Master Data Management (MDM) can create a 360-degree view of core business resources using master data; a uniform set of identifiers or attributes that describe the primary elements of the enterprise. For an efficient management system, data modeling as a core component can be used to explore data-oriented structures, technically integrate different systems, and align business rules. Using data modeling, data attributes are assigned to entity types and associations are created between entities. There are multiple ways to represent these data models, however, to leverage the benefits of modeling, it is always important to have a pre-determined structure to minimize the costs of creating and maintaining documentation or implementing alternate solutions that were not planned.
Creating checklists that focus on critical product related parameters and actions that are needed during implementation phases can be very helpful for project preparation and project revisions. Successful MDM implementations require prioritizing practices and technology deployments as it helps implementation teams to align their available tools to execute processes and meet expected goals. Clarity on project timelines, deliverables and full scope is vital along with detailed documentation to eliminate any roadblocks.
The dynamic nature of the business environment is a major factor as specifications and goals often change over project lifespans. Most data management strategies operate using conventional waterfall structures for projects that have complex dependencies or clearly defined time periods of design and build. However, if there are consistent revisions or updates that are often needed for projects, a more flexible approach should be taken by employing agile methodology instead for quick and high-quality iterations resulting in faster deliveries.
Based on key factors such as scope, budget, teams and constant feedback, a hybrid approach using best practices of both methodologies, or visual hierarchies can also be an excellent way to minimize delays, create buffer time for feedback implementation and quicker turnaround.