When external data returns demand data that institutions don’t routinely capture then processes need to be put in place to harvest the relevant data items. Costs can be minimised by expanding existing data capture processes (eg a student registration process) but sometimes new processes need to be established.
There are two types of burden in these cases – one to define and set up the new processes and the on-going burden of operating them.
These cases include situations where external demands necessitate a change to existing data capture – for example collecting more granular information for external reporting than the institution requires for its own needs.
There are two perspectives on the assesment of burden in this area. First is the difference between the external data demand and the scope and detail of the data that the institution is collecting for its own administrative and analytical purposes; there is a significant random element to this perspective.
Second is the idea that operating additional processes to capture data has a linear cost according to the number of records (students, staff etc) that are in scope of the requirement; this perspective suggests a cost that directly correlates to the size of the institution.
Data quality assurance
Every institution will work to ensure that the quality of their data is fir for their own purposes – administrative and analytical. If the external data return demands a level of quality that goes beyond this level then additional quality processes need to be established.
Again the assessment of burden here can be seen as directly related to the size of the institution while the difference between the BAU activities and the external demands introduces a significant random element to the assessment.