Waste in a Knowledge Workers Realm

Matthew Caine Uncategorized 0 Comments

Waste is an interesting topic. Just what is waste? How do we recognise it? Especially in the knowledge workers realm where we cannot physically see our waste.

A great way to appreciate waste is to have a look at some examples.

Several years ago I was guilty of great waste. I had to do some complex slicing and dicing data. So I extracted the data from its source cleaned it up and imported it into Excel. From here it was obviously easy to then filter and perform pivot functions.

However, I started to notice that whenever I filtered the conditional formatting did not work. So I then spent time correcting the conditional formatting to work with filtering. I noticed that the sub totals no longer work once the filter was applied. Again I spent time researching and fixing this problem. When we added to this all the trickery around borders etc I easily spent 2 to 3 weeks creating a perfectly formatted functioning data slicer and dicer excel spreadsheet.

It was however complete and utter waste. Who used the spreadsheet? Me! How long was the data accurate? About a week! So no question, the beautiful Excel spreadsheet was Waste.

My failure here was to produce things that nobody needed.

Now let’s look at another example. At one point in my career I was the head of testing and support. One day the head of development approached me and said that he could not reproduce defects. So with all good intentions I decided that we needed to take the 100 most important defects and put our resources into creating the reproduction steps to each one.

But can you guess how many of those defects were actually fixed? Yes you guessed it less than 10. So again we produced a lot of wasted work.

Our failure here was to focus purely on one element of the entire system and not consider the entire system.

And our last example is actually one with almost every single software company in the world will have. Defects are often recorded in some tracking system. Over time the number of open defects will rise. What tends to happen is that the older defect tickets are repeatedly opened, read, thought about, analysed and then the software displaying the ticket closed again. Not only that the older tickets often get sucked into reports and lists thus getting printed and considered by multiple people weekly if not daily. All of this is clearly waste.

Spotting waste

Whether we are working with HR business partners gathered together from across Europe at a Medtech company or a so-called modern Internet platform, waste in knowledge work occurs.

To help identify it, we consider classifications of waste, taken primarily from the Toyota lean manufacturing process. These classifications are:

  • Transport (of goods)
  • Movement (of people)
  • Idle time
  • Overprocessing
  • Delivery before being needed
  • Defects
  • Inventory
  • Producing things that don’t fulfil clients needs
  • Unused human talent

Clearly in a physical manufacturing environment it’s easy to visualise and appreciate these nine classifications.

What is however, less obvious is to understand these within the knowledge worker’s environment.

Let’s examine some examples.

Transport of Files

Clearly we’re not physically moving things such as products. But one of the greatest sources of waste is trying to remember where a file is located or where a file should be saved. Worst case is that someone does not share a file! The time wasted, when added together, can be is vast.

Movement (of people)

A team at an investment bank that was adopting Kanban, had identified that having developers sat in one area of the room and the testers in another was waste. They had to keep getting up and going over to talk to each other. The team wanted to sit next to each other.

Now what was really sad about the situation was that they were not allowed to change where they sat because the management of the developers and the management of the testers would not allow it!

Delivery Before Being Needed

Again this does not need to be the delivery of the physical things. At an online property searching platform, the team identified the following waste:

A lot of time had been spent implementing Google meta tags yet once live they were rarely maintained so why were they ever actually implemented? That was just wasted effort.

Isn’t identifying Waste also Waste?

Of course it is!

Simply identifying it but not actually doing anything is of course waste. It is therefore critical to identify which waste the team recognises as the “low hanging fruit”. That is to say with a little bit of effort, a lot of waste can be eliminated.

But it is equally necessary to keep looking at existing known waste and at new waste, and evaluating the entire picture to evaluate and identify measures that will reduce the greatest source of waste at that moment in time as context and environment changes.

So, What is Waste?

It is nothing other, when you look at all the examples above and the categories, than a waste of time.

So, we need to learn to recognise when where, who, why, when and on what we are wasting our time.

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