IIT authored article, as published in a Technical Industry Magazine. To see the original article, click here
In this era of social media and internet, there is a plethora of data to be stored and processed. The data can be from internal resources, customer data on the web/mobile, and other external resources. In larger organizations, there would be many services or products, and there would be many applications holding various data about customers, suppliers, employees, projects, finance, and accounting. Keeping all this data accurate, synchronized and consistent is becoming a challenge as companies become more reliant on this data.
Consider an example of a bank, which offers loans and checking/savings accounts. The bank may have different system for loans and different systems for consumer banking. If a single customer has both products from the bank, and this customer relocates to a new home, will the new address automatically be reflected in both systems? In addition to this complexity, large enterprises would have varying data in applications coming from other subsidiaries and results of mergers and acquisitions. It is to solve similar issues that organizations are turning to implementing Mater Data Management (MDM) solutions.
There are many commercial MDM products out in the market for the various verticals. The cost can be enormous for MDM systems implementations. However, if implemented properly, an established MDM system can reduce cost, automate processes and provide analytical insights. Regardless of commercial MDM products chosen, organizations must plan adequately. Several issues to consider when planning MDM implementation include:
- Identify the business requirements - MDM is built by collaboration of various departments. The requirements that can be addressed by MDM, must be collated and prioritized. Lack of clear business objectives can result in frequent changes and increased cost of implementation. Also, organizations must assure that MDM implementation is not solely an IT driven initiative. And key business executives must be engaged in this initiative.
- Understand the Business Process Model - The business process flow determines how the information flows through the systems for the various business activities in the organization. It is important not to confuse the business process with the business application. At the end of the day, all new IT applications must improve the processes, without having end users need to adapt their process to the new applications. There will be situations requiring compromises, but proper analysis must be done, and stakeholders need to be educated.
- Data Governance and Data Quality - Building an MDM system just to collate data from various systems, format it based on business rule and generate a consolidated record is just not enough. A data governance plan that manages the data that goes in and out of the MDM system has to be defined. The data usage and policies, data standards, defined roles and responsibilities of contributors and authoritative sources is necessary. Data governance plan would also result in better issue resolution process, and higher confidence in the data. It is also important to look into the quality of the data being imported. Data standardization and cleansing efforts may be required prior to import, and this can add significant efforts.
- Understand the metadata environment - In an organization, various systems would have evolved over time, on different platforms and then there are systems from the acquired companies. The recommendation is to have a single metadata definition. However, the experts in the field agree that, in certain contexts (e.g. users in different countries), different definitions exist for the same data element, and at times it is a necessity. The centralization of master metadata would limit the efficiency of the applications, whereas no control would lead to data duplication and integrity issues. It is recommended to have a 'virtual centralization' of managed metadata by allowing each department to manage its own proprietary definitions.
- Have the right tools - In the market there are various MDM products/vendors/ service providers, and not all would be the right choice for your organization. The MDM products must be accessed based on the current and future business requirements, data integrity plans, information flow across various business process and the various master data views required. Selecting the product and then trying to bend the requirement as per the product capabilities would defeat the purpose of building the MDM system. Several vendors have their own MDM bundled along with their application package. For example, Oracle's Fusion CRM has its Fusion MDM, Microsoft releases Dynamics CRM along with the Microsoft Master Data Services, SAP releases Business by Design for Chemical bundled with SAP MDM etc. In its own, each of them adds great value. But the downside is that, since they are from different vendors, it does not communicate with each other.
- Define phases and goals - MDM implementations are typically not deployed in a "big bang" approach where all domains are managed across all methods of use. Generally, enterprises start with a limited scope and as MDM implementations are rolled out over several phases, additional domains are added, the method of use may expand, or the implementation style may change to deliver extra business value.
- Assemble a talented team -You can get the executives buy in, and choose the right tools, but without the right team, the implementation will be a challenge. Internally, identify subject matter experts, data stewards, project charters and a sign off process. Externally, take your time to evaluate service providers. Take into account prior experience, references, access to decision makers, vendor's size and stability, and ease of working with the vendor(s). Sometimes very large vendors are expensive and less flexible, and very small vendors do not offer breadth or stability. This will be a long working relationship. Pay particular attention to choosing the right-size vendor with proper experience that you are very comfortable working with.
Master data management is an effective tool for the alignment of enterprise wide data. However, without proper planning, implementing MDM system may result in failures and/or increased costs. An effective MDM design would start by understanding the business process models, assessment of the existing systems, the pain-points, evaluation of the commercial products, and realistic expectations.