How to build a Masterdata governance model

Masterdata forms the basis for efficient processes. And to have a strategy for, and control over your master data is one of the most important prerequisites for a successful system implementation project. Even so, the subject is often passed between departments like a hot potato.  it is one of the prerequisites for a successful project.

 

Masterdata is shared between different processes in an organisation, and it is vital that there is a sense of ownership in the business to handle each part of the MDM (Master Data Management) program. Typical stakeholders or owners within MDM could be Supply Chain Manager, Category Manager or HR & Payroll.

 

 

The importance of liability within MDM

For a successful MDM it is vital that governance model is clear and that the correct department, whoever it might be, is taking responsibility for the data. Without a proper governance model, masterdata issues that arise could be floating around with no party taking ownership. This results in bad data and frustration towards other parts of the business.

 

– Is the IT department the ones to own master data because they configure the system or solution?

– Is it the Quality department that owns the data because they have information on all the Items?

– Is it Sales that own the masterdata because they handle the customers?

Is it the Project that is responsible for handling the masterdata?

 

 

Important parts of the governace model

There is no complete right or wrong in how one would setup a governance model around masterdata. Every company is different and the model for masterdata should reflect that. The governance model of the masterdata needs to remain after the project and be actively worked on. Below are some key points to keep in mind to ensure your MDM process is a success.

 

Data Governance roles

Resources that can define and give requirements on how the data should look like. These resources have the role of defining the use of masterdata and how the data should be managed. This role would e.g. be the ones to dictate administrators on what to create during an implementation and drive the requirements from the business. This role may dictate:

 

      • Time to onboard a customer.
      • Information that is mandatory when adding a new item to the ERP system.nformation som ska vara obligatorisk vid upplägg av nya data i verksamhetssystem.
      • Quality regulations that is mandatory.
      • How to merge masterdata lists between subsidiaries.

 

As masterdata spans many business areas in an organisation there must be coverage of all incoming masterdata components, like Suppliers, Customers, Items etc.

 

Process and policy

With or without a dedicated organisation to govern the Masterdata it is vital to have the means to handle this topic. The process of adding, editing and merging data needs to be well thought out. You need to think about your needs and the common errors that could occur with faulty data. In short:

 

      • Identify risks and proactively prevent them by building a solid creation process.
      • Adhere to your business needs and potential regulations within your industry.
      • Make sure to have the technology and tools to cover the process.
      • Involve different departments to create a buy-in to help adoption of new standards.

 

Master data list

If you are in a situation where you are maintaining many data entries and many data points you probably need to do some cleaning. Standardising and cleaning masterdata is a time-consuming task but with a high reward. Ways to having a good masterdata list:

 

      • Standardise and clean – Ensure up-to-date data with periodic audits. Decide on a standard and report on deviations.
      • Mainatain and improve – Automation and machine learning can be useful tools for maintaining and improving masterdata over time. It can be used to identify, merge and clean records or flag data points outside of tolerance levels.
      • Always relevant – Masterdata is not just relevant for large organisations. Any organisations that deal with complex data sets and multiple data sources can benefit from developing and maintaining strong masterdata practices.

 

 

Masterdata that meets the business needs

In conclusion it is easy to think about Masterdata purely as a technological issue. An unhinged solution without implications to the business. However, if you want to really optimise digitalisation, Masterdata needs to align with the business needs and how it evolves.

 

There has long been talk about MDM and the importance of supporting the business’s needs with technical solutions within Masterdata, and here at HerbertNathan & Co, we have written a large number of blogs over the years that deal with the topic, including the blog Masterdata – Super boring but also Super important! from 2018. Even though many years have passed since it was written, the views are still very current. Masterdata will not be a onetime project every 5 years. It is an elusive process that needs to evolve with the rest of the business if one should really make the most out of digital solutions.

Author: Bennet Liranzo