Explainer
Why is data quality important?
Reliable data decides whether services are funded and staffed correctly - and whether they get delivered the way they should. Poor data quality shows up as bad decisions long before it shows up as a bad dashboard.
Why it matters
Data quality decides who gets funded and staffed - and who stays safe
Reliable information is needed to understand demand and plan service provision: police officers on the ground, staffing for emergency services, patient demand in hospitals, and the impact of population growth on schools. Accurate activity data is what keeps services funded appropriately, and activity-based funding is now used across many public sector agencies. Mis-reporting of activity can have a severe impact on that funding.
Accurate, up-to-date information is also what gets welfare payments and other entitlements to the people eligible for them. Quality data contributes to employee safety too: it tells police and enforcement officers the risks in approaching a place or a person, and whether they need back-up.
Data quality insights
Six things worth knowing before you start a data quality program
Prevention beats cure
Invest in improving quality at the source. Errors at the source multiply further down the chain and become truly problematic by the time they reach reporting.
Quality is in the eye of the beholder
Statistical analysts might judge a dataset unacceptable, while the operational people who use it record by record consider its quality acceptable. Both views matter.
Process contributes to quality
Training and well-defined procedures matter. A system that supports the workflow, rather than capturing data after the fact, is more likely to hold high-quality data.
Technology design affects quality
An intuitive interface, correctly levelled classifications, sensible mandatory fields and logical navigation between screens all shape the quality of the data captured.
Prioritise what matters most
There is never enough resource to check and correct every dataset. Focus on the data items vital to meeting the organisation's strategic objectives.
Use data analytics where you can
Record inspection is the most resource-intensive audit method and should be minimised. Data analytics is repeatable, cost-effective and lets you compare across systems and time.
We provide data analytics and data quality services for organisations Australia wide.
Data quality sits within our wider information and data management solution.