How do you evaluate and select MDM tools and vendors?

MDM is like the boss of data—it keeps everything consistent across all the systems and applications a company uses. It's like the glue that holds everything together, ensuring there aren't any messy data mix-ups and helping everyone work more smoothly and efficiently.

In all enterprises, the data is entered/injected from multiple sources/ channels/ people. So, its very likely that the data will be either Duplicate/ Not confirming to standards/ Inconsistent. This will lead to issues/ mistakes in downstream systems (e.g. at the time of order entry, sales guy will select one item, shipping person will ship another item (with similar name)). To Avoid all these issues, we must have a proper Data Governance mechanism, Data Standards (nomenclature), Data Approval processes. These will ensure consistent data across enterprise and eliminates redundant data

A practical example of the importance of MDM for an organization is the following: a company that sells chemical products needs to take a series of precautions with their transportation and storage. It is through an efficient MDM that hazard information and government handling requirements are available to logistics professionals. Without this data control, a dangerous material could, by mistake, be stored in the wrong packaging or transported inappropriately, creating the risk of accidents and fines from inspection agencies.

Master Data Management is a solution that derives the single source of truth (also known as golden records) for data entities. In my definition, any logical entity that is associated with almost all the lines of the business, and has multiple source points qualifies to build master data on it. We need Master Data to avoid inconsistencies, duplicates, and out-of-standard data. Master Data helps business make efficient decisions; it helps business processes to run efficiently; it helps organizations move towards data-driven environment.

Selecting Master Data Management (MDM) tools and vendors involves defining your organization's needs, conducting market research, evaluating their features, considering deployment options, and assessing data quality and governance capabilities. The total cost of ownership (TCO) should also be considered. A proof-of-concept or pilot project should involve key stakeholders to ensure the chosen solution meets all needs.

Data Steward is kind of Custodian for the data. He is the one who defines Data standards, data entry points, approval workflows, data events and data policies

Data stewardship most certainly is a critical capability of MDM and should be part of your MDM vendor evaluation criteria, but data lineage is not. Data lineage capabilities are typically supported by data catalog software, which may also be referred to as data governance software, or metadata management software.

Data Stewardship refers to the role, created to support responsibilities on data, as part of Data Quality Management and Data Governance program. It also refers to the process that involves Data Stewards. Data Stewards know the system and they take help from Data Custodians to apply the changes. Data Lineage refers to the passage or trail that shows the origin of a data element, its travel into other entities or systems, and the end. Data Lineage highlights the systems affected when making changes to a data element. Data Lineage can be developed on 2 types of metadata : Technical (Technical Lineage) and Business (Also known as business lineage).

Data stewardship role is all about making sure data is properly defined, initiated and secured . Data stewards are the custodians of the data responsible for the data. Data lineage helps to track the flow of the data and its dependencies

I have been working in the MDM industry for almost two decades. During this time, I have observed that technical capabilities are often the primary criteria for vendor selection. While it is important to evaluate and consider vendors with superior features, organizations should also consider other factors such as the quality of the vendor's support, best practices, and availability of skills and partners to ensure successful implementation of MDM. It is also essential to understand the vendor's vision and product roadmap and focus on incorporating modern technologies such as AI. By doing so, organizations can ensure that their MDM strategies are aligned with the latest market trends and can reap the benefits of these technologies.

Efficiency of Matching mechanisms, Possibility of adding custom-made matching logic, Heterogeneous integration of data, Performance on handling high volumes of data, Capability to support Centralized, decentralized & Hub and Spoke models, Inbuilt Stewardship process that sends notifications and alerts, Easy configuration of roles and groups of Stewards and Custodians: are some of the features I will look for in an MDM tool.

Drawing from my nearly 8 years of experience in MDM, I emphasize prioritizing core capabilities. It's crucial to assess a vendor's flexibility in integrating AI/ML algorithms to enhance matching engines and overall quality and enrichment features. Additionally, considerations should include data quality, reporting, analytics, seamless integrations with inbound and outbound processes, and compatibility with third-party enrichment tools. High availability, scalability, and adherence to data protection regulations such as GDPR, HIPPA, CCPA, etc., are also significant factors.

Also look for a tool that not just solves your today’s problem but can solve your future needs and fits in your future landscape.

Evaluating a MDM tool starts with understanding of the scope of the project. Need to know why MDM tool is required , which all features you are looking from the tool . Business objectives and use cases should be clear. Next step is to evaluate vendors as per the top parameters required for the project goal . Invite them for demo and ask them to showcase your usecases so that you can judge them whether your defined scenario will work in that tool or not . Once you have judged the product technically, last is the cost of the tool which also matters in decision making

I agree with a scorecard approach - assuming you are scoring the vendor based on a real-world evaluation criteria. Ultimately, your POC should be tied to a first-phase MDM implementation, where you can easily transition from the POC to the implementation phase.

1) Always check their reviews on Gartner and check their standing on the magic quadrant. 2) You can always ask the Vendor for a POC before committing to a long-term deal.

??Define the criteria’s on which you want to judge the MDM tools ??Organise demo of the tools and check them on their ability to perform the use cases as per set criterias ??Create a scorecard and give weightage the features and criteria on which you want to judge them ??Give scores as per the capability you see during demo ??Once scoring is completed ,you can rank them tools as per ratings matrix ??Also remember comparison should be done Apple to Apple, you can’t compare a tool with expertise product domain to a tool which is strong in customer domain. That’s why said defining criteria is the most important aspect of MDM Tool comparisons . We did the comparative study at Nvizion Solutions, you can contact me for MDM tool comparison sheet

Request for a tailored demo as each business works differently. Provide a sample of your data set and see how easily that can be represented in their tool without customization.

Comparing MDM Solution vendors involves trade offs like the level of service and the cost of implementation and running the system. MDM should be viewed from the angle of Building a house with MDM being the foundation, a strong foundations helps the company to scale in so many ways including the adoption of AI to train transactional data sitting on top of the MDM foundations as well as give accurate financials for planning and forecasting.Note that there is no one size fits all solution , but there softwares that accommodates incremental changes that leads to near perfect system.Another thing is ease of use / user adoption as well as the integration with other systems for smooth data transfers and business collaboration.

Consider the following important things while deciding the best MDM tool for you: 1) Your MDM use cases and the ability of the tool to implement them 2) Time required to go live(lesser the better) 3) Vendor's reputation and Gartner comments

you can check existing successful implementation in your domain and according to your geographical area such as Banking, Healthcare , Real estate , Insurance , Entertainment ,etc. If the vendor has done implementation in your field ,there is option to consider Other way is gartner ,Forrester research reports

Beyond features and pricing, assess vendor stability and long-term partnership potential. Ensure they offer training resources, regular updates, and a supportive user community. This guarantees that your MDM tool can evolve with your organization's changing data needs.