Abstract
PurposeThe purpose of this paper is to design a framework for asset data management in power companies. The authors consider asset data management from a strategic perspective, linking operational-level data with corporate strategy and taking into account the organizational context and stakeholder expectations.Design/methodology/approachThe authors conducted a multiple case study based on a literature review and three series of in-depth interviews with experts from three Russian electric power companies.FindingsThe main challenge in asset data management for electric power companies is the increasing amount and complexity of asset data, which is frequently incomplete or inaccurately collected, hard to translate to managerial language, focused primarily on the operational level. Such fragmented approach negatively affects strategic decision-making. The proposed framework introduces a holistic approach, provides context and accountability for decision-making and attributes data flows, roles and responsibilities to different management levels.Research limitations/implicationsThe limitations of our study lie in the exploratory nature of case study research and limited generalization of the observed cases. However, the authors used multiple sources of evidence to ensure validity and generalization of the results. This article is a first step toward further understanding of the issues of transformation in power companies and other asset intensive businesses.Originality/valueThe novelty of the framework lies in the scope, focus and detailed treatment of asset data management in electric power companies.
Subject
Strategy and Management,General Business, Management and Accounting
Reference82 articles.
1. A framework of data warehouse systems success: an empirical study;International Journal of Electronics, Communications and Computer Engineering,2012
2. Investigator triangulation: a collaborative strategy with potential for mixed methods research;Journal of Mixed Methods Research,2016
3. Preventive maintenance (PM) planning: a review;Journal of Quality in Maintenance Engineering,2017
4. A sequential TPM-based scheme for improving production effectiveness presented with a case study;Journal of Quality in Maintenance Engineering,2019
5. Data quality problems in discrete event simulation of manufacturing operations;Simulation,2018
Cited by
7 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献