ADDRESS VERIFICATION - BEGINING DISCUSSIONS & REQUIREMENTS - 09-08/22
Major issue to be resolved: Jeannine wants to be able to present clear data that "X" has this score but "Y" is giving something different, what, why and where is the data coming in from to define the difference. It is important to show the data can make a huge difference because the number helps encourage a better response.
Bill: Report card for an address generally goes to Geocode but does it DPV - if it is meeting all the right criteria then it is good but he requires a "sliding scale" for example 1-2, would be in the "ok range" 1 for example would not be.
Corey: Is concerned about all the different data sources that feed each other. FCC is a particular top problem. He feels that the address fabric is a critical piece to get right for success.
Jeannine is going to discuss it with Jeff to see how to action it moving forward.
Corey is going to devise a way to resolve these issues, capturing the manual field because these usually present more accurate data, he feels this is time sensitive data because of the spatial components of addresses.
Erin: discusses how we current use Precisely data - LI is currently providing the home passed to compare to the FCC address fabric and it closely resembles precisely.
Corey: One of the issues for example is that townhomes do not currently break out the individual addresses on Precisely and there are many other issues.
Jeannine: Currently using many resources (and paying for each separately) to attempt to get the fabric with parcel data and other information that tells her if it is a small business or other for example.
Corey: Feels Prism is a huge issue for bad data along with the necessity for RDOF to be cleaned up and fixing all the known issues. The west are having unusually high issues.
Corey: The challenge is often new builds and feels a lot of the majority of errors come from those that do not Geocode like "new build area or government facilities".
Jeannine needs the master fabric to be built in. Suggests a system, in an ideal world, to capture the Lat/Long but not have to build them. For example, is it a hardship for construction and design teams to collect the Lat/Long info? That would help in time for them to find the address. Corey's issue is that he doesn't know who builds the addresses in PRISM.
Corey - when you capture Lat/Long - there are lots that have addresses in non-deliverable that has no structure - so how do we flag those that have no real home there? or that it could be a home soon? - Currently he does not know answer because Precisely has info as does Prism, do so how do we change that.
Erin was able to clean up some addresses - other billing issues such as duplicate addresses with different City and Zip
Corey wants to capture the issues in Serviceability and Prism etc - he wants to take a deeper dive into making sure they dont go through. He would like to show some examples of how we can perhaps move this forward on the next meeting. For example: Spatial attributes to identify issues - x boundaries are important - build sessions - serviceability workflow - the ones that dont get built or incorrect.
Corey has a pre-built database that he feels can be improved and perfected to start building around the issues at hand.
Corey & Jeannine to discuss with Lael to investigate further as she may have useful information that would work with what Corey has in mind.
County to County things change on who has what data on the County Assessor sites - Corey thinks most serviceability go to County Assessor sites to get their info so maybe that is something to be investigated further on how to use that resource.
Corey shows an example: 700,000 on Zillow that are unmailable to demonstrate the fact there are no real addresses (empty lots) - they do not DPV - which means secondary address is incorrect - Bill says if Charter try to mail there then it gets entered into USPS like that so essentially they mess up the USPS database too.
Corey is showing an example how the Assessors essentially take a guess at what other house numbers are, and they select houses and randomly attach numbers which are incorrect to what the flow of a street address would normally be.
Corey feels in tracking patterns to assess what is happening we can start to slowly resolve and fix the issues.
More discussion and a proposal to be presented at the next meeting on these various topic issues.