A key part of providing services to members of the public is the amount of information you need to collect. If you’re like most of the organisations that we work with then it is likely that the types of information you collect has grown over time and is now fairly comprehensive.
It’s probably an odd point of view from a company that supports organisations to measure impact but we think you collect too much data.
When we work with organisations we challenge them to carry out a systematic audit of all of the data that is collected in order to test it against two questions: –
Why do we collect it?
What do we do with it?
For many organisations the why is a really interesting question. There are a number of reasons why organisations collect data, because funders require it, because it ensures that services that are provided are safe and even because somebody feels that at some point the data will be useful.
Collecting too much data poses two practical risks to an organisation. Increasing the amount of data collect reduces compliance with the data collection process, the more data you collect the lower the quality of that data is likely to be. A common complaint that we help organisations manage is that data collection is intruding on the provision of service with little obvious benefit.
Equally an increase in the amount of data collected is likely to increase the chances that the data is collected in an inconsistent manner. Inconsistency in data collection reduces the confidence you can have in reporting.
Inconsistency can be mitigated through rigid data collection but this assumes that an organisation can anticipate all of the people they are likely to provide services to. Few organisations are able to predict this over significant time periods.
We believe that organisations should approach data collection from the other end by first focussing on what data is needed for. For example does it inform business planning? Does it help to maintain contracts? Does it help you to provide a safer service by being able to audit all interaction with a client?
By setting out the final reporting needs of the data you collect you begin to identify the most vital elements to the organisation. We recommend a detailed audit of all the data you collect to test it for relevance, purpose and balance.
The relevance and purpose of data operate hand in hand. You need to have a clear idea of the purpose of collecting a piece of data, for example does it go into a report? Who reads that report? Do they act on it? You also need to be clear on the relevance to your organisation.
A good example of examining relevance can be seen in collecting demographic data. There is a temptation to collect all aspects of demographic data but if you have a largely homogenous client group then there is little point in this. Conversely if you’re not using demographic data to inform how you shape services for vulnerable groups then there is little point in collecting it.
In terms of data balance, we ask organisations to consider the balance between data types in their overall data set.
Examples of different types of data are:-
- Identifiable data – data that helps you identify an individual. For example name, address, gender and date of birth.
- Demographic data – data that shows the protected characteristics of the people you work with have. This would include, ethnicity, disability and sexuality.
- Outcome data – the measures that demonstrate the outcomes that people have. This would include an assessment of the client and then a similar measure at points of time during contact with the client.
- Functional data – the data the outlines the activity that has happened with a client. Frequently these are the notes that can be used to identify the amount of work that has been done with an individual.
- Contract data – data you are required to record for funding bodies.
We believe by having an audited, evidence based approach to collecting data you are in a better position to begin having a conversation with funding bodies on the data you can already supply. A good balance of outcomes, activity and protected characteristics should fulfil all of the needs of contract data.
As part of the process to audit data we help organisations to list each element of data, identify it’s data type and define the purpose. This makes up a data schema that can be presented to funders in order to shape the conversation about how and why data is collected.
If you’d like to see what we can do to help you reduce data collection, get in touch.