Let's dive in and look at how you fix the behavioral layer. Well, really what we're trying to do is take good, strong, clearly declared usability hypothesis in the form of well-written user stories and consider multiple executions and test those. And that may sound difficult, it's actually not really that hard. I would say, from observing teams, the hardest part about this is the emotional experience of throwing away your work and just creating multiple things that you know you're going to throw away. And so I love this thing where these Buddhist monks create these, I believe, they're called mandalas out of sand and then they sweep them away. And so, I think, the hardest thing about starting to learn how to prototype well is getting over this idea that, well, I made this, I don't want to just throw it away. In design and innovation you've gotta be ready to discard stuff all the time, and you gotta pair that with working in small batches and doing low fidelity things and building up to high fidelity things so you don't generate excessive waste. And so that's actually one of the most difficult skills for doing this that you'll acquire with practice, but just bear that in mind how hard that is. There's nothing wrong with you if you think, I'm reluctant to throw away this prototype, but you've gotta temper that impulse. Why is it so important to do this? Well, the flexibility and the expense all work against you as you go out and you release software. So it's really cheap and really easy to prototype early, and we're going to learn how to do that, and to test a lot of different things. It's really expensive to change those things later because of user habits, because of working software out in the field that has to be maintained and kept compatible. And so with lots of users, you're going to have a lot more expense, you want to take advantage of this early and make a habit of prototyping early, and it's just really important. The critical thing that we talked about fixing the behavioral layer is that we bring in mappings that users already carry around with them. And so the most important thing we're going to do between having a clearly articulated usability hypothesis in the form of a user story and prototyping is looking at comparables. And there are some libraries here, pattern libraries, and we'll have those in the course resources. The whole point is you don't want to reinvent the wheel. If the user expecting to find a wheel or a dial in their tub or a certain kind of switch on the light, you want to ask yourself, what might they be expecting to find in this particular experience we're going to give to them? And how do we go out and look at how that's been approached elsewhere? And so let's look at a specific example. We have this epic user story about our friend Trent the technician, he wants to identify a part that needs replacing so he can decide his next steps. And this is the first chunk of the user experience our team is going to work on to deliver their proposition about putting the parts ordering process online and automating it and making it really accessible to Ted. And so they storyboard this, they think very explicitly about how this would work, and then the question is, all right, what is our next step? And that next step should be to articulate out the user stories and then look at comparables, and so how do you do that? Well, you don't usually go and look at other HVAC systems necessarily, for example, that's a little fraught. And more importantly, what you really want to do is unpack the individual user stories and look at what kind of patterns the users might be expecting to see. And so, for example, in this case what we have is a process where Ted is going to go and he's going to think about finding something from a set of relatively similar things, other HVAC parts. He wants to fund this one particular thing, and then he wants to see details about it, and then potentially order it. And so a few ideas about places where we can find different versions of that experience are online shopping, maybe, used car purchase, photo search. Or we probably just want to look at basic enterprise software patterns around searching through, for instance, CRM, like salesforce.com or something like that software. And then maybe just searching email, Mac Mail, Gmail, Microsoft Outlook. And so this is what you want to do is just think about all the places where you might find a pattern, a user interface pattern, similar to the user story that you're executing. And so is this a perfect list that I go through some kind of special process to find this? No, but as you get in the habit of doing this one of the things you want to make sure is to explicitly consider a bunch of possibilities and push yourself to look in the non-obvious places, especially relative to your topic. So let's say our team goes out and does this. While they might look at a few online shopping stores, these are some of the big retailers, and these are a few examples from the pattern library. So you have Target, Walmart, and then a couple of patterns that they zeroed in on, like product page and table filter, from things that they observed in these various sources. What I wouldn't do is, and I do see teams do this a lot, is go to the biggest online retailer, Amazon obviously, and say, well, the way they do it must be the right way to do it and, therefore, the way we should do what we're doing. What you're doing is different and the way that Amazon got to the design that they have and the way that they deliver their service, that's just really, really different than what you're doing. So consider a lot of different patterns, look at what they have in common because, again, what you're looking for is consistency and trying to pair your user story with the right signifiers and mappings that your user is going to bring with them into the experience. And so another idea that they might consider, just to dive into the divergence here, is used car purchasing. Why consider this in addition to the online shopping? I mean there's a difference. I mean, all these sites with cars are approaching this a little bit differently because they have a more homogeneous set of items. So whereas Amazon sells essentially everything, these places just sell cars. And a worthwhile question is do these guys, or these people that made these websites, do they approach that differently because of the homogeneity of these items? That's a worthwhile point of contrast in these comps. So they look at this, they identify screenshots, big visual things, and they find some patterns that might be interesting here. And what they arrive at, and what they should push themselves to do and you should push yourself to do, is consider two distinct directions. And say, for the same set of user stories, let's think about two really different ways that we might approach this. And if you can, you should bring both of those into testing. But let's just take a look at how they unpack their user stories and pair those with distinctly different concepts that deliver this user experience. So their first concept for these user stories here, these are the child user stories, the more detailed user stories from the epic we saw before. These are really inspired by this online shopping and these things that we saw for the car dealers, and so they would progress from that page to this Parts Detail page. One thing they noticed in the comparables was the ability to modify the search as the user does it because they may not know some of these stories have to deal with the user not knowing exactly which part, like by part number, they're looking for, but narrowing it down from make, model, type, things like that. And this is an example of the Parts Detail page and the relationship between the description and the data on it, like ordered 87 times in the last 90 days, so they can get a sense of frequency. If I'm not positive, has this part been ordered a lot, maybe that's a signal to the technician that makes it easier for them to make that final determination that it's the right part. And then this is how they approach the order button if the technicians going to order the part. Here's another totally different set of patterns they looked at was photo search. And so they looked at sites like Flickr and Instagram and Google and they came up with a second concept that's really different than the first. You can see here where they have these photos, you can roll over them for more detail, which is something that they saw, the search material is up here. And then the other patterns look similar, the Detail page, rightly or wrongly, what they decided was really important was to diverge the search options. And so how do we get to good usability? Well, we consider our user story and we clearly delineate our usability of hypotheses with good user stories that have a testable reward. And then we consider all the different mappings, all the different pairings of signifier and affordance that the user might be expecting to encounter and interact with for such a user story, those are the next two steps. As we go forward here, we're going to look at how we prototype those and then how we test those prototypes to see which direction performs the best.
