We’re down to the last talk of the day and the last full talk I’ll be Live Blogging for (I will be doing some coverage of Family Feud and some roaming around for dinner later tonight). Richard Bradshaw and Dan Ashby are riffing on the Power of Models.
Modeling sounds super exotic, doesn’t it? Well, not really. It’s something we do all the time, most of the time without even realizing it. A model is just a structured form of our ideas. They can range from very simple to super complex. Regardless, we hold that model in our head (or in more advanced examples on paper or in computer systems) but to interact with any system, we structure those interactions. Tada, that’s modeling!
When we think of modeling, it might help to think WHY we use it in the first place:
- Modeling helps us communicate with others
- Modeling helps us collaborate and solve problems
- Modeling helps us consider different issues and challenge our current level of thinking
- Modeling can provide visual aids to allow us to recall and remember things to help us with the previous three aspects
There are a variety of ways to capture information and construct models. Sketchnotes, mind maps and structured lists can all be used to help create a model for interactions. For that matter, a variety of automated tests also utilize models to help with their process and communication. IF we think of something like Cucumber, that’s also modeling once we get to the purpose and point of the Gherkin syntax used in the features statements. The Features file contains statements that have a semantic meaning to us as statements of intent, but by themselves, they don’t do anything. They need to be mapped to a step definition to be of any use. Therefore, the gherkin statements are modeling what we expect to see happen, and then the step definitions give us a more concrete specific example to run.
A lot of people will probably get hung up on the idea that you have to be someone artistic or capable of drawing to be able to make a model. Not true. ever drawn a simple line map? There you go, another model and one that everyone has probably done in some way or another.
So what’s the risk of not having a model? Typically, it makes a process vague or communication more complicated. Still, I’d argue that working without a model (as in literally) is virtually impossible. I’m not running out the possibility, but just by talking about something with someone else, we’re building a model of conversations. If we think about something quietly and ask questions to ourselves, we are building a model of thoughts. Feeling like we’re approaching “Inception” territory yet ;)?
One of the key takeaways is the notion that “all models are wrong but some are useful” Now, have you ever wondered where that idea came from? We can thank George Box and for those who really want to get a bit nerdy, here it is with its full context:
" Now it would be very remarkable if any system existing in the real world could be exactly represented by any simple model. However, cunningly chosen parsimonious models often do provide remarkably useful approximations. For example, the law PV = RT relating pressure P, volume V and temperature T of an “ideal” gas via a constant R is not exactly true for any real gas, but it frequently provides a useful approximation and furthermore its structure is informative since it springs from a physical view of the behavior of gas molecules.
For such a model there is no need to ask the question “Is the model true?”. If “truth” is to be the “whole truth” the answer must be “No”. The only question of interest is “Is the model illuminating and useful?”.