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What can we do with data?

Data alone tells you nothing. It’s all about what you do with it

Data shows you where you are. It enables you to prove that you have reached a particular position. Often it’s the distance you have traveled to reach that position that is more interesting that the data itself – and to be able to show this, you need to be able to compare data.

Comparing data

You might want to compare it with your previous data – you might have set a benchmark in relation to the percentage of your staff that define themselves as BME. By comparing against this benchmark, you can see if any new initiatives are impacting upon this – now that you have widened where you advertise, is it going up?

You might want to compare it with local or regional Census information ( How does your staff or participants data match the data available for your area. Are there any groups within your geographical area that you have not managed to tap into?

You might want to compare it with appropriate comparative data - perhaps with the results of other organisations, or with the results from relevant local authorities, against a national benchmark or standard. You could match it against national Labour forces surveys for a particular grade or type of job ( How do your results compare? Are you leading the field or tagging along behind?

Analysis of data

Comparisons should not just be about the numbers of people in positions or groups, it should be about the experiences of people. How do the experiences of different groups of people differ? Are there trends?

In relation to recruitment you can look at who was interested, who applied, who was shortlisted but not selected, not just who got the job.

For staff, you can look at the length of service, time and scale of training or promotion, the position and job level reached and so on. You can look not just at statistics, but at evidence from exit interviews, from staff appraisals, from staff surveys.

For participants and audiences, you can look at frequency of attendance. Can you ask have they been before, would they come again? If they were involved in a project, can you tell if they have been involved before, or whether they dropped out early, or if their attendance fluctuated?

The reason for analysising data is to help you uncover information that will help you identify unwitting barriers/blocks in what you do. If you find that a specific group is missing from your audience, you then need to try and find out why. If disabled people aren’t applying for jobs in your organisation, why is this?

The data alone doesn’t tell you what you need to do, but it can help identify priorities for action.

Don’t start by looking at what and how you can capture data… start with what you want the data to show you/tell you, and then work back from this - how can you get the data you need