IBM employs a network of expert analytics consultants for various projects. To help it determine how to distribute its bonuses, IBM wants to form groups of employees with similar performance according to key performance metrics.

Each observation (corresponding to an employee) in the file ibm consists of values for UsageRate which corresponds to the proportion of time that the employee has been actively working on high-priority projects, Recognition which is the number of projects for which the employee was specifically requested, and Leader which is the number of projects on which the employee has served as project leader. Apply k-means clustering with values of k = 2 to 8.

Standardize the values of the input variables to adjust for the different magnitudes of the variables.

How many clusters do you recommend for categorizing the employees? Why?