Research Proposal on Implementation of Six Sigma in Service Industry
Implementation of Six Sigma in Service Industry
1.0 Background of the Study
Six sigma is considered as a statistically-based quality improvement programs which aims on helping to improve business processes by reducing waste, reducing the costs due to poor quality, at the same time improving the degree of efficiency and effectiveness of the processes (Hoerl & Snee 2002). Generally, all of the said processes help to improve the customer satisfaction with the product as well as the profitability (Antony & Banuelas 2002).
It is important to consider that there are different propositions which show the different between services and manufacturing, which affect the complexity of service quality. These factors include the customer participation, inseparability, perishability, site selection dictated by location of customers, labor intensiveness, intangibility and difficulty in measuring output intangibility (Lovelock & Gummesson 2004). However, overall, it is important to consider that it is expected for businesses in service industry must focus on increase of productivity and profits because of reduced costs (Kandampully & Duddy 1999). With this, it shows that Six Sigma will be acceptable.
Researches show that most of the service processes, which include payroll processing, billing, invoicing, shipping, order entry, response to service request, baggage handling, etc. are performing at less than 3.5 sigma quality level with a defect rate of more or less 23,000 ppm or yield 97.7% (Yilmaz & Chatterjee 2000). If the sigma quality level will be improved in the service processes presented, to four sigma quality level, then the defect rate will drop to 6,210 ppm, which indicate a 3.5-fold improvement in terms of process performance. Thus, the process yield will increase to 99.39%, which will bring vital returns to the bottom-line of the organization (Antony 2006).
2.0 Objectives of the Study
The main aim of the study is to investigate the implementation of Six Sigma in the service industry. In line with this, the following are the specific objectives of the study:
· To study the application of Six Sigma in the service industry;
· To investigate the advantages of Six Sigma in the service industry; and
· To analyze if Six Sigma offers the same benefits it offer in the manufacturing industry.
3.0 Methodology
The research study to be used in the proposed study will be descriptive method. According to Creswell (1994) it intends to present facts about the nature and status of a situation as it exists at the time of the study. In addition, it also concerns with the relationships and practices that exist, beliefs and processes that are ongoing, effects that are being felt or trends that are developing (Best 1970). Therefore, it can be helpful in order to describe the current conditions and situations based on the impressions and perceptions of the respondents of the study (Creswell 1994). The study will also use case study, which is the “strategy for doing research which involves an empirical investigation of a particular contemporary phenomenon within its real life context using multiple sources of evidence (Robson 2002).” The case of Citibank will be used in the study.
4.1 Data Collection
Surveys will be implemented in the study. Surveys are the most common form of research method for collection of primary data (Commonwealth of Learning, 2000). One of its purpose is to describe, e.g., to count the frequency of some event or to assess the distribution of some variables such as proportion of the population of different age groups, sex, religion, castes and languages, knowledge, attitude and adaption of practices about particular issues, and other information of similar nature about the population (Commonwealth of Learning, 2000). Survey questionnaire and interview, and document analysis will be used in order to gather primary data.
4.2 Sample Frame
The target respondents are 50 employees – managers and leaders in Citibank who are connected to the operation in the company. The name of the employees will be selected in random manner in order to ensure that bias will be prevented which will greatly affect the efficiency and accuracy of the result of the study.
4.3 Data Analysis
The data results of the study will be analyzed by determining their corresponding frequency, percentage and weighted mean. The following statistical formulas will be used:
1. Percentage – to determine the magnitude of the responses to the questionnaire.
n
% = -------- x 100 ; n – number of responses
N N – total number of respondents
2. Weighted Mean
f1x1 + f2x2 + f3x3 + f4x4 + f5x5
x = ---------------------------------------------;
xt
where: f – weight given to each response
x – number of responses
xt – total number of responses
4.0 References
Antony, J., Banuelas, R. (2002), "Key ingredients for the effective implementation of six sigma program", Measuring Business Excellence, Vol. 6 No.4, pp.20-7.
Antony, J. (2006). ‘Six Sigma for Service Processes’, Business Process Management Journal, vol. 12, no. 2, pp. 234 – 248.
Best, J. W. (1970). Research in Education, 2nd Ed. Englewood Cliffs, N.J.: Prentice Hall, Inc.
Commonwealth of Learning. (2000). Manual for Educational Media Researchers: Knowing your Audience. Vancouver, Canada: Commonwealth Educational Media Centre for Asia (CEMCA).
Creswell, J.W. (1994). Research design. Qualitative and quantitative approaches. Thousand Oaks, California: Sage.
Hoerl, R.W., Snee, R.D. (2002), "Statistical thinking – improving business performance", Duxbury, Thomas Learning, Belmont, CA.
Kandampully, J., Duddy, R. (1999), "Competitive advantage through anticipation, innovation and relationships", Management Science, Vol. 37 No.1, pp.51-6.
Lovelock, C., Gummesson, E. (2004), "Whither services marketing? In search of a new paradigm and fresh perspectives", Journal of Service Research, Vol. 7 No.1, pp.20-41.
Yilmaz, M.R., Chatterjee, S. (2000), "Six sigma beyond manufacturing – a concept for robust management", IEEE Engineering Management Review, Vol. 28 No.4, pp.73-80.
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