INE4206 - Service Operations Management Mini Project Example

Consider a large retail store at a major shopping district. The store is managed by a store manager and his or her salaried staff. Each month the store manager receives sales and profitability targets from corporate headquarters, but each store manager uses his or her own experience and intiution to decide how to manage store processes.

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The store carries a wide range of brand-named and private-label clothing, accessories, shoes, cosmetics and home furnishings. The store is employing about 150 hourly sales personnel.

Sales personnel are classified based on their experience and expected conversion rates

(probability that a visiting customer will turn into a transaction). Junior sales personnel are paid $8 per hour and they are expected a 20% conversion rate, and senior sales personnel are paid $10 per hour and they are expected a 30% conversion rate. A junior sales personnel spends on average 15 minutes per customer and a senior sales personnel spends on average 10 minutes per customer. If a customer is not assisted because all sales personnel are busy then the conversion rate is 10%. Each transaction is expected to be worth $100. Out of 150 sales personnel about 100 are junior and 50 are senior.

In a typical day, the first shift of sales personnel arrives at 9:50 a.m., 10 minutes before store openning, to open their registers. Their day begin with a meeting with their sales manager where they discuss sales targets, promotions, etc. During the day, they assist customers and organize the mechandise in their sales areas. Since the traffic varies greatly during the day

the store uses the following shift rules:

Shift 1: from 10:00 to 14:00

Shift 2: from 12:00 to 16:00

Shift 3: from 14:00 to 18:00

Shift 4: from 16:00 to 20:00

Shift 5: from 18:00 to 22:00

The store manager decides on the number of junior and senior sales personnel for each shift each day of the week. His or her main goal is to maximize the expected profit while not violating the capacity constraints for the total number of personnel. In doing so, the store manager analyzes the historical sales data. Mini Project.xls file displays the historical data about the number of visiting customers to the store for each day of the week during 12 weeks.

Given the information above and the data in Mini Project.xls file, and by using Industrial Engineering skills and knowledge, solve the store manager's problem. Write a short report (including any excel file) that shows your analysis, solution methodology and results. You may also prepare a powerpoint presentation for the management.

Answer

All the detailed calculations are shown in Excel file.

First we need to know the dynamics of the visits to our store. According to the source data was plotted. As you can see, our store buyers attend with approximately the same frequency.

We construct a model by which we recognize our revenues, costs and the required number of employees in the change.

We need the staff are determined through the unknown x1 and x2

StuffSeniorJuniorX1 X2

Number of people who have been served by the staff:

served byserved by Senserved by JunSen+JunOtherKh1* servering time Kh1* servering time Visitors minus the number of personnel served

We determine how much money we will have to pay staff for an hour of their work.

CostsSenJunTotalX1*wage X2*wage

140,00 240,00 380,00

We determine what amount is likely to be done deals.

SalesSenJunPassiveTotalConversion*served by seniors*average check Conversion*served by juniors*average check Conversion*served by none*average check

2520,00 2400,00 60,00 4980,00

and we count our revenues

ProfitTotalSales-costs

For clarity, we create a summary table of the number of visitors.

With PivotTable We expect the average number of visitors every day of the week and at any time.

With the search for solutions, we find the necessary number of personnel for each day in each period.

We see that we always need to have a change of 50 seniors and a different number of juniors.

Having the required number of staff per hour, we can group it in shifts. For convenience, all shifts other than the first will be 2 hours.

Official DayTimeOur10-14 FridayShift 1 10-13

12-16 Shift 2 13-15

14-18 Shift 3 15-17

16-20 Shift 4 17-19

18-22 Shift 5 19-21

We summarize the average number of visitors to each shift and determine how much staff we need for maintenance.

We can also schedule the maximum number of staff and with the average, but then there is the risk of losing customers. As we can see, they are slightly different.

Timetable maxmiddleDayTimeSeniorJuniorSeniorJuniorSundayShift 1 50 100 17 33

Shift 2 50 100 50 100

Shift 3 50 100 50 100

Shift 4 50 100 50 100

Shift 5 0 0 0 0

MondayShift 1 50 96 50 32

Shift 2 50 100 50 83

Shift 3 50 100 50 80

Shift 4 50 100 50 69

Shift 5 50 76 50 38

TuesdayShift 1 50 32 46 11

Shift 2 50 73 50 37

Shift 3 50 71 50 36

Shift 4 50 97 50 49

Shift 5 50 80 50 40

WednesdayShift 1 50 55 48 18

Shift 2 50 100 50 52

Shift 3 50 95 50 48

Shift 4 50 100 50 64

Shift 5 50 93 50 47

ThursdayShift 1 50 100 50 40

Shift 2 50 100 50 73

Shift 3 50 100 50 71

Shift 4 50 100 50 86

Shift 5 50 100 50 83

FridayShift 1 50 100 50 63

Shift 2 50 100 50 100

Shift 3 50 100 50 100

Shift 4 50 100 50 100

Shift 5 50 100 50 100

SaturdayShift 1 50 100 50 90

Shift 2 50 100 50 100

Shift 3 50 100 50 100

Shift 4 50 100 50 100

Shift 5 50 100 50 100

When comparing income graphics with a maximum load and schedule with the average, it was found that when setting the schedule of load average, we lose about 178 thousand profit (sheet chek timet middle in T41 .

Ie, more profitable to pay staff for the "simple", than to lose customers.