The UX Design Strategist
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UX Design 101: Context in BI/Analytics Design


What’s the Context, Dude?

The first question I ask the stakeholder when starting any new UX research and design project is:

            “What’s the context?”

If that question can’t be answered, I know there’s more up-front work to be done before anything else happens.  When you ask this question, be prepared for a range of responses that swing from blank stares to, “I’ll send you the document”.

Without context, that expectation I hinted at in the last blog – Think UX Isn't Crucial...– means nothing.  Context gives the perspective for starting, and is a checkpoint for conclusion.


  • We have a group of analysts who each search through 100GB of data a day looking for credit card fraud.  They have to generate detailed analytical documents with alerts for our regional managers that are delivered every Wednesday afternoon.
  • Credit card fraud analysts
  • Big Data
  • Weekly analysis reports
  • Regional managers
  • Alerting capability
  • Our technicians are having a very difficult time figuring out if the best course of action is repair or replace.  We need them to diagnose a problem in 2 minutes, and then get the correct advice so they can make the decision that best solves the problem while reducing our overhead.
  • Repair shop technicians
  • Parts inventory
  • Part wear and tear history
  • Predictive and prescriptive analytics
  • High degree of accuracy
  • Loss prevention
  • Our head of research travels 250 days a year.  We need a dashboard application that he can use on his smartphone to keep up with very specific results from lab work from our six international facilities.
  • Senior VP
  • Clinical trials
  • Web-based, mobile ready

Each of these context examples would now allow you to get started with a focus towards the best solution.  There’s more research to do, but now you know what research needs to be completed.

“Can I see your data dictionary?” is another up-front question that must be asked, especially when the “context” question falls flat.  And it’s no one fault.  Some shops are just farther along the curve than others, but it is inevitable if your UX project is going to succeed.

Context is User Specific First

I think we can all agree that the context for a dashboard supporting a CEO is different than the context for a dashboard or InfoApp supporting an inventory specialist.  Each of those roles has a specific job and each therefore views their world through different lenses, hence, different types of analytical views.

Now you can start your research with user interviews and this template might help you if it’s a new responsibility for you.  Ask for personas and ask for use cases.  Do your research, understand your collection of users, and build context sensitive dashboards and infoapps for them.  These can include both predictive and prescriptive analytics and can be directly tied to performance, optimization, and monetization.

Data Science and Context and UX - Oh My!

Big Data!  McKinsey&Company called Big Data the next frontier in an article from way back in the stone-ages of 2011 and they’ve continued to write and speak about it ever since.  At a recent UX conference I attended in NYC, I discovered that they have a full-blown UX practice area now.  That was unheard of even 5 years ago.

So, where you have big data, you might also have data scientists.  Why mention this here?  Because I’m gaining a deeper understanding of how intricately entwined the goals of data science and UX really are.

You, The Scientist

Yes that’s right.  You are indeed a data scientist when you put on the hat of UX Designer/Researcher because you’re looking for the big ideas as well as the nuances hidden in the pile.  When no one can define an accurate context for you, the data, combined with a few other very specific lines of questioning, maybe even with the customer data scientist(s), can get you headed in the right direction.

You may discover several different contexts as you begin to dig.  Some will overlap, but with a little more work you can define each so that all users understand.  Consider that those overlaps are what form the workflow for the organization or department and all lead directly up to goals and performance.

Now It’s Time for a Review

Here are a few examples of what your research may have uncovered:

  • Total Retail Sales for the US seems to be important to the SVP of Sales
  • Sell-through seems to be important to the Regional Sales Managers
  • % of on-time deliveries seems to be important to the Shipping Clerk

Each is a context defined from your data research combined with your interview responses and now that you have both, you can define the context for an infoapp or dashboard.

Here’s a Quick Example

The Regional Sales Manager from above needs to know the sell-through so that she can keep on top of store inventories in her region.  When armed with this KPI and other data points you’ve discovered in your research, you can now design an annotated wireframe to take back to her for discussions and finalization.

You sit down with her and show what you’ve designed based on the interview.  She will do the following:

  • Tell you that you’re right on target and sign off on the design
  • Get other ideas based on what you’ve shown and ask you to include additional charts, KPIs, or summary reports
  • Tell you that you might have misunderstood something and what she really meant was…
  • Tell you that you’ve missed the mark entirely and must start over

While point 3 is unlikely if you’re using a good interview template, it is possible so just be aware and move on positively from there.

Big Picture Wrap-Up

Can you see now how the differing contexts within a project fit together to form the bigger picture?  Like pieces in a jigsaw puzzle, when you see each individually, you’re at a very specific and granular level of context, and when you put them all together, you articulate the overlying context that identifies the company goal, vision, and mission.