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Topic 1: Collecting and Analysing Data

On this page you will find guidance on collecting and analysing data for the transformed UK Athena Swan Charter.

On this page you will find guidance on the following;

  • Why we should be collecting equalities data
  • The types of data you might work with
  • What you might be looking for and why you might be looking for it
  • Methods
  • Ethics and data protection
  • Evaluating and analysing data

Why should we be collecting equalities data?

Firstly, there are legal requirements for equality and diversity in UK institutions. In order to address inequalities for staff and students with legally protected characteristics, we must identify and understand them. One of the most accurate and reliable ways to do this is to collect data in our individual institutions.

Data can help us get to know the inequalities within our institutions better.  It can highlight different experiences and help us to target support. It helps us recognise existing barriers and can help identify any information gaps. It is through collecting and analysing data that we can fully understand the current picture of our institutions and identify what needs to change.

After identifying what needs to change, data can then help us evaluate the impact of interventions and monitor equalities progress. This in turn also creates a record of the history of equalities within our institutions.

Types of Data

Broadly speaking there are two types of data you might work with: quantitative and qualitative.

Quantitative data is expressed through numbers. Methods of quantitative data collection include surveys and questionnaires that can be used to produce information in the form of statistics.

Institutions will often already collect quantitative data on a large scale. In some instances, this might be accessible and useful for you and may avoid the need to collect additional quantitative data.

For example, institutions often produce data through staff surveys, HR systems, admissions forms and student evaluations. Seeing what is available centrally can be a great starting point before you begin your own data collection.

Qualitative data is expressed through words. Methods of qualitative data collection include interviews and focus groups and generally this information would be presented as quotes or narrative.

For example, some faculties may have staff testimonials or have conducted focus groups for other reasons. As this form of data can tend to be a little more topic-specific however, you may find that you have to collect it yourself.

Different types of data are generally used for different purposes. Each is valuable in its own way. Quantitative data can be used to show trends, prevalence and patterns. As it can include a large sample number it can be powerful in showing a strong representation of the population you are looking at. Qualitative data on the other hand can offer a more nuanced and detailed look. It can be used to explore more descriptive and conceptual things such as experiences or opinions. The type of data you need will depend on what you are trying to find out and what you don’t already have access to.

For example, you may already have quantitative data available to you but you might not have any more person-centred perspectives. Running a focus group would be a great way to get a more intimate and personal reflection.

Considering sex and gender 

When collecting equality monitoring data in relation to Athena Swan, institutions and departments will need to consider how to collect data about sex and/or gender. We recognise the evolving social and legal landscape regarding data monitoring and rights in relation to sex and gender. Like many organisations we are reviewing our guidance. We also work closely with the sector on the ongoing development of the charter through the Athena Swan Governance Committee. In response to the changing landscape in relation to sex and gender we will continue these efforts to ensure it is fit for purpose and inclusive. As with everything we do, our members are at the heart of our considerations, and we’ll provide updated guidance as well as briefings on the rationale and outcome of our review. You can read a fuller statement here

Methods

This resource by Advance HE provides an overview of different types of data you might wish to collect and how best to collect it: https://www.advance-he.ac.uk/guidance/equality-diversity-and-inclusion/using-data-and-evidence/working-data

Choosing the right method is important as it affects what type of data you will collect. Consider what kind of information you are looking for and what kind of information you do not yet have. Many institutions will already collect large scale survey data so it may be that there is missing qualitative data that may offer a more detailed and nuanced perspective. Think about your capacity for data collection and the need for particular kinds of input. It might be that individual interviews can inform useful case studies or that a focus group will let everyone discuss their experiences.

Consider too the capacity of those who you are hoping to gather data from. For example, you may be better waiting until after the exam period to collect data from teaching staff.

It is important to choose methods that are realistic and that will be possible within the parameters of working with your target population. Remember not every approach will be suitable for every group. Large scale quantitative data might be easy for a large institution to collect whereas a smaller department might struggle to get enough responses for that approach to be valid. Often a mixed method approach can be best as it allows for an overview as well as more detail.

Certain groups may also have different accessibility needs. Ensure that data collection takes these into account and provides accessible options for providing information.

For example, an online survey may need to have adjustments in place for those who are visually impaired. Some staff may not be desk-based or have easy access to IT and so may need access to paper surveys rather than online ones.

Ethics and data protection

Be communicative and clear about your data collection with those who are taking part in it. Informed consent is important and those taking part in data collection and providing information need to know what the data is being used for and how it is being protected.

Data collection must adhere to data protection regulations throughout the entire process of collection, analysis and storage. You can find further information on data protection in relation to Equality Charter applications here: https://www.advance-he.ac.uk/sites/default/files/2020-04/19%20FAQ-on-Data-Protection-for-Charter-Applicants.pdf

Remember that data protection is not merely a tick box exercise, data can be a powerful thing and it is important to protect the people who are contributing it.

It might not be appropriate to collect data the same way if doing so across different campuses. Just because it might seem safe to ask about gender identity in one country doesn’t mean it is the same under every legal framework.

Consider confidentiality on a smaller scale too. For example, if working with a small team extra steps may need to be taken to ensure confidentiality such as employing external facilitators or making sure surveys ask questions in a way that ensures anonymity. Some methods may not be appropriate in this case, for example a faculty-run focus group might not be the best method as people may be nervous about speaking up in front of their peers. 

Evaluating Data Collection

It can be useful to evaluate your data collection throughout the collection process. Ask yourself who is missing from the discussion. Are there voices that haven’t been heard yet?

The methods themselves may need to be reviewed:

  • Are the chosen methods letting everyone be heard?
  • Are they accessible to everyone?
  • Are they effective and reliable?

Data collection is a process and it might need to be undertaken differently at different stages. Communicate with those who are contributing information and consult with them on whether the chosen methods of data collection are working for them.

In many instances there may need to be a mixed method approach. Consider follow-up interviews or focus groups after surveys. This will enrich the data and give a much broader view.

Analysing Data

An initial cursory analysis of your data will hopefully give you an overview of the context of equalities in your institution. Look for obvious trends and patterns. If more longitudinal data is available, then it can be helpful to look at areas of change and how the patterns of data have evolved over time.

Do not stop there, however. It is often not simply enough to offer an overview when a more complex analysis is needed. A deeper analysis will reveal more about the nuances of equalities and it is important to approach your data with a critical lens.

For example, an initial analysis might show that fewer women hold senior positions. However, it might not be initially clear why this is the case. Asking what findings might mean or why they might be the case leads to a more critical and complex exploration of issues. In this instance, data might also show that women more commonly have complex caring responsibilities. This might be obvious if there is a question about caring responsibilities, however this might also be implied by the individual indicating that they cannot be on campus during certain hours or that they must commit to working from home a lot.

If there is a “why” with no answer, then this is where follow up data collection may need to occur. As we discussed previously it is useful to plan for multiple layers of data collection. It might be that a topic or a voice was missing from the initial data collection and this can be addressed by doing a follow-up interview or a second survey.

You may find the Dealing with Data Athena Swan webinar helpful (though applicants should note that this webinar was recorded prior to the transformation of the Charter in the UK so some details relate to the May 2015 Charter): Athena Swan and dealing with data - webinar recording | Advance HE (advance-he.ac.uk). Additionally, more information on analysing qualitative data in particular can be found here: https://www.advance-he.ac.uk/knowledge-hub/analysing-qualitative-data

Be aware of the limitations of your own abilities with data analysis. If this isn’t an area you are confident in you may wish to bring in a colleague to help analyse the data.

Continuing Data Collection

Ongoing data collection is important to assess the impact of interventions. While you might be initially collecting data to inform an Athena Swan application it is important to look to the future with your data collection. Is this data collection replicable if it needs to be revisited? Can follow-ups be put in place to assess the impact of any changes? Is the data being used to inform changes effectively?

The purpose of data collection is to inform change and ongoing work on equalities. Continued data collection will allow the success of this to be measured. More information on monitoring and evaluating your impact can be found here: https://www.advance-he.ac.uk/knowledge-hub/monitoring-and-evaluating-impact

It is also important to revisit equality issues regularly as the population and their needs may have changed.

For more information and other resources on using equalities data and evidence, please see: https://www.advance-he.ac.uk/guidance/equality-diversity-and-inclusion/using-data-and-evidence