As education data come to the fore in efforts to improve the education system, so too will problems with those data. The return on your LDS investment is dependent on the quality of the data maintained in, and available through, the system. This reality necessitates a heightened commitment to data quality.
Bad data can lead to bad decisions. In addition, low quality data will not be trusted and, if they are not trusted, the system that maintains them will not be used for better decisionmaking. Worse, inaccurate data can send the wrong message, cause misallocation of resources, or misdirect interventions. Decisions based on misinformation may have potentially dire consequences for individual students, teachers, schools, and districts; and possibly affect funding, reputations, careers, and students’ educational opportunities. Fixing bad data ultimately saves staff time and resources. If data are of high quality from the moment they are created, the agency will be able to process and use the information more rapidly and effectively.
Poor quality data come from many sources: data entry and reporting errors, confusion over which data are the “right” data, and inconsistent or ambiguous standards are all common culprits. To avoid costly errors and arm decisionmakers, students, researchers, and other stakeholders with timely, high-quality information, education enterprises must strengthen strategies for creating and managing data. Data quality should be a high priority throughout the agency, with improvement efforts including data governance, clear and enforced policies and standards, careful and competent data entry, quality assurance procedures at all levels, and staff training and professional development. Staff must not only understand agency data procedures and requirements, they must also be convinced of the data’s importance. The records must not be seen only as chores; they should be treated as assets that can inform and enhance their work. To this end, it is very important that local staff are able to use the data they create.
The following three chapters aim to help agencies improve the quality of the data they create, collect, store,
and make available through their LDS. They provide an overview of many factors involved in creating quality
data, and will direct readers to other resources focused on these issues.