向数据驱动型组织过渡过程能力的评估:多学科方法

IET Softw. Pub Date : 2021-06-27 DOI:10.1049/sfw2.12033
M. Gökalp, Kerem Kayabay, E. Gökalp, Altan Koçyiğit, P. Eren
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引用次数: 5

摘要

Mert O. Gökalp,中东技术大学信息学研究所,土耳其安卡拉06800。摘要利用数据科学的能力可以通过增强数据驱动的决策来找到基于复杂业务参数和数据的最佳解决方案,从而在组织中产生有价值的见解和行动。然而,由于缺乏组织管理、一致性和文化,只有一小部分组织能够成功地从他们的投资中获得商业价值。成为一个数据驱动的组织需要一个组织变革,应该从一个整体的多学科的角度来管理和培养。因此,本研究试图通过开发基于ISO/IEC 330xx系列标准的数据驱动过程能力确定模型(DDPCDM)来解决这些问题。提出的模型使组织能够确定其当前的管理能力,推导差距分析,并以结构化和标准化的方式创建全面的改进路线图。DDPCDM包括两个主要维度:过程和能力。过程维度由五个组织管理过程组成:变更管理、技能和人才管理、战略一致性、组织学习,以及赞助和投资组合管理。能力维度包括从不完整到创新的六个层次。通过在两个组织中进行多案例研究,还对DDPCDM的适用性和可用性进行了评估。结果表明,所提出的模型能够评估组织在采用、管理和促进向数据驱动型组织过渡方面的优势和劣势,并为持续改进组织的数据驱动性提供路线图。
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Assessment of process capabilities in transition to a data-driven organisation: A multidisciplinary approach
Mert O. Gökalp, Informatics Institute, Middle East Technical University, Ankara 06800, Turkey. Email: gmert@metu.edu.tr Abstract The ability to leverage data science can generate valuable insights and actions in organisations by enhancing data‐driven decision‐making to find optimal solutions based on complex business parameters and data. However, only a small percentage of the organisations can successfully obtain a business value from their investments due to a lack of organisational management, alignment, and culture. Becoming a data‐driven organisation requires an organisational change that should be managed and fostered from a holistic multidisciplinary perspective. Accordingly, this study seeks to address these problems by developing the Data Drivenness Process Capability Determination Model (DDPCDM) based on the ISO/IEC 330xx family of standards. The proposed model enables organisations to determine their current management capabilities, derivation of a gap analysis, and the creation of a comprehensive roadmap for improvement in a structured and standardised way. DDPCDM comprises two main dimensions: process and capability. The process dimension consists of five organisational management processes: change management, skill and talent management, strategic alignment, organisational learning, and sponsorship and portfolio management. The capability dimension embraces six levels, from incomplete to innovating. The applicability and usability of DDPCDM are also evaluated by conducting a multiple‐case study in two organisations. The results reveal that the proposed model is able to evaluate the strengths and weaknesses of an organisation in adopting, managing, and fostering the transition to a data‐driven organisation and providing a roadmap for continuously improving the data‐drivenness of organisations.
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