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Data collection and analysis

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Good quality data is essential if reliable performance and financial information is to be reported on. The data must be fit for purpose and represent accurately the activity of the local authority or its partners over a specified time period. At the same time, a balance must be achieved between the importance of the information requirement and the cost of collecting the supporting data.

New technical guidance to support the collection of data for the national indicator set is due to be published early in 2008. This site will be updated once it is available

The Audit Commission has published a framework to support improvement in data quality in the public sector and a set of ‘Standards for better quality data’.


They define six key characteristics of quality data:


data should be sufficiently accurate for its intended purpose, representing clearly and in sufficient detail the activity it is reporting on. If compromises in accuracy have to be made due to timing or the costs of data collection, the limitations of the data should be clear

data should be recorded and used in accordance with agreed methodologies and requirements, including the correct application of any rules or definitions

data should reflect stable and consistent data collection processes across collection points and over time
data should be captured as quickly as possible after the event or activity and made available within a reasonable time period
data captured must be relevant to the purposes for which it is used and reviewed regularly to reflect changing needs
the data provided should be monitored to ensure it is complete against the specified information needs of the organisation.


In addition the ‘Standards for better quality data’ identify a number of key factors that will help any organisation collect quality data to enable its performance to be measured. These include:

-putting in place a corporate framework for management and accountability of data quality, with clear leadership from the top and a commitment to secure a culture of data qualityGood quality data is essential if reliable performance and financial information is to be reported on.

- having appropriate policies and procedures to secure the quality of data recorded and its use in reporting. This includes clear procedures for data collection, recording, analysis and reporting that are adopted across the organisation and where relevant by partners

- having systems and processes in place to secure data that is accurate, valid, reliable, timely, relevant and complete. Such systems should be based on the principle of joined up working and ‘right first time’ rather than having to employ data cleansing or manipulation processes to produce the information required. Where data is shared externally or provided by a third party, putting in place a data sharing protocol or service level agreement to ensure consistent quality of data, with validation processes.

– making sure that staff at all levels within the organisation have the appropriate knowledge, competencies and capacity for their roles in relation to data quality. Ensuring data quality policies, procedures and guidance are widely communicated. Making arrangements to regularly review the relevance of the data collected and to ensure it is actively used in decision making processes. Applying a system of internal control and validation proportionate to risk.


To see the full report click here.

Making good use of the data that is collected is also important. This could involve:

  • summarising data, including using averages; using frequencies and groups; looking at data issues - polarity, precision and data types; looking at distribution; using box plots and histograms and making use of sampling
  • comparing data, including using averages, using quartiles; using benchmarking and ranking; looking over time and using other variables
  • presenting and using data, using tables, maps and charts


Guidance on using data is available from the Audit Commission in the form of a web based tool which can be found here.

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