So springtime, so time to build things up data analysis. So we have a huge pool of stuff that we've gathered from all our different types of observational interviews. And now we're thinking right, so what can we see in there? So it's right really in front of you. You can organize it however you want it in pieces of paper and sticky notes on on anything, diagrams, anything. In a computer, there's plenty of free diagram software that you can use.
It's completely up to you. So one thing you have to make sure though, it's, as I said already, before you have enough data, and then you start to see some things recurring again, and no new information is coming in. So it could be a good place to start drawing some conclusions. But never try to analyze them dry. And especially if you're, if you feel like you might be getting an explanation But you're still very much in the data collection phase, you maybe have like two interviews, and you have 20, more lined up. But you start to see something emerging, don't jump in and try to shape the data that that person is giving you their responses.
By your end, you don't lead them don't ask leading questions like so it doesn't work because of, would you say it's broken? Or would you, you know, these kinds of little leading questions that put people in corners, just because you think you understand this, too, it's not a good practice at all. You're shaping the direction of the data. But you have to basically just shut up and listen. Write everything you found. And if you if you find yourself in a position, where you should be in a data analysis phase, because you have so many interviews, you've really done a lot of observation, you know, it's been months of work, but there aren't any patterns at all, then maybe you should go back to data collection.
Where because otherwise you could draw completely wrong conclusions. So, so cautions, aside from what I've just said, is that what you've discovered is what you've discovered. So do not twist your explanations. So if you if you see something totally unexpected, you have no idea how to explain this. But it's there well is that that's it. And don't try to come up with a way of explaining it if if you see that people are bypassing a certain phase on the website, or on an app, which they should really be using, will do try to explain when they are bypassing it and upset.
And then of course, remember, always, the frequency is not an indication of high importance, just because something is prevalent, and there's loads of it. Well, it doesn't mean it's important, otherwise maybe raps would be the best animals. And that's kind of coming back to the messaging system case that I mentioned before. It's a case when you have probably about Problems somewhere, but it might not be where everyone is saying it is. So don't just follow what people say. First you break down this problem will completely look at it from the smallest smallest pieces, which means observing, asking, interviewing, probably also using this tool yourself or living with this tool for a long time.
And once you got your own data, then you can build up what you see and what those problems are. But don't try to solve some problem before you have a really, really, really good thing around. So this is why we training, observation and intuition on skills like this, because they are really vital in this tasks. And otherwise, you end up curing the symptoms, which so often happens and not be honest. And it's kind of shallow qR is basically the same as the example I gave you with a novel where Characters a lot of different things I mentioned to them at all, it was just all about events that happen around them. So then you think, Oh my god, how do I get better at this?
It seems like a bit impossible. Well, that's I'm coming back to when I said that this course is very practical. So what I would like you to do is really practice the skills that I've just been talking about. So observation and curiosity and asking questions, and really living and working in someone else's shoes. And it's only really about practicing these core skills that you can improve in them in specific challenges. But these skills can be practiced anywhere at any time.
There are people absolutely everywhere and what you clean from observing people in some kind of action in some kind of situation, doing almost anything. You can always apply in your future challenges.