Assurance Plan Is Essential For Successful Implementation Of Master Data Management

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    Dec 15, 2013
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Controlling IT Costs; Enterprise Architecture (EA) strategy, a shared lexicon, and enforced change
Controlling IT Costs; Enterprise Architecture (EA) strategy, a shared lexicon, and enforced change
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The importance of quality data cannot be ignored in modern times. With the majority of companies who operate on a global scale, the need for reliable information has become vital. While allocating information is already a difficult task, analyzing and segregating the existing data in a language that is compatible with business systems has added more complexity to the whole process, hindering the growth pace of organizations. Luckily, it is the availability of master data management software that has enabled major Fortune 1000 companies to secure their existing data and manage it effectively.

Many business executives, who have a far-sighted approach towards business, appreciate the existence of best practices and abide by data quality management rules to enhance the usability of the existing information and its quality. While problems are bound to arise if the practices are not maintained and the implementations lack quality, cleansing of the existing data in a viable method will surely support the organizations growth and increase its productivity. With businesses competing against each other every single moment, data quality assurance has become more of a need, than an added asset.

Lack of a comprehensive assurance plan leads to duplication, repeated work, increased expenditure, apart from hindering the continuous flow of consistent information. What is worse, it may also lead to abrupt downfall of a business, in case sudden business related decisions are made by using incorrect information. Therefore, it is wise to plan and invest in an assurance plan earlier, than pay the debts of an unsuccessful master data management program in future.

Data quality assurance is a process that analyzes existing information, profiles the database to discover inconsistent information and variations, and cleanses it, at the same time. The process also transforms the derived error-free data in an easily interpretable manner for the users. Improvement of existing data, prevention of errors and continuous monitoring, are the three core functions of an assurance plan. Apart from maintaining the quality of the information, the assurance plan allows better understanding of business objectives and its requirements. It helps in the identification of data issues and allows the data maintenance department to create better policies, that would aid in building new systems for a current or new project.

The co-operation and co-ordination of a quality assurance team is extremely vital, when it comes to projects that build new systems, and the ones that merge with existing ones. Their knowledge will aid in creating better information systems that abide the assurance plan, which is to be introduced by the organization. However, execution of data assurance program alone, cannot guarantee successful implementation of data quality management . The plan can only be successful when other essential features like inspection, audit and quality control are implemented, along with it. Moreover for added efficiency, it is important to introduce the plan in every project and existing data storage system.

Author's Profile

Jessica Banks has immense experience in the field of master data management. With her articles, she aims to spread awareness on the best practices of MDM.

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