As we established in the first blog post in the series, MDM can be divided into two topics; "master data" and "management", where master data is the company's core information, and management is the management and governance that you introduce in your organization in order to implement your MDM strategy.
Managing and maintaining the necessary data governance is not only a technical exercise but a continuous and structured process that requires a nonstop focus.
It is therefore important that you organize yourself in a way that ensures ownership and anchoring in your business. Therefore, in this blog post, we will look at what this organization could look like.
Organization
The management and associated executive roles should be organized to ensure the necessary organizational anchoring throughout the company. MDM often spans several units, and your ability to collaborate in everyday life is therefore important in order to be successful with MDM.
It can be beneficial to place responsibilities and tasks in a centrally located data governance unit that acts as a competence center if your company already has a shared service approach to cross-cutting functions - such as HR, IT, legal and finance. In addition, a competence center can be an advantage in a start-up phase and where the level of maturity with MDM is low. The competence center will thereby become an anchor point and leader for an ongoing interdisciplinary focus and will in addition act as advisors and sparring partners for your entire organization.
The competence center must, in collaboration with stakeholders across the organization, ensure that the overall policies and procedures are integrated into all the company's business areas.
The chosen kind of organization, which also becomes the basis for your collaboration model, must be addressed at all 3 levels; strategic, tactical and operational in terms of:
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Organizational structure – including reference lines, escalation paths and mandate
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Distribution of roles and responsibilities within and across the organizational structure (a classic RACI model can be used)
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Policies - as a minimum policies for data security, data ownership and collaboration model are addressed
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Procedures - as a minimum for decision, problem-solving and maintenance (which can advantageously be based on the data life cycle)
To ensure compatibility with your company's vision, strategy and priorities, it is recommended to establish a steering group whose main task is to prioritize and approve new, larger MDM initiatives (which often turn into projects). The steering group can be composed of permanent members from the Executive Board, the head of the competence center and decision-makers from the business units.
In addition, the involvement of a business sponsor can help to ensure that there is a focus on the overall business need and that the responsibility for releasing the necessary resources for the project phases is placed - and above all, that someone is responsible for anchoring, ongoing maintenance and operation.
For all major MDM initiatives, it is recommended that you follow a fixed delivery model and thereby also establish project management and delivery group consisting of stakeholders for the respective data area in focus, data owner, process owners and data stewards as well as members from the central competence center. The project management and delivery group will be shut down when the initiative has been completed and the MDM task in operation.
Roles and responsibility
Selection of relevant roles
Once an organization is in place, it must be decided what roles should be at each organizational level. It is important that the roles cover both business ownership, technology and solution ownership as well as process ownership.
MDM roles can vary from company to company depending on size, complexity and needs, but some of the classic roles are; data owner, process owner, product owner, master data manager, architect and data steward.
Make sure that from the very beginning you have an overall role description that tells; activities you are part of, areas of responsibility including clarification of what you are not responsible for, mandate, reference lines and skills.
RACI division of responsibilities
Once the roles are in place, it is a good idea to go a level higher and divide responsibilities between the roles. You may find that some of the work tasks in the individual roles, based on the description, overlap other implemented roles in the organization - especially within other data departments such as BI, Analytics and IT. Therefore, we recommend using RACI to break down the responsibilities and to make some of the interfaces visible to other roles.
In addition, RACI is often used for projects or processes where several groups of people are assigned a task and have a shared responsibility, which is also the case within MDM. It helps streamline processes by ensuring that each team member and all stakeholders understand their specific role.
If you do not know RACI, we will briefly summarized it;
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R stands for Responsible: The one who performs the work and completes the task
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A stands for Accountable: The one who delegates tasks, and is the last to review the delivery before it is considered complete. This person also has the authority to make decisions
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C stands for Consult: The person who provides input, knows the influences of other tasks and is a domain expert
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I stand for Inform: This person is kept in the loop with information about progress, impacts and risks
Assignment of roles
There are different principles for assigning roles in the organization, and it can be difficult to choose the right approach to allocating data ownership and data stewards, especially because the use of data for a single data object affects the entire organization and systems. Of the principles you can choose, five different can be mentioned: Per business unit / organizational, per business process, per data area, per system or per project.
To succeed with MDM, you must have a holistic perspective on the specific tasks, which is why it can be advantageous to stick to one of the first three principles. The last 2 become more silo-oriented and challenge the ambition of a holistic approach to MDM and one golden record, which is why these should be “the last choice”.
A rule of thumb is to choose the same principle of allocating data ownership and data stewardship. So, if data ownership is assigned per business area, data stewards should also be appointed per business area. However, the location of data stewards may depend on the complexity of your business and the number of systems.
Tips for data ownership
We often find that it can be difficult to introduce and implement data ownership, and it is therefore neglected in a busy everyday life. After all, data is widely used in the organization today, so who is actually responsible for it?
Here are some tips to help you:
Start by looking at the relationship of the individual departments to a particular set of master data:
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Who feels the most pain when data is incorrect?
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Who worries about data quality?
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Who will typically be the first to identify quality issues?
Then identify the person in that department/area:
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Who has the authority to change business processes and IT systems to improve the data quality?
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Who has the budget and resources to solve the quality problems?
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Who has the knowledge and ability to initiate activities for the computer?
In the end, all that is left is to find the right people in your organization to fill the roles, communicate it, and then start the journey of implementing and anchoring your new MDM Governance.
We have now, in a series of blog posts given you an introduction to the key parts of master data management, which has hopefully inspired you to investigate the status of MDM in your own company. Where should you develop? Where do you need to get better? And how much or how little do you already know needs to be maintained?
In the next and last blog post, we will give you some inspiration for dos and don’ts, you can take with you on the journey.