Data Strategy

Improving the quality, management and governance of University data

The University's Data Strategy sets out key aims and principles that will underpin improvements to, access to and use of our administrative data.

Better quality data is not just about IT systems. It is about how data is valued and managed day to day. Through the implementation of the Data Strategy we are working towards:

Data is... Principle is established when...

...a valued University asset

Data is given the same consideration as buildings, people and money and is prioritised and resourced appropriately.

...managed

It is clear who is accountable for what, to whom.

...fit for purpose

There is a common language to underpin productive discussions about data.

...standardised, comparable and linkable

There are consistent methods of recording individual data items across purposes and across systems.

...secured and subject to risk management

Staff feel confident that data is secured and controls are in place.

...made accessible and available

Accessing data where legitimate to do so is straightforward; data sharing is expected subject to controls.

The Data Strategy 2023-2026 outlines 3 goals, 9 priorities and a number of deliverables for each which will be reviewed by Data Governance Group and Data Executive Group at least annually.

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Many staff have reported feeling frustrated when they need data or receive data due to:

  • difficulties accessing data
  • being unsure about the accuracy of data in reports
  • experiencing gaps in the data available

We all need data that works for us and key data often passes through a number of teams and processes during its lifecycle, from when it is first entered to when it is used in returns or decision-making. Therefore, it is important that we take a coherent, organisation-wide approach to tackling the challenges.

Better data should help make lots of tasks easier including:

  • team and department planning
  • reporting to committees
  • business continuity planning
  • Athena Swan submissions
  • REF submissions
  • regulatory returns
  • completing projects

Significant work has been undertaken around data quality with the development of the Data Quality assurance policy, data risk management toolkit and the establishment of the Data Assurance Group.  This has led to a robust approach to delivering the University’s returns for external bodies.   

The Data Strategy brings this together with an all-encompassing approach that goes beyond looking at processes and technology alone. It includes: 

  • developing a more collaborative culture around data, recognising the interconnectedness of our data and treating it as a shared asset
  • providing training so that everyone understands their role in data and how it connects with others
  • tackling existing data problems
  • providing a clear framework for preventing and addressing issues in the future, including establishing data governance
  • improving the University’s business intelligence capability, including leveraging technology to deliver data more quickly

 

The Data Strategy Implementation Programme (DSIP) is coordinating delivery of the Data Strategy.  This team is made up of colleagues from Planning and Council Secretariat (PACS) and IT Services.

The team is accountable to and works in partnership with  Data Executive Group  and  Data Governance Group  .

Improving the quality and management of our data is a task for all staff, no matter where they are in the organisation. Here are some ideas for how you can make a difference:

  • Issues: if you suspect something isn’t right, make it known. It is likely that others are experiencing similar issues.  Some issues might be easily solved, some might be really complex. But if the University has visibility of what the issues are, we will be in a better position to focus efforts to resolve them
  • Inter-connectedness: whenever you handle data, consider the person who might need it next or in a year’s time, for example for Athena Swan or the REF. What will they need and how can you avoid making their job harder?
  • Right first time: if there isn’t time to do it right first time, there may not be time to fix it later. Wherever possible, data entered into enterprise systems should be as complete and accurate as possible at point of entry
  • Find out more about how you can contribute by completing the 30 minute data quality training module  
  • The condensed data self-assessment tool  is designed to help you identify areas of good practice to share, build on and better integrate, and also areas for improvement, both locally and collectively across UAS. Completing this form might help you identify and consider potential improvements in your area and can also help you liaise with colleagues in other areas. If you want to discuss the outcomes of your condensed assessment or do a more comprehensive exercise, please contact your Data Governance Group  representative or Ayoola Bamgboye, Data Governance Manager (via ayoola.bamgboye@admin.ox.ac.uk).
  • In addition, your Data Governance Group  representative might contact you regarding specific tasks required to improve the quality of data you are involved with

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