Data Overview

Your Current Stage

Learning

• Though errors remain, data collection methods and processes are being improved.
• Staff are trained in data collection.
• Data is reviewed to assess how relevant, meaningful, and necessary it is.
• The organisation knows how good or bad its different data sets are; and knows which data sources can/can’t be trusted.
• Gaps, overlaps, and mismatches in the available data have been identified.
• Data is becoming richer, more relational and therefore versatile.
• Starting to explore how internal data (perhaps in multiple, fragmented or isolated locations) can be shared and utilised.
• Additional internal and external data is sourced.
• All data assets are known but may not be formally recorded.

The next stage up for your organisation is

Developing

• Data requirements defined and consistently collected via a range of methods.
• Investment in staff training to ensure consistency and quality of data collection.
• Tests and refines how relevant, meaningful, and necessary its data is.
• Focuses on collecting the right data for clearly specified purposes.
• Data is monitored for quality including completeness, accuracy, and validity. Tools and systems exist for cleaning and maintenance.
• Richer data collection with more integration/alignment between systems reduces duplication, inefficiency and error.
• Data sharing internally is becoming the norm.
• Occasional commissioning of independent research and evaluation.
• Extensive use of externally available research and evidence around needs and successful interventions.
• Open datasets are occasionally used.
• Exploring shared measures and benchmarks with other organisations.
• Recorded list of all data assets, whether they include personal/sensitive data, and assigned responsibility.