What to think about when getting data to measure performance of your back office
The first and most obvious consideration is why do you want the data and what are you going to do with it? There can be many valid reasons for measuring performance of the back office, for example:
Baseline – to document performance levels now, so you can see how they change once some improvement initiative has been implemented.
Inform – to target where to deploy different types of improvement initiatives. Which activities are consuming enough time to deliver a payback from an RPA project? Where should we focus retraining?
Sourcing – to change where the work is done, or whether it’s best done internally or with a 3rd party service provider.
Compare – understand the variation of performance between individuals, teams, units?
Account – to work out how much it costs to produce different units of output?
Optimise – to deliver better outcomes by improving the management (through better decision making) of the operation.