Mixed Identities

A frequent challenge when building a customer master data hub is dealing with incoming records from operational systems where the data in one record belongs to several real world entities.

One situation may be that that a name contains two (or more) real world names. This situation was discussed in the post Splitting names.

Another situation may be that:

  • The name belongs to real world entity X
  • The address belongs to real world entity Y
  • The national identification number belongs to real world entity Z

Fortunately most cases only have 2 different real world representations like X and Y or Y and Z.

An example I have encountered often is when a company delivers a service through another organization. Then you may have:

  • The name of the 3rd party organization in the name column(s)
  • The address of the (private) end user in the address columns

Or as I remember seen once:

  • The name of the (private) end user in the name column(s)
  • The address of the (private) end user in the address columns
  • The company national identification number of the 3rd party organization in the national ID column

Of course the root cause solution to this will be a better (and perhaps more complex) way of gathering master data in the operational systems. But most companies have old and not so easy changeable systems running core business activities. Swapping to new systems in a rush isn’t something just done either. Also data gathering may take place outside your company making the data governance much more political.

A solution downstream at the data matching gates of the master data hub may be to facilitate complex hierarchy building.

Oftentimes the solution will be that the single customer view in the master data hub will be challenged from the start as the data in some perception is fit for the intended purpose of use.

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4 thoughts on “Mixed Identities

  1. I would think this is a common occurrence when dealing with corporations and in particular multiple people belonging to one corporation at one address.

    Any ideas on mitigating potential mistakes when this occurs?

  2. Thanks William. I guess you are thinking about a situation like this, where you may have two records like:

    • J. Smith, Acme Ltd on 1 Main Str in Anytown
    • Mary Doe, Acme on 1 Main Street in Anytown

    Here you have to build a hierarchy with one Address:

    • 1 Main Street in Anytown

    having one Business (account):

    • Acme Ltd

    having two Employees (contacts):

    • J. Smith
    • Mary Doe

  3. Definitely a real life situation in my experience, although it represented a small % of my scope. My objectives are usually about integrating customer information across our enterprise. The scenario usually took the form of a company name who placed the order (often a financing company), and an address where the order was shipped to (usually unrelated to the order company – hence different ‘identities’). This situation can be dealt with providing the data standards and appropriate db fields are adhered to correctly. As is often the case, it transpired the issues were down to core data quality issues created at record creation.

    From a data standards point of view, this is where standards can fall short ie. it is not good enough to specify only individual fields such as company name, address line 1, address line 2, etc. Often other fields need to be maintained and defined which infer what the company or address represents ie. address type : a bill to address, a ship to address, an installed at address, etc.

  4. Thanks Nigel. I certainly agree about your remarks about metadata.

    Solutions to these challenges is also discussed in the MDM – Master Data Management group on LinkedIn here.

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