Catch Bad Data Before It Wrecks Your Business
3. Address Standardization
Here is a simple scenario, followed by what should be a simple question: You have an item you would like to have delivered to a specific individual at a particular location and you plan to engage an agent to deliver the item on your behalf. How can you communicate to the agent where the item is to be delivered? From the modern day perspective, it should be obvious—you only need to provide the street address and can expect the agent will be able to figure it out on his own.
We expect the delivery agent will be able to figure out how to get to a location, because the standard address format contains a hierarchical breakdown for refining the location at finer levels of precision. In the U.S., an address contains a street name and number, as well as a city, state and a postal code. This process works in the U.S., because there is a postal standard and, in fact, the driving force behind addressing standards is the need for accuracy in delivery. Ultimately, delivery accuracy saves money because it reduces the amount of effort to find the location and it eliminates the rework and extra costs of failed delivery.
Problems occur when, for one reason or another, the address does not conform to the standard. If the address is slightly malformed (e.g. it is missing a postal code), the chances are still good the location can be identified. If the address has serious problems (e.g. the street number is missing, there is no street, the postal code is inconsistent with the city and state, or other components are omitted), resolving the location becomes much more difficult, and therefore, costly.
The primary way of dealing with this problem is to treat each non-standard address as an exception, forcing the delivery agent to deal with it. The other approach attempts to fix the problem earlier in the process by using data tools to transform a non-standard address into one that conforms to the standard.
Greg Brown is vice president of Melissa, provider of global contact data quality and identity verification solutions that span the entire data quality lifecycle and integrate into CRM, e-commerce, master data management and Big Data platforms. Connect with Greg at email@example.com or via LinkedIn.