Most companies and government agencies address data quality reactively after errors are made, and as a direct result, suffer from bad data. To date, it has taken a special person to challenge the status quo within his or her work team, address data quality by “getting in front” of the issues, making a huge improvement, and, in effect, showing the rest of the company what is possible. I call this person the “data provocateur.”

I recently introduced the term publicly (see for example, “Data Quality Should Be Everyone’s Responsibility” in HBR), and many people have asked “How can I become a data provocateur?” This mini-boot camp provides the answer. It aims:

• To provide you with the skinniest possible set of materials needed to become an effective data provocateur and
• To empower and embolden you to move forward.

1. An exemplary provocateur: Bob Pautke at AT&T

• I’ll go into detail about Bob’s thinking, his first steps, how AT&T built on his efforts, and the results he and AT&T obtained.

2. What is a “data provocateur?”

• Why data quality problems arise? (Ans: The rising middle manager)
• The hidden data factory
• Provocateur defined, with a special emphasis on soft skills
• Discussion: Can you fill the role?

3. A Four-Step Process for Becoming a Provocateur

• Step 1: Answer “Do I (we) have a data quality problem?”
• The Friday Afternoon Measurement
• Other impacts of bad data
• Answering the question
• Step 2: Clarify, document, and communicate customer needs.
• Step a: Name the most important customers (including required documentation)
• Step b: Learn how they use the data (including required documentation)
• Conduct a customer needs workshop
• Step c: Determine required features and quality requirements (including required documentation)
• Step d: Prepare a Customer Requirements document
• Discussion: Put yourself in the customer role. What would it take to complete such an analysis for yourself and your work team and communicate your requirements to a data creator?
• Step 3: Make improvements to close the gaps.
• Quality Improvement and the Scientific Method
• The Quality Improvement Cycle
• Discussion: Can you do this work?
• Step 4: Summarize the results.
• What success looks like
• Presenting results
• Building support to “get to the next level”
• Discussion: Any questions about what is required

Wrap Up and Next Steps

• A Promise to Yourself: Make a list of the steps you propose to take in the next ten, 30 and 60 days.