Master Data Management
Insights can't drive action without context.
Nearly 1 out of every 10 people who walk into a hospital or doctor’s office can’t be confidently matched by the person in admissions to one unique medical record.
There will never be one enterprise application configured in a single, consistent way used by a diverse group of departments with different process needs and different customers. Running your complex business in an agile way will always require the integration of business processes and systems, which is why the coordination and automation of maintaining critical business information across the enterprise is so important. Master data management methods and technologies enable effective data governance and accelerate the rate at which business processes can deliver results.
But it’s not an easy fix. Most master data management programs take years to complete because of the required coordination across business groups, and many of those still fail to deliver any meaningful business value. A truly successful program will have all of the following characteristics:
- Coordination with data governance
- Focus on the required business process changes and not the technology
- Appropriate technology and architecture selection
- Prioritized and measurable goals
Get Cozy with Data Governance
“Mastering” critical business information necessarily requires the coordination of cooperative decision-making across different departments and lines of business who all have different needs and objectives. A strong data governance program will help to drive the value and prioritization of master data management implementations, and master data management will help data governance deliver on its promises more effectively than without.
Master data management also involves technology implementation, application integration and new data maintenance processes that may or may not be on the data governance radar. So, don’t just wait for data governance to tell you what to do. Be sure you are aware of their priorities and keep them informed of your success and you’re sure to create a virtuous cycle of growing business value.
Focus on People and Processes
When you search for master data management, Gartner’s Magic Quadrant for MDM vendors will show up near the top of the results. To do master data management requires the implementation of technology, whether you choose to build your own purpose-built solution or use an MDM platform. The implementation of that MDM solution will necessarily disrupt existing business processes and change both how applications are configured and what information the application is responsible for. In tandem, the processes implemented with those business applications will also be changing.
Change is hard. So, the implementation of a master data management solution will require a heavy focus on collaborating with business process owners and users to determine how their processes will change. Decisions on those changes will drive the MDM requirements, and the MDM capabilities will drive those decisions.
Be Choosy about Technologies and Solution Architecture
You can certainly choose to develop your own purpose-built master data management solution for a particular scenario, but there are vendor platforms that can be used to accelerate development time and leverage best practices and standards. Before jumping into vendor selection though, think about the architecture that will best match with your enterprise architecture and goals:
- Registry
- MDM is used only as a central way to logically link records.
- Consolidation
- All source systems should feed into an MDM hub that provides a unified, integrated and matched view across those systems.
- Centralized
- All business processes that need to access an existing record use the MDM database as the authority and all new records are created in the MDM database first.
- Coexisistence
- A blend of consolidation and centralization in which data can be authored in the MDM database or in core business applications and updated information can flow both upstream and downstream.
Once you know the architectures that you will need to use for each of your master data management use cases, then you can review your technology options and find the best combination of tools to achieve those objectives.
Stick to the Program
Many master data management implementations end with the platform installation and the creation of a hub that “could and should be used” but never actually is – typically because of a lack of coordination with data governance or the missing business process involvement. In order to be sure that your master data management program will achieve real business value, make sure that all of the stakeholders involved agree on the desired outcomes and how they will be measured. Then talk about those desired outcomes every week. What is the project team doing to get closer to those goals? What can the team be doing differently to reach those goals more quickly?
Don’t let the project team off the hook for delivering those results. If the people who are on your project team aren’t the people who can deliver the business changes, then you need to add people who will be involved in the implementation.
More than a Technology Implementation Team
Amitech’s master data management methodology links business outcomes measurement, governance alignment, operational/organizational change management, technology expertise, and deep healthcare knowledge to deliver successful implementations and high value.
We have master data management evaluation and selection tools, reusable models for common healthcare data domains (e.g. provider, member/patient, medication, item, location), and an experience-built methodology for driving master data management discovery, implementation and ongoing operations. If you’re interested in discussing how we can put that expertise to work for you, please contact us.
