Public sector organizations experience many pitfalls of poor data quality, including:
- Unreliable data and unfavorable output.
- Inefficiencies and costly remedies.
- Dissatisfied citizens.
- Poor data quality hindering successful decision making.
Our Advice
Critical Insight
Not understanding the purpose and execution of data quality causes some disorientation with your data. This could be:
- Failure to realize the importance/value of data quality.
- Being unsure of where to start with data quality.
- Lack of investment in data quality.
Organizations tend to adopt a project mentality when it comes to data quality, instead of taking the strategic approach that would be all-around more beneficial in the long term.
Impact and Result
Address the root causes of your data quality issues by forming a viable data quality program.
- Be familiar with your organization’s data environment and business landscape.
- Prioritize business use cases for data quality fixes.
- Fix data quality issues at the root cause to ensure a proper foundation for your data to flow.
- It is important to sustain best practices and grow your data quality program.