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Background

Why Use the DQO Process?

Using the DQO Process will help to ensure that when a data collection endeavor has been completed it will have accomplished two goals:

• Provided sufficient data to make required decisions within a reasonable uncertainty.
• Collected only the minimum amount of necessary data.

The DQO Process embodies both of these two main goals and it is difficult to separate which is the more important or which drives the other. For example, the DQO Process will strive to provide the least expensive data collection scheme, but not at the price of providing answers that have too much uncertainty.

For anybody involved in any aspect of using data for the purpose of making decisions, the Data Quality Objectives Process is a framework for developing decision performance criteria and data collection justification that will result in a data collection that meets the criteria for the lowest possible cost.

There are two problems to deal with in decision making

• Do not have infinite resources to address the question being asked.
• Will never have 100% guarantee that the right conclusion has been reached.

Unfortunately there is a corollary relating these two problems, Uncertainty and Resources are inversely related, i.e

Less Uncertainty -->> More Resources

The DQO Process attempts to weigh these two problems and provide a balance that is satisfactory to all interested parties between the resources that must be committed and the uncertainty that is acceptable.

The DQO Process achieves this by determining the quality and quantity of data needed while minimizing costs to the extent practicable, i.e.:

• Make sure you collect enough of the appropriate data to answer your question(s) with a tolerable degree of uncertainty

but:

• Don't collect (and pay for) data you
  • don't need
  • won't use
  • can't use

to answer the question(s) that must be answered.

The DQO Process invests up-front time and money in the planning stages in return for ensuring that the end-product will satisfy all the needs of the data users. The DQO Process strives to focus the data collection activities to only those questions that are of the most critical concern.

There are two major activities in the DQO Process:

• Very specifically state the question(s) that needs to be answered for the problem at hand.
• Very specifically state the amount of uncertainty you are willing to tolerate when you attempt to answer that question with collected data.

The DQO Process will then provide cradle-to-grave justification of data collection:

• What is the question?
• Will the data answer the question?
• What quality of data is needed?
• How much data is needed?
• How will the data actually be used in decision making?

The DQO Process is a planning tool that can save resources by making data collection operations more resource-effective. Good planning will streamline the study process and increase the likelihood of efficiently collecting appropriate and useful data.