Securing confidence in ‘rightness’ of the master data

Securing confidence in ‘rightness’ of the master data

I was reading an excellent post by Julie Hunt on how business priorities point the way for MDM. (Originally posted on Hub Design Magazine).

Julie explains how important it is to focus MDM implementation on what matters most for the goals of the business. The great way to do this is by planning and re-planning at regular intervals of project execution to evaluate current state of the implementation and make minor tweaks when necessary (More like an agile methodology). This kind of contemplation and focus helps in creating reliable, unified and quality data in order to make crucial and timely business decisions.

What captured my attention in the article is the section which lists the key challenges for MDM practice and solutions. One of the items Julie mentions here is the difficulty in gaining confidence of the users in ‘rightness’ of master data. If you are in MDM consulting and have worked with many customers for long time, you will agree to this at blink of an eye.

We tend to think, why gaining customer confidence in data residing in master data management system is a big worrying factor as the utter purpose of MDM is to make sure there is ‘right’ data in first place. Isn’t achieving superior quality of data an integral part of MDM? Why would it be difficult gaining faith of customers in MDM?

Well, there are many aspects which lead to this situation, some of them are-

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Unlike other product adoptions, MDM implementation affects larger part of the organization. Once MDM solution is in place, many consumers of data within the organization will be directed to refer MDM for their key data requirements. This generates lot of skepticism because most of these folks have to leave their 100 year old ‘trustworthy’ system and start relying on the new kid in town.
The processes and technologies used in MDM implementation are fairly advanced compared to those typically found in existing home grown/legacy systems. The new age MDM tools require complex configurations and settings. For example, data matching algorithms, standardization rules, deduplication and survivorship functionalities require enormous experience, technical and logical skill. Most of the time, customer technical folks who eventually will be taking care and enhancing the solution lack these expertises. This generates lot of chicken heartedness resulting in mistrust.
The clean nature of data in MDM often raises eye brows and is dealt with scrutinizing eyes during initial phases. This is mainly due to the user’s comfort and know-how part of old systems. The users are usually well acquainted to the existing applications which manage their data and will have knowledge of loopholes and the tactics to overcome them.
The fear that MDM may not be properly built as most of the time the implementation team will consist of consultants. The general consensus among the client team members is that the project team hired to do the specialized work will not know as much as they themselves know about the organizations business. If you have observed it clearly, this angst often shows up while interacting with client teams.
Usually, there is not enough knowledge about core MDM concepts among client team members. Lack of planning and execution of training in the project plan perhaps is the single most contributing factor to this causing a lot of doubts among the crowd.

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Gaining confidence of the users of the system and technical folks working in the project is a crucial factor in every MDM implementations. This is a challenging task mainly due to the fact that each of these people involved with MDM are from different areas of the business and have different expectations. In my future posts, I will explore some of the key steps which will help in building this trust.

Do share your thoughts on what other factors detour customers confidence during such large MDM implementations. I would love to hear from you.

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