這項研究涉及評估一個組織中主數據管理的重要性及其在決策中的影響。我將提出方法框架，允許以中心為主的數據流向不同的系統。本研究將采用質的方法和解釋范式。

掌握數據管理的重點是為組織中的各種系統提供決策信息。基于系統預期收益的增加，他們將提供一個關鍵組織實體的單一版本。“MDM代表政策，集治理、標準、流程和工具，定義和管理大師和企業組織的參考數據提供一個單一的參考點。”

年的使用和保留在不同的數據存儲數據，導致數據描述沖突，數據結構，以及數據的價值，這使得它對于理解組織和正確使用的關鍵數據。

數據幾乎用于公司的所有活動，并構成決定業務和戰略層次的基礎。數據質量差會對一個組織的能力有顯著的負面影響，而高質量的數據往往是一個公司成功的關鍵。

 

Contents

 

Proposed Title

 

Abstract

Background of the study

Research Problem

Research Objectives

Preliminary Literature Review

Theoretical Framework

Research Questions

Mantaining high data quality

Benefits of Master Data Management

Challenges of Master Data Management

Hypothesis

Hypothesis 1

Hypothesis 2

Hypothesis 3

Research Methodology

Research design

Research approach and strategy

Data collection

Sampling and population

Data analysis

Knowledge gap

Conclusion

References

 

Abstract 摘要

This research deals with assessing the importance of Master Data Management in an organization and the impacts it has when making decisions. I will present the methodological framework which allows a centered master data to flow to different systems. This research will use the qualitative approach and interpretive paradigm.

 

Master Data Management - MDM

 

Keywords: Master Data Management, Data Quality, Information Management, Data Governance

 

Background of the study 研究背景

The focus to Master Data Management is to provide relevant information for decision making using the various systems in the organization. Based on the increasing number of expected benefits of systems that they will deliver a single version of key organizational entities. “MDM represents the set of policies, governance, standards, processes and tools that define and manage the master and reference data of a business organization to provide a single point of reference.“(Subotic, Jovanovic, Poscic, 2014)#p#分頁標題#e#

 

Years of using and retaining data in different data stores have led to conflicts in data descriptions, in the way data is structured, and the values of data, which makes it impossible or hard for an organization to understand and properly use its key data(Cleven & Wortmann).

 

Data are used in almost all the activities of companies and constitute the basis for decisions on operational and strategic levels. Poor quality data will have significantly negative effects on the competence of an organization, while high quality data are often crucial to a company’s success (Haug, Zachariassen & van Liempd).

 

Integrating those business definitions and data records across business lines and across subsidiaries is no simple task, demanding rearranging of data ownership and governance, however also requiring advanced technology for policies and business rules to be enforced(Scheidl 2011).

 

The goal of MDM is to create and maintain consistent and complete business data for all stakeholders in a controlled and single-view capable manner across the whole organization which will help them figure out the improvement areas so they become more efficient and competitive. MDM is meant to provide organizations with the ability to integrate, analyze and exploit the value of their data assets, regardless of where that information was collected (Milanov & Njengus 2012).

 

Research Problem 研究問題

Organizations deal with different data which may be scatted across the whole organization where systems do not communicate with each other causing the organization to make decisions based on data that is not accurate.

 

Research Objectives 研究對象

Master Data Management seeks to consolidate data that resides in various systems that do not communicate with each other, in such a way that accurate and up to date organizational data is available in a single place (Reichet, Otto, Ostele, 2013).

 

This research will discuss on how Master Data Management can manage the organizations data and outline the benefits of using MDM which will permit the organization to understand their key data. Consequently, the lack of a suitable master data management may lead to severe problems like operational faults, inadequate decision making. The bigger the company, the bigger the issue of managing the data will be. If companies grow the data landscape gets more complicated and managing data becomes an issue that is hard to deal with (K Pietzka). Companies need to make decisions based on the data that they understand and has qualities of data quality dimensions – Timely, Consistent, Completeness, Integrity, Accuracy, Conformity. To be successful in business, you need to make decisions fast and based on the right information. (Thatipamula 2013)

 #p#分頁標題#e#

Preliminary Literature Review 初步的文獻綜述

Master data form the basis for business processes. Master data represent a company’s essential basic data which remain unchanged over a specific period of time. Which include customer, material, employee and supplier data. Inconsistent master data cause process errors resulting in higher costs. With proper governance, the master data can be regarded as a unified set of data that all applications can rely on for consistent, high quality information (Hamilton G).

 

Theoretical Framework

This framework will allow master data to flow from the Master Data System to the applications, making sure that all applications use the same data. It ensures that the data used is always created the same way and is unique. Which will then allow all linked applications to use the centralized master data.

 

 

By: C LOSER, Dr. C LEGNER, D GIZANIS showing Central Master Data System

 

Research Questions

Asking the right questions will enable the organization to better the way they make decision and the processes involved in their every day to day transactions (Cleven & Wortmann). This research will use a qualitative research to answer the following research questions:

 

How to maintain high data quality?

The impacts in business for not having high quality data

What causes data redundancy in the organization

Maintaining high data quality

Achieving better insight into the performance of processes involved in the everyday running of the business, the customers they have and product profitability and market share is one of the goals. These reporting understandings are the base for key decision making, however, the quality of the reporting is directly impacted by the quality of the data. Data that is not of high quality leads to under-informed decisions. Also, the return on costly investments in business intelligence is partly diminished if the source data is corrupt (C Loser, Dr. C Legner and D Gizanis 2004)

 

A major factor of any company’s day-to-day business is the data that is used in business processes and is available to the operational staff. If it happens that this data is not available, out of date or incorrect, the business may suffer delays or financial losses. “The implications of poor quality data carry negative effects to business users through: less customer satisfaction, increased running costs, inefficient decision-making processes, lower performance and lowered employee job satisfaction“(Haug A, Zachariassen F, van Liempd D, 2011)

 

Data in an organization needs to be controlled and managed. Without having specific rules in place or enforcing data governance, this will cause data to be redundant in different places/systems across the organization. Data governance specifies the framework for decision rights and accountabilities to encourage desirable behavior in the use of data (Otto B, 2009)#p#分頁標題#e#

 

When wrong data is identified in the system, some analysis would have to be performed to find out why it happened and how it can be prevented from happening again. The process of correcting the issues will take time and organizational resources.

 

Benefits of Master Data Management

The key benefit of Master Data Management is to integrate similar data management processes, consolidate the critical information that is scattered across the organization, improve the integrity of data which makes sure that the data available is complete and accurate and business will be able to make more effective business decisions from the data with integrity. (Al-Zhrani, 2010)

 

Challenges of Master Data Management

Master Data Management challenges consists of managing the data as there is continuously increasing amount of data which will come with unclear processes of how to collect and maintain that data. Because master data is often used by multiple applications and processes, an error in master data can have a huge effect on the business processes. (Gustafsson, Franke, Johnson, Lilliesköld)

 

Hypothesis

Having implemented MDM effectively, the following can be made from the evidence gathered.

 

Hypothesis 1(H1): Understanding the company’s customers will lead to increase in market share

 

Hypothesis 2(H1): Data inconsistencies are caused by the distribution of data ownership across different business and function areas and across IT systems.

 

Hypothesis 3(H0): Companies that explicitly create a master data stewardship program are significantly more successful in terms of data governance

 

Research Methodology

Research design

For this research I will be using interpretive research design, as its main idea is to assist in understanding, recognizing and restructuring the subject meanings that already exist in the social world so we can use that understanding as steps into theorizing (Goldkuhl, 2012)

 

Research approach and strategy

Qualitative approach will be used for this research as it is suitable for discovering and gaining insight about a problem (Scheidl H, 2011)

 

Data collection

The data collection technique used for this research was one-on-one interview using a semi structured questionnaire. This technique is appropriate to this research as it allows elicitation of information that is not yet uncovered. Time kept for each interview is 45 min for each respondent. (Scheidl H, 2011)

 

Sampling and population

For this research I will use everyday decision makers so to get an understanding of how data influence the decisions that they make.#p#分頁標題#e#

 

Data analysis

After having the interviews, I will then summaries the whole interview by making notes of the key points that were given by the respondents. This will assist in making sure that I familiarizes myself with my research.

 

Knowledge gap 

In recent studies there have been increased focus on the importance of Master Data Management. This research contributes to the improvement of the scientific body of knowledge since it explores a part where only little previous study are available.

 

Conclusion 結論

Poor data quality means there will be difficulties where decision makers have to build trust in the company data. Therefore, addressing and integrating MDM at the start should be part of an operational excellence initiative, in order to solve part of the process inefficiencies.