Introduction
Quality management in the public sector has ignited a heated debate among scholars, some arguing that the applicability of quality management in the public sector is a hectic task. The skeptics of the public sector’s quality management techniques cite the political interference and the bureaucracy in the public sector as the main challenges limiting the operation of the quality management techniques in the sector (Flynn, 2007).
The need to provide quality goods and services to the customers has facilitated the adoption of quality management techniques in the past few decades. The private sector has fully implemented the quality management techniques documented in the literature to improve the quality of goods and services. This paper proposes research to unravel the applicability and efficiency of the quality management in the public sector. To achieve the stated objectives, the paper shall propose the conduction of the research through both the qualitative and the quantitative techniques. The paper shall also describe the process of designing an effective questionnaire and highlight the importance of statistical analysis in research.
Literature review
Diefenbach (2009) posits that bureaucracy and politics derail the implementation of quality management in the public sector. He argues that the changes in policy caused by changes in the administration cause instability in the sector. The elected government can alter the policies implemented by the previous regime. Additionally, the policymakers are usually politicians, which means that a change in government will mean a change in the policies.
Karia and Hasmi (2006) identify the staff resistance to change as a causal factor of the slow pace of the adoption of quality management techniques in most institutions. Employees are usually reluctant to embrace changes in the operations due to the perception that such changes may complicate their work or lead to unemployment. In that regard, the application of the quality management strategies in public institutions is derailed by the mentioned misconceptions. For quality management to work in the public sector, employees need to be trained to handle their new tasks following the implementation of the quality management systems.
Van Dooren, Bouckaert, and Halligan (2015) argue that quality management is non-existent in the public sector, with customers obtaining poor quality goods and services from the government institutions. The author proposes the introduction of Total Quality Management (TQM) that is currently being applied in the private sector. West and Blackman (2015) identify the benefits of quality management in the public sector as high-quality services, higher customer satisfaction, and lowered administration costs.
Sources of secondary data
There are two types of data sources, namely the primary and secondary data sources. The primary data refers to the researcher’s original data in the course of conducting research (Van Dooren et al., 2015). The primary data is acquired using interviews and questionnaires. On the other hand, the secondary data refers to the data used by a researcher, and it may be unoriginal. In other words, secondary data denotes unoriginal data obtained from already existing knowledge—sources of secondary data in clued the literature, statistics, census, and findings by other researchers. The secondary data is only applicable in research if they are modifiable to fit the research requirements. A review of the literature is the most commonly used form of data in both qualitative and quantitative studies.
The questionnaires
The questionnaire is another method used to collect data in qualitative research. The questionnaires contain pre-prepared questions that attract the relevant answers from the participants. The questionnaires may be grouped into two based on the type of questions contained. The two major types of questionnaires are closed and open-ended questionnaires. In a closed questionnaire, the participants’ answers are restricted to the pre-prepared answers contained in the questionnaires. On the other hand, an open-ended questionnaire contains questions that require the participants to formulate their answers. The answers are not given in the questionnaire thus the participants need to provide their answers based on his/her knowledge of the topic
Advantages of the open-ended questionnaire
In an open-ended questionnaire, the participant has the option to describe his/her feelings about the subject as opposed to the case of the closed questionnaire, where the answers are restricted to the pre-prepared ones. The additional information provided by the participant may be used to verify the results.
Disadvantages
The open-ended questionnaire requires participants to give his/her answers based on their understanding of the topic. This aspect leads to varied answers complicating the work of the researcher during the analysis stage. For example, the researcher has to sample the answers to detect those with similar responses and give them a special code. Besides, the answers are heavily dependent on the participant’s knowledge and memory. The data may lose its reliability when a participant is not conversant with the topic or s/he has a poor memory.
Advantages of the closed questionnaire
The closed questionnaire restricts the answers to the ones provided by the researchers. In that regard, the analysis of the data is much easier than in an opened ended questionnaire where the answers vary.
Disadvantages
In a closed questionnaire, the researcher may not obtain further information regarding the topic of research. In other words, the actual feelings of the participant are not reflected in this type of questionnaire.
Importance of data analysis
Data analysis is a system of data analytics, which involves the collection of data regarding a certain population, analyzing it, and presenting it to the users in an understandable manner. It denotes the collection and the classification of the data to determine the trend in the variable being measured (Rice, 2006). A sample is drawn from a population whose data is required. The result from the sample is deemed representative of the whole population.
Statistical data analysis is important since it allows the researcher to determine the trend in the variable being examined. Moreover, the descriptive statistical analysis converts the data into a form that is understandable by the users who may not have the expertise to interpret it. There are various methods applied in data analysis. However, the following methods are commonly used by contemporary researchers:
Descriptive statistics
The descriptive statistical method involves analyzing the historical aspects of the variable under examination to determine the trend. Data about the variable in question is examined for a consecutive period and used to determine the trend. However, descriptive statistics does not allow for the generalization of the results, and they only help in the presentation of the results of the study population in an understandable way. Examples of descriptive statistics include graphs, pie charts, and the measures of central tendencies.
Inferential statistics
The inferential statistics denote a form of statistical analysis whereby the results obtained from a sample population are deemed representative of the whole population. In this method, the Chi-square or T-test, are used to test the reliability of the results for their generalization. This inferential statistics is the commonly used method in modern research.
Methodology
Sample population
The study shall recruit participants from a cross-section of senior officials from the public sector. The study shall specifically recruit operational managers from the health sector due to the heavy criticism of government hospitals’ services. The study shall recruit 50 operation managers from hospitals in New York.
Study objectives
The primary objective of this study will be to add to the knowledge regarding quality management in the public sector. The study shall also seek to uncover the effectiveness of the quality management systems in place in the public sector.
Significance of the study
The public sector has been accused of neglecting the customers, as evidenced by the governmental sectors’ poor quality of the goods and services. The public has resulted in procuring goods and services from the private sector as opposed to the government institutions. Given that the government sector forms more than 50% of the institutions, it is imperative to consider improving the sector (Diefenbach, 2009). This study seeks to add to the existing knowledge regarding the topic and offer recommendations on how to improve the quality of the goods and services in the public sector. The recommendations, if implemented, may go a long way in improving the quality and services offered by the sector.
Study limitations
The study population is limited to 50 participants drawn from a cross-section of the health care facilities located in New York. The small sample population may lead to the collection of inadequate data for the generalization of the results. Additionally, the study’s limitation in the health sector is a major shortfall since the public sector has other sectors, such as the education and the financial sectors. Such sectors will not be reflected in the research. Lastly, the study is limited to the services sector, ignoring the existence of government institutions that offer goods to the public. Future researchers should recruit a larger sample from a cross-section of the various goods and services government sectors.
Ethical issues
Confidentiality
The law provides that the confidentiality of the data solicited from the client be maintained at all costs. In the compliance of the mentioned provision, the data collected from the clients shall be used for this study and not for any other purpose. Moreover, the computers used to store the data shall be password protected to avoid unauthorized access. The participants’ anonymity shall be emphasized, whereby the participants’ names will be banned in the questionnaires. All the participants shall be guaranteed the privacy of the information given to encourage them to give all the relevant data.
Informed consent
This research involves the solicitation of information from clients using interviews and questionnaires. The law provides that the researchers obtain written consent from the participants before engaging them in a study. To comply with the said provision, the participants shall be advised of the objectives of the research, and their rights and obligations during and after the study. After the issuance of such information to the participants, each participant shall be required to sign a document declaring their consent to participate.
Qualitative methods
The qualitative method of research involves the use of both the interviews and the questionnaire in the collection and the analysis of the data. This study shall utilize both methods to acquire relevant data from the sample population.
Interviews
The interviews shall take the form of one-on-one contact between the interviewer and the interviewee. Each participant shall be engaged for 45 minutes in which s/he will be required to answer the questions posed by the interviewer. Some of the questions that will be posted to the participants include:
- What is quality management?
- What are the strategies in place in your organization to promote quality services to clients?
- How does Quality management systems compare in both the public and the private sector?
In some special cases where the interviewee has a tight schedule, the Internet shall be used to solicit the required data. Internet-based interviews shall be conducted using Skype.
The questionnaires
The questionnaires shall be used alongside with the interviews to ensure the collection of reliable data. This study shall utilize the open-ended type of questionnaire to collect the relevant data. The questionnaires shall be distributed to the study group a day after the interviews. Each respondent shall be allowed a maximum of two hours to complete the questionnaire and forward it back to the researching team. Some of the questionnaires that will be included in the questionnaire include:
- What is quality management?
- What are the benefits of implementing quality management systems in the public sector?
- What are the challenges of implementing Quality management systems in the public sector?
- Describe the efficiency of QMS in the public sector.
- Describe the nature of the current QMS in the public sector.
Qualitative methods
The quantitative research method shall involve a review of the literature about the topic. To qualify for inclusion, the articles to be reviewed shall have to meet the following criteria:
- Must be based on either a qualitative or a quantitative research.
- Must have been authored within the past ten years.
Data analysis
Two members of the study team shall scrutinize the data obtained from the qualitative methods to verify its reliability. Similar responses shall be grouped and given special codes to facilitate their analysis using the relevant software. Similarly, the articles with similar arguments shall be grouped and assigned special codes. The data shall then be input to the computer for analysis. The Computer-Assisted/Aided Qualitative Data Analysis Software (CAQDAS) shall specifically be used to analyze the data (Rice, 2006).
Conclusion
Quality management refers to the utilization of management techniques to improve the quality of goods and services. Quality management is premised on the principle of customer-centered goods and services, whereby the quality is emphasized in the production phase. The private sector has fully implemented quality management techniques to maximize customers’ value. The public sector has been accused of diverting from the principles of quality management hence providing poor quality services to the public. The bureaucracy and resistance to change are among the factors that contribute to the slow pace of the adoption of quality management tools in the public sector.
This paper proposes research to uncover the strategies in place to ensure quality management in the public sector. The research shall be conducted using both the quantitative and the qualitative methods, and the results shall be generalized. The duo methods have been described in detail in the paper.
References
Diefenbach, T. (2009). New public management in public sector organizations: the dark sides of managerialistic ‘enlightenment.’ Public Administration, 87(4), 892-909. Web.
Flynn, N. (2007). Public sector management. New York, NY: Sage. Web.
Karia, N., & Hasmi, M. (2006). The effects of total quality management practices on employees’ work-related attitudes. The TQM Magazine, 18(1), 30-43. Web.
Rice, J. (2006). Mathematical statistics and data analysis. Boston, MA: Cengage Learning. Web.
Van Dooren, W., Bouckaert, G., & Halligan, J. (2015). Performance management in the public sector. London, UK: Routledge. Web.
West, D., & Blackman, D. (2015). Performance Management in the Public Sector. Australian Journal of Public Administration, 74(1), 73-81. Web.