Some time ago I’ve watched a funny video on personalities that actually has absolutely nothing to do with this article, except one funny notion that I wanted to use here:
this person was a Greek philosopher,
fantastic job actually,
you sit on a stone the whole day long and you think of stuff
That person, or actually two of them, was Meno and Socrates. No idea if they were sitting on stones thinking actually, but they managed to get some pretty cutting edge research done. They were namely arguing about Virtues and came up with a paradox statement:
And how will you inquire into a thing when you are wholly ignorant of what it is?
Even if you happen to bump right into it, how will you know it is the thing you didn’t know?
Possibly they didn’t use English to formulate it, but still, the quote should be close enough to capture the idea (badum, tss)
But what is so remarkable about it?
Funnily enough, this paradox draws on the axis of uncertainty, or being informed about something. The closer one is to one edge of it (the less one knows about a topic), the more difficult it becomes to actually even ask the right questions. Not even mentioning to answer these.
Let’s have a walk down the axis
How it feels being on the leftmost of this axis, one can imagine when talking to a scientist doing cutting edge research:
William Gladstone: But after all, what is the use of it?
Michael Faraday: Why, sir, there is every probability that you will soon be able to tax it!
Mind it, Faraday supposedly said it upon demonstrating an experiment with electricity. He just didn’t know what the possible applications of it could be. I guess it wouldn’t be also such a wild presumption to expect that he had even less clue how much time it would take to invent the experiment when he got interested in the topic itself. When will a scientist be done with research? Once he’s done.
How it feels being on the rightmost of the axis? Try imagining buying a piece of furniture from IKEA. Do you expect to have all necessary parts inside the box? Do you expect to have a manual how to put things together? Do you expect the assembled thing to ‘work’? Do you expect it to be warranted that, should it not work, that you can just give it back and get a replacement?
So, pretty much ‘everything’ is known. Including how much it will cost, how much time it will take to assemble, deliver, etc.
What wild-lands lie in-between of those two?
Places where you have some information, but not exactly all that you need. So some things run predictable, others require experimenting. The closer to the left side, the uncertainty – the more experimenting.
What is known here? Hah! Very good question! But at least one can approximate.
How does it look like in the IT world?
This very situation occurs day-in day-out in IT.
Ask a designer when he will come up with a new, revolutionary, nice, user-friendly design of a user-interface …. you could just as well be asking Faraday about the applications of his freshly discovered electricity. Unclear specifications mean unclear time schedule.
The peculiarity is when people expect such creative tasks to be predictable and plannable and try to squeeze those into sprints in Scrum instead of just monitoring those in a Kanban approach.
I would venture a guess that Project Managers’ dream come true are the lands of the Waterfall – where (almost) everything can be perfectly planned ahead. How things are built, how they are tested, how much time they take, how much money they cost, etc.
However for it to be like this, the uncertainty about the information, requirements, etc. must be minimal. The remaining uncertainty can usually be handled by hand-ruled adding of ‘safety buffer’.
In between, where nobody, the customer, the developer, tester, product owner, really NOBODY really knows what the end product will be… one can only ‘endlessly’ improve.
Make a prototype. Verify it. Think of improvements. Make another prototype. Verify it. Think of more improvements ….
Good old, and so buzz-worded, Agile.
Solving the paradox
The interesting bit is – the Agile approach is actually ‘the solution’ to the Meno’s paradox and happens underlies the paradigm of research and learning:
- Make a hypothesis
- Construct a model / prototype
- Verify the hypothesis – make an experiment
- Find areas of improvement
- Iterate the points using improved hypotheses until desired accuracy is achieved
The clue here is – without formulating the hypotheses and measuring the results the improvement circle is broken and does not deliver as much value.
Senior Quality Assurance Automation Engineer