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Data Analytics: Common Pitfalls of Not Asking Enough Questions and What Questions You Should be Asking

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As part of my job, I receive requests for data daily from those within my department and those outside my department. The requests usually come in one of two forms. The first form is typically a question and is usually the easiest to act upon. The requester typically asks, “Could you tell me how often x happened over the course of 18 months at y location?” The second form is generally more challenging. This form is delivered typically in a phrase or two with some data points the requester believes will answer their question(s). For example, the requester may say “I need to know about x, and I need m and p fields.” While the requester has the best intentions in both scenarios, it could be challenging to fulfill the second request without asking some follow up questions. 

Before you get to asking the requester some questions, let me outline the number one pro tip to avoid data analytic pitfalls.

#1 Pro Tip: Take notes! 

We live in a fast-paced world. Companies can deliver packages within 24 hours. A video on the internet could go viral in hours. Things happen. Life moves fast and things get forgotten by mistake. 

Remember that you don’t know what you don’t know. This goes both ways. The requester may not know about a data point that would answer their question in less steps. You may not know about the end game or plan from the analysis that you perform.

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Below are the questions and steps I take for each data request to minimize rework and maximize informational value for the requester.

Before you start asking questions. This first step needs to be completed. 

Indicate that you have some questions in order to provide the most meaningful data to the requester. Ask them if they have time right now or would it be better to regroup later. Why is this step critical? It will help break down barriers and feelings that they are being interrogated as well as show respect for their time. 

Now onto the questions and steps you should ask and take: 

  1. Ask who is the audience that will be using/relying on the results from this analysis?
  2. Will this be sent outside the organization? If so, consider confidentiality/security. 
  3. How will the audience use the results?
  4. Write down fields, time periods, and any issues mentioned.

Pro Tip: Ask the requester, “What issue or question are you looking to answer with this data?”

  1. When is the first analysis due? 
  2. Does the requester want the analysis sent out to the whole audience or solely the requester?
  3. Restate the requested information back to the requester. Ask if you missed anything. Give the requester a minute to respond.
  4. If something is not clear, ask for clarification. This will save you time redoing the work.

When you send the data be sure to ask if the analysis be needed on a regular basis going forward. If so, ask about the frequency

What you should consider:

  1. Do you have an existing report that meets the requester’s needs? 
  2. Does a current report just need slight changes to accommodate the request?
  3. Do you have the necessary access to obtain all the data elements?
  4. Do you need to work with someone else? Will this cause any delays? If so, notify the requester. 
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Remember that the requester came to you because of your expertise and knowledge. Own it!

A problem is a chance for you to do your best. – Duke Ellington

Source: https://bonniecasella.org/2019/11/17/data-analytics-common-pitfalls-of-not-asking-enough-questions-and-what-questions-you-should-be-asking/

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