scholarly journals Master Data Governance Best Practices

Author(s):  
Ronak Pansara

Master data governance is not a new field, and it has existed since the early 90s (8). However, the demand for master data governance has been rising recently due to the ever-increasing demand for cost optimization, faster product innovations, compliance with the set rules and regulations, and competitive advantage in the business field. One of the areas in which companies can achieve master data governance is through maintaining consistent data quality. Handling data is one of the pain areas in most companies due to the complicities involved in managing data. Still, companies that succeed in handling data compete well in their business since data leads to optimal decision-making. Data mismatch is putting so many companies projecting to accelerate their growth on brakes. This paper outlines the best practices of master data governance, which can help the companies solve and improve their odds in data governance and improve their business quickly, predictably when planning and implementing the decisions made.

Stat ◽  
2021 ◽  
Author(s):  
Hengrui Cai ◽  
Rui Song ◽  
Wenbin Lu

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Guangsheng Zhang ◽  
Xiao Wang ◽  
Zhiqing Meng ◽  
Qirui Zhang ◽  
Kexin Wu

PurposeTo remedy the inherent defect in current research that focuses only on a single type of participants, this paper endeavors to look into the situation as an evolutionary game between a representative Logistics Service Integrator (LSI) and a representative Functional Logistics Service Provider (FLSP) in an environment with sudden crisis and tries to analyze how LSI supervises FLSP's operations and how FLSP responds in a recurrent pattern with different interruption probabilities.Design/methodology/approachRegarding the risks of supply chain interruption in emergencies, this paper develops a two-level model of single LSI and single FLSP, using Evolutionary Game theory to analyze their optimal decision-making, as well as their strategic behaviors on different risk levels regarding the interruption probability to achieve the optimal return with bounded rationality.FindingsThe results show that on a low-risk level, if LSI increases the degree of punishment, it will fail to enhance FLSP's operational activeness in the long term; when the risk rises to an intermediate level, a circular game occurs between LSI and FLSP; and on a high level of risk, FLSP will actively take actions, and its functional probability further impacts LSI's strategic choices. Finally, this paper analyzes the moderating impact of punishment intensity and social reputation loss on the evolutionary model in emergencies and provides relevant managerial implications.Originality/valueFirst, by taking both interruption probability and emergencies into consideration, this paper explores the interactions among the factors relevant to LSI's and FLSP's optimal decision-making. Second, this paper analyzes the optimal evolutionary game strategies of LSI and FLSP with different interruption probability and the range of their optimal strategies. Third, the findings of this paper provide valuable implications for relevant practices, such that the punishment intensity and social reputation loss determine the optimal strategies of LSI and FLSP, and thus it is an effective vehicle for LSSC system administrator to achieve the maximum efficiency of the system.


2021 ◽  
pp. 103418
Author(s):  
Xiangqian Zhu ◽  
Wenfeng Wang ◽  
Suhong Pang ◽  
Chaoyin An ◽  
Xiaoliang Yang ◽  
...  

2010 ◽  
Vol 14 (1) ◽  
pp. 74-88 ◽  
Author(s):  
Domenico Conforti ◽  
Francesca Guerriero ◽  
Rosita Guido ◽  
Marco Matucci Cerinic ◽  
Maria Letizia Conforti

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