kraljic_quadrant assigns the Kraljic purchasing matrix quadrant based
on the attribute value score of x and y
kraljic_quadrant(x, y)
| x | Numeric vector of values |
|---|---|
| y | Numeric vector of values with compatible dimensions to |
A vector of the same length as x and y with the relevant
Kraljic quadrant name
SAVF_score for computing the exponential single attribute value
score for x and y
# Given the following \code{x} and \code{y} attribute values we can determine # which quadrant each product or service falls in: # to add a new variable while preserving existing data library(dplyr) psc2 <- psc %>% mutate(x_SAVF_score = SAVF_score(x_attribute, 1, 5, .653), y_SAVF_score = SAVF_score(y_attribute, 1, 10, .7)) psc2 %>% mutate(quadrant = kraljic_quadrant(x_SAVF_score, y_SAVF_score))#> # A tibble: 200 x 6 #> PSC x_attribute y_attribute x_SAVF_score y_SAVF_score quadrant #> <chr> <dbl> <dbl> <dbl> <dbl> <chr> #> 1 D233 3.01 4.84 0.7887459 0.9336977 Leverage #> 2 F352 4.34 5.64 0.9573299 0.9629164 Leverage #> 3 T713 3.37 4.30 0.8495938 0.9023958 Leverage #> 4 K833 2.67 5.53 0.7165401 0.9598009 Leverage #> 5 Q121 3.48 4.33 0.8655080 0.9044624 Leverage #> 6 C791 3.32 7.32 0.8419735 0.9898314 Leverage #> 7 Y207 3.48 5.42 0.8655080 0.9564360 Leverage #> 8 W439 2.47 3.35 0.6659448 0.8084720 Leverage #> 9 N290 1.66 4.02 0.3778582 0.8808636 Strategic #> 10 C251 1.00 7.47 0.0000000 0.9910284 Strategic #> # ... with 190 more rows