CammBA$51.$E$\mathrm{.}009.$

A supermarket has been experiencing long lines during peak periods of the day. The problem is noticeably worse on certain days of the week, and the peak periods are sometimes different according to the day of the week. There are usually enough workers on the job to open all checkout lanes. The difficulty for store managers is knowing when to call some of the workers stocking shelves up to the front of the store to work the checkout lanes.

$($a$)$

How could analytics be used to help the supermarket?

A predictive model could be created to estimate the expected number of shoppers and how long they are expected to shop for any given day of the week and time of day. This model could be used to know when more checkout workers are necessary to prevent long lines.A data dashboard could be created to keep track of how many customers each employee is able to check out each day. The company should then only ever assign the highest performing employees to the checkout lanes.$$A prescriptive model could be created to tell the supermarket how many additional checkout lanes should be built in order to prevent lines from becoming too long.A data dashboard could be created to keep track of the daily maximum line length. If the line length extends past a certain threshold one day, the supermarket can assign more workers to the checkout lanes during the next day.

$($b$)$

What data would be needed to implement the plan in part $($a$)?($Select all that apply.$)$

the total number of employeesthe total number of checkout lanes available each dayhow long each person shops before checking outhow long each employee takes to check out a customerthe number of people entering the store each day and the times at which they enter