Heard on Reddit: Defining Requirements Remains Top Challenge of Traditional B.I. Process
The title of the top post on Reddit's r/businessintelligence forum this weekend intrigued me - "What is the most difficult part of a BI project to get right in your opinion?"
The #1 answer, with over 50 upvotes (Reddit's version of "likes") was defining the business user's requirements of the dashboard/report.
It's 2019 and the game of telephone between "the business" and "the analysts" continues, causing frustration, delays, and decision-avoidance on both ends, as evidenced by many of the replies below:
I'm so glad this is at the top of the list. The translation between business and tech staff can be very tough.
Agree. "Just make something and then we'll check if that is what we want" is a comment i hear way to often...
Super difficult, usually require a tons of meeting and still can't get it right.
I remember a meeting we had with the managers at my company. After 1 hour of explaining what a field in the soon to be new ERP was supposed to mean, how it would be used by every department, who would do what, I thought we all agreed on the definition of this field. We all congratulated ourselves at the end saying we did it. 1 week later, you could ask 5 person for the meaning and purpose of this field and you would get 5 different answers. %#@$ that.
Coding is easy, getting the business folks to agree on the definitions of a measure is the most difficult.
(Business users) change definitions frequently, and if coordination is poor they have different definitions, and even if coordination is good they still have different definitions anyway. But when they ask for reports they only use one word. Or they adjust requirements/logic definitions to hit goals instead of improving the process.
Others are right (its requirements), but the second toughest task lurks right after: setting expectations. Making sure you properly estimate the time and that others understand and agree to that timeline is really tough to get right. It's a balancing act between what time you need to do a quality job and the time constraints of the business that needs the data now.
You can read the full post + comments here.
Curious to hear from both business users and data professionals - do the above quotes capture your experience accurately?