Data Analytics

### Excel Modelling and Individual Report – The University of Puddletown’s Students’ Union Shop

Description of the assignment:

Background

(Any similarities to the student shop at the University of Hertfordshire are entirely coincidental. This is a fictional example.)

The Students’ Union Shop is trying to work out how many cashiers it needs to employ in order to provide an adequate service level. Customers at the shop line up in a single queue and are called forward to pay for their purchases when a till becomes free. To help determine the busy times of the day, the shop has recorded the number of customers arriving at the tills in each 5-minute interval during the shop’s opening hours, from 8am until 6pm (N.B. this is the number who actually make a purchase and does not include customers who are just browsing). Records for a period of 5 weeks are available. All the data were collected during term time.

The shop usually functions with just three cashiers but it has the capacity to support up to 6. The shop is open for approximately 50 weeks each year. The management has also collected data about the time it takes for cashiers to take payment. These data come from term time and 1000 records are available. Management are concerned that customers wishing to buy food, in particular, may be going to other outlets within the university such as the Big Ears Sandwich Shop or the Noddy Bar. Management are also concerned about the turnover of their staff and would like to reduce their stress and also stop them getting bored. They would be interested to hear about any innovative operating strategies for doing this.

You are employed as a consultant for the Students’ Union Shop. The shop management would like to hear insights from you, but does have a few specific questions they would like to ask. These are

• What is the average customer arrival rate per hour based on the current data?
• The management reckons there are more customers during the lunch break, and would like you to look into this matter. Could you spot any busier period during the day? If so, what are the busier hours?
• What is the average customer arrival rate per hour during busier period?
• What is the average customer arrival rate per hour during quieter period?
• How fast on average does a cashier serve a customer in our shop?
• Have you spotted any outlier in the collected service data? If yes, did you include (or exclude) those outliers when coming up the average, and why?
• How many cashiers does the shop need to have a reasonable performance?
• When taking the average daily arrival? Would you consider the average daily arrival a good measure for cashier arrangement, and why?
• During busier period if observed?
• During quieter period if observed?

The shop management is also interested in hearing your thoughts on how the adoption of business analytics in general could positively impact the shop performance. (For students who participant in the Young Enterprise competition AND wish to work this part in their YE group, please see alternative arrangement here.) They would appreciate that you keep this part under 2 pages.