Workforce data was provided in the form of an ESR extract, and activity data was given by location and named staff member who effected the activity in a particular location.

This presented a challenge in that staff did not neatly sit in a cost centre where their activity was recorded. In fact their activity was often across service types and in multiple locations

In order to align the data in the correct way, the wrapt team created entirely new cost centres that contained both the location of the activity and the type of activity done. i.e. whether it was community activity that was recorded in sessions, or private activity that was recorded in “Units of Dental Activity” (UDA’s).

By looking at the amount of activity each person did, it was then possible to understand how much of their WTE was spend in the new “costs centres” and adjust the workforce data set accordingly.

The resulting data sets provided the basis for driver creation by using the same proportional spilt of each staff members time between the locations and activity types in the same way that the cost centres had been created.

This data was then uploaded into the tool and presented back to the dental management team.

Despite high levels engagement and enthusiasm from the management team, analysis of the final model did not meet the needs of the team at this time due to the need to account for the complex interdependent relationships between the dental team operatives.

The WRaPT tool applies a linear relationship to activity. It assumes that each team member independently performs an amount of the activity attributed to their team, this principle cannot be applied to dental services.

This case study prompted research into additional model development that will enable the tool to define dependencies between team members in completing particular activities.