Data Governance

Create the right business and organizational framework for successful master data management and continuously high data quality

The path to high data quality

Data governance framework

Top-down approach

What is data governance?

The realization that quality master data is an elementary prerequisite for business success has established itself in almost all companies. Nevertheless, many companies fail in practice to maintain their data quality at a high level over the long term. When searching for the causes, it turns out that a suitable organizational framework for successful master data management is often lacking − a framework that data governance can provide.

Data governance ensures that data is managed and maintained in a consistent and disciplined manner. It defines precise responsibilities, establishes data ownerships and ensures a stringent security concept. Furthermore it designates clear roles that are responsible for compliance with data quality and implement the strategic requirements from a functional perspective.

Master data management vs. data governance

Master data management

Master data management is the operational administration and maintenance of data in order to achieve economic goals.

  • Correct, reliable master data

  • Company-wide standards

  • Clearly defined, automated processes

  • Single point of truth for master data

Data governance

Data governance is the organizational framework that ensures that data is maintained in a consistent and disciplined way.

  • Defined responsibilities

  • Clearly divided data ownerships

  • Implemented security standards

  • Clearly defined and documented processes

  • Established data stewards

Data governance describes a holistic system that determines, among other things, who in an organization has access and authorizations with regard to master data. It covers people, processes, and the tools and mechanisms used for this purpose.

 

Our approach to data governance

In order for companies to make their master data a long-term success factor, they must maintain their data quality at a permanently high level or increase it continuously. An effective data governance program plays a decisive role in achieving this goal.

The establishment of governance processes ensures consistently high data quality. Data governance creates stable strategic conditions for effective master data management.

We address all relevant topics related to data governance in a pragmatic top-down approach (see below):

  • Based on the strategies, challenges and goals of the company, we analyze the existing processes and define an organizational model with corresponding roles.

  • Based on this, we define the responsibilities in a RACI matrix (RACI = Responsible, Accountable, Consulted, Informed) and assign detailed field responsibilities for all relevant master data objects.

  • In a final step, we take care of the handover for implementation, plan the governance roll-out and install the new organization.

Your contact person

IBsolution_Michael_Mueller_Web

Michael Müller

michael.mueller@ibsolution.com
+49 7131 2711-3000

The development of a data governance strategy is the foundation for the sustainable increase of data quality in the company.

 

The IBsolution Data Governance Framework

Data Governance Framework englischBased on our many years of experience in master data management, we have developed a data governance framework with six pillars that creates the strategic framework for successfully managing master data and permanently ensuring high data quality. This includes setting up a data governance organization and integrating it within the corporate structure. The definition of roles serves to clarify responsibilities and to create a sustainable role concept for the organisation. The tasks and activities that have to be performed within the framework of a data governance program are determined in the definition of tasks. This not only determines what needs to be done, but also which departments of the company perform the tasks.

The definition of processes aims to describe, document and optimize the existing master data processes. Assigning responsibilities creates a clear allocation of the role concept on the one hand to the tasks and processes on the other hand. The responsibilities are detailed with the help of a RACI matrix. In this context, the definition of ownership for the various master data objects is also part of the process. Data maintenance defines how the theoretical descriptions are to be transferred to operational master data management. The aim is not only to define the data maintenance processes from a functional point of view, but also to clarify the technical implementation and describe the change management.

How we proceed within the context of the data governance framework

Vorgehen im Data Governance Framework englisch neuAlthough a standardized approach to data governance has proven itself, the individual characteristics of each company must be taken into account in every project. Data governance only has a chance of success if it is in line with the corporate strategy and supports it in the best possible way.

An analysis of existing processes provides information about how master data management is currently organized in the company. Based on existing processes, an optimized set of processes is developed in line with industry standards and best practices. In parallel, the data governance organization within the corporate structure must be defined. Among other things, this involves the question of whether activities should be mapped centrally or organized in local units.

The next step is to derive tasks from the target processes and a role concept from the data governance organization. A RACI matrix links tasks and roles. In addition, the field ownerships are defined: Who has tactical responsibility for the fields? Who is responsible for operational data maintenance?

Once this theoretical framework is established, the roll-out into the organization takes place.

 

Our top-down project approach

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Strategy for master data management

  • Support in deriving the master data strategy from the corporate strategy

  • Support in the definition of measurable goals and the creation of a master data roadmap

  • Joint development of a communication and change management strategy

Master data organization

  • Definition of an organizational concept
  • Establishment of an operating model (coordination and methods)
  • Support in setting up the organization and roles (nominations, definition)
  • Support during the transition and roll-out of the operating model

Process framework

  • Review and, if necessary, documentation of existing processes in the master data environment

  • Support in the development of optimized target processes and tasks

  • Definition of the tasks in RACI

  • Documentation of the final framework, based on customer standards

Ownership mapping

  • Preparation of ownership templates and task definition

  • Coordination and moderation during the development of the ownership mapping

  • Support for the introduction of a data dictionary

Master data maintenance processes and data quality

  • Visualization of master data maintenance processes (creation, modification, enhancement, blocking, deletion, ...)

  • Definition of the working model for process governance

  • Process documentation and training of process participants

  • Support in setting up data quality KPIs and a monitoring system

Data management organization

  • Setting up the data management organization

  • Supporting the coordinated roll-out with the SAP S/4HANA migration

Further information and offerings related to data governance

Data Governance | IBsolution
Blog

Data governance: basic framework for master data management

A stable strategic foundation can provide the best possible support for the challenge of operational data management and maintenance. This foundation for master data management in the company is called data governance.

Read more
Implementation of data governance | IBsolution
Webinar

Strategic implementation of data governance within a company

Data governance encompasses people, processes, and technologies required to manage and protect data assets. In this webinar, we will show you how to set up data governance in your company.

Watch now

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