Data governance capability in HE

Over summer 2020, prompted by the Covid crisis, the Data Governance Network (in partnership with HESPA and UCISA) undertook a survey of university’s perceptions of their data governance capabilities. We wanted to use this opportunity to reflect on data capabilities, on what had been needed in response to the Covid crisis, and what lessons could be drawn from how the sector responded. 

There is considerable variation across the responses that we were given. Whilst respondents generally agreed that data is valued, that they have a central, trusted ‘Planning’ function, and that data can broadly be accessed and used as needed, there were much lower overall scores for data management, data strategy deployment and the flexibility of data to support change.

After running the survey and in order to support the sorts of step changes that will be needed post-Covid, the Data Governance Network also formulated a series of prompt questions to sit alongside the results that are intended to enable consideration of individual institutional priorities and needs.  We hope that some of these questions are of use to you and your organisation.   

What can the C-19 response teach us about how to behave when in steady state? 

• We should continue the more collegiate behaviour that has been a hallmark of this period; with more effective internal data sharing, more responsive IT developments and a national emphasis on intelligible data being amongst the highlights. How will you coalesce around the next ‘common problem’ in this manner in the future?
• Covid exposed some less than perfect internal practices that had been laid down over long periods. How do we make sure that we do not go back to old ways of working, of transacting data and displaying it?
• Covid has placed a focus on a more meaningful interpretation of GDPR; how do we build use cases to support this?

How do we ensure that the Data Governance brief moves along, especially in the current resource environment? 

• In organisations without a designated data governance role, data governance ends up being by assumption and not by appointment. As with all resource decisions, the risks of not investing in this role need to be considered and a view taken on how diverse threads (projects, systems, analytics) can be meaningfully pulled together. Where does this work sit in your organisation? Where should it sit in five years’ time?
• The data governance role is not the same as other compliance-type roles such as Data Protection Officer. Is the difference between Data Governance and Data Protection well understood? Where does Information Management sit in your organisation?
• There is frequently an overlap between the investment in data governance and in systems. Where is this overlap in your organisation, and what are the ways in which you might justify investment in data governance when systems investment is often better understood and tolerated?
• Some universities have a shadow hierarchy of data owners and data stewards, with those colleagues tasked to move the data agenda forward in their own functional spaces. Where does your organisation place this agenda and is it in line with these roles?

How do we really make decisions and what information do we need to do so?  

• This year has represented a truly foundational shift in our perception of what we can achieve and in what timescales; not least because our choices have been more constrained. How can your organisation sustain an environment where assumptions can be swiftly challenged to deliver value?
• Data that has been opaque before now has become more available as it has been pulled out of its silo to serve new operational need. What is this data for your organisation, and how can sustainable access to it be maintained?
• Despite the necessary swiftness of decision making, there has been no converse decline in any tolerance for mistakes. How will your organisation ensure that you can continue to access the data needed to reinforce decision making?

What are the links to the data science agenda? 

• Not all data is created equal, and there is a balance to be maintained between what we might call working data, and the data that can be used for more ad hoc purposes. What are these sets for your organisation and what is your relative approach to their quality?
• Data science initiatives often generate new data or information which then ends up needing to be managed in its turn. How does your organisation accommodate and incorporate such data in a managed way?
• Algorithms have been in the news this year. How can data governance help to explain the content of these and similar opaque transactions?
• Data science cannot answer all the questions we might want to ask of our data. Within your organisation, what data science work is in train and how can you ensure it is built on good data? What governance e.g. in linking data domains, needs to be put in place for this to be effective?

How can a small project approach be implemented to target quick wins? 

• In the present resource environment, small and agile data governance projects that show value and convince others that change is possible are likely to be most effective. Where are the areas in your organisation where a small data governance project could be implemented?
• Often one of the biggest process challenges is access; user access permissions, training and skills. What is the position of your organisation on these? How do you ensure that ‘data doers’ are aware of their roles and responsibilities?
• Data quality is a critical aspect for obtaining buy-in. What are the ways in which you can communicate effectively about ownership of data and business processes to convince colleagues that action should be taken?

What case studies and stories can we tell to make the business case for change in the most useful places?

• There has been a considerable challenge this year around ensuring that data is lined up so it can simply be used; for example, if online learning is to work the timetable has to be right and therefore so do module registrations. How has your organisation had to go back to basics this year, and what problems has this revealed?
• The student experience has been considered in more detail than ever before. How can your organisation tie together siloed data to give a clear picture around engagement and satisfaction? What new data sets have come through this year? What are the onward uses of the data and how can these be managed?
• The stories we tell about data are often about how things go wrong. What are the stories that you can tell from this year that demonstrate innovation and excellence in the use of data, and what consideration ought to be given to the ethics of data collection and use?

If you would like more information on the survey or on the Data Governance Network please contact Helen Butler via h.je.butler@bham.ac.uk