Posted by Michele Goetz on June 3, 2014
Master data management is a hot topic. And, this is at times surprising to me because the noise of big data is deafening. Big data is certainly sexier. MDM is like mom nagging to clean up the room - necessary, but a total buzz kill.
Here is some of the anecdotal evidence that is raising my eyebrows:
- Our Forrester Wave for MDM was at the top of most read reports during Q1.
- MDM inquiries from clients keep me very busy.
- Vendors see MDM as a key growth area in their portfolios.
- Consultancies are consistently pointing to client gaps in data governance and data architectures that point toward a master data problem.
But, here's the rub. MDM is thrown around like a silver bullet to master data problems. It is a single box that looks so innocent in a reference architecture with names like product, customer, location, etc. Data architecture recommendations add it as a bullet, something to check box in a mature practice.
Even as companies have implemented MDM packages or home grown solutions, the success stories are limited. MDM runs in the background, forgotten about until the business has changes to the way they look at their data or execute a business process, or worse, when the maintenance bill comes due. It has fallen into the trap of deploy and forget. Where is impacts the business is rarely if ever understood. It seemed like a good idea at the time....
So, why the renewed drum beat?
It's because of big data. Not the volume of data. It is the volume of data sources, the variety of data, and the speed at which data comes in and changes. Managing a customer isn't simply to maintain the golden record in a CRM application or data warehouse. Data silos are becoming networked organisms across distributed filesystems. databases and in-memory grids. How can you orchestrate a consistent trusted view of master data without a master data management solution? That team of data remediation specialists certainly can't keep pace with the task.
What concerns me is that MDM is still misunderstood. Even as companies take the recommendations to implement it, they don't really know what they have. They want to load data into the hub, standardize the view, then push the data. Huh, sounds like ETL. Thus, how do you justify the value?
I'll be honest, if you don't have to implement MDM - don't! You need to weigh your options carefully. "Why" is not too hard to guess. But, it is important to repeat in case you are ready to just take the plunge and buy a tool and compliment of tools.
- MDM is expensive.
- It is resource intense.
- It is implemented over months if not years.
- Most organizations don't have the right skills.
- It has taken down data professionals before, and it will do so again because ROI is ambigous.
MDM is not a check box in your data strategy. Master data management is a data strategy, and not just for traditional environments. It matters for big data too in order to apply context to that data lake, making data useful in analytics and real-time engagment across a variety of engagement scenarios.
The value of MDM is context at automation and scale. It provides the foundation for your enterprise data model. The model that ate your business is tamed. MDM can more easily brake down the the semantic and logical models, contextually syndicate proper views, maintain links and consistency between the views and how the data is used, and become another system of record to more easily explore data relationships and attributes of important data domains.
If someone recommends MDM, be wary. Be very wary. Don't buy the tool before you know:
- The domain model
- The scope of consistency across systems and business views
- The scale of data sources to harmonize
- The quality of the data coming into the MDM tool
- The standards data has to comply with
- The number of buisness values it will support
- The topline business impact to achieve
MDM is for quality, consistency, relationships, scale and automation of master data definitions and views, all for the sake of personalizing data for unique and varied business scenarios. That is a tall order. Are you ready?
Search Forrester's Blogs
Free Webinar Series
The Top Emerging Technologies To Watch »
- Alan Weintraub (5)
- Alex Cullen (41)
- Brian Hopkins (36)
- Charlie Dai (24)
- Cheryl McKinnon (6)
- Clay Richardson (41)
- Craig Le Clair (56)
- Derek Miers (24)
- Ellen Carney (1)
- Gene Leganza (23)
- Gordon Barnett (3)
- Henry Peyret (9)
- James Staten (3)
- Leslie Owens (10)
- Michele Goetz (44)
- Sharyn Leaver (3)
- Skip Snow (2)