Brainstorming About Data Quality

Brainstorming About Data Quality

Data quality can be improved at any organization including higher education institutions. And it is a team effort with thoughts from many. To do this, we suggest getting individuals into a room together to discuss. We will call these sessions, brainstorming sessions. A lot can be gained from getting a group of smart people in a room or online or over the phone. Start any project such as improving data quality with planning and in most cases that should include a brainstorming session where you get stakeholders together. The goal of these sessions is to create a plan and action items on how to improve data quality.


During these meetings ask the following questions and come up with answers (or action items):

  1. What data quality issues is the organization experiencing?
  2. How can data quality be improved?
  3. What does high data quality mean in each department, domain or data system?
  4. What tools are in place or need to be in place regarding data quality (incident tracking, data governance, etc.)?
  5. Who should be involved in assisting with improving data quality?
  6. What is in place now regarding data quality (program, previous assessments, training, tools, resources, etc.)?
  7. What are the benefits of improved data quality?
  8. What are the sources of data quality issues (data entry, imports, integration, etc.)?
  9. What training is necessary for staff to improve data quality and how should that training be delivered (online, face to face, mandatory, etc.)?
  10. What staff communication is necessary in the area of data quality (initial, ongoing, yearly)?
  11. What is the timing of the data quality improvements necessary after looking at other priorities and resources?
  12. What is the readiness of the organization to formalize the data quality activities?
  13. Who do we present the findings from these data quality brainstorming meetings to and when?
  14. When should we meet again regarding data quality?

Document the thoughts and outcomes of these meetings including actions items that come from the meetings. Make sure the documentation is accessible on a collaboration web page or a public spreadsheet. Remember, the objective is to improve data quality, not just hold meetings and not create a large report. Once you have the list of actions necessary, look for the quick wins and tasks that can be done simply. You want to create a data governance and data quality culture along with helping the staff at the institution.

Look at the 5 whys which is an iterative interrogative technique used to explore the cause-and-effect relationships underlying a data quality problem. The primary goal of the technique is to determine the root cause of a data quality problem by repeating the question "Why?". Each answer forms the basis of the next question.

Who should be involved in these brainstorming meeting? Here are some thoughts on the subject:

  • Get as many departments involved as possible. Might breakdown silos. Relationships can be formed in these brainstorming meetings.
  • Have diversity in the brainstorming group. Different perspective will provide additional insights.
  • You will add additional folks during the project but the more you include in the beginning the better the project will be.

Here are a few thoughts regarding the meeting itself:

  • You need one individual to organize them and you need someone to facilitate the meeting.
  • Make sure you allocate enough time for the meeting so that the necessary thoughts can be documented.
  • Have the right resources in place (white boards, phones, computer access, projection screens, etc.)
  • Make the meetings a safe space where attendees feel comfortable in speaking their mind.
Be agile. After the sessions, you might have identified the top data quality issues different than what you thought going into the sessions. You can’t improve data quality at once but hopefully from these brainstorming sessions you will come up with a few actions that will improve the data quality which will lead to more actions. Ask the right questions. Document the answers and action items. Try to get to the root causes of the data quality issues. Make sure the right environment for the sessions is in place and you have the right people attending the sessions. Hope that this post helps with the data quality brainstorming and let us know if we missed any questions.

IData has a solution, the Data Cookbook, that can aid the employees and the institution in its data governance and data quality initiatives. IData also has experts that can assist with data governance, reporting, integration and other technology services on an as needed basis. Feel free to contact us and let us know how we can assist.

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(image credit StockSnap_KOHGRXNXL0_BrainstormDataQuality_BP #1081)

Jim Walery
About the Author

Jim Walery is a marketing professional who has been providing marketing services to technology companies for over 20 years and specifically those in higher education since 2010. Jim assists in getting the word out about the community via a variety of channels. Jim is knowledgeable in social media, blogging, collateral creation and website content. He is Inbound Marketing certified by HubSpot. Jim holds a B.A. from University of California, Irvine and a M.A. from Webster University. Jim can be reached at jwalery[at]

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