Data Quality and Data Sharing

 

An intensive one-day course covering the key concepts and benefits of data quality and data sharing;  risk and risk management, and both incremental and strategic options for its improvement.

 

Data quality and data sharing are issues that should underpin just about everything that a public sector organisation does. Data quality and data sharing are essential for service delivery, for providing information and advice, and for decision making. Without good quality data, an organisation cannot properly understand whether transformation and efficiency projects are delivering real benefits, or whether they are simply shifting costs and problems to other areas.

 

 

Many organisations are collecting the same data over and over again from their service users who often rightly ask ‘haven’t I already told you this?’ And yet, despite all the data collection, large amounts of data are both duplicated and incorrect. The longer data quality issues are not addressed in the organisation, the more expensive in the long run it will be to correct all the errors. No organisation can claim to be efficient if it is collecting the same data over and over again, if the data is not accurate, and if it cannot be trusted to be used for service delivery. Many parts of the same organisation are collecting data for different purposes but are not sharing this data. This makes it difficult to get a comprehensive view of service delivery or to plan effectively.

 

The real costs of poor data quality and misunderstandings about data sharing can be considerable in terms of:

•  risk
•  inefficiencies
•  loss of reputation and trust regarding personal data
•  time spent checking and correcting
•  failure to comply with legislation
•  barriers to joined-up working, shared services and service transformation
•  other lost opportunities
•  inaccurate and misleading performance information

 

 

Why attend? 

 

Data quality can be improved in all organisations, and it is not difficult to address, once staff and managers have the knowledge, tools and support to do this. This one day course will be a small investment that can lead to substantial savings.

 

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Delegates will gain an understanding of the key concepts and practical issues about data quality and data sharing They will learn what data quality is, where data quality needs to be applied, how data quality can be validated and improved and what the benefits of this are to the organisation. The course will cover the legislative and policy framework that drives data sharing and will outline the key issues about when to share, and when not to share data.

 

The course will include practical approaches that people can take back into their organisation to create both quick wins and long term solutions.

 

 

 Who Should Attend

 

Information professionals

Managers and supervisors responsible for collecting, maintaining and verifying key data.

Business analysts

Service delivery managers

Performance managers

Records Managers

Customer Services Managers

 

To Book

 

To book online please select the course date from the table to the right or else contact us on 0845 241 2773

 

Course Content?

 

Data Quality - Overview

•   Data, information and knowledge - definitions
•   Data, information andkKnowledge as key assets of the organisation
•   What is data quality and why is it important?
•   Data collection, organisation, retrieval and purging

 The key attributes of quality data

 

Drivers, risks and benefits of good data management, data quality, and data sharing

• Customer expectations
•  Reducing and managing risk
•  Efficiencies
•  Effective measurement and performance management
•  Service transformation
•  Shared services
•   Integration
•   Better governance
•   Legislation and policies
•  Human error

 The risks and costs arising from poor data quality

•  Identification
•  Economic management of risks
•  Ensuring accurate data capture from the outset

 

 The business and service benefits of accurate and dependable information

 

The people aspects

•  Stakeholders
•  Roles, responsibilities and accountability
•  Establishing ownership
•  Key messages for staff and management
•  Culture and governance

 

 Processes, People and Technologies

• Data capture
• Data recording
• Data sharing
• Monitoring & checking
•  Auditing

 Data Quality and Data Sharing

•  Barriers and enablers
•  Data protectio9n considerations and myths