of cards. Strictly speaking, this estimate is a prospective estimate, “how long will it take to do this in future?”

Once they have estimated how long each task will take someone is appointed product owner and they have to plan the tasks to be done (with the team).

What I do not tell the teams is that I’m timing them at this stage. I let the teams take as long as they like to get ready: estimate and plan. But I time how long the estimation takes and how long the following planning takes.

Once all the teams are “ready” I ask the teams: “how long did that take?”

At this point I am asking for a retrospective estimate: how long did it take. The teams have perfect estimation conditions: they have just done it, no time has elapsed and no events have intervened.

Typically they answer are 5 or 6 minutes, maybe less, maybe more. Occasionally someone gets the right number and they are then frequently dismissed by their colleagues.

Although I’ve been running this exercise for nearly 10 years, and have been timing teams for about half that time I’ve only been recording the data the last couple of years. Still it comes from over 65 teams and is consistent.

The total time to get ready to do 2 minutes of work is close to 13 minutes – the fastest team took just 5.75 minutes but the slowest took a whopping 21.25.

The average time spent estimating the tasks is 7 minutes. The fastest team took 2.75 minutes and the slowest 14 minutes.

The average time planning once all tasks are estimated is just short of 6 minutes. One team took a further 13.5 minutes to plan after estimates while another took just 16 seconds. While I assume they had pretty much planned while estimating it is also interesting to note that that team contained several people who had done the exercise a few years before.

(For statistics nuts the mean and median are pretty close together and I don’t think the mode makes much sense in this scenario.)

So what conclusions can we draw from this data?

1) Teams take longer to estimate than do

Everyone taking part in the exercise has been told – several times – that they are preparing to do a 2 minute iteration. Yet on average teams spend 12.75 minutes preparing – estimating and planning – to do 2 minutes of work!

Or to put it another way: teams typically spend six times longer to plan work than to do work.

The slowest team ever took over 10 times longer to plan than to do.

In the years I’ve been running this exercise no team has ever done a complete dry run. They sometimes do little exercises and time themselves but even teams which do this spend a lot of time planning.

This has parallels in real life too: many participants tell me their organization spend a long time debating what should be done, planning and only belatedly executing. One company I met had a project that had been in planning for five years.

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2) Larger teams take longer to estimate than small teams

My second graph shows there is a clear correlation between team size and the time it takes to estimate and plan. I think this is no surprise, one would expect this. In fact, this is another piece of evidence supporting Diseconomies of Scale: the bigger the team the longer it will take to get ready.

This is one reason why some people prefer to have an “expert” make the estimate – it saves the time of other people. However this itself is a problem for several reasons.

Anyone who has read my notes on estimation research (and the later more notes on estimation research) may remember that research shows that those with expert knowledge or in a position of authority underestimate by more than those who do the work. So having an expert estimate isn’t a cure.

But, those same notes include research that shows that people are better at estimating time for other people than they are at estimating time for themselves, so maybe this isn’t all bad.

However, this approach just isn’t fair. Especially when someone is expected to work within an estimate. One might also argue that it is not en effective use of time because the first person – the estimator – has to understand the task in sufficient detail to estimate it but rather than reuse this learning the task is then given to someone else who has to learn it all over again.

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3) Post estimation planning is pretty constant

This graph shows the planning delta, that is: after the estimates are finished how long does it take teams to plan the work?

It turns out that the amount time it takes to estimate the task has little bearing on how long the subsequent planning takes. So whether you estimate fast or slow on average it will take six more minutes to plan the work.

Perhaps this isn’t that surprising.

(If I’ve told you about this data in person I might have said something different here. In preparing the data for this blog I found an error in my Excel graphs which I can only attribute to a bug in Excel’s scatter chart algorithm.)

4) Vierordt’s Law holds

People underestimate longer periods of time (typically anything over 10 minutes), and overestimate short period of time (typically things less than two minutes).

Not only do trainees consistently underestimate how long it has taken them to get ready – which is over 10 minutes – but teams which record how long it takes to actually do each task find that their estimates are much higher than the actual time it takes. Even when teams don’t time themselves observation shows that they do the work far faster than they thought they would.

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5) Less planning makes more money

One of my extensions to the original game is to introduce money: teams have to deliver value, measured in money. This graph shows teams which spend less time planning go on to make more money.

I can’t be as sure about this last finding as the earlier ones because I’ve not been recording this data for so long. To complicate matters a lot happens between the initial planning and the final money making, I introduce some money and teams get to plan for subsequent iterations.

Still, there are lessons here.

The first lesson is simply this: more planning does not lead to more money.

That is pretty significant in its own right but there is still the question: why do teams which spend less time planning make more money?

I have two possible explanations.

I normally play three rounds of the game. When time is tight I sometimes stop the game after two rounds. In general teams usually score more money in each successive round. Therefore, teams who spend longer in planning are less likely to get to the third round so their score comes from the second round. If they had time to play a third round they would probably score higher than in round two.

This has a parallel in real life: if extra planning time delays the date a product enters the market it is likely to make less money. Delivering something smaller sooner is worth more.

This perfectly demonstrates that doing creates more learning than planning: teams learn more (and therefore increase their score) from spending 2 minutes doing than spending an extra 2 minutes planning.

The second possible explanation is that the more planning a team does the more difficult they might find it to rethink and change the way they are working.

The $1,600 shown was recorded by a Dutch team this year but the record is held by a team in Australia who scored over $2,000: to break into these high scores teams need to reinterpret the rules of the game.

One of the points of the game is to learn by doing. I suspect that teams who spend longer in planning find it harder to break away from their original interpretation of the rules. How can you think outside the box when you’ve spent a lot of time thinking about the box?

In one training session in Brisbane last year the teams weren’t making the breakthrough to the big money. Although I’d dropped hints of how to do this nobody had made the connection so I said: “You know, a team in Perth once scored over $2,000.” That caused one of the players to rethink his approach and score $1,141.

I’ve since repeated the quote and discovered that simply telling people that such high scores are possible causes them to discover how to score higher.

* * *

I’m sure there is more I could read into all this data and I will carry on collecting the data. Although now I have two problems…

First, having shared this data I might find people coming on my agile software training who change their behaviour because they have read this far.

Second: I need more teams to do this to gather data! If you would like to do this exercise – either as part of a full agile training course or as a stand alone exercise – please call (+44 20 3286 4292) or mail me, contact@allankelly.net, my rates are quite reasonable!

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Product Ownership book – a work in progress

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A quick update: most of my recent blogs about the product owner role together with some new material, is now available in book form from LeanPub – https://leanpub.com/productownership.

I’m surprised to find I’ve written over 60 pages so far! Still, this is very much a work in progress, there are a few more chapters to add to part 1: The Product Owner role.

But it is part 2 which I’m itching to start writing: the tools of the trade.

For those who don’t know, the beauty of LeanPub is that you can buy my unfinished book now and you will receive updates – to your iPad, Kindle, PC, whatever – as they are produced.

That means three things to me.

Firstly I can receive your feedback – what do you like? What did I get wrong? What else should be in there?

Second, money is feedback, the more of you who buy the book the more motivated I am to write it – I like seeing sales, it tells me people want this book. And if you don’t buy… well maybe I should pivot and abandon it.

Third, it gives me a little beer money.

The bad news is: you also get my dyslexic spelling and grammar.