You speak geek, they speak analytics. You want data, they want answers. You say to-mae-toe, they say to-ma-to, etc. We have many different ways of saying it, but we know that in the end we all want the same thing; a successful business intelligence solution that will empower us to stay in touch with our customers and make better business decisions. Here are 3 ways to bridge the communication gap between IT professionals and end users.

Listen for context clues

You have to learn their language before any true communication takes place. It is common for people (even technical people) to mis-use technical terms. Several contractors I worked with used the terms data mart and data warehouse interchangeably, even though the first is simply a subset of the latter. Listening to the context of the sentence rather than focusing on the exact meaning of each key word allowed my development team to understand what the contractors were trying to communicate.

Monkey see, monkey do

Mimicking the language of the person you are communicating with creates a common ground and provides a sense of understanding. If a business analyst refers to his consumers as clients rather than customers then you should also refer to them as clients. The comradery that developes from this type of interaction will lay the foundation for the next step…

Ask A LOT of questions

Now that you understand the user language and you have established common ground, there is less of a chance of annoying the users with all of the questions you will be asking. A common conversation might go something like:

Analyst: “I want to know everything about the customer.”

Geek: “OK, what specific questions would you like answered?”

Analyst: “I want to know what the customer did while they were at my business.”

Geek: “OK, we have a lot of that data available. Would you like to know where they ate and what outlets they spent money in?”

Analyst: “Yes, and I would like to know how much they spent and how often they visit the property.”

It’s likely that dozens of questions will stem from every question you ask. Before you sign off on the final data model of your data warehouse, you will gather all of the questions that you have collected by interviewing the users. Search through the data model for answers to each of these questions. A very smart (and patient) co-worker of mine spent many hours verifying that our data model would meet the needs of our users. While such a methodical approach is painful and boring, the results will be a robust business intelligence solution that is backed by a rich data warehouse.

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Tags: Job Role - IT

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