Lyndsay Wise
The cause of poor customer service ratings, ineffective marketing initiatives, faulty financial planning, and the increase in fraudulent activity can, in many cases, relate back to an organization's management of its data. As the data collected and stored in organizations has grown exponentially over the past few years, its proper management has become critical to the successful implementation of such business initiatives as product marketing and corporate planning. Additionally, as fraud and acts of terror receive greater attention, it has become essential to use data to identify people and their relationships with one another.
This article will define master data management (MDM) and explain how customer data integration (CDI) fits within MDM's framework. Additionally, this article will provide an understanding of how MDM and CDI differ from entity analytics, outline their practical uses, and discuss how organizations can leverage their benefits. Various applications of entity analytics, including examples of its application to different types of organizations, will be highlighted along with the benefits it offers organizations in such service industries as government, security, banking, and insurance.
Data Management—Its Broad Spectrum
MDM has emerged to provide organizations with the tools to manage data and data definitions effectively throughout an organization in order to present a consistent view of the organization's data. In essence, MDM overcomes the silos of data created by different departments and provides an operational view of the information so that it may be leveraged by the entire organization. It focuses on the identification and management of reference data across the organization to create one consistent view of data. MDM's application identifies how different subsets of MDM address separate aspects of an organization's needs.
MDM manifests its importance when a customer service representative (CSR) cannot access customer information due to inconsistencies introduced by a corporate acquisition or a new system implementation, which may lead to the frustration (or even alienation) of the customer. Add to this the extra time the CSR spends accessing the appropriate data, and the issue extends to wasted time and money. MDM focuses on the identification and management of reference data across the organization to create one consistent view of data.
CDI is a subset of MDM, and serves to consolidate the many views of a customer within the organization into one centralized structure. This data consolidation provides the CSR with the information required or the ability to link to the required information, which may include billing, accounts receivable, etc. Once the data is consolidated, references to each customer file are created that link to one another and assign the "best" record from the available information. Consequently, data inconsistencies that occur across disparate systems, such as multiple address formats, are cleansed based on defined business rules to create one version of customer data that will be viewed across multiple departments within the organization.
The creation of "one version of the truth" presents unique challenges to organizations In many organizations, there are multiple views of the customer, such as accounts payable, call center, shipping, etc. Each profile may have the same customer name, but different addresses or other associated information such as unique customer numbers for each department, making it difficult to link one person to multiple processes. The difficulty comes when determining which view is the most correct. For example, if four versions of the same customer name and associated address exist, one version should be chosen from the four files to represent the most correct view in order to create a consolidated profile of that customer. The issue that arises here is that each department may have a different definition of "customer," making reconciliation of customer data an enormous task. For instance, organizations often profile their customers differently in systems across the organization, giving employees an incomplete view of the customer. The resolution of this issue allows the redundant or inaccurate customer records to be purged.
Aside from incomplete records, as the customer information is entered into the system multiple times, more silos are created, amplifying the problem. In addition to CSRs and employees having direct contact with the customer, marketing is another department that may have a different or incomplete view of the customer. This can translate into ineffective marketing campaigns and missed revenue opportunities. Although this last example may seem farfetched, the reality is that poor management of data within an organization affects the bottom line. CDI, when implemented properly, can not only reduce costs, but also increase sales, customer service ratings, and customer loyalty.
SOURCE:
http://www.technologyevaluation.com/research/articles/business-intelligence-and-identity-recognition-ibm-s-entity-analytics-18862/
The cause of poor customer service ratings, ineffective marketing initiatives, faulty financial planning, and the increase in fraudulent activity can, in many cases, relate back to an organization's management of its data. As the data collected and stored in organizations has grown exponentially over the past few years, its proper management has become critical to the successful implementation of such business initiatives as product marketing and corporate planning. Additionally, as fraud and acts of terror receive greater attention, it has become essential to use data to identify people and their relationships with one another.
This article will define master data management (MDM) and explain how customer data integration (CDI) fits within MDM's framework. Additionally, this article will provide an understanding of how MDM and CDI differ from entity analytics, outline their practical uses, and discuss how organizations can leverage their benefits. Various applications of entity analytics, including examples of its application to different types of organizations, will be highlighted along with the benefits it offers organizations in such service industries as government, security, banking, and insurance.
Data Management—Its Broad Spectrum
MDM has emerged to provide organizations with the tools to manage data and data definitions effectively throughout an organization in order to present a consistent view of the organization's data. In essence, MDM overcomes the silos of data created by different departments and provides an operational view of the information so that it may be leveraged by the entire organization. It focuses on the identification and management of reference data across the organization to create one consistent view of data. MDM's application identifies how different subsets of MDM address separate aspects of an organization's needs.
MDM manifests its importance when a customer service representative (CSR) cannot access customer information due to inconsistencies introduced by a corporate acquisition or a new system implementation, which may lead to the frustration (or even alienation) of the customer. Add to this the extra time the CSR spends accessing the appropriate data, and the issue extends to wasted time and money. MDM focuses on the identification and management of reference data across the organization to create one consistent view of data.
CDI is a subset of MDM, and serves to consolidate the many views of a customer within the organization into one centralized structure. This data consolidation provides the CSR with the information required or the ability to link to the required information, which may include billing, accounts receivable, etc. Once the data is consolidated, references to each customer file are created that link to one another and assign the "best" record from the available information. Consequently, data inconsistencies that occur across disparate systems, such as multiple address formats, are cleansed based on defined business rules to create one version of customer data that will be viewed across multiple departments within the organization.
The creation of "one version of the truth" presents unique challenges to organizations In many organizations, there are multiple views of the customer, such as accounts payable, call center, shipping, etc. Each profile may have the same customer name, but different addresses or other associated information such as unique customer numbers for each department, making it difficult to link one person to multiple processes. The difficulty comes when determining which view is the most correct. For example, if four versions of the same customer name and associated address exist, one version should be chosen from the four files to represent the most correct view in order to create a consolidated profile of that customer. The issue that arises here is that each department may have a different definition of "customer," making reconciliation of customer data an enormous task. For instance, organizations often profile their customers differently in systems across the organization, giving employees an incomplete view of the customer. The resolution of this issue allows the redundant or inaccurate customer records to be purged.
Aside from incomplete records, as the customer information is entered into the system multiple times, more silos are created, amplifying the problem. In addition to CSRs and employees having direct contact with the customer, marketing is another department that may have a different or incomplete view of the customer. This can translate into ineffective marketing campaigns and missed revenue opportunities. Although this last example may seem farfetched, the reality is that poor management of data within an organization affects the bottom line. CDI, when implemented properly, can not only reduce costs, but also increase sales, customer service ratings, and customer loyalty.
SOURCE:
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