The life-changing magic of tidying your work

Surprise! Managing work in a large organisation is a lot like keeping your belongings in check at home.

Get it wrong at home and you have mess and clutter. Get it wrong in the organisation and you have excessive work in progress (WIP), retarding responsiveness, pulverising productivity, and eroding engagement.

Reading Marie Kondo’s The Life-Changing Magic of Tidying Up (Amazon), I was struck by a number of observations about tidying personal belongings that resonated with how individuals, teams and organisations manage their work.

First, reading TLCMOTU helped me tidy my things better. Second, it reinforced lean and agile management principles.

I won’t review the book here. Maybe the methods and ideas resonate with you, maybe they don’t. However, because I think tidying is something that everyone can relate to, I will compare some of KonMari’s (as Marie Kondo is known) explanations of the management of personal belongings with the management of work in organisations. The translation heuristic is to replace stuff with work, and clutter with excessive WIP, to highlight the parallels.

I’d love to know if you find the comparison useful.

On the complexity of work storage systems

KonMari writes:

Most people realise that clutter is caused by too much stuff. But why do we have too much stuff? Usually it is because we do not accurately grasp how much we actually own. And we fail to grasp how much we own because our storage methods are too complex.

Organisations typically employ complex storage methods for their work: portfolio and project management systems with myriad arcane properties, intricate plans, baselines and revisions, budget and planning cycle constraints, capitalisation constraints, fractional resource allocations, and restricted access to specialists who are removed from the outcomes but embrace the management complexity.

And this is just the work that’s stored where it should be. Then there’s all the work that’s squirrelled away into nooks and crannies that has to be teased out by thorough investigation (see below).

Because organisations don’t comprehend the extent of their work, they invent ever-more complex systems to stuff work into storage maximise utilisation of capacity, which continues to hide the extent of the work.

Thus, we fail to grasp how much work is held in the organisation, and the result is excessive WIP, which inflates lead times and reduces productivity, failing customers and leaving workers disengaged. Simplifying the storage of work – as simple as cards on a wall, with the information we actually need to deliver outcomes – allows us to comprehend the work we hold, and allows us to better manage WIP for responsiveness and productivity.

On making things visible

KonMari observes that you cannot accurately assess how much stuff you have without seeing it all in one place. She recommends searching the whole house first, bringing everything to the one location, and spreading the items out on the floor to gain visibility.

Making work visible, in one place, to all stakeholders is a tenet of agile and lean delivery. It reveals amazing insights, many unanticipated, about the volume, variety and value (or lack of) of work in progress. The shared view helps build empathy and collaboration between stakeholders and delivery teams. You may need to search extensively within the organisation to discover all the work, but understanding of the sources of demand (as below) will guide you. A great resource for ideas and examples of approaches is Agile Board Hacks.

So get your work on cards on a wall so you can see the extent of your WIP.

On categories

KonMari observes that items in one category are stored in multiple different places, spread out around the house. Categories she identifies include clothes, books, etc. She contends that it’s not possible to assess what you want to keep and discard without seeing the sum of your belongings in each category. Consequently, she recommends thinking in terms of category, rather than place.

If we think organisationally in terms of place, we think of silos – projects, teams, functions. We can’t use these storage units to properly assess the work we hold in the organisation. Internal silos don’t reflect how we serve customers.

Instead, if we think organisationally in terms of category, we are thinking strategically. With a cascading decomposition of strategy, driven by the customer, we can assess the work in the organisation at every level for strategic alignment (strategy being emergent as well as explicit). Strategy could be enterprise level themes, or the desired customer journey at a product team level.

With work mapped against strategy, we can see in one place the sum of efforts to execute a given branch of strategy, and hence assess what to keep and what to discard. We further can assess whether the entire portfolio of work is sufficiently aligned and diversified to execute strategy.

So use your card wall to identify how work strategically serves your customers.

On joy

KonMari writes:

The best way to choose what to keep and what to throw away is to … ask: ‘Does this spark joy?’ If it does keep it. If not, throw it out.

We may ask of each piece of work: ‘Is this work valuable?’ ‘Is it aligned to the purpose of the organisation?’ ‘Is it something customers want?’ If it is, keep it. If not, throw it out.

KonMari demonstrates why this is effective by taking the process to its logical conclusion. If you’ve discarded everything that doesn’t spark joy, then everything you have, everything you interact with, does spark joy.

What better way to spark joy in your people than to reduce or eliminate work with no value and no purpose?

On discarding first

KonMari observes that storage considerations interrupt the process of discarding. She recommends that discarding comes first, and storage comes second, and the activities remain distinct. If you start to think about where to put something before you have decided whether to keep or discard it, you will stop discarding.

Prioritisation is the act of discarding work we do not intend to pursue. Prioritisation comes first, based purely on value, before implementation considerations. Sequencing can be done with knowledge of effort and other dependencies. Then scheduling, given capacity and other constraints, is the process of deciding which “drawers” to put work in.

On putting things away

KonMari observes that mess and clutter is a result of not putting things away. Consequently she recommends that storage systems should make it easy to put things away, not easy to get them out.

Excessive WIP may also be caused by a failure to rapidly stop work (or perceived inability to do so). Organisational approaches to work should reduce the effort needed to stop work. For instance, with continuous delivery, a product is releasable at all times, and can therefore be stopped after any deployment. Work should be easily stoppable in preference to easily startable. (This could also be framed as “stop starting and start finishing”.)

Further, while many organisations aim for responsiveness with a stoppable workforce (of contractors), they should instead aim for a stoppable portfolio, and workforce responsiveness will follow.

On letting things go

A client of KonMari’s comments:

Up to now, I believed it was important to do things that added to my life …  I realised for the first time that letting go is even more important than adding.

I have written about the importance of letting go of work from the perspective of via negativa management in Dumbbell Delivery; Antifragile Software, and managing socialisation costs in Your Software is a Nightclub.

However, KonMari also observes that, beyond the mechanics of managing stuff (or work), there is a psychological cost of clutter (or excessive WIP). Her clients often report feeling constrained by perceived responsibility to stuff that brings them no joy. I suspect the same is true in the organisation: we fail to recognise and embrace possibilities because we are constrained by perceived responsibilities to work that ultimately has no value.

Imagine if we could throw off those shackles. That’s worth letting a few things go.

Arguments with Agency

Here are slides from my talk at LASTconf 2015. The title is “Bring Your A-Game to Arguments for Change”. The premise is that there are different types of arguments, more or less suited to various organisational and delivery scenarios, and the best ones have their own agency. In these respects, you can think of them like Pokemon – able to go out and do your bidding, with the right preparation.

Change agents
Change agents

The content draws heavily from ideas shared on this blog:

Dumbbell Delivery; Antifragile Software

Not online fitness shopping. Not the brogrammer pumping iron. This is a brief discussion of Antifragile – the latest book by Nassim Nicholas Taleb – and relevant insights for software delivery or other complex work.

This isn’t meant to be an exhaustive exploration of the topics. It’s more a join-the-dots exercise, and it’s left up to the reader to explore topics of interest.


Antifragile is a word coined by Taleb to describe things that gain from disorder. Not things that are impervious to disorder; the words for that are robust, or resilient. Of course, things that are harmed by disorder are fragile. Consideration of the fragile, the robust, and the antifragile leads Taleb in many interesting directions.

Fragile, Robust, and Antifragile Software

A running software program is fragile. It is harmed by the most minor variations in its source code, its build process, its dependencies, its runtime environment and its inputs.

But software is eating the world. The global software ecosystem has grown enormously over an extended time – time being a primary source of variation – and hence appears to be antifragile. How do we reconcile this apparent paradox?

Here is a grossly simplified perspective.

First, software code can evolve very quickly, passing on an improved design to the next generation of runtime instances. In this way, tools, platforms, libraries and products rapidly become more robust. However, human intervention is still required for true operational robustness.

Second, humans exercise optionality in selecting progressively better software. In this way, beneficial variation can be captured, deleterious variation discarded, and software goes from robust to antifragile.

So – as fragile parts create an antifragile whole – runtime software instances are fragile, but fragile instances that are constantly improved and selected by humans create an antifragile software ecosystem. (If software starts doing this for itself, we may be in trouble!)

Some Delivery Takeaways

Yes, I know that’s an oxymoron. Nonetheless, here are some of my highlights. It’s a while now since I read the book, and I might add to this in future, so don’t take it as the last word.

Dumbbell Delivery

The idea of “dumbbell”/”barbell” risk management is that you place your bets in one of two places, but not in between. You first ensure that you are protected from catastrophic downside, then expose yourself to a portfolio of potentially large upsides. In such cases, you are antifragile.

If, instead, you spread yourself across the middle of the dumbell, you carry both unacceptably large downside exposure and insufficiently large upside exposure. In such cases, you are fragile.

For me, “dumbbell delivery” is how we counter insidious elements of the construct of two-speed-IT (insidious because no one has ever asked to go slow, or asked for high risk as the alternative). We ensure any project is as protected as possible from catastrophic downside – by decoupling the commission of error from any impact on operations or reputation – and as exposed as possible to potentially large upsides – by providing maximum freedom to teams to discover and exploit opportunities in a timely manner.

Donald Reinertsen makes a similar argument for expoliting the asymmetries of product development payoffs in The Principles of Product Development Flow.

Via Negativa

Those who intervene in complex systems may cause more harm than good. This is known as iatrogenics in medicine. To manage complex systems, removing existing interventions is more likely to be successful than making additional interventions, as each additional intervention produces unanticipated (side) effects by itself, and unanticipated interactions with other interventions in tandem. Via negativa is the philosophy of managing by taking things away.

Software delivery, and organisations in general, are complex in that they are difficult to understand and respond unpredictably to interventions. What’s an example of an intervention we could take away?  Well, let’s say a project is “running late”. Instead of adding bodies to the team or hours to the schedule, start by trying to eliminate work through a focus on scope and quality. Also, why not remove targets?

Big Projects, Monolithic Systems

Anything big tends to be fragile. Break it into smaller pieces for greater robustness. Check.

Waterfall and Agile

Waterfall done by the book is fragile. Agile done as intended is antifragile.

Procrustean Beds

Forcing natural variation into pre-defined, largely arbitrary containers creates fragility. Velocity commitments and other forms of management by performance target come to mind.

Skin in the Game

Of course, anyone making predictions should have skin in the game. On the other hand, Hammurabi’s code is the converse of the safe-to-fail environment.

The Lindy Effect on Technology lifespan

The life expectancy of a technology increases the longer it has been around. Remember this the next time you want to try something shiny.

Phenomenology and Theory

Phenomenology may be superior to theory for decision-making in complex work. Phenomenology says “if x, then we often observe y“. Theory says “if x, then y, because z“. Theory leads to the illusion of greater certainty, and probably a greater willingness to intervene (see above).

Flaneurs and Tourists

Chart your own professional journey. Allow yourself the time and space for happy discoveries.

Playing Games is Serious Business

Simple game scenarios can produce the same outcomes as complex and large-scale business scenarios. Serious business games can therefore reduce risk and improve outcomes when launching new services. Gamification also improves alignment and engagement across organisational functions.

This is a presentation on using games to understand and improve organisational design and service delivery, which I presented at the Curtin University Festival of Teaching and Learning.

(Don’t be concerned by what looks like a bomb-disposal robot in the background.)

The slides provide guidance on applying serious business games in your context.

Iterative vs Incremental Flashcard

Sometimes, the difference between incremental and iterative (software) product development is subtle. Often it is crucial to unlocking early value or quickly eliminating risk – an iterative approach will do this for you, while incremental will not.

Incremental vs Iterative
Incremental vs Iterative

Let’s review the distinction. Incremental means building something piece by piece, like creating a picture by finishing a jigsaw puzzle. This is great for visibility of progress, especially if you make the pieces very small. However, the inherent risk is that an incremental build is not done until the last piece is in place. Splitting something into incremental pieces implies the finished whole is understood (by the jigsaw designer, at least). If something changes during the build, like a bump to the table,  all of your work to date is at risk. Future work – to finish the whole – is also at risk of delivering less than optimal value, if our understanding of value changes during an incremental build. Much development work done under an agile banner is in fact incremental, and therefore more like a mini-waterfall approach than an essentially agile approach.

Iterative, on the other hand, means building something through successive refinements, starting from the crudest implementation that will do the job, and at each stage refining in such a way that you maintain a coherent whole. You might think of this like playing Pictionary. When you are asked to draw the Mona Lisa, you start with (perhaps) a rectangle with a circle inside. If your partner guesses at this point, great! If not, you might add the smile, the hair, the eyes. Hopefully, your partner has guessed by now.  If not, embellish the frame, add the landscape, draw da Vinci painting it, show it hanging in the Louvre, etc. Your risk exposure (that time will expire before your partner guesses) is far lower with an iterative approach. With each iteration, you have captured some value. If your understanding of value changes (eg, your partner shouts something unhelpful like “stockade”), you still retain your captured value, and you can also adjust your future activities to accommodate your new understanding.

I think I capture all of this in the diagram above. If you’re having trouble articulating the difference between incremental and iterative (because both show similar signs of progress at times), or you’re concerned about the risk profile of your delivery, refer to this handy pocket guide.

The Like-for-Like Project Antipattern

Like-for-like replacement.

Sounds pretty simple, doesn’t it? That’s an easy project to deliver, right?


Why would we do a like-for-like (L4L) project? The IT group may want to upgrade to a new system, because the old one is broken, or because they’ve found something better. Maybe we want to avoid re-training users. Or, maybe our L4L project is hiding in a larger project. It could be phase 1, in which functionality is replicated, while new value is delivered in phase 2. There’s no strong pull from users for this L4L project, so to avoid ‘disruption’, the project plans to hot swap a technology layer while otherwise preserving functionality, much like a magician yanking off a tablecloth without disturbing any of the tableware. However, someone is about to have their dinner spoiled.

A clarification. L4L exhibits some of the characteristics of refactoring. But refactoring deliberately tries to stay small, in time and cost. The success criteria are also easily established, for instance, as unit tests. I’m talking here about replacing one non-trivial IT system with another, especially if the target system is primarily bought rather than built.

The Key Problem

Too many constraints
Too many constraints

Framing a project as L4L is not just demonstrably incorrect, it is lazy to the point of negligence. The L4L framing is incorrect because it can never be achieved. The current technology solution has constraints, and business processes have evolved under the current technology constraints. But the new solution will have new technological constraints. There is no chance the two sets of constraints will be equivalent (if they are equivalent, why would you bother changing systems?) Therefore, business processes will be forced to evolve under the new solution. If business processes are changing, this cannot be a L4L project, and the framing is incorrect.

It’s irrelevant whether we’re talking about L4L functionality or L4L business outcomes. As above, L4L functionality is a logical impossibility. If we’re talking L4L business outcomes, which users are going to support a disruptive change in functionality in order to be able to achieve exactly what they do today, and no more?

The L4L framing is lazy because it discourages critical thinking. Stakeholders will confuse the apparent simplicity of framing with simplicity of execution, meaning they will be less engaged in resolving the thorny problems that will inevitably crop up. This is especially important for project sponsors and other senior stakeholders. The business will not be engaged in a process that gives them no voice. This will be doubly so if, as above, the project is not actually like for like, and the deleterious changes in business process are being driven by IT.

The real negligent laziness, however, is in assuming that collectively we haven’t learnt any more about how to deliver business value since we implemented the current system. The current system is probably five to ten years old, and inevitably has shortcomings – why would we copy it? We might, at great effort, be able to figure out what the system is capable of, then build this, but this is far more than users actually use, and entirely different from what they want. This lazy framing leads to much more work than would be required if we simply went to the business/customers to understand what they really need at this time.

You’ll end up taking longer, costing more, and delivering poorer outcomes if you frame your project as like-for-like.

More Problems

Like for like framing is the key problem, but it spawns a host of other problems:

  • Inflexible execution means no ability to respond to change
  • Analysis by reverse engineering is very wasteful
  • Sysadmin as the customer precludes insight
  • Prioritisation is backwards to avoid destroying value
  • Value delivered in a Phase 2, which never happens
  • Reporting misses the fact that there are two different things to report

These are substantial topics in their own right. I’d like to finish this post sometime, so I’ll try to pick up these threads in detail in future posts.

What Might Happen?

So, how might an L4L project play out?

Well, it’s hard to predict the future, but like Plutonium , L4L projects are unstable and tend to disintegrate. While a typical agile project is self-correcting, in that everyone sees the value, scope can be adjusted to meet time, and so on, a L4L project has no give.

When estimates are discovered to be optimistic – as complex workarounds will inevitably be required to deliver old results on new technology – the only option for a true L4L project is to run late. Or, we expose the L4L fallacy by making functional or non-functional compromises. Likely, it will be a combination of both.

Stakeholders who were reluctant from the start are now in an even worse position. They originally stood to gain nothing but disruption, but now they definitely lose out. They may begin political manoeuvring to make the project go away. Governance will probably start sniffing around if this late, costly project is not delivering value.

Again, at this point, there’s not much room to move in a L4L project. There may be nothing of value delivered. You stuck with either writing the project off, or toughing it out to an expensive and unsatisfactory conclusion. You may even tough it out only to write it off later. Of course, you can change the way you are doing things, but that basically means starting over. So, why not get it right from the start?

The Solution

The solution is, of course, to frame the project as delivering new value.

Project framing report card
Project framing report card
Like-for-like Delivering value
Technically can’t be achieved Value drives right behaviours
Business disengaged – everyone wants to go last Business engaged – everyone wants to be first
Analysis & design = reverse engineering Break current constraints for better solution
Wasteful and high risk Efficient and low risk

Even if you’re being forced to replace a system, make sure you go out to the stakeholders and ask them what they want to make their lives better, right now. This is the only way you really get their buy-in, the only way they’ll make do with less here and there because they’re getting more overall, the only way they’ll be engaged in resolving difficult delivery problems, the only way they’ll back you up instead of sell you out when things get tough. It’s also the only way you’ll avoid perpetuating those arbitrary constraints you inherit with a L4L project.

Next time you’re asked to start a L4L project, start by changing the framing.

Backwards Prioritisation

Imagine you’re in the middle of a big software project. Maybe, you’re replacing an internal system, or something like that. You make an observation: when asked to prioritise, everyone wants to go last. They want to hang on to the status quo for as long as possible.

Instead of beating down your door to get their hands on desirable new features, they are all running for the exits in the hope that your project fails before it impacts them.

This is logical from an economic or financial perspective. If value is to be destroyed, then you should destroy the items of least value first, and of most value last, as you maximize value-in-use in this scenario. When your action would result in reduced future cash flows, the longer you wait before acting, the better.

Imagine your home was being gradually inundated; floodwater seeping in and rising toward the ceiling. Imagine that you were waiting for rescue and knew that you could take some things with you. You might pile up your possessions in the living room. Where would you put your most treasured possessions? At the top of the pile, of course, where they would be last to suffer water damage. Though you don’t know when help will arrive, when it does you will know you have saved only the most important stuff.

Maybe, though, the new solution is just as good as – if not better than – the old, but people fear change and disruption. If the level of disruption is high, and the new solution is no better, this is indeed value destruction. However, if the disruption is less than feared, and the new solution does offer benefits that haven’t been effectively sold, then this needs to be demonstrated to stakeholders so they come seeking change. This requires senior leaders to change the framing of the project to highlight the value created, not the value destroyed. It also requires the delivery team to support the new framing by delivering a high profile change that  adds value.

Just as value-creating projects maximize value delivered by creating the items of largest value first, value-destroying projects minimize value destroyed by destroying the items of largest value last. So, if your prioritisation looks backwards, ask seriously if your project is destroying value.