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Using the Story Wall for Chunking User’s Tasks

February 4, 2012 Leave a comment
Matt is working at the story wall

Matt is working at the story wall. He is looking at stories that equate to task chunks. IxD sketches of components that support the user in doing various tasks are pinned to the wall next to the stories

I am grateful to be working with Matt Hixson on some really neat tools that will help people realize the power of social media for their business.  I won’t say a lot about that — but  do check out Matt’s blog here:  http://www.thestudyofsocial.com/.

He and his scientists are working on some crazy maths that surface some data that will be visualized.  He’s spent a bunch of time thinking about what those visualizations could be.

As we are working on building an enterprise application,  am concerned with designing a framework that supports intuitive workflow for the people who need to administrate the tool.  If I learned one thing working on enterprise applications, making mundane tasks easy and intuitive goes a long way towards driving more use of a tool.  To that end,  I am thinking about how I can help Matt think about supporting tasks in the various contexts different users will have for meeting their goals.

I know we can get to a scalable solution — a component approach to design.    Our approach to this is to take the context scenarios we wrote a few months ago and break them apart into  types of work the user is doing along the way to meeting goals.    As we break the scenarios into stories, we have a conversation about the type of task the user is engaged in.   Is the user adding/editing?  Is the user combining elements to make something?  Is the user Is the user opening a layer of detail?  Is the user sorting results? Is the user culling a list?   Is the user focusing on a specific data point?  Is the user pivoting a view?   Is the user looking at the big picture?   Once we have a list of tasks we need to support throughout the application, we can design a set of interaction patterns that will support them.

In parallel we have to be thinking about the   framework of the application.  How do all these components hook together to support the context scenario we wrote in the first place.    When we start organizing the little tasks we are supporting building them back up into domain stacks, we start to get something that looks like a mental model.

mental model

This is a model of a huge enterprise task -- broken into stacks and mapped to types of work done by various project specific personas.

This is when Matt and I back up from the  detail of the task , look at the whole wall and ask….  Where  is the navigation that supports users in finding things?  How do users get to tools?  Do they go get a tool….or does it appear as they need it as part of the general flow?

Once we get this nailed down,  we can go wild with data visualization.

Categories: Methods

Agile Grrrls Rock….plus top 200 blogs

January 5, 2012 1 comment

   Yesterday I found that  I was listed in agilescout’s “Top Women in Agile Thought Leadership.”    I was completely surprised, and quite honored to be amongst the women who are sharing their experience, strength … and success working with Agile software development teams.    I stayed up too late last night surfing their blogs and “instapapering” a bunch of stuff to read in a few weeks when I am on the road again.

For those of you who are interested in Agile, here is something totally awesome!  Peter Saddington,  put together a list of the top 200 Agile blogs (UXSuccess was #158 when he posted in June)  http://agilescout.com/top-agile-blogs-200/

I didn’t see much UX love represented in that list….  Surprised not to see Jeff Patton’s seminal work in UX Agile Product Design  http://www.agileproductdesign.com/  ….

Interesting project … not only in culling blog feeds, but in how the list was computed.  (the web and social media analytics geek in me is fascinated)

I am cutting and pasting straight from his article, but go there to see the list yourself:

HOW THE LIST IS COMPUTED

  1. 864 blogs were reviewed in a preliminary screening to determine if their statistics are competitive enough to be ranked.
  2. 383 blogs were selected to be ranked.
  3. Data was collected for each blog from all 7 measured criteria (Alexa Rank, Compete Visitors, Google PageRank, Google Reader Subscribers, Yahoo Inlinks, Twitter Follower Count, Klout Score).
  4. For each of the 7 measured criteria, each blog is ranked in comparison to all other blogs being evaluated.
  5. A composite rank for each blog is determined by averaging each blogs ranking from the 7 measured criteria + partial Power 150 Weighting + social media influence mapping.
  6. The top 200 blogs are published.  

 

 

 

 

 

Categories: Musings
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