This post is the 3rd in a series of challenges in Data Matching with Party Master Data hierarchies.
80 % of all business entities are one-man-bands operated from so called SOHO’s (Small-Office-Home-Office). The home part is very often seen as a business is sharing a private residence address with a household.
Examples are:
- Farmers
- Healthcare professionals
- Small shops
- Small membership organisation administrations
- Fawlty Towers
- Independent Data Quality consultants
Here we have a 3 layer relationship:
- An ADDRESS occupied by a HOUSEHOLD and a BUSINESS (if not several)
- The HOUSEHOLD consists of one or several CONSUMERS
- The BUSINESS(s) has an EMPLOYEE being the Business Owner / Representative
One of the CONSUMERs and the EMPLOYEE is the same real world individual.
(About party master data entity types please have a look here.)
This very, very common construction creates some challenges in Data Matching and Master Data hierarchy building such as:
- If you focus on B2B (Business-to-Business) you want to include the Business and Owner in that role, but not the same individual in the consumer role.
- If you focus on B2C (Business-to-Consumer) you want to include the consumer role of that individual, but not the business (owner) role.
- If you do both B2B and B2C you may want to assign either a B2B or a B2C category, and that’s tricky with those individuals
- In several industries business owners, the business and the household is a special target group with unique product requirements. This is true for industries as banking, insurance, telco, real estate, law.
In my previous post on B2B (E2E) and B2C hierarchies methods for solving this is fuzzy matching, exploiting external reference data and other investigations – and so it is with this challenge as well. This makes Data Matching and Master Data hierarchy building a very exciting profession were you need both business and technology skills – and a real world perspective – to go all the way.
Liliendahl on Data Quality 
Hello Heinrick
This could be a classic argument for NOT using hierarchies or taxonomies. In the traditional construction of databases, applications and directory structures to name a few, one entity could not occupy multiple ‘locations’. In the real world, as you illustrate in your example this is not the case. Our future reality – notwithstanding the lack of data structures to model it – can have split budgets, multiple positions and two or more different aliases for the same physical entity.
Time to change the way we handle this stuff.
Cheers.
John O’
Thanks John. I guess you have some guidance about the other way?
Hi Henrik
First thing: let me apologize for misspelling your name. I’m usually very careful but I posted in a bit of a rush. I should also explain that I meant no disrespect in my post…I’m evangelizing for a see change, and I get caught up sometimes.
I have developed a framework for managing these types of use cases. It suggests that the best way to handle them is to deconstruct the use case language; assign fixed categories to each element of the use case; then make associations (as many as required) to fully and accurately describe what’s going on.
Please permit me to give your readers a sample of how it’s done:
Use Case Language
An ASSET: Single Family Ranch-Style House
An ADDRESS: 3017 Flyaway Lane, Calgary, Alberta Canada
OCCUPANT: Big Daddy Bee
OCCUPANT: Big Momma Bee
OCCUPANT: Janis Joplin Bee
OCCUPANT: Baby James Bee
HOUSEHOLD: The Bees
BUSINESS: The Bees Alphabet Soup Co.
PRODUCT: Alphabet Soup
CONSUMER: Big Momma Bee; Janis Joplin Bee
EMPLOYEE: Big Daddy Bee; Baby James Bee; Big Momma Bee; Little Auntie Ant
OWNER: Big Momma Bee, Big Daddy Bee (Home); Big Momma Bee (Business)
REPRESENTATIVE:
B2B, B2C
Banking
Insurance
Telco
Real Estate
Law
The Classification
ASSETS: The house; the soup
AGENTS: The ‘people’; the business; the household
LOCATION: 3017 Flyaway Lane; Calgary; Alberta; Canada
ROLE: Owner; Cosumer; Employee; Representative; Occupant; Visitor
DISCPILINES: Banking; Insurance; Telco; Real Estate; Law; Food Processing
STATES: Active; Occupied;
ACTIVITY: B2B, B2C
The Facts
Any collection of associations between and among the values above that make sense.
Thanks for the space in your blog, Henrick. Hope it was ok.
John O’