Developing a customer master data management model

Abstract

Master data is the most important data to the organization because it describes the main business objects that are used in different business processes, and business transactions are dependent on master data. Customer data is one typical master data object. Master data is usually quite complex since it is used in many business areas inside organizations, and it is typically stored in multiple information systems at the same time. Since it is used and stored in different places inside the organizations, the data may vary between different business units, and the quality of master data may be affected by the disparate systems and increased number of users handling the data. Master data management (MDM) tries to tackle these master data challenges.

Master data management is an organization-wide management activity that enables organizations to achieve a single version of the truth in master data objects. Disparate organizations, processes, and systems have created segregated information. The goal of MDM is to bring disparate and segregated information together and ensure it is easily accessible and available in the whole organization when needed. MDM consists of a set of the best data management practices. It tries to tackle the master data issues by managing business processes and data quality as well as standardizing operations and creating integrations between separate information systems. Master data governance is one important management practice in MDM. Master data governance consists of rules, policies, responsibilities, and ownership of the master data. The goal of data governance is to ensure that the data is managed.

The goal of this research is to create a customer master data management model to support the management and governance of the master data for a case organization. The research material in this research is collected with semi-structured interviews in the case organization. Based on the data collected and the existing MDM models in the literature, the MDM model for the case organization is created. The case organization has faced multiple challenges with customer data due to the lack of data governance and MDM actions. The lack of MDM has caused that the data quality is not good, the global processes are disparate, and the ERP system does not guide the users enough. The main business processes are delayed due to incomplete customer data. Finding the right information is challenging, and the missing roles and responsibilities around customer data have caused ambiguity on who should do what in the case organization. Also, the lack of training has frustrated the employees in the organization. The MDM model created in this research addresses these challenges.

The MDM model that is created in this research starts by defining the MDM vision, which should be defined in the organization’s context, and should be in line with the business vision of the organization. After the MDM vision is defined, the six steps of the MDM model are executed. The MDM steps should be executed in the following order: defining core data and processes, defining data governance, cleaning and updating current data, defining data lifecycle and maintenance processes, defining MDM architecture and future roadmap, and planning and executing training and communication. The second step of the MDM, data governance, also includes seven steps, which are: defining principles, responsibilities, policies and rules, data standards, issue management, tools, and audit and metrics. With these master data governance steps, the organization can ensure compliance, alignment between business and IT, and organization-wide common understanding around master data.