APPLICATION OF 6-SIGMA FOR SERVICE IMPROVEMENT-AT INTERNATIONAL MANAGEMENT INSTITUTE CANTEEN

APPLICATION OF 6-SIGMA FOR SERVICE IMPROVEMENTAT INTERNATIONAL MANAGEMENT INSTITUTE CANTEEN

ACKNOWLEDGEMENT

We hereby regard our sincere thanks to Prof. XYZ , under whose guidance this project was undertaken.

We sincerely acknowledge the canteen staff, International Management Institute for their valuable assistance throughout the production of this project.

We would like to thank our friends for their generous support and the respondents who gave their valuable piece of time for participating in the survey to complete the study.

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Table of Content Table of Content.....................................................................................................................3 Executive Summary..........................................................................................................................4 1 Overview: Project Selection............................................................................................................5 1.1 Background Information......................................................................................................5 1.2 Problems and its Symptoms.................................................................................................5 Define................................................................................................................................................7 1.3 Goals and Expected Results.................................................................................................7 1.4 Framework...........................................................................................................................7 ...........................................................................................................................................................8 1.5 Assumptions.......................................................................................................................10 1.6 Constraints..........................................................................................................................10 1.7 Variables.............................................................................................................................10 2 Measurement.................................................................................................................................11 2.1 Time-Motion Study............................................................................................................11 2.2 Revised Process Diagram...................................................................................................11 2.3 Questionnaire.....................................................................................................................13 3 Analyze..........................................................................................................................................16 3.1 Cause and Effect................................................................................................................16 3.2 Correlation & Pareto..........................................................................................................17 4 Improvement.................................................................................................................................19 4.1 Design of Experiment........................................................................................................19 4.2 Simulation..........................................................................................................................23 5 Conclusion & Outlook..................................................................................................................27 Appendix A: Questionnaire.............................................................................................................29 Appendix B: DOE results................................................................................................................30

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Executive Summary 6-sigma is a powerful tool to detect errors within a process regardless whether it is a manufacturing process or service process. We applied the 6sigma Methodology with its roadmap DMAIC (Define – Measure – Analyze – Improve – Control) on the serving process of the IMI canteen in order to reduce the service time per customer and therefore the waiting time.

During the define step we drew our project scope, specified our goal concerning the improvements we want to make and made assumptions concerning the process. A CTQ tree and a rough process diagram were drawn to illustrate the process understanding. Constraints were set limit the range of the task and Variables (decision and dependency) were defined to give additional insight into the whole field of the project.

The measurement step contains a time-motion study of the service process at the canteen and a revised and improved process diagram with times measured for each single action. Furthermore a questionnaire was designed in order to find out more about the average number of ingredients ordered by students and their satisfaction with the present situation concerning waiting time and serving time. In addition to that suggestions were collected to find out the factors that need to be changed in order to achieve a higher customer satisfaction.

The analyze step deals with a cause and effect diagram to find many factors that might have an influence on the output – the long waiting time.

After a qualitative selection of the most important ones a correlation matrix helped to find an order of the main factors and their importance.

In the Improvement stage a DOE was conducted to reveal the impact of those factors which are considered as the most important in a process.

Simulation was done using data from the measurement phase provided additional data for another DOE to test the other factors

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1 Overview: Project Selection 1.1 Background Information International Management Institute is one of the premier management institutes situated in New Delhi. Apart from the state of the art facilities available for students in areas of academics as well as round about performance the Institute has a state of the art canteen facility located just at the heart of the facility. Students round the globe are a part of this prestigious organization. With over a thousand students including faculty and service staff available at the campus premise round the clock, there is much space for improvement for the service systems in our campus. In this research project, DMAIC (Define – Measure – Analyze – Improve - Control), the implementation steps for 6-sigma Projects are followed to analyze and improve the service quality of the IMI Canteen.

Quality especially service quality is a crucial factor in the fast growing modern India. 6-sigma is in the large bunch of the quality management methods and it is very popular nowadays. 6-sigma can help to improve the service process. The term 6-sigma is based on a statistical measure that equals to 3.4 or fewer errors of defects per million opportunities. 6-sigma can be described as a business improvement approach that seeks to find and eliminate causes of defects and errors in manufacturing and services process by focusing on outputs that are critical to customers.

6-sigma provides a blueprint for implementation of total quality system.

Its roadmap – DMAIC (Define-Measure-Analyze-Improve-Control) means: Define the problem of the process; Measure the performance of the process; Analyze the cause if the process, Improve the process, reduce waste; Control the process, eliminate the occurrence of the same problem.

1.2 Problems and its Symptoms A significant phenomenon in our campus is the long queues in the canteen during the rush hour (i.e. after-class hours). For example, the average time for a student from joining a queue to getting the food in the IMI canteen is about 10 minutes, while the minutes for enjoying this meal are just 15! Thus the waiting (or wasted) time takes 40% of the whole time of a student in the canteen (Figure 1)

5

Unit: minute

10 15

Eating Waiting

Figure 1-1: Composition of time spent in IMI canteen

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Define 1.3 Goals and Expected Results The 6-sigma team aims at reduce the total waiting time to 7 minutes or less and remain the same level of customer satisfaction. The critical-to-quality (CTQ) tree is shown in figure 2. There are 3 CTQs: diversity, waiting time and serving time. And the diversity is required to be high, while the others are required to be low.

Figure 2-1: CTQ flow down for IMI service process

1.4 Framework Figure 3 shows the SIPOC framework of our project and the scope of improvements

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Input: Ingredients

Canteen Serving Process

Output

Customer : Students

supplier

Staff & Refectory

Figure 2-2: SIPOC framework

Our scope of work focuses on the IMI canteen serving process and the related output. We do not consider the complete input and output of the process. Within the scope is furthermore the staff of the canteen. A rough process diagram (Figure 4) helps to illustrate the general idea of the serving process at IMI canteen. As one can see the ‘Store’ does not lie within the red line and is therefore not part of the project scope. We focus on the interaction between ‘Students’ and ‘Staff’ which embodies the service process.

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Figure 2-3: IMI Canteen serving process & the project scope

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1.5 Assumptions The queue of waiting for service is G/G/2, and the distribution of interarrival and service time will be further studies and assigned in our simulation.

This is in accordance with the fact of the IMI canteen.

The patience of customers in the queue is unlimited and they will not leave until they get the service. This is generally correct since the waiting people rarely leave the queue before get the service at the IMI Canteen.

The queue follows First-Come-First-Serve (FCFS) criterion. It is true since the IMI queue hardly has queue jumpers.

The amount of spice is infinite. It is almost true since the usage of spice is little and it almost needs no replenishment during the process of service.

1.6 Constraints There are some fixed parameters in the canteen which is difficult or impossible for the 6-sigma team to change and is considered as constraints: Total number of cook units is 6 in the IMI canteen.

Total number of front staffs is 2 in the IMI canteen.

Total room space of the IMI canteen is a constraint and cannot be modified.

Although the proportion of ingredients (vegetables, meat, and rice etc) can be changed, the amount remains constant due to the limited inventory space.

1.7 Variables The variables are divided into 2 categories: decision variables, which can be decided by the 6-sigma team, and dependency variables, or outputs, which are directly or indirectly determined by the decision variables

1.7.1 Decision Variables The decision variables are: the process itself, proportion of ingredients and the layout.

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1.7.2 Dependency Variables As mentioned before in section 1.3, the dependency variables for our evaluation are: average / maximum waiting time, average / maximum queue length, cost, and some subjective factors such as satisfaction of students

2 Measurement 2.1 Time-Motion Study Given on the 1st version of the process diagram we did time motion study of the serving process of the IMI canteen. We intended to determine the time for the single actions the cooking operator needed from the beginning of taking the order over the cooking process till the end of the process the handing over of the finished dish.

We did time-motion study to provide an authentic working condition and without manipulation concerning motivation or anything else which might have affected the outcome

2.2 Revised Process Diagram The analysis of the procedures shown in the time-motion study made us redraw the process diagram. From the time-motion study we could determine the times needed for each action step during the whole service process. Our observations from the new process diagram with process times were: This process contains a lot of branches and therefore is has a lack of standardizations; Much time is spent in the region between input two and output two of the operation sub process; "Replenish sub process" takes almost 1 minute. Proper configuration of the ingredients in front to reduce the frequency of replenishment, the total efficiency will improve a lot.

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Figure 3-1: Process diagram version 2, 1/3

Figure 3-2: Process diagram version 2, 2/3

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Figure 3-3: Process diagram version 2, 3/3

2.3 Questionnaire

2.3.1 Questionnaire Design We designed a survey distributed among random students who came to the IMI Canteen on the Feb 11th 2009. Altogether we handed out 50 sheets of questionnaires and among those 47 valid returned back to us.

The questionnaire contained the questions involving the frequency to have meal & time taken, number of ingredient ordered, perception of queue length, waiting time and satisfaction, etc. Concrete questions can be found in (Appendix A). The aim of this survey was to detect the customers’ demand towards possible service improvement in process and their satisfaction regarding the waiting / queering time The questionnaire contained the listed questions. The aim of this survey was to detect the customers’ demand towards possible service improvement in canteen process, parameters related to customers (for modeling) and their satisfaction regarding the waiting / queering time.

2.3.2 Statistical Results From the questionnaire there are some conclusions: Most people (73%) will not give up queueing even if the queue is longer than 2 windows, and 1/3 of the people will never give up (Figure 8). So in our 13

model, we added an assumption that servers are always busy.

Figure 3-4: Acceptable queue length

Another main findings from the statistical result of the survey is the fact that in average the students are not satisfied (Figure 9) with service and waiting time at the IMI canteen.

Figure 3-5: Dissatisfaction level Note:

If we give the “dissatisfaction� levels some weight: 14

No 0 Little 1 Dissatisfied 3 Very Angry 9 Then we can get the average dissatisfaction level of 3.563

There are also some improvements regarding the serving time as suggested by the customer themselves, Figure 10 gives number of the suggestions by categories.

Figure 3-6: Customers' suggestions for further Improvements

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3 Analyze Now we know that customers want to be served faster. This will automatically lead to higher satisfaction level among students and will reduce the overall queuing time for everybody.

The next step will be to gather a high quantity of reasons which causes that long waiting / serving time.

3.1 Cause and Effect A fishbone chart, also called ‘Cause and Effect’ diagram, is helpful to brain storming many reasons that can lead to an outcome and is the first step to identify the key-reason and most crucial factors that have the highest influence on the outcome.

Figure 4-1: Cause and Effect Diagram

Since it is a service process and not a manufacturing process the 5 P’s are uses instead of the 5 M’s. The main outcome is ‘long waiting time’ which is caused by 5 major symptoms and each has several reasons or causes itself.

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3.2 Correlation & Pareto After the Selection of the most crucial factors from the Cause and Effect Diagram a correlation analysis of these main causes was mode. After serious consideration, some factors were not taken into further consideration since it is not possible or hardly possible to change the factors in order to achieve improvements. The analytic hierarchy process (AHP) method is used to determine the weight of those causes (Figure 12), excluding some reasons that cannot be further improved.

Figure 4-2 AHP result of weight of causes

From the weight above a Pareto-chart is drawn to illustrate the crucial factor to concentrate on during further project process.

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Pareto Chart for Causes 1.000

1

0.9007 0.8085

Importance

0.8

0.6836

0.6 0.4

0.5414

0.341 0.2004

0.2 0

0.1422

No std.

Layout

0.1249

Pos.of Many ingredient branches

0.0922

0.0587

Prop.of ingredient

Low space

0.0226 Fatigue

0.0176 Mood

Causes Figure 4-3 Pareto chart for causes

The accumulated weight of the main causes shows that a total of 5 main causes contribute over 90% of the whole amount of causes. So the 5 critical factors or reasons for a high waiting time at IMI Canteen are found now.

1. No standard 2. Process layout 3. Position of each single ingredient 4. Many branches in the actions and during process 5. Proportion of ingredients The first and fourth points are more related to psychological issues and can be further studied by design of experiments (DOE). Our efforts in improving the process time will concentrate on these 2 main causes. The other 3 are systematic factors and can be studied by modeling and simulation.

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4 Improvement 4.1 Design of Experiment

4.1.1 Introduction This DOE should find out about the influence of standardized patterns and branches on the actual working or process time. The primary objective of this design of experiment is to find the crucial factors that might change the process time of a task.

DOE is known as a structured, organized method for determining the relationship between factors that affect a process and the output of that process. After the experiment we want to use the Response Surface Methodology to find the optimum combination of factors that yields to a minimum working time.

Our objective is to find out how much standardized actions and branches contribute to the process time of a task (measured in seconds) and ultimately find a fitted model to best predict the final working time

4.1.2 Methodology

Figure 5-1 DOE Scene Layout

Figure 16 shows a general overview of the scene layout on which we conveyed our DOE. There are 9 tasks carried out during the DOE: 1 2 3 4 5 6

Walk to one side of the source Pick an item

Walk to center table

Put the item on the center table Walk to the other side of the source Pick an item

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7 8 9

Walk to center table

Put the item on the center table Next cycle, until all books is moved to center table

In order to investigate the influence of the factors we picked from the Pareto-chart analysis on the outcome of the DOE. The output of the DOE is the time needed to complete all the tasks under certain working conditions.

The Factors considered in the 23 experiment is as shown in Table 1 Table 5-1 Factors of DOE Factors

Level -

+

Branch

A

No branch

Has branch

Sequence (Std.)

B

Fixed order

Free Order

Unexpected tasks (Std.)

C

No

3

Description of factor A “-“: the person can use all books in source 1 and then use books in source 2. “+”: the person should use one book from 1 and then in the next cycle the person should use one book from 2, and then continue Description of factor B "-": the person should pick one book and then one piece of paper in a cycle "+": the person may either pick a book or paper first in each cycle, decided by random variable generator Description of factor C "-": no interruptions "+": when finish a cycle, the person may be interrupted by other things. After which cycle is decided by random variable generator. The total number of interruptions in one repeat (16 cycles) is 3

4.1.3 Results Table 5-2 Experiment results of DOE Factors

A

+

-

+

-

+

-

+

-

B

+

+

-

-

+

+

-

-

20

Result

C

+

+

+

+

-

-

-

-

Mean time

206.53

191.03

188.02

183.6

186.14

191.63

177.92

175.94

Using data from Table 2, the analyzing of factorial design and factorial plotting in MINITAB 15 are performed. Figure 5-2, 5-3 and 5-4 are the results

Figure 5-2 General analysis results from MINITAB

Figure 5-3 Main effects plot for process time

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Figure 5-4 Interaction Plot for Process Time

Figure 5-3 shows the main effects and indicates that the sequence order and the appearances of unexpected tasks have the main influence on the final process time. This confirms our findings from the Pareto-Chart where we identified those as critical factors that have the highest contribution towards a long process time and therefore leads to high waiting time in a service process.

Figure 5-2 and figure 5-4 underlines the high importance on focusing on the two factors ‘unexpected task’ and ‘sequence’ which both are requirements that stand for a standard process diagram where each action happens according to a given and predefined sequence.

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4.2 Simulation

Figure 5-5: Simulation Screenshot

The simulation is based on the process diagram version 2 and the results from the questionnaire. Some information like the number of ingredients is on the basis of the statistical result of the questionnaire and is defined as a random value within a certain range. Each type of ingredients has a probability to be selected. This probability will called selection probability. The simulation developed shows the complete process of the IMI canteen.

4.2.1 Time as Output The simulation provided data for another DOE. We picked the values which are randomized as new factors that influence the total serving time.

The factors are: Factor A: Capacity of the basket “-“: all is set to 30 “+”: ingredients with high demand are set to 40, the others are set to 20 23

Factor B: Variance of Selection Probability “-“: the variance of selecting different ingredients remains small “+”: the variance of selecting different ingredients is high

Factor C: Ingredient Position “-“: the probability of selecting ingredients which has a high or low distance to each other is the same “+”: the probability of selecting ingredients which are closer to each other is higher

Using data from simulation the different random seed, we get different replication for our 23 factorial design. Figure 5-6, 5-7 and 5-8 are the results

Figure 5-6 General analysis results for simulation

Figure 5-7 Main effects plot

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Figure 5-8: Interaction Plot

The plots show that the factor position has the highest contribution towards the process time. The interaction and strong correlation of the factors should be taken into account since synchronized their changes all result in a higher process time.

However, p-value is too low, which implies that the unidentified block factors affecting service time are too many. Hence we turned to another indicator: number of finished orders.

4.2.2 Finished Orders as Output

Figure 5-9: Simulation DOE Results

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Figure 5-10: Main Effects Plot

Figure 5-11: Interaction Plot

We can see that all 3 factors have strong positive correlation with number of finished orders.

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5 Conclusion & Outlook 6-sigma was a useful method to identify the key factors of the service process. It could have a great effect on improving the service time.

Using 6-sigma roadmap DMAIC, refectory in general can raise their throughput and serve a higher number of customers than they do now which means that they can greatly raise their effectiveness and efficiency.

The major conclusions we drew were: 1. Fewer branches in the process make lower service time 2. Standardization of the tasks, especially fixed task performing order and fewer occurrences of unexpected tasks can give lower service time 3. The affection of position and proportion of ingredients is not significant on average service time.

4. However, there is integrated optimization so that the total number of finished orders in the given hours has a significant increase. In concrete, if the most demand ingredients are put at front and give more resource like capacity, total number of finished orders will increase. Moreover, the increasing will become more significant as the demands for different ingredients become more different.

It was not possible for us to match our defined goal. Though we think that the reduction of time is possible, but we cannot predict the queue length and therefore the waiting time since many factors are with the customer and the variation is too high to promise a certain level of service speed.

Our report does not include a control stage. We thought that it is not appropriate to use statistical control methods to see whether the service process is working well or not. Since variation that comes from the customer which has a great influence on the service time might lead to the conclusion that the process time is too high, though all improvements were already implemented.

Since the service quality is theoretically improved by 6-sigma more customer requirements can be met, but not all. The service still has some problems to deal with like the variety of customer group. The next step of improvement would be to take the popular ingredients into account and make re-arrangement of the ingredients according to their frequency of usage. By this it is not guaranteed that every process will be accelerated but though the average throughput-time will shortened and hence this will finally lead to a

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smaller queuing time. .

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Appendix A: Questionnaire The following questionnaire relates to the delay in time spent in serving food at International Management Institute canteen. Please fill in your responses to the below mentioned questions in the best of your knowledge.

1. How much time do you generally take to eat your Lunch/Dinner. ________________ 2. What time do you generally select to eat both at noon and at night? Mark your responses.

Noon 11:00 - 11:30 11:30 - 12:00 12:00 - 12:30 12:30 – 13:00

Night 17:00 – 17:30 17:30 – 18:00 18:00 – 18:30 18:30 – 19:00

3. How many vegetables generally can you select to eat at one time? ________________ 4. Say yes or no in the questions given below?

A I like to eat only hot meals……………………………….

B Waiting time in the canteen is too much and should be reduced……………

C During rush hours relevant arrangements should be made by the canteen staff to cater students…………………………..

D. Canteen facilities in terms of layout should be changed……………………

5. What do you think is your waiting time while standing in a queue to take your supper at IMI canteen? ________________ 6 Mark your responses by ranking them in ascending order with 1-Strongly agree, 2Definitely agree 3- Agree 4- Partially agree 5-Disagree?

A. Waiting time in the canteen is due to the congested process layout of the canteen.

B. Waiting time in the canteen is due to the position of ingredients kept on the table.

C. Waiting time is due to the proportion of ingredients D Waiting time in the canteen is due to the haphazard movement of people while taking their meal.

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7. What do you think should be the standby period for taking a meal after placing an order?

A. Any time is convenient for me.

B. Less than 20 minutes.

C Just as I place an order it should be ready.

8. How long of the queue will make you give up?

A Never give up.

B. Longer than 3 windows C Longer than 2 window D Longer than 1 window E Very short

THANKYOU FOR YOUR CO-OPERATION

Appendix B: DOE results Replication 1 Factors A

B

Result

C

Person 1 Perf. Seq.

Time / s

Person 2 Perf. Seq.

Time / s

Person 3

Mean time

Perf. Seq.

Time / s 209.8

+

+

+

8

219.4

12

215.8

17

206.50

-

+

+

6

194.5

13

172.5

24

184.3

183.50

+

-

+

4

178.5

15

173.4

21

178.2

187.23

-

-

+

3

191.7

16

181.8

18

185.2

186.23

+

+

-

5

189.8

9

176.6

20

187.4

184.60

-

+

-

1

195.7

14

191.8

23

203.6

197.03

+

-

-

2

174.6

11

178.6

22

180.3

179.13

-

-

-

7

185.4

10

168.4

19

175.2

179.37

Replication 2 Factors A

B

C

Result Person 1 Perf. Seq.

Time / s

Person 2 Perf. Seq.

Time / s

Person 3 Perf. Seq.

Mean time

Time / s

+

+

+

41

216.3

32

214.3

33

190.5

207.03

-

+

+

44

204.6

29

204.2

40

189.4

199.40

+

-

+

48

191.3

30

186.2

36

194.4

190.63

-

-

+

46

193.3

27

186

35

177.5

185.60

+

+

-

42

201.9

28

189.1

39

184.9

191.97

-

+

-

43

192.3

31

186.3

37

188.7

189.10

30

+

-

-

47

186.4

25

181.2

38

179.6

182.40

-

-

-

45

184.6

26

171.9

34

163.8

173.43

Replication 3 Factors A

B

C

Result Person 1 Perf. Seq.

Time / s

Person 2 Perf. Seq.

Time / s

Person 3 Perf. Seq.

Mean time

Time / s

+

+

+

59

209.5

65

211.5

53

197.2

206.07

-

+

+

62

199.2

67

187.2

55

184.2

190.20

+

-

+

64

182.2

68

196.7

54

179.7

186.20

-

-

+

60

186.5

69

179.4

52

171

178.97

+

+

-

58

188.1

70

174.5

50

183

181.87

-

+

-

57

186.8

66

185.7

51

193.8

188.77

+

-

-

61

168.6

72

171.8

49

176.3

172.23

-

-

-

63

172.7

71

184.5

56

167.9

175.03

31