PDCA循环理论在外汇数据质量管理上的应用研究与实践

A PDCA Based Model on the Application and Practice of Foreign Exchange Data Quality Management

针对外汇数据质量影响因素多、数据质量管理难、部分业务数据质量水平低等问题,提出了一种基于PDCA循环思想的数据质量管理办法。在计划阶段定义数据质量管理需求,设计数据质量管理业务规则和量化指标,制定了评估规则和指标,在实施阶段确定数据质量水平并进行数据质量监测,在检查阶段实施登记评估,系统流程控制和层级反馈,在行动阶段解决数据质量问题,通报考评并且总结修正。通过4个阶段和12个过程,形成了数据质量管理的闭环和循环改进机制,通过在对外金融资产负债及交易统计数据上一年的实践,数据质量得到显著提升,影响数据质量的内在和外在因素得到了有效抑制。

There are many factors affect the data quality of foreign exchange, so data quality management is difficult in this area, quality of part business data is at the low level. To solve the problem, a new data quality management approach based on PDCA cycle is presented. In the planning phase,we define quality management needs,design business rules and quantitative indicators of data quality, and evaluate these rules and metrics. In the implementation phase, we determine the level of data quality and imprement to monitor data quality. In the checking phase, we do registration and evaluation of data quality, adopt system flow control and level feedback. In the action phase, we resolve data quality issues, circulate information and take assessment. Finally we summarize and correct all the phases. These four phases and 12 sub-processes form a closed loop and circulation mechanism for improving data quality. Through a year of practice in foreign financial assets, liabilities and transactions statistical data, data quality has been significantly improved, the internal and external factors of data quality have been effectively restrained.