Effective public management and high-quality evidence require good data. Data are turned into evidence through data analyses and well-designed research. Quality data turned into evidence can help government agencies, officials, and others decide where to focus their efforts, find ways to improve, increase adoption of good practices, and build public understanding of and trust in government. This brief provides a general discussion of governments’ decisions about what data to collect and how to collect, store, analyze, share, and use (or require others to use) data.
Government policymakers, program administrators, and staff use data and data analyses for multiple purposes, including description and analysis (e.g., of conditions, impacts, costs, supply and demand trends), diagnoses, predictions, and prescriptions. In addition, data analyses help individuals and organizations choose among products, services, providers, and practices and even decide whether something such as air quality, swimming water, or drinking water is sufficiently safe. Program administrators make many decisions about data that enable more useful information for operations, management, performance, evaluation, and other analyses,
Much remains to be learned as knowledge, technology, and the world evolve. Preventing problems while tapping the benefits of advances in technology and analytic methods can be aided by building and sharing evidence and expertise about wise data handling. Programs, agencies, and cross-program efforts to make progress on specific outcome goals are aided by many governmentwide councils, including councils for performance improvement officers, chief evaluation officers, chief data officers, chief technology officers, chief information officers, and the Federal Privacy Council. Working together, agency administrators, program offices, and researchers and management experts continue to build federal agency knowledge and capacity about ways to collect, store, analyze, and share data and data analyses to improve outcomes, operational quality, and government transparency and accountability.
Government policymakers and program administrators need to make careful decisions about how much data are collected, how to protect privacy, and how to share collected data and analyses. Otherwise, data collection just becomes burdensome and annoying, requiring work without generating action-informing insights. Rapidly evolving technologies and analytic methods make wise data handling more feasible than ever before, and much can be learned from past and current practices about more and less effective data-handling strategies for different purposes.
