THREE RIVERS
DISTRICT COUNCIL
DATA QUALITY
STRATEGY
MARCH 2008
CONTENTS
Item
1.
2.
3.
4.
Introduction
Definitions
Current Position
Characteristics of Data Quality
4.1. Accuracy
4.2. Validity
4.3. Reliability
4.4. Timeliness
4.5. Relevance
4.6. Completeness
5. Data Quality Standards
5.1. Governance and Leadership
5.2. Policies
5.3. Systems and Processes
5.4. People and Skills
5.5. Data Use and Reporting
6. Review and Action Plan
Management Arrangements Scores – November 2006
Action Plan for Improvement
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Appendix 1
Appendix 2
1. Introduction
The Council needs information that is fit for purpose in order to manage services and
account for performance. Information is used throughout the organisation to make
judgements about the efficiency, effectiveness and responsiveness of services and in making
complex decisions about priorities and the use of resources. Service users, and in particular
members of the public, need accessible information to make informed decisions and
Regulators and government departments must satisfy their responsibilities for making
judgements about performance and governance.
The 2006 Local Government White Paper, Strong and Prosperous Communities, and the
Local Government and Public Involvement in Health Act 2007 set out a new performance
framework for local services. This places greater reliance on data quality, to provide robust
data for local performance management, and to inform performance assessments. It also
emphasises the need for local public services to use information to reshape services
radically and to account to local people for performance. As increasing reliance is placed on
performance information in performance management and assessment regimes, the need to
demonstrate that the underlying data are reliable has become more critical.
In November 2007 the Audit Commission published ‘Improving information to support
decision making: standards for better quality data’. This paper encourages public bodies to
improve the quality of the data used for decision making, presenting a set of clear and
concise standards, based on accepted good practice, which can be adopted on a voluntary
basis.
The Council has published a Policy Statement for Data Quality1 which outlines a commitment
to data quality through the adoption of the Audit Commission’s Standards for Better Data
Quality. This strategy builds on the Policy Statement and outlines an approach to improving
Data Quality across the Council. Consistent, high-quality, timely and comprehensive
information is vital to support good decision-making and improved service outcomes.
2. Definitions
The terms ‘data’, ‘information’ and ‘knowledge’ are frequently used interchangeably and are
defined in the following table. This document and the standards it introduces, focuses on
data; that is, the basic facts from which information can be produced by processing or
analysis.
Data
Information
Knowledge
Data are numbers, words or images that have yet to be organised or
analysed to answer a specific question.
Produced through processing, manipulating and organising data to
answer questions, adding to the knowledge of the receiver.
What is known by a person or persons. Involves interpreting
information received, adding relevance and context to clarify the
insights the information contains.
Source: Audit Commission
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See page 10 of the 2008/11 Strategic Plan
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3. Current Position
During 2006 the Audit Commission implemented a revised approach to the audit of
performance indicators in local government. This required the Council’s External Auditors to
conclude on the arrangements for monitoring and reviewing performance, including
arrangements to ensure data quality. A score was attributed, derived from a number of key
lines of enquiry (KLOE) and areas of audit focus and evidence under the following;

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


Governance and leadership
Policies
Systems and processes
People and skills
Data use and reporting
The arrangements for 2005/06 achieved an overall score of two or ‘adequate performance’
for the Council’s management arrangements in respect of data quality. Details of the scores
for each of the key lines of enquiry, which combine into the overall score of two, are shown at
Appendix 1. The subsequent recommendations made by the External Auditor have been
taken into account when developing this Strategy.
4. Characteristics of Data Quality
The Audit Commission have identified six key characteristics of good quality data.
4.1. Accuracy
Data should be sufficiently accurate for the intended use and should be captured only
once, although it may have multiple uses. Data should be captured at the point of activity.



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Data is always captured at the point of activity. Performance data is directly input into
PerformancePlus2 (P+) by the service manager or nominated data entry staff.
Access to P+ for the purpose of data entry is restricted through secure password
controls and limited access to appropriate data entry pages. Individual passwords can
be changed by the user and which under no circumstances should be used by
anyone other than that user.
Where appropriate, base data, i.e. denominators and numerators, will be input into
the system which will then calculate the result. These have been determined in
accordance with published guidance or agreed locally. This will eliminate calculation
errors at this stage of the process, as well as provide contextual information for the
reader.
Data used for multiple purposes, such as population and number of households, is
input once by the system administrator.
4.2. Validity
Data should be recorded and used in compliance with relevant requirements, including
the correct application of any rules or definitions. This will ensure consistency between
periods and with similar organisations, measuring what is intended to be measured.

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Relevant guidance and definitions are provided for all statutory performance
indicators. Service Heads are informed of any revisions and amendments within 24
hours of receipt from the relevant government department. Local performance
indicators comply with locally agreed guidance and definitions.
PerformancePlus is performance management software purchased in April 2006 from InPhase Ltd.
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4.3. Reliability
Data should reflect stable and consistent data collection processes across collection
points and over time. Progress toward performance targets should reflect real changes
rather than variations in data collection approaches or methods.

Source data is clearly identified and readily available from manual, automated or
other systems and records. Protocols exist where data is provided from a third party,
such as Hertfordshire Constabulary and Hertfordshire County Council
4.4. Timeliness
Data should be captured as quickly as possible after the event or activity and must be
available for the intended use within a reasonable time period. Data must be available
quickly and frequently enough to support information needs and to influence service or
management decisions.

Performance data is requested to be available within one calendar month from the
end of the previous quarter and is subsequently reported to the respective Policy and
Scrutiny Panel on a quarterly basis. As a part of the ongoing development of
PerformancePlus it is intended that performance information will be exported through
custom reporting and made available via the Three Rivers DC website. This will
improve access to information and eliminate delays in publishing information through
traditional methods.
4.5. Relevance
Data captured should be relevant to the purposes for which it is to be used. This will
require a periodic review of requirements to reflect changing needs.

We have a duty to collect and report performance information against a wide range of
statutory indicators. These are set out in the context of the Government’s White
Paper – Strong and Prosperous Communities. Where appropriate each service will
identify reliable local performance indicators to manage performance and drive
improvement. These are reviewed on an annual basis to ensure relevance.
4.6. Completeness
Data requirements should be clearly specified based on the information needs of the
organisation and data collection processes matched to these requirements.

Checks will be made to ensure for completeness of data. An annual assessment of
this is undertaken by Internal Audit.
5. Data Quality Standards
The Standards for Better Data Quality as identified by the Audit Commission define a
framework of management arrangements that bodies can put in place, on a voluntary basis,
to secure the quality of the data they use to manage and report on their activities.
These Standards reflect the KLOE as described in paragraph 3. Below, this Strategy
identifies the extent that we currently meet with these standards and recognises those areas
that are not yet fully developed.
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5.1. Governance and leadership
We will put in place a corporate framework for management and accountability of data
quality, with a commitment to secure a culture of data quality throughout the organisation.
Key components:
5.1.1. There will be clear corporate leadership of data quality by those charged with
governance.
5.1.2. A senior individual at top management level (for example a member of the
senior management team) will have overall strategic responsibility for data
quality, and this responsibility is not delegated.
5.1.3. The corporate objectives for data quality will be clearly defined (although this
may not necessitate a discrete document for data quality), and agreed at top
management level.
5.1.4. The data quality objectives will be linked to business objectives, cover all our
activities, and have an associated delivery plan.
5.1.5. The commitment to data quality will be communicated clearly, reinforcing the
message that all staff have a responsibility for data quality.
5.1.6. Accountability for data quality will be clearly defined and considered where
relevant as part of the performance appraisal system.
5.1.7. There will be a framework in place to monitor and review data quality, with
robust scrutiny by those charged with governance. The programme will be
proportionate to risk.
5.1.8. Data quality will be embedded in risk management arrangements, with regular
assessment of the risks associated with unreliable or inaccurate data.
5.1.9. Where applicable, we will take action to address the results of previous
internal and external reviews of data quality.
5.1.10. Where there is joint working, there will be an agreement covering data quality
with partners (for example, in the form of a data sharing protocol, statement,
or service level agreement).
5.2. Policies
We will put in place appropriate polices or procedures to secure the quality of the data it
records and uses for reporting.
Key components:
5.2.1. Comprehensive guidance for staff on data quality, translating the corporate
commitment into practice, will be provide and published. This may take the
form of a policy, set of policies, or operational procedures, covering data
collection, recording, analysis and reporting. The guidance will be
implemented in all business areas.
5.2.2. Polices and procedures will meet the requirements of any relevant national
standards, rules, definitions or guidance, for example the Data Protection Act,
as well as defining local practices and monitoring arrangements.
5.2.3. Policies and procedures will be reviewed periodically and updated when
needed. We will inform staff of any policy or procedure updates on a timely
basis.
5.2.4. All relevant staff will have access to policies, guidance and support on data
quality, and on the collection, recording, analysis, and reporting of data.
Where possible this will be supported by information systems.
5.2.5. Policies, procedures and guidelines will be applied consistently. Mechanisms
will be in place to check compliance in practice, and the results will be
reported to top management. Corrective action will be taken where necessary.
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5.3. Systems and processes
We have put in place systems and processes which secure the quality of data as part of
the normal business activity of the body.
Key components:
5.3.1. There are systems and processes in place for the collection, recording,
analysis and reporting of data which are focused on securing data which are
accurate, valid, reliable, timely, relevant and complete.
5.3.2. Systems and processes work according to the principle of right first time,
rather than employing extensive data correction, cleansing or manipulation
processes to produce the information required.
5.3.3. Arrangements for collecting, recording, compiling and reporting data are
integrated into our business planning and management processes supporting
the day-to-day work of staff.
5.3.4. Information systems have built-in controls to minimise the scope for human
error or manipulation and prevent erroneous data entry, missing data, or
unauthorised data changes. Controls are reviewed at least annually to ensure
they are working effectively.
5.3.5. Corporate security and recovery arrangements are in place. We regularly test
our business critical systems to ensure that processes are secure, and results
are reported to top management.
5.4. People and skills
We will put in place arrangements to ensure that staff have the knowledge, competencies
and capacity for their roles in relation to data quality.
Key components:
5.4.1. Roles and responsibilities in relation to data quality will be clearly defined and
documented, and incorporated where appropriate into job descriptions.
5.4.2. Data quality standards are set, and staff are assessed against these.
5.4.3. Staff are trained to ensure they have the capacity and skills for the effective
collection, recording, analysis and reporting of data.
5.4.4. There will be a programme of training for data quality, tailored to needs. This
will include regular updates for staff to ensure that changes in data quality
procedures are disseminated and acted on.
5.4.5. Corporate arrangements will be in place to ensure that training provision is
periodically evaluated and adapted to respond to changing needs.
5.5. Data use and reporting
We will put in place arrangements that are focused on ensuring that data supporting
reported information are actively used in the decision making process, and will be subject
to a system of internal control and validation.
Key components:
5.5.1. Internal and external reporting requirements will be critically assessed. Data
provision is reviewed regularly to ensure it is aligned to these needs.
5.5.2. Data used for reporting to those charged with governance are also used for
day-to-day management of our business. As a minimum, reported data, and
the way they are used, will be fed back to those who create them to reinforce
understanding of their wider role and importance.
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5.5.3. Data will be used appropriately to support the levels of reporting and decision
making needed (for example, forecasting achievement, monitoring service
delivery and outcomes, and identifying corrective actions). Evidence is
provided so that management action is taken to address service delivery
issues identified by reporting.
5.5.4. Data which are used for external reporting are subject to rigorous verification,
and to senior management approval.
5.5.5. All data returns are prepared and submitted on a timely basis, and, where
appropriate, are supported by a clear and complete audit trail.
6. Review and Action Plan
We are currently awaiting the outcome of the annual assessment of data quality undertaken
by our External Auditors during 2007. On receipt of the assessment and report we will
develop and publish an action plan to address those areas requiring further attention with a
view of improving our overall score against the KLOE.
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Appendix 1
Management Arrangements Scores – November 2006
Theme and Key Line of Enquiry
Score
Governance and Leadership
1.1
Responsibility for data quality is clearly defined
2
1.2
The body has clear data quality objectives
2
1.3
The body has effective arrangements for monitoring and review of data quality
2
Policies
2.1
A policy for data quality is in place, supported by a current set of operational procedures
and guidance.
1
2.2
Policies and procedures are followed by staff and applied consistently throughout the
organisation.
2
Systems and Processes
3.1
There are appropriate systems in place for the collection, recording, analysis and reporting
of the data used to monitor performance, and staff are supported in their use of these
systems.
2
3.2
The body has appropriate controls in place to ensure that information systems secure the
quality of data used to report on performance.
2
3.3
Security arrangements for performance information systems are robust, and business
continuity plans are in place.
2
3.4
An effective management framework for data sharing is in place.
2
People and Skills
4.1
The body has communicated clearly the responsibilities of staff, where applicable, for
achieving data quality.
2
4.2
The organisation has arrangements in place to ensure that staff with data quality
responsibility, have the necessary skills.
2
Data Use
5.1
The body has put in place arrangements that are focused on ensuring that data supporting
performance information is also used to manage and improve the delivery of services.
2
5.2
The body has effective controls in place for data reporting
2
Overall Score
2
Key to score
1 = below minimum requirements – inadequate performance
2 = only at minimum requirements – adequate performance
3 = consistently above minimum requirements – performing well
4 = well above minimum requirements – performing strongly
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Appendix 2
Action Plan for Improvement
To be developed on receipt of the 2007 Assessment and Report
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