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Subject: CIQ TC WELCOMES JOHN D. PUTMAN OF FEDEX AS A NEW MEMBER


CIQ TC,
 
John D. Putman of FEDEX is interested to contribute to the TC.
John is having some problems with the Kavi setup and will be on
our mailing list soon. I have copied this email to him.
 
Please find below John's expertise.
 
Welcome John and the CIQ TC looks forward to your contributions!
 
Regards,
 
Ram
------------------------
From: "John D. Putman" <jdputman@scanningtech.fedex.com>
To: "'ciq@lists.oasis-open.org'" <ciq@lists.oasis-open.org>
Subject: Hello
Date: Tue, 14 Dec 2004 18:21:30 -0600

I have just completed getting into this CIQ / on the mailing list and would
like to introduce myself to the committee -

My main experience with names and addresses has been in my current capacity
as "the address expert" for Federal Express ("FedEx"), starting around 1993.
Throughout my IT carrier, however, I have had some intermittent or
peripheral name and address experience elsewhere; for instance -
        +  at a bank where names and addresses were "sacrosanct" identifiers
for account holders;
        +  at St. Jude Children's Research Hospital, where patient AND
parent names AND addresses were critical to identifying and keeping up with
clinical trials enrollees (children were often enrolled - at least serially
- in several clinical research trials and so needed to be cross-referenced
using those data elements);
        +  I also like to think that a couple of stints as a DBA (for
network topography and mil-spec equipment assemblage modeling, and then for
clinical trials data at St. Jude), helped prepare me somewhat for complex
data modeling - address definitely being complex.

At FedEx, I have been involved in the implementation of standardized address
correction APIs for USA, Canada, and International.  That included not only
vendor product evaluation, familiarization / implementation, and
maintenance, but also custom design for "special features" such as
        +  possible address production when postal quality matching fails,
        +  character-level standardization change detection and indication
setting,
        +  dropped data sensing and preservation / reinstatement,
        +  address element input order reinstatement after correction /
standardization,
        +  address quality and confidence codes generation,
        +  and a variety of custom controls to affect address correction
behavior and/or output format;
        +  in addition, I designed and helped perform "address audits" over
our 10-14MM account addresses to detect "false positive" matches.
Practically all of these required becoming very involved in address element
identification and parsing.

At FedEx, address correction is used not only for FedEx shipment addresses
but also for postal invoice mailing, employee and customer communications,
and vendor / supplier information.  Indeed, "address" permeates almost all
of our systems (a study during the Y2K effort found that address elements
were 4 times more prevalent in FedEx systems than date elements!).  Perhaps
some of the more esoteric address uses to which I have been exposed or in
which I have been involved include -
        +  inbound shipment sensing and notification based on name and
address for the purpose of recipient manifests,
        +  in-transit rerouting of misrouted packages (misrouted due to
"bad" addresses),
        +  location, shipment network node, and service area identification
based on address and/or postal code,
        +  and courier route planning and optimization.

I am most familiar with USA address data / parsing and correction processing
and its intricacies (of which there are quite a few even though USPS has
made USA addresses VERY "standard").  Though I have somewhat less experience
with Canadian addressing, it is very like that for the USA and so I think I
have a fair handle on that.  As for International addressing, I have worked
with that for some time (starting around 1999), but - due to the scope and
breadth of that (along with the only recent availability of fairly good
reference data) - I feel I have a long way to go there.

My academic background is in Philosophy and ancient Greek (the latter of
which, with little use, I have almost totally forgotten), with a Math minor.
My interest / emphasis in Philosophy gravitated toward philosophy of
science, symbolic logic, and set theory, which somewhat prepared me for a
career in IT in general and data modeling in particular.

I look forward to working with the committee,
David Putman



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