Lean software development: Why reduce cycle-time?

Or why reducing cycle-time is like Aikido

Why, indeed?

To cut a long story short, the answer to why reducing cycle-time matters is that a short cycle-time is the only thing that can truly differentiate between a great development team and a mediocre one. A team that has reduced its cycle-time to say, about a day, has mastered many things in the process. In other words, it takes a lot of things for a team to be able to deliver software in a super-short cycle, but it is those very things that become its biggest advantages.

Let’s talk about some of these – both what it takes, as well as the advantages that these translate to.

Understanding delivery

To be able to even talk about a short cycle-time, it is important to first establish what the starting point is and what finish-line is. The first one is relatively easy. It is simply the point in time when a requirement has been recognized as something that would add value to the software being developed. This recognition might come from a customer who made a request, or it might come from an internal product-management function, or a combination of the two.

The finish line is more fuzzy – at least it is with many traditional software development teams. Some people call a feature done when it moves out of development, some call it done when it moves out of QA, some when it moves out of user-acceptance testing, some when it moves into the backlog of the depoloyment team, and so on. Sometimes, there are multiple levels of done-ness, so to speak – development-done-but-not-integrated, integrated-but-not-tested, done-but-not-verified, done-but-not-user-accepted, all-but-deployed, and so on and so forth.

The first thing that a focus on reducing cycle-time brings about is a clear understanding of what being done means. And here, like in many places, the common-sense answer is the best. Something is done, when a customer can use it. Period.

The aim, then, of reducing cycle-time simply becomes that of getting a feature into the hands of a customer as fast as possible.

Identifying waste

If the goal is to get something into the hands of the customer as fast as possible, then anything that gets in the way of doing that becomes waste. This gives a simple definition to what qualifies as an inefficiency. Cause and effect – the goal of delivering quickly to a customer gives rise to the next goal – removing obstacles from the path of this delivery. In other words – removing waste from the team’s software development process.

If weekly or daily status meetings that last an hour or longer dont seem to be helping anyone move towards this delivery, then in the spirit of removing waste, these meetings should be cancelled. The best way for an integration defect to get fixed usually isn’t filling out a bug-report in the tracking system and having it run through a workflow involving the enterprise-architect, two tech-leads, the QA manager, and the project-manager. Again, to eliminate waste, process needs to be changed. It might just become scheduling time to get the two concerned developers to talk and fix the issue. So on and so forth.

Avoiding rework, upping quality, and root-cause analysis

If a feature has to be worked on again because of defects, it represents a large waste of time and effort. This wasted time doesn’t help in getting software in the hands of the customers, therefore, an effort should be made to reclaim it. The only way to do that would be to – get it right the first time. To do that, one has to ensure that no (or as few as possible) bugs are found during the final testing, instead, everything ought to be caught and fixed earlier.

This means two things – one, that testing needs to be done early in the game and continously through all stages of the game. The second is that each time a non-trivial issue is found – a root-cause analysis is done to ensure that the same kind of thing doesn’t occur again. This is the equivalent of the ‘stop-the-line’ philosophy of lean manufacturing.

Getting better at the difficult stuff

One reason why certain teams don’t truly deliver software frequently is because deployment is hard. They’re not good at it, or it is an arduous process with lots of moving parts etc. These are all just excuses – if something is difficult to do – it shouldn’t be put off and worked-around. Instead, it should be tackled head-on – and be thoroughly analysed for root-causes – and all issues should be fixed so the problem actually goes away.

So basically, time should be taken to look into and simplify the difficult parts of the process, and the team should ultimately become good at those things. There can be no excuses about this – the debt that inevitably piles up from not doing this boldly, simply must be avoided at all costs – else it will kill even the possibility of speedy delivery.

Poly-skilled people

When a team-member is an expert at something, and only that one person is an expert at it, she becomes a single-point of failure. If she takes some time off, getting something that involves her area of expertise into the hands of the customer becomes impossible. What if she should leave the team? What if there is more than one thing in the pipeline at a given point of time that needs the expert?

To be able to truly deliver software to customers in the shortest time possible, such bottlenecks must be resolved. When there is work for two in a certain area and only one ‘expert’, then another team-member should be able to help out. If a QA person becomes unexpectedly unavailable for a period of time, a developer or anyone else ought to be willing and able to step in to fill the gap.

Being poly-skilled in a lean team is extremely important – because the final delivery of software is the culmination of the team’s effort – not of a subset of team-members or of only one or two functions. To be able to perform as efficiently as possible, sometimes, having poly-skilled team-members becomes a life-saver.

A culture of excellence

There are other things a team must be able to do (indeed, has to!) to be able to reduce cycle-time to a minimum. These include taking on just enough work, taking on work in smaller chunks, limiting the size of its queues, using pull scheduling systems, and so forth. It also entails always looking for the next bottleneck so it can be resolved, the next piece of waste that can be trimmed from the process, and the next optimization that would improve throughput of the team.

Each team-member should have a caring attitude for the customer – and also an attitude that asks a lot of questions. One set of questions are directed towards the customers themselves – so as to gain a real understanding of what they’re trying to achieve – so that the best, most creative, and efficient solution can be found. Another set of questions are directed at the team and its processes – there should be no sacred-cows when it comes to trying to improve things. Anything that wants to stay on as part of the team’s process should be able to withstand stringent questioning and devil’s advocacy. By doing all this, things become better for the customer, thereby for the company and the thus for the team as well.

This culture of excellence judges its results by one metric alone – throughput. It realizes that any step taken to improve things needs to be questioned, yes, but if put into practice, its effects are to be measured. Measurements are extremely important to a lean software development team – but it only cares about the one measure that matters – that of delivery to the customer. This is why no optimizations should be made at a local level (say within QA or deployment), at the expense of the global work-product. In other words this culture is always looking to optimize the whole system, and not a part of it. Cycle-time is the easiest and most effective measure of this throughput.

A short cycle-time as a secret-weapon

This matters most to me, on a personal level, because I work for a small company today – and probably always will. If you’re competing with large software corporations with deep pockets that throw large development teams at projects – indeed specifically at ones that related to the product your little start-up is undertaking – then the only advantage you have is that of agility.

This is where the Aikido thing comes in – to succeed in a world dominated (for better or worse) by large companies that usually have wasteful processes, traditional project-management philosophies, old technology stacks, but often lots of cash and people – you have to use their ‘strenghts’ and weaknesses against them.

If your little start-up can turn out a feature in a day or two, what customer will be able to resist? Sure, you still have to get over other obstacles in the path of business success (like building what the customer actually wants) – but at least one thing will be possible. Because of the small size of your team, you’ll be able to adopt all kinds of agile and lean practices quickly – and deliver features into the hands of customers so fast that you could run circles around your larger competitors.

Reducing cycle-time and doing all that it entails is all you have to do.

P.S. If large corporations are able to successfully pull this off as well – then… who knows what innovation is possible?

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12 thoughts on “Lean software development: Why reduce cycle-time?

  1. Another reason to reduce cycle time is the time value of money: A dollar today is worth more than a dollar tomorrow. The more quickly I deliver something of value, the more quickly I potentially realize revenue and ultimately profit, which I reinvest to do the whole thing over again. In short, my goal is to provide high quality value as quickly as possible to increase the wealth of my organization and the people with in it–the invisible hand at work.

  2. That is a great point, Christopher. Also – once you are able to rely on cost-estimates for features (taking into account time-value of money), you can more accurately estimate returns on features that aren’t worked on yet.

    This allows you to stop development on something as soon as the estimated return on what remains falls below the investment cost.

  3. Another reason for shorter cycle is because to be honest you can only predict at a shorter time frame with limited variables that short term has. The number of variables that effect a delivery on a long term are much more than you can possible fathom and more often than not you will be wrong.

    • Incorrect, Look into statistical modeling.
      As long as you have a large enough sample of accurate metrics from past development with the same team you can estimate even the largest projects within one standard deviation.

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