20210512Avista to Staff 147 Attachment A.pdf

Project Name: Data Science App 2020 - Pkg. 1 - 09906624
Clarity Project ID: PR00013065
Acctg Project #: 09906624
Business Case Name: Enterprise Data Science BI
ER/BI: 5038-38X09
Item
#
Approved Scope
Item
Scope Item Detail Business Value
1 Dashboard - Gas
Engineering
Monthly Project
Update
Tableau visualization developed by
Data Science to display monthly
budget view of gas engineering capital
projects; includes tracking by ER
(expenditure requisition) and
Responsible Engineer.
Enables users to more effectively
understand and manage
budgetary progress of approved
gas engineering capital projects,
including breakdown of projects
by Responsible Engineer.
2 Dashboard -
Meter Counts by
Day (sortable by
Revenue Class)
Tableau visualization developed by
Data Science to display active daily
meter counts, by meter type.
Dashboard enables further sorting by
revenue class within the meter types.
Enables users to easily understand
the make-up of active meter
devices installed in Avista's service
territory. Provides insights into
the changing dynamic of Avista's
active stock of meter devices.
3 Dashboard -
Usage
Dashboards for
COVID EOP
Tableau visualization developed by
Data Science, displays delivered usage
for the following segments:
· WA Residential AMI meters (electric
+ gas)
· MV90 meters (WA + ID electric)
· Large Gas Commercial & Industrial
customers (WA, ID, OR)
Enables business users to
understand usage trends that
span pre-COVID versus COVID-era
periods. Forecasted usage trends
also reflect weather normalization
adjustment for both AMI and
MV90 meter devices. Provides a
benchmark for how Avista's
delivered energy trends are
changing during COVID-era.
4 Dashboard -
Labor Actuals to
Budget
Tableau visualization developed by
Data Science, displays labor actuals
and budgets by organization. Data is
combined from Oracle EBS for actuals
and Ava_Plan for capital budget.
Enables business users to analyze
labor expenditures in comparison
to budgeted amounts.
5 Dashboard -
Dithiazine
Mitigation
Project
Developed a dashboard to track the
expenses related to Dithiazine
Mitigation in WA, OR, and ID.
Enables project engineer to track
costs associated to the Dithiazine
mitigation project across
jurisdictions.
Staff_PR_147 Attachment A Page 1 of 3
6 Dashboard - X09
Software
Expense
Developed dashboard to show the
Data Science's historical allocation of
software expense, by ER (expenditure
requisition) description and Project
Name.
Enables budget owner to review
budgetary allocations to help
manage both direct software
expenses as well as those
allocated from a shared budget
7 Dashboard - EOP
COVID
Key Corporate
Metrics
Developed dashboard to show daily
key metrics as have been identified by
COVID EOP business team.
Enables enterprise leaders to view
key metrics in a centralized
location (Tableau), enabling single
source of metrics for easy
reference within the organization.
8 Municipal
Uncollectibles
Developed an automated process that
calculates the amounts owed by Avista
to each municipal jurisdiction in
Avista’s service territory.
Provides value to the Accounting
Department by streamlining and
automating the calculations;
enhances productivity and
reduces chances of manual error.
9 Usage Data
Configuration 1.0
Data Engineering to assist in usage
data
· WA Residential AMI (power and gas)
· MV90
· Large Gas C&I
Enables analysts to have access to
usage data more easily and in
standardized formatting
10 Usage Data
Configuration 2.0
DSW: Data
Science
Warehouse
Data architecture and associated data
engineering to enable usage data to
flow more easily, automated, from
other systems of record (i.e. MDM,
CC&B). These efforts are the
framework for data to flow in a
standardized manner, to enable more
useful data availability for analysis.
Framework design to enable
automation of data movement
between systems, in anticipation
of analysts within the enterprise
needing usage data (at the
granular level) for various
analytics for different benefits as
determined when needed.
11 Bill Prediction
Phase 1 (MO &
PRD)
Architecture &
Statistical
Analysis &
Visualization
Provided Data Architecture and Data
Engineering services to read/relate
CC&B bill projection data; Additionally,
provided statistical analysis of CC&B
bill prediction tables in Tableau
dashboard format to visualize the
CC&B bill prediction accuracy and
distribution by various visual layers.
Enables Products and Services
business unit to better understand
how well their bill predictions are
performing, allowing for drill-
down at both the macro and
micro (customer level). The
statistical insights provided will
assist in refining Products and
Services offered to customers.
Staff_PR_147 Attachment A Page 2 of 3
12 Idaho Tax Credit
Process
Automation
Developed automated workflow in
Alteryx to calculate annual Idaho Tax
liability
Enables the Tax Department to
speed up certain manual
processes when calculating
retirements and additions. The
Alteryx workflow provides a
framework for future tax liabilities
to be ran in seconds that used to
take the business unit one to two
days. Tool provides insight into
the types of tasks that can be
considered for automation for the
business unit.
13 Crawl: Clarity
DW in AC2
Identified and pointed to source data
sets for enterprise data catalogue.
With proper permissioning, these
data sets can be used by various
users in the organization. The
value of pointing to these source
data sets is to avoid one-off
extractions made from non-source
data, and to conform users into
looking at the same source data
for all potential business
applications, thereby eliminating
discrepencies between users.
14 Crawl: NUCPRD,
NUXPRD (clones)
15 Dashboard -
Forecasting A/R
Write-Offs
Developed dashboard based upon
automated workflows in Alteryx to
show the forecasted A/R write-offs
for:
· Idaho Electric Commercial
· Idaho Gas Commercial
· Idaho Electric Residential
· Idaho Gas Residential
· Oregon Gas Commercial
· Oregon Gas Residential
· WA Electric Commercial
· WA Gas Commercial
· WA Electric Residential
· WA Gas Residential
· Uncollectible
A proof of concept that showed
how specific write off types could
be statistically forecasted. These
time series models could allow for
more accurate assumptions of
what the future write off amounts
will be. Enabled the Accounting
business unit to better understand
the seasonality and trend of their
data.

Staff_PR_147 Attachment A Page 3 of 3