The resource frequency metric allows the computation of the number/frequency of resources at the levels of log, case, activity, resource, and resource-activity.
%>%
patients resource_frequency("resource")
## # A tibble: 7 × 3
## employee absolute relative
## <fct> <int> <dbl>
## 1 r1 500 0.184
## 2 r2 500 0.184
## 3 r6 495 0.182
## 4 r7 492 0.181
## 5 r5 261 0.0959
## 6 r3 237 0.0871
## 7 r4 236 0.0867
Resource involvement refers to the notion of the number of cases in which a resource is involved. It can be computed at levels case, resource, and resource-activity.
%>%
patients resource_involvement(level = "resource") %>% plot
It this example it shows that only r1 and r2 are involved in all cases, r6 and r7 are involved in most of the cases, while the others are only involved in half of the cases, more or less.
The resource specalization metric shows whether resources are specialized in certain activities or not. It can be calculated at the levels log, case, resource and activity.
%>%
patients resource_specialisation("resource")
## # A tibble: 7 × 3
## employee absolute relative
## <fct> <int> <dbl>
## 1 r1 1 0.143
## 2 r2 1 0.143
## 3 r3 1 0.143
## 4 r4 1 0.143
## 5 r5 1 0.143
## 6 r6 1 0.143
## 7 r7 1 0.143
In the simple patients event log, each resource is performing exactly one activity, and is therefore 100% specialized.
A handover-of-work network can be created with the
resource_map
function. It has the same arguments as the
process_map
function.
%>%
patients resource_map()
A more compact representation of hand-over-of-work is given by the
resource_matrix
function, which works the same as the
process matrix
functions.
%>%
patients resource_matrix() %>%
plot()
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