By Jill Dyché
TDWI best practice award winner JEA talks
to Jill Dyché about winning the award,
what they did right and how partnering
with the business made all the difference
I’ve seen Faye Chatman in action, so when
she recommends finishing lunch at BB’s in
Jacksonville with the coconut cake, who am
I to say no? I recently caught up with
Chatman, director of enterprise business intelligence (BI) for JEA, the eighth-largest municipal
electric utility company in the U.S., and her boss,
Wanyonyi Kendrick, CIO of JEA, to congratulate
them on winning TDWI’s best practice award in
the “BI on a Limited Budget” category and to ask
them to share how they did it.
Jill Dyché: As with many best practice BI environ-
ments, JEA’s has actually solved a high-profile business
problem. What were the initial drivers of the data
warehouse at JEA?
Wanyonyi Kendrick: We knew that if we didn’t pre-
pare to have a business intelligence system while we
didn’t have a specific problem, we wouldn’t have the
time. So Faye and her team were given 18 months to
really set up a data warehouse ... from hardware to
software to resource needs, and that’s how we started.
The first major business initiative was AMR [auto-
mated meter reading], which began in 1995. Our
vision was to take our meter readers off of the classic
manual meter reading and to do all that remotely.
JD: So how did you know that you’d need your data
warehouse to be part of the AMR solution?
Faye Chatman: We had a lot of data, and we were get-
ting more. With over 400,000 electric meters and
300,000 water meters [JEA has approximately a half
million customers], we were gathering that information
all the time, and we knew we could do a lot with it.
JD: So with the data warehouse foundation in place,
you were able to hit the ground running when AMR
came along.
FC: Right.
JD: Describe a little about why AMR is so critical to
your business.
FC: This is our first opportunity to look at our usage
patterns at a lower level of granularity than just
monthly, which is all we’ve had in the electric utility
industry for years. So we had monthly consumption
[data] on a customer, but you had no idea what the
patterns were, in terms of when customers were using
energy. So this is helping us help our customers.
