Embedding Data Reliability Evidence-based Decision-making

[...]Review policies and procedures to address consistency of relevant data attributes. Since data attributes do not carry the same level of importance, identify the ones that are crucial to decision-making. * Inspect information system configuration and interfaces for compliance with policy requirements to record relevant attributes consistently across different systems. * Confirm that the data integrity process identifies data standards, inventories, and dictionaries and that it meets regulations, supports data throughout its lifecycle, and enforces internal data standards. * Identify data sources, alignment, and gaps to make sure information is available and avoid having to fill (or not fill) gaps after the fact. Data sources include entities that administer federal funds, such as state and local governments and contractors, because data risk assessment does not end when these funds are disbursed by federal agencies. * Develop a risk matrix for the use of information that has not been validated, is of dubious reliability, or is known to be unreliable or inconsistent. * Remember that data risk assessment is a continuous process, integral to enterprise risk management. According to the Pew Research Center, 66% of Americans "harbor hope that open data will improve government accountability.7711 Data reliability was crucial to the Pandemic Response Accountability Committee (PRAC), established at the outset of COVID-19 and led by the federal inspectors general (IGs) to oversee and provide transparency for what became $5.2 trillion in relief spending. Under program evaluations, auditors answer questions related to audit objectives (e.g., is the program reaching its intended recipients, having the expected impact, or being managed effectively and efficiently?)15 GAGAS recognize "auditors may use GAGAS in conjunction with professional standards issued by other authoritative bodies," such as the American Evaluation Association's Guiding Principles for Evaluators.16 Auditors, evaluators, investigators and other professionals, such as management analysts and consultants who provide management studies or oversight requiring data analysis, often use a four-step process to evaluate data reliability: 1.