Remove Yourself from the Equation.

It's happening again.  The conversations sometimes feel like background noise, but each and every sentence said is very important to deciding which way we go in terms of design direction.  Or is it?  Drawing is great.  Discussing is as good.  Making the discussions meaningful is best.  So how do you do that?

I'm going to let you in on a little secret on my unique ability.

We do this many times.  Whether it's discussing the results of a usability testing session, or trying to determine what style or pattern to use in our user interface, I find that there is something missing.  I sit there and stay quiet.  I let others talk and concentrate on the problem and get to the root.  I reflect back in what seems like a lifetime, but in fact is milliseconds, to all the years of knowledge of past usability testing sessions, the type of feedback we received and the design decisions that were made as a result.  This is what I do during heated discussions - when my colleagues try to figure out the ins and outs of the results, what was said or even how the user behaved, etc., etc., etc...

This is when I remove myself from the equation.

Why do I do this?  Sometimes I'm my own worst enemy.  I get too attached to the outcome so I feel the need to argue or justify or persuade.  What most people don't get is that great analysis comes from looking at all perspectives and not being attached to anything.  Only then, after the work in your mind has been done, should you come out with something that changes other people's minds.

What happens is that most people look at the surface - what color to use on the user interface.  Others look just under the surface - how does the user interface behave, or what is its immediate impact.  What I do is look at all those layers, including the Why's, and beyond - through my own collected experience of UX itself.  Those experiences are a part of me but they're also external to me.  What I learn from it is the treasure, not the outcome itself.

I think many of us as UX practitioners is forgetting the full breadth of knowledge and perspective we've accumulated over the years.  And I think we've forgotten it because we're just too busy defending our design decisions or discussing something we think is profound but turns out to be something superficial.  And many times, we take it too personally.

Some people think monkeys can do this.  "Just train him and all things will go well."

No.

While indeed, having a starting a point is good, having someone with experience is even better.  And the objective is to gain that experience from the time you're committing yourself to the practice.  And it requires a lifetime to do so.  It requires design knowledge, not just the practicalities of usability testing.  That of course, is another topic.

Analyze well!

Reinvigorating this blogspace

Hi there.

In the next few months, I will be reinvigorating this blogspace since there have been several developments in the UX world and the lessons learned in my profession.  I'll be talking about ubiquitous computing and doing a book review I haven't posted in a long time.  I will also be talking about a game I dearly love, Gran Turismo 5, which had finally been released late last year.  Among the subjects, the ever blurry role of the analyst turned generalist and pseudo-designer and the challenges facing this time, design epiphanies, and finally, the refocusing of our very own Maine IxDA chapter.  I will probably do the last first, since it's extremely important, necessary and timely.

See you soon!

UX Book Club - Sketching User Experiences by Bill Buxton

Last month we had our first UX Book Club meeting. Apparently, as I'm told, it was the first ever professional book club meeting in Maine. Really? - I thought.

After having read the book and listened to other people's thoughts about the book, it actually improved the experience of the book itself. It wasn't just me reflecting (in my head) upon what was written, and that was a fresh change. Now I'm finding that the book and the thoughts by everyone else who had attended the meeting, is starting to reform my thinking, burning new neural paths and creating new behaviors. In that respect, the UX Book Club did the job as much as the book itself.

And now, after having seen Bill Buxton in a great video at MIX'10, I understand him more and where he comes from, beginning to model how he thinks.

One of the biggest takeaways from the book (hence Bill) is the fact that:

"Design is a compromise."

I had known that for quite some time but really couldn't articulate that feeling about what Design was about in that aspect, until now. It also occurred to me that "design not being a compromise" might have been the old artisan-based way of thinking. There is no longer the genius designer that we used to think existed and much of that came from Industrial Design even though I'm certain some people don't want to admit it.

So where does this leave the UX professional? Since design is a compromise because the designer is working with all different kinds of people in different disciplines (from marketing, to engineering to sales, etc.) it requires someone who is especially empathetic to not just the users/humans using the product/application/building but also to people he is working with.

I'd like to continue on with the discussion we had from the book club. But for now, I'm going to send you to the Maine IxDA thread where there's a list of topics covered in the book.

Design Decisions by the Percentages

I've learned a long time ago in hockey about the concept of "playing the percentages". What this means is that a certain action or play will have a particular success factor over others given the situation. For instance, in a power play when a team is shorthanded one person, one of the best (high percentage) ways to get the puck into the neutral zone and out of your zone is to shoot it off the boards or the glass. The only risk here is having an unpredictable bounce off the glass and the puck stays in the zone. The alternative is to shoot it out in the center through a gap and risk the puck staying in the zone with the opponent quickly covering any gap. One last alternative is to actually carry the puck out of the zone in risk of shorthanding your defense further if the puck-carrier makes a mistake.

So how does this apply to the field of UX?

Well, if a certain play has a specific percentage of success, something that can be measured, it can also be applied to making design decisions - could it not?

The reason why I'm exploring this concept is because we're currently developing a U.I. Pattern Library. (Here's a case study.) And because we're rapidly developing these patterns, there will be some that need to be used immediately and thus cannot be tested right away. So we need to explore all options for a solution to a pattern. There are indeed some patterns that are "straightforward" but then there are those requiring a little more work. And with this work, we need to figure out the best solution. How better to do this than by design by the percentages?

The fact is, most UX designers and analysts have basic knowledge to design based on past data and experiences. (e.g. We know when to use radio buttons instead of checkboxes.) The caveat is that an untested pattern may be completely wrong, especially if after testing, we find out the user behavior and expectations are mismatched. By designing by percentages, we mitigate enough of the unpredictable and also keep cognoscente of our decisions and how they came to be. (This also means that there needs to be documentation that will log these decisions.)

So how can this be used immediately? To me, it's more of a concept I keep in the back of my mind. I think of alternatives and go through a cognitive walkthrough to anticipate what the user may interpret and thus behave when interfacing with the product. However, doing just that may not be as rigorous as some might like. To make is rigorous and more apparent, documentation can accompany each decision made along with alternatives and why they were not chosen. While it can take long to do, at least when the patterns are tested afterwards, the assumptions can be referenced and validated/invalidated.

In the end, this concept is not 100% correct though it does give you progress because you're spending time worthy on exploring the pattern probabilities. To adopt Bill Buxton's axiom that you can only design the framework and not the user behavior, design by percentages can at least get you one step closer to designing an effective framework that gets you eventually closer to influence user behavior.

Video game review - Need for Speed Shift for PS3

I've rarely written about video games. Usually, I just like to play them, experience them and just enjoy it. However, there's this one game I recently bought that haven't met my expectations, and I'm ready to return it to the store. Electronic Arts just released Need for Speed: Shift. It was a big deal in the E3 gamers expo with better graphics and supposed better gameplay. It was suppose to match the caliber of Gran Turismo 5, GRID and Dirt. Let me just say - it doesn't. NFS:Shift follows the formula that the Gran Turismo series uses. Beautiful graphics and theatrics in the beginning so that the petrolheads of the world can salivate over, awesome music and even more awesome exotic, high-performance cars. NFS:Shift even has features to modify your vehicle so you can go with any kind of paint scheme you want and upgrade your car to perform better. Sound familiar?

Where NFS:Shift fails is in several areas:

1. From the start when the game is trying to determine the level of play and control settings, you are sent through a trial by driving a car on a course. If you do well, they may increase your level by reducing the number of computer nannies controlling your car and set the artificial intelligence engine to a higher level. If you do poorly, the game piles on the computer controls to a point where you don't actually drive your car anymore. Guess how I did? And this was very disconcerting because I had played driving games since Gran Turismo 2 (GT2).

For a good 15 to 30 minutes I was looking for the settings to change the level of play and rid myself of most of the computer nannies. As for the cause of this poor performance? The controller settings forced me to use a specific set of buttons for certain controls instead those I was acclimated to on Gran Turismo. Perhaps this is their way of forcing gamers to buy the overpriced steering wheel control that has a flimsy ergonomic infrastructure to support it. (Yes, I know I'm not being nice.)

2. EA put what's called, "EA Messenger" in a horrible place where it can be easily pressed by accident and pause the game. This feature is activated by the same mechanism as the accelerator (the right thumbstick) by pressing on it (R3). Unfortunately, because of this new paradigm forced upon me on the controller settings, I've actually crashed my car because of where this function is located. Obviously, there wasn't enough usability research done to foresee such an instance. 3. Loading the game is an extremely boring process. I've counted that I had to press the "O" button ("X" on NA consoles since, mine is a Japan console) 5 times to load the game all the while watching different progress bars do their thing.

Why couldn't these processes be done automatically and without my knowing? Wow me with your car graphics and not your system messages.

All in all, I really wanted to love this game, I really did. Driving the new cars make this game addictive - but each and every time, it also makes me wince because of the lack of respect of these three crucial things in the user experience. Back to GT5 for me.

Here are my recommendations for racing games for the Playstation console, best user experience listed first:
1. GRID
2. GT5 Prologue
3. GT4
4. GT3
5. Colin McRae 2
6. Colin McRae 1
7. WRC
8. DiRT
9. Ridge Racer 5
Dead last perhaps umpteenth million NFS:Shift

Learn from Polyphony

We can learn a lot from game development companies like Polyphony, who is more concerned with giving their followers a great user experience instead of putting out a product out on time. The company who has developed the screen interface for the navigation and on-board system metrics in latest iteration of the Nissan GTR is doing us all a favour not to get hung up on time-to-release. And this makes sense, especially since I've been reading Alan Cooper's book, "The Inmates are Running the Asylum". Take a look at page 45 and then you'll see.

But for now, follow me.

Testing for Learnability - the quantitative side

A question was posed by a good friend and colleague a while back about testing for learnability. The discussion was quite good in terms of defining possible qualitative data to compare. However, what I'd like to know, is there a simple, quantitative way of testing for learnability?

Here's my take, and unfortunately, it's only a theory for now because I haven't practiced it:

There's one metric that hasn't been mentioned and that is time-to-task. Now, what if time-to-task can be measured several times on the same task as opposed to just once? If the user is suppose to learn about how to use an application, shouldn't the time-to-task be reduced on subsequent tries? Isn't that an indication that the user have learned how to use it? When we play video games, the second or third time around seems easier to get through a level, doesn't it? So in that sense, how do we test for it?

After determining what kind of learnability you are testing for, a possible usability session may consist of the following guidelines:

1. Have the participant perform a repeated task.

2. In the series of tasks, mix in another task that could be something completely different (or something related). This disjointedness could test the user on how well they remember to perform the previous task again.

3. Increase the time between the first time and the subsequent times of performing the repeated task.

This method can be a sure way of quantifying the learnability of a particular function or process because what will happen with a successful design is that the time-to-task should be decreased with each repeated tries. Something that is very learnable may takes significantly less time than the initial stab. If there is no difference on subsequent tries, well, you know it isn't learnable.

The idea is to reduce the learning curve (dictated by time) and with this method, the time-to-task metric can be used to its full potential.