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Guidance

Diversity monitoring


Whether you’re collecting service user/customer information or recruiting staff, our guide to diversity monitoring and data collection will help.

Devon has diverse communities. It may not appear diverse when compared with other parts of the country but that does not mean that diversity does not exist – it’s just in smaller numbers or more spread out across our large, rural county. Those who are in minority groups may experience isolation, ‘invisibility’ and exclusion and it’s therefore important we take notice of their experiences and needs.

Monitoring diversity has many benefits – knowing we have reached a range of people and have obtained a cross-section of views; knowing we have a workforce that reflects the community it serves so that needs are understood and met; knowing whether certain groups experience barriers because policies and practices have been developed with ‘the majority’ in mind.

There are many studies which show that bringing together a wide range of people with different backgrounds, characteristics and experiences is beneficial for innovation and improvement. This is why diversity should be celebrated, but also information about diversity is collected and monitored so that we can evidence that we have reached, listened to, reflected, and removed barriers for everyone.

‘Equality and diversity monitoring’ is where anonymous data collected about people is analysed to look for differences between groupings. Where gaps are identified, this can help us explore the issue further and develop strategies and target resources to close the gaps and reduce inequalities. For example, health inequalities are identified through data collection and monitoring such as looking at life expectancy between men and women, local areas, ethnic groups, disabled and non-disabled people. In education, we will look for differences in achievement for SEN children, boys and girls, for example. We can only do this by collecting data about people.

We may also need to collect ‘personal information’ (not anonymous) in order to correspond with people or understand their needs or eligibility so that an appropriate service is provided to them.

However, in decision-making processes such as employment recruitment and selection, it is best practice to put all personal information in a section that can be separated – and is visibly separate – so that decision-makers do not have access to it. This is because personal information may influence the decision-making processes through ‘unconscious bias’. Unconscious bias is where we make judgements and assumptions about people based on previous experience and stereotypes. An example of a stereotype is that women make better carers than men.

 

 

 


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