How to develop a governance model for Masterdata Management

Masterdata forms the cornerstone of the ability to create effective processes. And having a strategy for, and control over, your masterdata is one of the most important prerequisites for a successful system implementation project.

Despite this, the topic is often thrown between departments like a hot potato. Masterdata is shared between different processes in an organisation, and it is important that there is a sense of ownership within the business to manage each part of the MDM programme. Typical stakeholders or owners within MDM can be Supply Chain, Category Management, or HR & Payroll. There are also cases where it can be a completely separate department depending on the size of the organisation.

The importance of responsibility distribution within MDM

To manage MDM successfully, it is crucial that there is a governance model, that it is clear, and that the right department has responsibility for the data. Without a proper governance model, masterdata issues that arise can float around without anyone taking ownership. This can result in poor data quality as well as frustration towards parts of the business where they believe the problem lies.

- Is it IT that owns the masterdata, since they configure the systems or solutions that hold the data?
- Could it be that the Quality department owns the data because they have the detailed information about all articles?
- Is it Sales that owns the issue because they manage all customers?
- Is it the Project that is responsible for managing the masterdata?

The most important parts of the governance model

There is no complete right or wrong in how you can build a governance model. Every organisation is different, so the model for masterdata should reflect that. Building a model for masterdata can be a large activity, but it must not end there; the governance model for masterdata needs to remain after the project and be actively worked on. Below are some important points to consider to ensure your MDM process is successful.

Data governance roles

Roles with the task of defining the use of masterdata and how data should be managed. This role must clarify how admins in systems set up various data and also drive requirements from the business. The role determines, for example:

• • • Time and information needed to create a new customer.
    • Information that must be mandatory when entering new data in business systems.
    • Mandatory quality rules.
    • How masterdata is consolidated between subsidiaries/affiliates.

These are just a few examples but there needs to be coverage for all incoming data components within an organisation: vendors, customers, articles, etc.

Process and policy

With or without a dedicated department that manages data, it is crucial to have a plan for how to capture and use it. The process to add, edit, approve, or merge data needs to be well thought out. You need to cover scenarios that may arise and plan to be able to resolve them. In summary:

• • • Identify risks and proactively prevent them by building a robust creation process.
    • Follow your business needs and potential regulations within your industry.
    • Ensure you have technology and tools to support the process.
    • Engage different departments to create buy-in to help adopt new standards.

Masterdata list

If you are in a situation where you manage many data registers or just many data points, you can create a masterdata list. In other words, rules and a plan to approach your masterdata. There are mainly a few points that are relevant:

• • • Standardise and clean - Ensure data is up to date with periodic reviews over quality. Set a standard and report changes.

• • • Maintain and improve - Automation and machine learning can be useful tools to maintain and improve quality over time. They can be used to identify, merge and clean records or flag data points outside tolerance levels.

• • • Always relevant - Masterdata is not just relevant for large organisations. All organisations managing complex data sets and multiple data sources can benefit from developing masterdata work.

Masterdata that matches business needs

Finally, it is easy to think of masterdata as something purely technical. But if you really want to optimise your digitalisation journey, masterdata must align with business needs and how they will develop.

There has long been a focus on MDM and on the importance of supporting business needs with technical solutions within Masterdata and we at HerbertNathan & Co have over the years written a large number of blogs that are about or touch on masterdata. Among others, we can recommend the blog Masterdata is super boring but super important from 2018. Although many years have passed since it was written, the views are still very relevant. Masterdata will not be a one-off project every five years. It is rather a difficult-to-catch process that needs to develop with the rest of the business if you really want to benefit from digital solutions.