How to deal with master data management properly

Master data management is a common term entering technology for a long time. However, some companies today are not still learning from the mistakes made by previous pioneers.

Master data management is among the most popular terms mentioning in conversations about data management. The ideas are not new and strange yet the combined concepts are now being researched and studied under this new kind of data management. Master data management involves all of the data which is vital for the business work. For most companies, this kind of data is related to customers and transactions.

Every company, no matter how big or small it is, comes with problems with data inconsistency. Data is gathered from different apps and various parts within the company, thus its quality and timeliness is all different.

According to some firms, their data comes from a number of different sources of customer data as well as product data.

What is more, data is taken from systems which are in enterprise resource planning to supply chain as well as salesforce automation systems. According to a survey, only 40 percent of companies make effort to assure data quality throughout the enterprise. And even 22 percent of companies do not have any data quality tools.

It can be witnessed that dealing with master data is not a really difficult task as for a long time, a lot of data management practices have turned up.

Businesses ought to adopt master data management

First and foremost, master data management are relying much on business leaders who are responsible for their data. If problems with data are considered to be an IT difficulty, it will be really hard to improve. All businesses have their own kind of data and of course, none of them want to stop controlling it.

There was a consulting engagement for a global company in which a lot of business data owners in all over the world came to a central office to have a discussion on common standards. Each of them had their own common standard and wanted to tell others to follow them and stop what they were doing. They tried to prove their opinions were right and others were wrong. All of them made effort to come to an agreement towards the problem.

Giving up control is a difficult task as it will demand on leadership as well as a give and take activity from different lines of a business. In several years, data governance has turned up to be a common term relating to capturing ideas of getting business ownership and assigning responsibilities for data consistency and quality to some business staff, and making different processes and arrangements inside the company to make it work.

According to another survey, only 24 percent of master data management projects were able to reach success. It is predicted that the large percent of failed projects was resulted from little or no effective data governance activities.


Moving to the next issue, master data management should be a joined-up exercise in which the same approach is applied to different master data domains no matter what they would be, a customer, a product, an asset or a person. Currently, a lot of master data management technologies improved to be able to manage one specific kind of master data and in spite of the fact that many service providers nowadays claim that they are in multi-domain, the reality is not often the same as what we saw on advertisements.

Some companies even do not have any idea about opting for master data management technology as the market is increasing daily and everything works effectively or they trust completely their choice to consultants who may even have no experience in the field. The assumption that everything is fine is totally wrong.

What is more, some service vendors these days even do not have any track record with product data or they have no discernible master data management product. When you start to choose a master data management solution, you should not rush into any options immediately. Instead, you need to carry out a right technology evaluation of software tools which already had some track record in that area.

This is another example. When visiting a consultancy firm that recommends many master data management projects to a customer, you may be tempted by their advertisements. However, when you mention that you would like to know every specific things about that project, you may realize that that firm even has no track record in delivering master data management projects. They advise by basing on the brand instead of having a deep and close look into whether the company ever has delivered a proper and successfully master data management project.

Think big, start step by step

The last lesson to learn is that you should think big while starting small. This lesson is applied to many things but especially true when it comes to master data management. If you want to get business buy-in to your work, you should start by choosing a manageable area resulting some problems in the business no matter where that kind of data comes from.

If your master data management project is able to deliver a big improvement successfully in a small and specific area within a few months, there will be many improvements later and other parts of the company would be more receptive.

In spite of the fact that this approach would take you longer time but it will lead to more success than big bang approaches which aim at dealing with all data domains and issues at one time.

When you are at the beginning of master data management projects, you should learn to make sure effective data governance, opt for technology rightly, only choose people coming with a track record in delivering master data management and finally take into consideration all data domains but start step by step wisely to deliver the right value throughout the organization.


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