Avoid The Graveyard Of Master Data Management Projects
Updated: Jan 25
It's a brand new year, and it's been a fun 2021; as we head into 2022 thought we share a few experiences and lessons learned on some of our master data management projects. We hope this article will help you plan your MDM project and avoid some of the pitfalls and missteps that can lead to failure.
Master Data Management Projects need executive sponsorship. A critical step, you need someone high up in the corporate hierarchy to support and actively monitor the project. When you do not have active participation from senior management, you will see a drop in the commitment to the project. Delays in data availability from source systems, resource allocation to the project, and a lack of data governance agreements between teams are symptoms of this problem. In addition, MDM projects can lead to a power-play between different departments, data owners, and other stakeholders. Senior-level executives can help iron out some of these issues.
Recommendation: Executive sponsorship and involvement are critical for the project to succeed.
The technical team is the most crucial aspect of a Master data management project. The technical team can either drive the project straight to the graveyard or create the magic to succeed. One common issue we have generally seen is that customer technical teams unfamiliar with master data management concepts struggle to understand some of the process steps. For example, fuzzy matching and artificial intelligence based match resolution is an area that takes time and effort to grasp. While it is hard to find, the technical team members should have at least have one project life cycle experience in MDM projects. The other major issue is that MDM projects involve multiple technology stacks; they are not plug-and-play except for simple use cases. Getting a customer's technical team to go from zero to building and rolling out a production-grade solution in a short period is an unreasonable expectation.
Recommendation: Leverage the Vendor's technical team to deliver at least phase-1 of the project into a production environment. Get your team trained and ready for the next set of enhancements.
A team is required to maintain and manage master data management projects. This could be news to many people who do not have experience in master data management systems. However, the actual work with a master data management project starts when the solution moves into production. This is because data flows from multiple systems and changes based on different process steps. A team needs to be in place to handle the various aspects of data management. A governance team to adjudicate data-related issues. A technical team to address the problems around data flows and data integration in real-time and batch. Without a good team in place, data in the MDM system degrades quickly. Once users lose trust in the data, it is hard to regain confidence, and the solution can become irrelevant quickly.
Recommendation: Plan for a data governance team from the beginning, involve the team early in the decision-making process.
Please do not shoot for the moon; these sound great in books and podiums. Master data management projects need buy-in and modifications to the source and target systems a lot of times. Trying to boil the master data ocean is a sure-fire way to introduce confusion and disgruntlement. Start with one or two domains. Generally, the Customer domain is the most critical for the organization. It takes time for all the systems to come online and start sending and receiving updates. One other important issue to watch for is defining too many rules. Sometimes users start defining rules because they do not understand the capabilities of an MDM system. We had a customer's team member who came up with an excel spreadsheet full of rules to match a customer. He started his rule book with a rule to match the first three characters of the first and last names and extended this concept to 300 lines of variations and sub-cases.
Recommendation: Start with one or two domains and roll out the solution quickly into production, win the users' confidence, show them the power of the MDM solution.
Please do not forget data quality. Data in the MDM system is supposed to be the golden version of the data and the reference record for the entire organization. Imagine serving up this data with missing, incorrect, inconsistent data elements and data that does not meet the business definitions and business rules. Users lose trust in the MDM system quickly and question the solution. Many MDM solutions do not include data quality as a part of the standard stack, it's usually an add-on, or you need to buy a separate data quality solution. This will add to the overall cost of the solution and, if you do not have the budget, your MDM solution is compromised.
Recommendation: Data quality is a critical part of the MDM solution, do not compromise on this essential software.
Sign up for a demo of our Zero license cost OpenDQ solution. OpenDQ has built-in data quality, data governance, and multi-domain master data management. In addition, one can extend the solution to include Customer 360 dashboards and Knowledge graphs.