Developing a framework for identifying and assessing data quality issues in asset management decision-making

[摘要] ENGLISH ABSTRACT: Assets allow organizations to achieve their strategic objectives. Asset managementtranslate these objectives into asset related decision and actions. A key enabler of asset management decision-making is data. Data quality, however,is a common challenge faced by many organizations, especially in the asset-intensive industry. This problem is compounded by the multitude ofbusiness intelligence systems and data standards competing for market share in some subset of an organization's data pipeline. With rapidly increasing data volumes and global competition demanding optimal management of assets,data quality is a problem that all asset mangers will have to face.With the release of the ISO 55000 series of international standards for asset management in February 2014, many asset managers will seek to implementa compliant asset management system. The ISO 55000, however, intends to be applicable to the broadest range of assets, organizations and cultures andtherefore does not provide specific technical requirements. Previous studies have attempted to provide such technical requirements for data quality in asset management and subsequently contributed one more standard or systemto an already crowded market.Asset managers' continued struggle with data quality is thus not due to a lack of standards or systems. In fact, the many competing and often incompatiblesystems and standards are one of the many reasons for poor data quality. The severity of data quality issues and their impact on asset managementdecision-making were observed in a Southern African diamond mine.A preliminary literature review confirmed that these observations were not isolated. Data quality, however, was also found to be a complex and contextspecificproblem, especially in asset management. Thus, instead of developing yet another standard or system to either replace or provide compatibility between existing systems, this study adopts a pragmatic approach to developa framework to help asset managers identify their most critical data quality issues.To answer the question of what such a framework would look like, a pragmatic research approach was adopted. The framework and its components were developed through an iterative cycle of development and evaluation. Applicableknowledge from a comprehensive literature review assured innovation and the business needs from the diamond mine case study ensured that the solution is relevant. The study found that the framework requires three componentsto be of value. The three components are: (1) a data pipeline reference model, (2) a methodology to guide asset managers in collecting the relevant data and (3) a tool to help asset managers populate their data pipeline modeland identify data quality issues.The usefulness (which is the measure of value in the pragmatic world view) of the framework was demonstrated by applying the framework in practice andfixing the critical data quality issues that it identified.The modular nature of the framework allows future studies to be carried out to integrate the framework with various other disciplines to not only identify data quality issues, but also systematically address them. The hope is thatthis framework will eventually become part of a larger, pragmatic approach to allow asset managers to implement an ISO 55001 compliant asset management system.

[发布机构] Stellenbosch University