We’ve been talking lately about the importance of data quality to your company or organization. What we haven’t talked much about are the players on the data quality team. Like the Abbott and Costello skit, “Who’s on First?”, figuring out who the players are and where they play in the process of generating, collecting, and maintaining data quality can be confusing. And the results aren’t usually very funny.
Of course, you’ve got job descriptions, organizational charts, protocols, and policies and procedures to tell everyone what to do. You have front line people collecting data, information services people verifying data, reviewing data and maintaining data storage. Users pull data and use it. Sometimes they correct errors they find. Sometimes they don’t. Mid-level and upper management folk decide on the goals and protocols for data collection and dissemination through the company. All these people should help insure the quality of your data. But only if they understand just the importance of data quality.
It’s not enough to tell staff that data is important. They have to believe. A high level of data quality contributes to your organizations overall success. But if the people who collect and manage that data don’t buy that idea, they aren’t motivated to make that extra effort to maintain a pure data stream. It’s important that you identify the key contributors in your company and Once you’ve done so, you’ll need to ensure they understand:
- Data quality not only benefits the company, but also contributes to their ongoing success within the company.
- Data quality increases their value to the company. The better data they produce in their daily data collection activities, the more valuable they are to the company.
- Quality data production is a key evaluation point when their performance goals are reviewed. Staff attention to goals for achieving and maintaining high quality data, helps them achieve personal goals for career advancement.
- Quality data collection, maintenance and distribution are valued by the company and staff need to know the company is watching and will notice good work in this area.
The Invisible Team Member
Be careful not to ignore the often invisible member of your data quality improvement program – the people who fill out the forms and provide you with data.
- Examine items in any data collection instrument you use, then re-examine the instrument regularly.
- Make sure you need the info, that you will use it, that it’s important and that you can’t get it somewhere else.
- Make sure your staff participates in such evaluations and that they recognize why it is important to reduce the intrusiveness and burden of your data collection activities on your respondents.
- Make sure each item in any forms or questionnaires is understandable.
- Make sure technical terms are within the respondent’s ability to understand.
- Keep questions clear and unambiguous.
- Ask yourself how much time they have and how likely they are to take time to provide you what you ask.
- Make sure that any data fields prompt for definitions and analyses that are within the capabilities of typical respondents.
If your team understands where the data comes from, where it’s going to, and how to make it get there, you can make your data flow properly. But it’s understanding why the data needs to be clean and complete, what it will be used for, and how their personal efforts contribute to the company reaching its goals that determines whether or not your organization will be able to translate its high quality data into big scores in the marketplace.