Definition of Ready considered harmful


Earlier this week I was with a team and discussion turned to “the definition of ready.” This little idea has been growing more and more common in the last couple of years and while I like the concept I don’t recommend it. Indeed I think it could well reduce Agility.

To cut to the chase: “Definition of ready” reduces agility because it breaks up process flow, assumes greater role specific responsibilities, introduces more wait states (delay) and potentially undermines business-value based prioritisation.

The original idea builds on “definition of done”. Both definitions are a semi-formal checklists agreed by the team which are applied to pieces of work (stories, tasks, whatever). Before any piece of work is considered “done” it should satisfy the definition of done. So the team member who has done a piece of work should be able to mentally tick each item on the checklist. Typically a definition of done might contain:


  • Story implemented
  • Story satisfies acceptance criteria
  • Story has been seen and approved by the product owner
  • Code is passing all unit and acceptance tests

Note I say “mentally” and I call these lists “semi formal” because if you start having a physical checklist for each item, physically ticking the boxes, perhaps actually signing them, and presumably filing the lists or having someone audit them then the process is going to get very expensive quickly.

So far so good? – Now why don’t I like definition of ready?

On the one hand definition of ready is a good idea: before work begins on any story some pre-work has been done on the story to ensure it is “ready for development” – yes, typically this is about getting stories ready for coding. Such a check-list might say:


  • Story is written in User Story format with a named role
  • Acceptance criteria have been agreed with product owner
  • Developer, Tester and Product owner have agreed story meaning

Now on the other hand… even doing these means some work has been done. Once upon a time the story was not ready, someone, or some people have worked on the story to make it ready. When did this happen? Getting this story ready has already detracted from doing other work – work which was a higher priority because it was scheduled earlier.

Again, when did this happen?

If the story became “ready” yesterday then no big deal. The chances are that little has changed.

But if it became ready last week are you sure?

And what if it became ready last month? Or six months ago?

The longer it has been ready the greater the chance that something has changed. If we don’t check and re-validate the “ready” state then there is a risk something will have changed and be done wrong. If we do validate then we may well be repeating work which has already been done.

In general, the later the story becomes “ready” the better. Not only does it reduce the chance that something will change between becoming “ready” and work starting but it also minimises the chance that the story won’t be scheduled at all and all the pre-work was wasted.

More problematic still: what happens when the business priority is for a story that is not ready?

Customer: Well Dev team story X is the highest priority for the next sprint
Scrum Master: Sorry customer, Story X does not meet the definition of ready. Please choose another story.
Customer: But all the other stories are worth less than X so I’d really like X done!

The team could continue to refuse X – and sound like an old style trade unionist in the process – or they could accept X , make it ready and do it.

Herein lies my rule of thumb:


If a story is prioritised and scheduled for work but is not considered “ready” then the first task is to make it ready.

Indeed this can be generalised:


Once a story is prioritised and work starts then whatever needs doing gets done.

This simplifies the work of those making the priority calls. They now just look at the priority (i.e. business value) or work items. They don’t need to consider whether something is ready or not.

It also eliminates the problem of: when.

Teams which practise “definition of ready” usually expect their product owner to make stories ready before the iteration planning meeting, and that creates the problems above. Moving “make ready” inside the iteration, perhaps as a “3 Amigos” sessions after the planning meeting, eliminates this problem.

And before anyone complains saying “How can I estimate something thing that is not prepared?” let me point out you can. You are just estimating something different:


  • When you estimate “ready” stories you are estimating the time it takes to move a well formed story from analysis-complete to coding-complete
  • When up estimate an “unready” story you are estimating the time it takes to move a poorly formed story from its current state to coding-complete

I would expect the estimates to be bigger – because there is more work – and I would expect the estimates to be subject to more variability – because the initial state of the story is more variable. But is still quite doable, it is an estimate, not a promise.

I can see why teams adopt definition of ready and I might even recommend it myself but I’d hope it was an temporary measure on the way to something better.

In teams with broken, role based process flows then a definition of done for each stage can make sense. The definition of done at the end of one activity is the definition of ready for the next. For teams adopting Kanban style processes I would recommend this approach as part of process/board set-up. But I also hope that over time the board columns can be collapsed down and definitions dropped.

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What if it is all random?


What if success in digital business, and in software development, is random? What if one cannot tell in advance what will succeed and what will fail?

My cynical side sometimes thinks everything is random. I don’t want to believe my cynical side but…

All those minimally viable products, some work, some fail.

All those stand-up meetings, do they really make a difference?

All those big requirements documents, just sometimes they work.

How can I even say this? – I’ve written books on how to “do it right.”
I advise companies on how to improve “processes.” I’ve helped individuals do better work.

And just last month I was at a patterns conference trying to spot reoccurring patterns and why they are patterns.

So let me pause my rational side and indulge my cynical side, what if it is all random?

If it is all random what we have to ask is: What would we do in a random world?

Imagine for a moment success is like making a bet at roulette and spinning the wheel.

Surely we would want to both minimise losses (small bets) and maximise wheel spins: try lots, remove the failures quickly and expand the successes (if we can).

I suggested “its all random” to someone the other day and he replied “It is not random, its complex.” And we were into Cynefin before you could say “spin the wheel.”

Dave Snowden’s Cynefin model attempts to help us understand complexity and the complex. Faced with complexity Cynefin says we should probe. That is, try lots of experiments so we can understand, learn from the experiments and adjust.

If the experiment “succeeds” we understand more and can grow that learning. Where the experiment “fails” we have still learned but we will try a different avenue next time.

Look! – it is the same approach, the same result, complexity, Cynefin or just random: try a lot, remove failure and build on success. And hang on, where have I heard that before, … Darwin and evolution; random gene mutations which give benefit get propagated and in time others die out.

It is just possible that Dave is right, Darwin is right and I am right…

Today most of the world’s mobile/cell telephone systems are built on CDMA technology. CDMA is super complex maths but it basically works by encoding a signal (sequence of numbers, your voice digitised) and injecting it into a random number stream (radio spectrum), provided you know the encoding you can retrieve the signal out of the randomness. Quite amazing really.

Further, provided the number sequences are sufficiently different they are in effect random so you can inject more signal into the same space.

That is why we can all use our mobile phones at the same time.

Put it another way: you walk into a party in London, in the room are Poles, Lebanese, Germans, Argentinians and the odd Brit. They are all talking in their own language to fellow speakers. Somehow you can hear your own language and join the right conversation. Everything else is random background noise.

Maybe the same is true in digital business and software development…

Perhaps it is all complex but it is so complex that we will never be able to follow all the cause and effect chains, it is so complex that it looks random. Dave is right with Cynefin but maybe there is so much complexity that we might as well treat it as random and save our time.

Back to CDMA and London parties, faced with apparent randomness there are useful strategies and signals can still be extracted.

Perhaps the way to deal with this complexity is not to try and understand it but to treat it as random. Rather than expend energy and time on a (possibly) impossible task accept it as random and apply appropriate strategies.

After all, if we have learned anything from statistical distributions it is that faced with actual and apparent randomness we can still find patterns, we can still learn and we can still work with, well, randomness.

Programmer’s Rorschach test

The picture above, I recently added this picture to Continuous Digital for a discussion of teams. When you look at it what do you see:

An old style structure chart, or an organization chart?

It could be either and anyone who knows of Conway’s Law shouldn’t be surprised.

When I was taught Modula-2 at college these sort of structure charts were considered superior to the older flow charts. This is functional decomposition, take a problem, break it down to smaller parts and implement them.

And that is the same idea behind traditional hierarchical organizational structure. An executive heads a division, he has a number of managers under him who manage work, each one of these manage several people who actually do the work (or perhaps manage more manager who manage the people who do the work!)

Most organizations are still set up this way. It is probably unsurprising that 50 years ago computer programmers copied this model when designing their systems – Conway’s Law, the system is a copy of the organization.

Fast forward to today, we use object oriented languages and design but most of our organizations are still constrained by hierarchical structure, that creates a conflict. The company is structurally decomposed but our code is object oriented.

The result is conflict and in many cases the organization wins – who hasn’t seen an object oriented system that is designed in layers?

While the conflict exists both system and organization under perform because time and energy are spent living the conflict, managing the conflict, overcoming the conflict.

What would the object-oriented company look like?

If we accept that object oriented design and programming are superior to procedural programming (and in general I do although I miss Modula-2) then it becomes necessary to change the organization to match the software design – reverse Conway’s Law or Yawnoc. That means we need teams which look and behave like objects:

  • Teams are highly cohesive (staffed with various skills) and lightly coupled (dependencies are minimised and the team take responsibility)
  • Teams are responsible for a discrete part of the system end-to-end
  • Teams add value in their own right
  • Teams are free to vary organizational implementation behind well defined interface
  • Teams are tested, debugged and maintained: they have been through the storming phase, are now performing and are kept together

There are probably some more attributes I could add here, please make your own suggestions in the comments below.

To regular readers this should all sound familiar, I’ve been exposing these ideas for a while, they draw on software design and Amoeba management, I discuss them at greater length Xanpan, The Xanpan Appendix and now Continuous Digital – actually, Continuous Digital directly updates some chapters from the Appendix.

And like so many programmers have found over the years, classes which are named “Manager” are more than likely poorly named and poorly designed. Manager is a catch all name, the class might well be doing something very useful but it can be named better. If it isn’t doing anything useful, then maybe it should be refactored into something that is. Most likely the ManagerClass is doing a lot of useful stuff but it is far from clear that it all belongs together. (See the management mini-series.)

Sometimes managers or manager classes  make sense, however both deserve closer examination. Are they vestige from the hierarchal world? Do they perform specialist functions which could be packaged and named better? Perhaps they are necessary, perhaps they are necessary for smoothing the conflict between the hierarchal organization and object oriented world.

Transaction costs can explain both managers and manager classes. There are various tasks which require knowledge of other tasks, or access to the same data. It is cheaper, and perhaps simpler, to put these diverse things together rather than pay the cost of spreading access out.

Of course if you accept the symbiosis of organization and code design then one should ask: what should the organization look like when the code is functional? What does the Lisp, Clojure or F# organization look like?

And, for that matter, what does the organization look like when you program in Prolog? What does a declarative organization look like?

Finally, I was about to ask about SQL, what does the relational organization look like, but I think you’ve already guessed the answer to this one: a matrix, probably a dysfunctional matrix.