Introduction
The information upon which the council relies to make decisions, manage services and account for performance must be reliable, accurate and timely.
In common with all councils, Lancaster City Council operates in an increasingly complex environment and must respond to a variety of demands from local residents, stakeholders, inspectorates and central government. The council’s activity is widely spread so it is vital to ensure that everything joins together seamlessly in terms of outcomes for our communities and the processes we have in place to ensure their delivery.
This strategy outlines our processes for the management, collection and reporting of performance data – in particular nationally set indicators – and the roles and responsibilities assigned to those involved in this process at all levels of the organisation. Its purpose is to highlight good practice and to ensure that everyone involved in the collection, retention and dissemination of performance data carries out their activities successfully.
Our position with regard to the management of data quality is subject to an annual Audit by the Audit Commission. It is their opinion that our existing systems are robust and getting better, but there is still some scope for improvement. We have managed our improvement to date through our previous Data Quality Strategy and Action Plan.
It is council policy to refresh all strategies on a regular basis to ensure that they are fit for purpose. The recent publication of National Standards for Data Quality[1] means that our previous strategy has been refreshed to take them into account. We hope you will find it a practical and helpful tool. It is our aim that it becomes a ‘living document’, regularly updated to reflect both national best practice and our own experience. We are therefore happy to receive any comments or suggested revisions which you think may strengthen it still further.
CLLR JOHN GILBERT – Cabinet Portfolio Holder
ROGER MUCKLE – Corporate Director Finance and Performance
1. Background
1.1 The purpose of this strategy is to outline 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.
1.2 Lancaster City Council is responsible for ensuring that its business is conducted in accordance with its statutory obligations. In discharging our responsibilities, the council must also ensure that there is a sound system of internal controls that facilitates the effective exercise of the Council’s functions, this includes data quality.
1.3 Much work has already being undertaken to provide relevant information for Members, managers and external audit. What is needed now is a framework which will ensure that national standards are being met throughout the Council.
1.4 The Government has set out a new performance framework for local government which places a greater reliance on data quality.[2] Performance information is increasingly being used by external bodies to assess our performance, and inform scored assessment.
1.5 In particular, the external audit approach of checking calculations and system reports has evolved into a more challenging external scrutiny of systems controls. A rigorous Audit Commission assessment of our data quality arrangements feeds into the Council’s annual scored Use of Resources assessment.
1.6 There are internal drivers too, it is one of our medium term objectives to ensure that the council offers value for money in all its activity. It is important that a balance is struck between the importance of the information required and the cost of collecting the supporting data with the necessary accuracy, detail and timeliness. To achieve this balance, Lancaster City Council, like all public bodies needs to determine its information priorities and put in place appropriate arrangements to ensure quality of data.
1.7 There have been many recent changes to the processes and systems used by staff such as the introduction of the web based Escendency Performance Management System and other specialist software used by our services. This means that we are less reliant on more traditional paper based systems and have built controls and audit trails into electronic systems, reducing the risk of poor data quality.
1.8 The terms ‘data’, ‘information’ and ‘knowledge’ are frequently used interchangeably. This strategy focuses on data, that is the basic facts from which information can be produced by processing or analysis.
Table 1 – source Audit Commission
Definitions
Terminology / Definitions /Data / Data are numbers, words or images that have yet to be organised or analysed to answer a specific question
Information / Produced through processing, manipulating and organising data to answer questions, adding to the knowledge of the receiver.
Knowledge / What is known by a person or persons. Involves interpreting information received, adding relevance and context to clarify the insights the information contains.
1.9 This strategy outlines all the steps necessary to maintain the highest possible standards throughout the data collection process, from first principles and setting up indicators to the eventual publication of a robust set of performance data which is accurate and fit for external scrutiny.
2. The Scope of the Strategy
2.1 All aspects of the production of performance information are within the scope of this strategy including systems, processes and governance arrangements
2.2 The objective is to ensure that the Council continues to develop robust arrangements in relation to data collection and reporting, which ensures that accurate and timely information is available for the Council, its partners/stakeholders and inspectors.
3. What makes good quality data?
Table 2 – source Audit Commission
AccuracyData should be sufficiently accurate for their intended purposes, representing clearly and in enough detail the interaction provided at the point of activity. Data should be captured once only, although they may have multiple uses. Accuracy is most likely to be secured if data are captured as close to the point of activity as possible. Reported information that is based on accurate data provides a fair picture of performance and should enable informed decision making. The need for accuracy must be balanced with the importance of the uses for the data, and the costs and effort of collection. For example, it may be appropriate to accept some degree of inaccuracy where timeliness is important. Where compromises are made on accuracy, the resulting limitations of the data should be clear to their users. This must be a judgement determined by local circumstances, and is unlikely to be appropriate in the case of the data supporting published performance indicators.
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. Where proxy data are used to compensate for an absence of actual data, bodies must consider how well these data are able to satisfy the intended purpose.
Reliability
Data should reflect stable and consistent data collection processes across collection points and over time, whether using manual or computer based systems, or a combination. Managers and stakeholders should be confident that progress toward performance targets reflects real changes rather than variations in data collection approaches or methods.
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.
Relevance
Data captured should be relevant to the purposes for which they are used. This entails periodic review of requirements to reflect changing needs. It may be necessary to capture data at the point of activity which is relevant only for other purposes, rather than for the current intervention. Quality assurance and feedback processes are needed to ensure the quality of such data.
Completeness
Data requirements should be clearly specified based on the information needs of the body and data collection processes matched to these requirements. Monitoring missing, incomplete, or invalid records can provide an indication of data quality and can also point to problems in the recording of certain data items.
4. Maintaining Quality Data
4.1 The Audit Commission framework for improving data quality identifies five main components which together ensure that the quality of the council’s data is maintained. These are:
§ GOVERNANCE AND LEADERSHIP
§ POLICIES
§ SYSTEMS AND PROCESSES
§ PEOPLE AND SKILLS
§ DATA USE AND REPORTING
Each of these is discussed in detail below
5. LEADERSHIP AND GOVERNANCE
5.1 The council is committed to robust data quality. Clear strategic leadership at the highest level is provided by the Cabinet Portfolio holder and the Corporate Director (Finance and Performance). Information Management Group (IMG) ensures a sustained focus on Data Quality management and receives regular updates on key issues arising. IMG monitors delivery of the council’s high level Data Quality Action Plan. The Action Plan is regularly updated to reflect emerging best practice and the outcome of the most recent Data Quality assessment. Targets are articulated in Service Business Plans.
5.2 The council’s Corporate Strategy Service has a programme of Data Quality assessments based on local risk assessments. These reviews ensure that all the appropriate systems and processes are in place for the compilation of performance information. Data Quality exceptions are reported to both Information Management Group and Audit Committee.
5.3 TheAudit Committee has delegatedresponsibility for monitoring the development and operation ofrisk management and governance within the Council. In doing so it seeks to receive assurancethat performance management arrangements are effective, including those relatingto the provision of high qualitydata. The Committee will consider any significant risks presentedby any weaknesses identified in relation todata quality and seek assurance that any such weaknesses are addressed.
5.4 Accountability for data throughout the organisation at all levels is clearly and formally defined. All Heads of Service, supported by Information Custodians have their data quality responsibilities explicitly identified in their job descriptions and effectiveness is reviewed through our Employee Development Personal Appraisal (EDPA) process.
5.5 The corporate commitment to data quality is also communicated clearly and this message is cascaded down to all staff involved in data collection. Roles and responsibilities in terms of data management are constantly reinforced by those tasked with governance and leadership. Corporate Strategy Service provides regular training and gathers feedback through the Information Custodians Group. Information Custodians ensure services hold specific guidance individual seminars/workshops appropriate to local circumstances.
5.6 The Council has in place an information sharing protocol and where relevant, service level agreements, to ensure the quality of data used to govern our work with partners.
6. POLICIES
6.1 Our corporate commitment to data quality is supported by a range of practical processes which ensure our stated aims are transformed into good practice in all areas of council activity. This corporate policy is underpinned by a range of operational procedures, designed on a service by service basis, to reflect local systems and practices. Information Custodians ensure that policies and procedures are applied consistently in every service and regularly updated. Compliance is reported to Information Management Group who take corrective action where necessary.
6.2 Information Custodians also have responsibility for Freedom of Information and Data Protection and are trained and equipped to ensure compliance with the requirements of these acts in all systems and processes.
6.3 Strong operational procedures in relation to data, exist throughout the organisation. For example, there are clear procedures laid down on the various aspects of the council performance management framework. Our Corporate performance management system, Escendency has built in a range of policies, procedures, templates and advice which are accessible to all staff involved in the process.
6.4 All council systems, whether paper based or electronic, provide clear audit trails to enable internal controls and external audit.
6.5 Information Management Group guides the development of the data quality process and monitors implementation of the Data Quality Strategy across the council. They are supported in this by the Corporate Strategy Service which ensures that agreed procedures, processes are adhered to and local guidance is followed. This is done by a regular programme of testing and sampling on a risk assessed basis.
7. SYSTEMS AND PROCESSES
7.1 Services have appropriate internal controls in terms of data quality and all systems are auditable and can be interrogated. Each system has a named officer responsible for data quality and that person ensures the following:
§ Users are trained
§ Integrity tests take place regularly
§ Systems meet the expected needs
§ Written procedures exist along with a business continuity plan
7.2 There must be adequate controls over the input of data. Systems produced figures are only as good as the data input into that system in the first place. The aim should be 100% accuracy 100% of the time. A key requirement is that data should be entered on an ongoing basis, not saved up to be entered in a block at the end of the period. This reduces the error rate and the need for complex verification procedures.
7.3 Nevertheless in complex systems, even when there are strong controls over input, errors can creep in and so verification systems are in place as close to the point of input as practicable. Information systems have built in controls which also minimise the scope for human error and clear audit trails identify manipulation, incorrect data entry, missing data or unauthorised data entry.
7.4 Systems and processes surrounding data quality are streamlined to ensure integration into day to day work. Our guiding principle is to add value throughout the business planning and reporting process. Ensuring high data quality is simply good working practice and should be seen as such.
7.5 The Council has developed a Business Continuity Policy and also an Overall Business Continuity Plan to provide a structure and procedures for Business Continuity within the Council. Business Continuity plans have been produced by all Services who will continue to develop and revise their respective plans on a regular basis because they understand their own areas of business, the services that must be kept going and the risks to those services.