Matching – MDM’s “Secret Sauce”
Few areas in master data management (MDM) are as critical as identity resolution. Just yesterday, I was working with a client on a matching issue where their customer (a car dealership) was matched to a veterinary clinic because the business names both contained the city and the client had somehow entered the address of the vet clinic in their customer record.
This situation (a “false positive” if ever there was one) is far too common. While the current generation of MDM platforms has come a long way in the last five years, identity resolution is one of the most difficult problems to solve, especially when both your source data and the hub or referential source you’re matching to have data quality issues.
There are several times in a typical MDM project’s life cycle when matching is critical:
• the initial load of data from the first source system into the hub,
• every subsequent load of additional source systems being brought into the hub,
• ongoing data stewardship looking for unmerged duplicate records,
• providing a robust “New Customer” service to the enterprise, searching for existing records before allowing new ones to be created, and
• searching in general, bringing back the right number of matches for the user’s criteria.
All of these are critical functions for an MDM system, and all depend heavily on how good your hub’s matching / identity resolution capabilities are.
And once you’ve solved the identity resolution question (“who’s who”) at the “entity” level (typically, either an organization / business or a person / consumer), then you’ve got to handle the “who knows whom” question, looking for obvious and non-obvious relationships between entities.
External content providers like D&B (for businesses) and Acxiom (for consumers) can help with that, but many applications like fraud detection, denied parties lists, terrorist watch lists, etc. typically require a more robust approach.
Matching typically varies widely from company to company and even from application to application within a company. So having an identity resolution engine with a robust set of algorithms that is easily tunable eliminates a lot of the cases of car dealerships being matched to veterinary clinics.
Dan Power is president of Hub Solution Designs, Inc., a consulting firm specializing in master data management and data governance. He has 22 years of experience in management consulting, enterprise applications and strategic alliances at companies like D&B, Deloitte & Touche, and CSC. He writes a popular blog and a column for Information Management magazine, speaks frequently at technology conferences, and regularly advises clients on developing & implementing high impact MDM and data governance strategies.
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