Why a Tailor-Made Master Data Management Strategy Will Always be Your Best Bet to Grow
Master data management (MDM) plays a critical role in consolidating and cleansing data to provide reliable information for actionable insights. It serves as a go-to solution in this wave of unstructured data growth that wraps every platform or existing system in the organizational framework to provide a single source of truth. Dietmar Rietsch, CEO of Pimcore, describes the key steps businesses should consider while building an intelligent and smart master data management strategy in 2020.
Data management strategies must help organizations gain the best benefits from their data and data assets. This data can be master, operational, transactional, or any other form. Whatever you strategize for MDM, it forms the backbone of the data management program as long as the program continues. Ensuring that this backbone is firmly architected is one of the factors for reaping the benefits of a successful strategy. A well-planned MDM strategy ensures consistency across integration processes, encourages best practices in data usage and implementation, and facilitates new technology adoption in 2020.
Here are the Key Factors You Should Consider While Building Your Master Data Management Strategy
1. Elucidate your MDM Requirement
Clarify whether MDM is the most suitable answer to your data management problem, or if it is just a technology problem. Map the exact benefits achievable by MDM for every stakeholder, such as whether you are focusing on operational MDM or analytical MDM. Understand which business initiatives require better master data to succeed and clearly lay them out. This step is crucial to assess the effectiveness of MDM implementation. A clear definition of benefits makes it easier to track the return on investment at the end of each implementation phase.
2. Prioritize the Criticality of Data
Recognize the most important master data in your organization (customer, product, process, financial, etc.) based on business process enablement and optimization. Now, identify the appropriate solution for them. The solution should support holistic implementation and end-user experience across domains, use cases, and deployment methods. You should also evaluate the feasibility of simpler solutions, for example, customer data platforms. Also, identify your organization's most fragmented, but reused, data domains. You can focus your MDM efforts on those domains and easily expose newly managed master data early in analytics platforms.
3. Evaluate Technology and Architectural Style
Identify the architectural role of each MDM solution in your approach to handling enterprise information management (EIM). Compare the benefits and limitations of enabling technology choice, architectural and implementation style, keeping in mind your strategic goals and organizational impact. You can use MDM to implement sound information architecture fundamentals, such as canonical transaction formats for master data domains, as part of a well-managed data integration practices. Consider which implementation style is right for you such as consolidation, registry, centralized, and coexistence. Moreover, check whether the solution may be the re-engineering of existing business processes or better governance practices. If you are not reluctant to put your master data in the cloud, then cloud-based MDM deployment is also a viable option.
4. Keep a Tab on Cost
MDM implementation is not a 'plug and play' game. It involves lots of stakeholders across the board. Don’t fall prey to the hype and confusion related to the MDM solution. The only thing that matters is what your organizational demand is, and how an MDM solution right sizes into your budget and requirement. Different vendors offer many innovative or advanced features. For example, AI, ML, and NLP are rising trends. But you must analyze whether these features add values to your business objectives. The most important thing is a robust technological foundation of your MDM platform that scale fast with the growing data velocity and demand. Save the cost where you can. If a license-free solution like an open-source MDM platform can work for you, you must give it a try.
5. Assess Governance Rules
All data is not master data. Classify only the most widely shared application data as master data. This helps minimize data governance efforts to the least amount of data while simultaneously creating the most significant impact on business outcomes. All other less-shared application data should be subject to application data management.
6. Start Small and Think Big
An MDM program is more than just an implementation of a technology solution. In 2020, factors like organizational silos and political complexity will remain a challenge for organizations. MDM is a big investment, so assess factors like a cross-department consensus, organizational culture, and data-driven maturity beforehand to succeed fast. Avoid executing your MDM strategy in one go. Prioritize those data sets that are causing serious challenges to your business operations. First, try to roll out your MDM strategy on a smaller set of data such as your product information, digital assets, or customer data of a specific territory, then scale it across the geography.
7. Keep Your Data Up to Date
Outdated data can cost you huge dollars. Maintain a single source of your data and regularly update and sync them to get the maximum business mileage. With information accurate and up to date, you are most likely to see increased momentum in your delivery and unlock the hidden potential of your enterprise data.
Source: Read the full article at CMSC MEDIA.