When requests for proposal (RFP) for master data management solutions are narrowly focused on a short-term business need within a single business function or on a single business data type - such as customer (customer data integration - CDI) or product (product information management - PIM) - critical master data management (MDM) functionality can be easily overlooked. Wrongly, IT teams and systems integrators run the risk of selecting and investing in technologies that may be difficult to extend to other data types or difficult to scale across the organization. Worse yet, such solutions will likely require costly and extensive custom coding in order to add additional business data entities or data sources, or to extend the system to other lines of business or geographies. In order to avoid these costly pitfalls, bolster the return on investment, and reduce the overall project risk, it is important that your RFP include key business data requirements across several critical business functions, including sales, marketing, customer support and compliance.
By including the most important MDM requirements in your RFP, you will achieve greater success with your MDM initiative along with a more rapid deployment and faster time to value. A well thought-out RFP will allow you to quickly reap the returns from selecting a complete and flexible MDM platform that is able to address both your current and future business requirements.
Ten MDM Blunders to Avoid
1. Failing to ensure multiple business data entities can be managed within a single MDM platform.
When you select and deploy an MDM platform, make sure it is capable of managing multiple business data entities such as customers, products and organizations all within the same software platform. By doing so, system maintenance is simplified and more cost-effective, which results in lower total cost of ownership. A less favorable alternative is to deploy and manage separate master data solutions that each manages a different business data entity. However, this approach would result in additional system maintenance and integration efforts and a higher total cost of ownership. Another advantage of an MDM platform that can handle multiple data types is that implementation can begin with a single business data entity like customer, and can later be extended to accommodate other master data types - resulting in rapid ROI.
2. Ignoring data governance needs at the project or enterprise level.
Data governance is unique to each and every organization since it is based on the company’s business processes, culture, and IT environment. However, companies typically select an MDM platform without much thought to their enterprise data governance needs. It is critical that the underlying MDM platform is able to support the data governance policies and processes defined by your organization. In contrast, your data governance design could be compromised and forced to adapt to the limitations of some MDM software platforms with fixed or rigid data models and functionality. Controls and auditing capabilities are also important data governance components. In order to properly support this functionality, your RFP should require the MDM platform to integrate with your security and reporting tools to provide fine-grained access to data and reliable data quality metrics.
