Prioritizing the Key Actors of an Organization for Business Excellence Using the Efficient Interpretive Ranking Process

Sumit Kumar, Pardeep Gupta
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Abstract

Flexibilities are involved in the process of decision-making. They offer much freedom of choice in terms of the selection of suitable actors who interact with the dynamic environment of the organization. This paper presents a systematic and holistic approach to ranking key actors responsible for the business excellence of an organization. The study highlights the area where the actors of the organization should focus on achieving desired business excellence. It portrays the outcome in the form that top management is the most influential actor since it is responsible for the formulation of the vision/mission of the organization along with the setting of plant quality targets, cost-saving targets, manpower planning, and policy formulation for energy-saving. Top management is followed by cross-function teams (CFTs) and the government of India (GOI) in terms of interaction with the various processes. The novelty of this case study is that it utilizes qualitative and interpretive tools for the analysis, which does not require much statistical knowledge to produce outcomes, and the results are easy to understand. The reported results are in consensus with the results reported by various studies that are conducted using quantitative tools like Analytic Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), total interpretive structural modelling (TISM), etc. that require statistical excellence for the calculation, interpretation, and dissemination of results to the general public and shopfloor employees.
利用有效的解释性排名过程对企业卓越组织的关键角色进行优先排序
决策过程中涉及到灵活性。在选择与组织的动态环境交互的合适参与者方面,它们提供了很大的选择自由。本文提出了一种系统和全面的方法来对负责组织卓越业务的关键角色进行排名。该研究强调了组织的参与者应该专注于实现期望的业务卓越的领域。它以最高管理层是最有影响力的行为者的形式描绘了结果,因为它负责制定组织的愿景/使命,以及制定工厂质量目标、成本节约目标、人力规划和节能政策。高层管理人员之后是跨职能团队(CFTs)和印度政府(GOI)与各个流程的互动。本案例研究的新颖之处在于,它利用定性和解释性工具进行分析,不需要太多的统计知识就能产生结果,而且结果很容易理解。报告的结果与使用定量工具(如层次分析法(AHP)、理想解决方案相似性偏好排序技术(TOPSIS)、总解释结构模型(TISM)等)进行的各种研究报告的结果一致,这些研究要求在计算、解释和向公众和车间员工传播结果方面具有统计上的卓越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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