Mike MacDonagh's Blog

Somewhere in the overlap between software development, process improvement and psychology

Reduce waste: Visualise the value stream

A big thing in software process improvement (urgh) is reducing waste.  A great idea, but how do you identify waste?

One powerful method that I use is value stream visualisation. There’s a number of ways of getting information about the value stream ranging from physically walking the chain to simply asking people.

Sounds simple doesn’t it? But one of the best sources of information about wasteful processes and ways of working in a team is simply asking the team what they feel they shouldn’t be spending time on. By freeing up people to actually do their job they can reduce waste and improve productivity. One method I use is to ask each team member to identify a list of n items that they have to spend time on that they think are either entirely or partially wasteful. Basically a list of their impediments. I then anonymize the list look for commonality and then the top few are a reasonable target for improvement.

Alternatively actually walking the path of a piece of work through an organisation can really open the eyes to the sheer number of people and unnecessary waiting involved in some wasteful processes…

Anyway, having got some data I find it useful to visualise it in terms of waiting time and doing time. In Lean-speak cycle time is the time it takes to actually do something, lead time is the time it takes from the request being made to it finally being delivered. In many tasks the lead time far outstrips the cycle time, visualising it can make that very clear.

Low Lead time For example, a task with has a lead time of 5 days might actually be made up of 2 days waiting time before it actually gets picked up and the cycle time of 3 days starts.

Large lead timeIf you look at all of the tasks in your value chain you might find that many of them look more like this, with very large wasteful waiting times. There are many reasons why there might be a large waiting time, typically the team doing the tasks is over-subscribed, or a team might be protecting it’s SLAs, KPIs or other TLAs. These problems can have significant effects when looking at the system as a whole.

Even more interesting is looking at how these tasks might fit together in a value stream. If we imagine a business function that involves a request moving through a bunch of tasks across a number of teams that have different waiting and doing times a simple sequence of tasks, with a little buffering between them from the Project Manager to allow for schedule variance naturally, might end up looking like this:

 sequential_value_chain_arrows

Here we have 26 days of actual work spread over almost 60 days (12 weeks) of elapsed time = 40% waste. Even if the person planning the work is willing to accept some risk and try to optimise their workflow a bit without improving the waste inherent in the tasks involved there’s still a lot of waste in the system.

parallel_value_chain_arrows

By visualising the value stream in this way we can see straight away (apologies to red/green colour blind folks) that there’s a lot of red, a lot of waste. In many cases planners aren’t willing to accept the risks inherent in overlapping activities as shown here, or aren’t even aware that they can leading to the more sequential path shown above. The result is a minimum time that it takes a request to get done, based on the impedence of the current value chain of, in this case, 38 days before we even start thinking about actually doing any work.

Surely that’s not right.

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