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What To Do About Bad Data |
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Page 3 of 4
Preventing Errors
If you're now convinced that your company's data problems are urgent, what can you do about it?
One of the most important data quality lessons to learn from the companies that handle it best is you need to focus on preventing errors at their source, not in finding and fixing them as they crop up. Redman provides 10 tactics that organizations focus on when they think about creating quality data-but he underscores that the emphasis is less on the individual 10 habits than on "how they work together and fit into and help the organization's other management systems evolve." The 10 habits are:
1. Focus on the most important needs of the most important customers. Adopt a customer-facing definition of quality.
2. Apply relentless attention to internal business processes.
3. Manage all critical sources of data, including suppliers.
4. Measure quality at the source and in business terms.
5. Employ controls at all levels to halt simple errors and establish a basis for moving forward.
6. Develop a knack for continuous improvement.
7. Set and achieve aggressive targets for improvement.
8. Formalize management accountabilities for data.
9. Lead the effort using a broad, senior group.
10. Recognize that the hard data quality issues are soft, and actively manage the needed cultural changes.
Redman has much more to say in his book about how to improve data quality, make better decisions using data and information and how to market your data as a product or service. I won't go into all that rich information here, but I do want to capture his point of view about who should be responsible for championing and managing data and information issues. Who do you think it is? You might reply it is the CIO, but if you guessed that you'd be wrong.
Next: Who Should Be Responsible For Data?
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