Kindel, Carrol Benner (1986, ASQC) Standards and Audits Energy Information Administration, Washington, DC
The purpose of this paper is to focus on the future of quality by discussing quality control applications in a newer, nontraditional context: information management. As the management of information and information systems absorbs more and more of our national resources, thought must be given to the maintenance of quality in vital information products. It is time for forward-thinking managers to consider the application of traditional quality control in this broader context. Many quality control concepts from the manufacturing sector can be applied, as long as one thinks of information (data) as the final product of the information management process, analogous to, for example, an automobile as the final product of a manufacturing process.
Specifically, the paper discusses the application of quality control concepts to federal government data collection programs. Data quality is especially critical here, as the information collected must be as accurate as possible to be of use to decision makers. Federal managers responsible for collecting and disseminating information, as well as the consuming public, are, therefore vitally concerned with the quality of such data.
The paper focuses on the experience of a particular federal agency, the Energy Information Administration (EIA), mandated to collect and disseminate information on the national energy picture. The approach taken by the paper will be to describe aspects of EIA's data quality program, which was developed by applying concepts and methods from the manufacturing sector.
Specific aspects covered will include, first, how one determines the appropriate standards against which to measure quality performance. Some attention will also be paid to the applicability of terms such as "quality control", "quality assurance", "quality maintenance", and "quality audits" in a nonmanufacturing context. Another aspect involves the organization of the quality program at EIA. There, quality control is a decentralized function with oversight responsibility delegated to the Office of Statistical Standards. Examples of the oversight programs will be described. Finally, the issue of building quality into individual data collection programs will be discussed, including operational aspects such as data editing and survey coverage, and how that activity is planned and monitored.
Most of the conceptual framework of EIA's program was established through reading texts and articles designed for other applications. However, EIA staff found that they were not alone in their efforts. Various other federal data collection agencies, notably, the Bureau of Labor Statistics, the Census Bureau, the National Center of Health Statistics, and the Internal Revenue Service were also devoting considerable resources to structuring data quality programs. Discussions with staff from these agencies helped in bridging information gaps.
The body of knowledge that is beginning to accumulate in this area needs circulation, discussion and evaluation. As information becomes an increasingly important commodity, there is an increasing need to discuss its quality. In these days of stringent budgets it is particularly important to build in mechanisms to detect any deterioration before it gets out of hand, much like inspecting an automobile to protect against costly breakdowns. This forum, and others, will provide encouragement and open channels of communication.