Lean Thinking

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Last time we looked at the concepts of accuracy and precision and how getting the two mixed up can lead to all sorts of problems. We also looked a little at our cognitive bias, that has us assuming that precise numbers are also automatically accurate. The upshot of that is that we humans are absolutely terrible at estimation. We mistake precision for accuracy and our accuracy is really bad to begin with.

That last statement is only half true. We are really, really bad at things like guessing how many jelly beans are in a jar, or how tall that person is, or how much does that thing weigh. What we are bad at is absolute estimates. To make up for that, we are really, really good at relative estimates.

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Last time we looked at why we estimate and why there is always pressure to make our estimates more accurate. We have come up with a vast number of methods for estimation all of which aim to improve accuracy. The problem is that most of them don't. What they improve is precision instead.

Most people think of accuracy and precision as being the same thing. But they aren't. My nerdy and pedantic engineering background tells me that accuracy is how close to the true value a measurement is, while precision is a measure of how reproducible the measurement is. A more formal definition (thanks to Wikipedia) is -

In the fields of science, engineering, industry, and statistics, the accuracy of a measurement system is the degree of closeness of measurements of a quantity to that quantity's actual (true) value. The precision of a measurement system, related to reproducibility and repeatability, is the degree to which repeated measurements under unchanged conditions show the same results.

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A couple of posts back I mentioned Estimation and my desire to poke a stick at the hornet's nest that estimation can be. Estimation is always a controversial topic. It's often at the heart of serious conflicts within organisations. There are a huge number of estimation methods and techniques but nothing seems to prevent these issues from coming up. Before I poke a stick into the hornet's next (well, not so much poke as take a full bodied swing with run up and follow through), I'll spend a little while looking at why we estimate in the first place.

Any time we have two parties involved in something there is estimation happening. Right back from prehistoric times -

Ogg - I estimate that this stone axe is worth the same as that reed bag filled with nuts so let's trade.

Ugg - I estimate that this reed bag filled with nuts is worth at least 2 axes so let's not.

Ogg - Seriously? You're taking food away from my family... these axes are the finest workmanship. Maybe one axe plus a flint scraper but that’s the best I can do.

And so on.

 

24 February 2014

Story Smells

Written by Published in Agile

Most agile teams these days organise their backlog into user stories. The user story isn't mandatory in any agile methodology but they have become the defacto standard for agile projects. There are many good reasons for this, not least of which is that a well written user story keeps the focus squarely on delivering something of value to the user. Many user stories though are not well written. It takes more than using "story normal form" - As a I want so that I can - to generate a good story.

Many of the backlogs I see are filled with stories that, frankly, stink. Bad stories don't keep the focus on what is important. They distract, confuse and mislead. There are some criteria like INVEST that we use to assess user stories and properly applied they make a big difference to the quality of the stories. They do take some time to learn and apply though so I'll give you a few quick tips to get started. Over the years I have come across a number of common mistakes that teams make when writing stories that cause their backlogs to stink –

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