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In briefShow moreShow lessHigh-quality data is essential for efficient operations, sound decision-making, and a seamless customer experience.
- High-quality data is essential for efficient operations, sound decision-making, and a seamless customer experience.
- Poor data quality can lead to delays, customer complaints, fines, and inefficient processes.
- Data quality needs attention where information is recorded.
The story
High-quality data is essential for efficient operations, sound decision-making, and a seamless customer experience.
What this means for the work
Poor data quality can lead to delays, customer complaints, fines, and inefficient processes.
Standardized guidelines, regular data reviews, and validation procedures are key measures for ensuring high data quality.
Independent research places the subject in a wider context than the tool itself. In March 2023, Forrester identified data accessibility, availability and readiness as persistent barriers to turning analytics into decisions. A report or platform therefore has to be assessed together with definitions, ownership and working practices.
Gartner’s April 2024 trends highlighted trust in data as a central challenge for data and analytics leaders. Faster visualisation or more self-service creates value only when users understand where figures come from and when they can be used.
Management should agree on data quality, access, common metric definitions and responsibility for corrections. The effect can be measured as less manual work, shorter time from question to answer, or fewer disputes about the underlying figures.
Sources and perspectives
ProsessPilotene: Data quality and management responsibility highlighted in ProsessPodden
Forrester: The Key To Insights-Driven Decisions Is Curiosity Velocity (8 March 2023)
Gartner: Top Trends in Data and Analytics for 2024 (25 April 2024)
Practical follow-up
Data quality needs attention where information is recorded. Managers need clear definitions, responsibility for corrections and a way to detect errors. The conversation connected this work with everyday reports and decisions.
UK Government: Data Quality Framework
Join the discussion
What would you investigate first before using this? Share your questions or experience in the discussion.
The UK Government Data Quality Framework emphasises fitness for purpose. This gives managers a concrete question: Is the information good enough for the decision we need to make?
