Importance of User Interface and User Experience in BI

One thing that takes a backseat in majority of BI initiatives is the importance assigned to User Interface Design i.e. UI for short and Overall User Experience, referred as UX in short form. Gone are the days when a simple printout with numbers and tables are accepted by the users. As information consumers, we can observe this phenomenon driving inroads into our day to day life and a good example lies in the newspapers today. If you can, compare the UI layout of a news paper or magazine a decade back with today’s edition. Pay special attention to articles that deals with numbers for example in finance, economics etc and the subtle changes will become very evident.

A report sans UI layout actually burdens the user to find the information he/she is looking for. Assume that a report with multiple cross tab data blocks showing sales data of a company for different Products, Customers, Regions, Promotions and Employee is presented to the user. If the user is looking at the report and trying to analyze it, the typical questions arise are

  • Which Employee is star performer
  • Which Product is in Top in which Region
  • Are there any Top Customers in multiple Regions
  • Which Promotion is effective in which Region and which Customer avails it

Users will not have a consistent trail of thought as represented the list above. If a bland report is given to user, the data blocks are analyzed and data points are memorized. Since questions that materializes in the mind are unpredictable and never consistent, the user has to treat the report as “source data”. From user perspective, they treat this as a base to build an additional report that will have the information, they actually need. Just to give an example, refer to the picture below that shows a clear difference that a UI design can convey. There are many more nuance to be considered in UI & UX arena and this is just a beginning.

UIUX_1

A quick eyeball scan reveals more information about the data and it becomes evident that the right presentation style can convey more information, while using the same real estate.
From DIKW pyramid perspective, differentiation between the data and information layers has blurred into a single layer in this scenario because the chart above seeks to convey as much information as possible from the data set. Although it was unintentional, this will be a side effect because, any visualization should be less noisy and convey maximum information without users trying to re-interpret the metrics. Unless this is adhered to, “driving user adoption” will become a major concern.

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