Cost versus urgency
The dataset vacancies_impact we just created contains the total_cost and cost_impact for each case, but it also contains a data attribute urgency, which indicates whether the vacancy is urgent (urgency == 10) or not (urgency == 1). Use dplyr's case_when() to create the variable cost_profile, which indicates whether costs where incurred appropriately:
- Disproportionate if cost_impact == High and urgency less than 7
- Excessive if cost_impact == Medium, and urgency less than 5
- Lacking if cost_impact == Low and urgency is greater than 6
- Appropriate otherwise
This exercise is part of the course
Business Process Analytics in R
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Create cost_profile
vacancies_profile <- vacancies_impact %>%
mutate(
cost_profile = case_when(
cost_impact == "High" & urgency < 7 ~ "Disproportionate",
___
___
TRUE ~ "Appropriate"
)
)