In this paper, we will introduce the process of official statistics and the organizational structure including staffing levels. Additionally, we will briefly outline two inappropriate incidents in two official statistics and introduce initiatives related to Total Quality Management（TQM）that have been reconstructed based on the lessons learned from these incidents. We will specifically focus on the “ PDCA cycle for official statistics ” and the “ diagnosis of the official statistical process ” among these initiatives, providing explanations. This paper will offer an overview of the actual initiatives and highlight their application achievements. Furthermore, we will explain the considerations behind the setting of requirements for the diagnosis of the official statistics process.

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　A brief summary of TQM activities in the field of official statistics. In doing so, the TQM framework will consist of three principles and six activity elements. Efforts toward TQM activities have just begun. There are many deficiencies in most activity elements. Additionally, there are some items that are difficult to tackle due to the characteristics of official statistics. Among the six activity elements, although some progress has been made in “ Daily Management ” and “ Process Assurance ”, it cannot be said that the same progress has been made in other areas due to various circumstances. In the future, in order to improve the quality of official statistics, it is necessary to address these unimplemented and insufficient items as much as possible while evaluating their importance based on the characteristics of official statistics.

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　The policy of initiatives aimed at improving the overall quality of official statistics is the same stance taken by private research companies contracted to carry out large-scale official statistical surveys. This paper introduces project management efforts for large-scale statistical surveys at a private research company. Specifically, this includes setting up a Project Management Office (PMO) and developing a management system, as well as designing communications to oversee the project and distribute information. While none of these efforts are new, they are crucial in achieving the collection rate, delivery set by the government, as well as ensuring operational quality. Simply establishing a large-scale system with a large number of personnel is not enough, it must be a system that has accumulated knowledge in managing large projects. Preparing procedure manuals, setting skill requirements, and educating and developing human resources are important endeavors.However, implementing these tasks while managing large-scale surveys poses its own challenges.

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　As one of the Japanese g overnment’s central statistical organizations, The National Statistics Center (NSTAC) is responsible for tabulating tables for various important government statistical surveys, including the Population Census.
　The NSTAC is committed to total quality management (TQM) to provide statistics that ensure high quality and reliability. We have formulated a fundamental quality control policy and defined seven quality elements to aim for. These quality elements include suitability for needs, accuracy and reliability, timeliness, appropriate tabulation methods, protection of secrets, etc.
　Each fiscal year, we set quality targets and control items. And based on these, we carry out daily quality control efforts in each section responsible for tabulation. Also, quality targets for the next year are being reviewed based on the status of quality control implementation. In this way, we implement the PDCA cycle to continuously improve our operations.

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　The “ diagnosis of the official statistical process ” is one of the Total Quality Management activities for maintaining the good quality of the official statistics which are produced by the ministries and the cabinet office in Japan. The diagnosis had been tried and improved several times for about two years since 2021, and then it has been formally launched at 2023. In this article, we describe about the trials of the diagnosis for the Ministry of Health, Labour and Welfare, the Ministry of Economy, Trade and Industry, and the of Ministry of Agriculture, Forestry and Fisheries, which authors attended.

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　Since 2010, the JSQC TQE Special Committee has been working to popularize “the scientific problem-solving method” in school education as a means of fostering “zest for life”, “acknowledge yourself”, and “joy in life”. For promoting this dissemination as All Japan, we held and co-hosted various symposiums, and released best practices videos for problem solving and TQM. Thanks to the Ministry of Education and academic societies, a “data utilization” area was added to the 2017 revised curriculum guidelines in elementary school mathematics and junior high school mathematics.In high school Mathematics I, the idea of hypothesis testing has been added to “data analysis” and “problem solving in the information society” has been added to Information I which has become a new compulsory subject. However, there is still a gap between the actual state and the scientific problem-solving method that this committee aims for. For overcoming this issue, we will look back on our activities and describe future challenges.

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　This paper introduces the activities of the Yokoyama Seminar of the Faculty of Service Innovation at Chiba University of Commerce (CUC). Section 2 introduces the characteristics of CUC. Section 3 describes the features of the Faculty of Service Innovation. Then, in Section 4, the activities of the Yokoyama Seminar are introduced. In the Yokoyama Seminar, there are three groups: the “ Data Analysis Group,” the “ Mobile Application Development Group,” and the “Sales and Public Relations Group,” which take on practical challenges.
　By facing challenges with a sense of responsibility and based on logical thinking skills, students are developing into human resources who can actively solve problems and accomplish tasks based on data in the field of service.

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　MT System is the generic name for a set of methodologies developed by Dr. Gen-ichi Taguchi for the purpose of anomaly detection and prediction.
　Dr. Taguchi has proposed various methods of MT systems based on his rich insight. On the other hand, the methods were widely used without sufficient explanation of their theoretical basis and points to be noted. Each method of the MT system is a statistical methodology based on observational data and can be theoretically examined within the framework of conventional statistics.Careful reading of Dr. Taguchi’s paper also allows us to find features and points of caution in their use.
　This paper describes the characteristics, cautions, and basic mathematical properties of each of the MT system methods that the authors have studied. In particular, MT, RT, and T methods will be explained, and the issues of multicollinearity and units will be discussed as related topics.

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　Small group improvement activities such as QC circle activities and team improvement activities are intended to achieve three purposes (ideals) at the same time. In this paper, for both manufacturing and non-manufacturing workplaces, a) the organizational promotion of TQM, b) the ingenuities in the activities, c) the effect of the activities, and d) the degree of achievement of the three purposes obtained through these were comprehensively investigated, and the causal relationships of a) to d) and the impact of workplace attributes on these relationships were analyzed.As the results, it was found that 1) the relationship between a) and b), the relationship between b) and c), and the relationship between c) and d) depend on the workplace attributes, 2) each TQM’s element such as policy management, daily management, human resource development, and small group improvement activities drives specific ingenuities in activities, and each ingenuity produces specific effects of activities, and therefore, combining these specific relationships effectively can promote ingenuities in the activities, produce desired effects, and achieve the purposes of small group improvement activities. In addition, based on these results, the points that should be focused in each workplace were discussed.

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　Focusing on the manufacturing industry, this paper investigated the difficulties in the activities to prevent quality problems due to inappropriate human behavior, and the current status of implemented countermeasures, and clarified why the activities could not be implemented effectively and what kind of efforts were effective to overcome the difficulties. As the results, it was found that 1) quality problems were frequently caused by inappropriate human behavior in many organizations, 2) the rate of unintentional errors was particularly high, 3) among the elements of preventive activity, the level of implementation of those related to grasping improvement opportunities based on case studies and planning, implementing and establishing countermeasures was low, and 4) difficulties shared by many organizations included the lack of a common understanding of the necessity of preventative activities, and the difficulty of predicting risks and analyzing root causes, and 5) there were effective countermeasures to overcome the difficulties, and by making good use of these,the implementation level of preventive activities could be improved and the difficulties could be overcome.

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