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A call centre has been experiencing significant challenges in their current operations and profits. In order to understand their current annual profit projects, they would like to call on your help developing a Monte Carlo simulation.

The call centre sells insurance policies to customers who call in due to referral incentives spurred on from existing clients. Currently, they have 100 call consultants employed.

For the entire year, call volumes are normally distributed with a mean of 580 calls with a standard deviation of 11. At any time in the day, call consultants are available to accept calls. Each consultant has an equal probability of being able to take between 20 and 45 calls per day.

Server costs are incurred each day. For every call consultant (available or not), they are charged R1 000 for 10 or less consultants, R5 000 between 11 and 100, and R15 000 for more than 100 consultants. They would like this included in the simulation since other franchise stores vary.

There is an 80% chance that each call will be successful and a customer would want a policy. Each policy is sold for R75. This is also dependent on whether there is sufficient call consultant availability for the call volumes each day. Also, the company pays each consultant R300 each day.

3.1.1 Write a Monte Carlo function in R, simulating a year by calculating the average total profit of this call centre. Assume a constant of 100 call consultants, working all 365 days in the year. When creating your code, also plot each respective cost for the last year simulated. Use the readline command to prompt for the number of MC iterations that need to be evaluated. Insert the R code in the space below and submit an R Script using the naming convention:

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