Research Presentation

1. woodmac.comTrusted intelligence
GTM Event:
The Data-Driven Transformation of the Distribution
Utility
Ben Kellison
Director, Grid Edge
Ben.Kellison@woodmac.com

2. woodmac.comTrusted intelligence
1. The traditional utility approach to software
development
2. Where are we going from here?

3. woodmac.comTrusted intelligence
The traditional utility approach to
software development
1

4. woodmac.comTrusted intelligence
For many utilities, it is the same as it ever was
Hint: it is not all that different then capital assets out in the field.
Traditional utility view of software adoption
1. Define and execute decade-long lifecycle roadmaps
2. Buy then customize
3. Undergo long data collection/cleaning efforts
4. Develop the data and processes necessary to support
projects, one at a time

5. woodmac.comTrusted intelligence
But, the shear volume, variety and velocity of adoption of new internet of things
devices in the United States outpace legacy system’s ability to integrate them,
Source: Wood Mackenzie Power and Renewables, DOE, EIA
of thousands of
communicating DA devices in
the field by 2019.
10sOf thousands
smart meters installed by end of
year 2017.
80Million
Residential DER assets alone
by end of year 2019.
>30Million
Nearly

6. woodmac.comTrusted intelligence
And the complexity of our IT environments is growing as we contract more and
more applications to leverage this data to drive customer and utility value.
Cumulative known utility and energy provider contracted analytics, 2010-2018
0
200
400
600
800
1000
1200
1400
2010 2011 2012 2013 2014 2015 2016 2017 2018
#ofanalyticsapplications
contracted
Energy Efficiency Engagement VVC All others
DER Marketplace Distribution O&M Predictive Outage & Reliability
Switching Forecasting
Source: Wood Mackenzie Power and Renewables’ s Grid Edge Data Hub

7. woodmac.comTrusted intelligence
Where are we going from here?1

8. woodmac.comTrusted intelligence
Digital first employees and projects look at their work differently
Transformation needs to start with a plan and a team.
Digital-first outlook
1. Architect and maintain data assets, while
augmenting with new solutions
2. Develop quarterly ongoing evaluation of functional
needs to guide investment.
3. Buy and use tools as needed
4. Led by digital executive with cross-functional team

9. woodmac.comTrusted intelligence
Digitalization is not a physical capability, it is an institutional competency driven by
human and organizational capital accented by tools.
As such, improvement and investment should be incremental and driven by value assessments
1. Hire a core team, select a lead for the team.
2. Create and prioritize use cases.
3. Evaluate outsourced vs. in-house development
4. Select a use case, acquire the necessary tools, and prep your data platform
5. Interview end users and SME, develop minimum viable product, iterate, commercialize
6. Turn over to IT and business units

10. woodmac.comTrusted intelligence
A. Regulatory resistance or insufficient incentives
B. Too much focus on short-term gain and ROI
C. Insufficient funding
D. Lack of digital team resources
E. Limited relationships and trust between business units
F. Gathering support to get started
G. None of the above
Poll Question: What do you think your organizations biggest barrier to a
successful digital transformation?
Poll

11. woodmac.comTrusted intelligence
Data scientists alone will are not enough
Hire a core team: To build an ongoing capability, you have to build an internal team
External professionals Internal hires
Advantages:
• Digital native
• Little technical training required
• Uncertain commitment to the industry
• Does not share utility culture
Disadvantages
• Expensive
• Lack of industry context
• Does not share utility culture
Advantages:
• Shares utility culture
• Has company and industry context
• Growth opportunity for high performers
• Developed internal network
• Cheaper
Disadvantages
• Requires training and time
• Lack of experience outside the industry
vs.
Full use case project team
• Enterprise architect
• Data engineer
• Data scientist
• Designer
• UX developer
• Project manager
• Subject matter expert
• User base
SME’s
fromBU
Data
Team

12. woodmac.comTrusted intelligence
Create, prioritize and select build or buy option
Approach to
develop use
case?
Develop business
case for analytics
use case
Public or
private
RFP?
Co-develop
with vendor
orconsulting?
Need
consulting
support?
Develop
in-house
Co-develop
with third-
party
Procure from
third-party
• Need additional people or skills
• Tight timeline
yes
vendor
public RFP
no
consulting
private RFP
• Strong analytics team
• Technology-driven use case
• Process-driven use case
• Lack of vendor diversity
• Strong vendor diversity
• Existing partnership with solution
provider
• Lack of vendor diversity
Drivers:
Choosing a course of action will be effected by your regulatory situation, maturity of the solution and the breadth of its
applicability
Select based on impact:
• Revenue
• Profitability
• Safety
• Reduced cost
• Reg Requirement
• Etc.

13. woodmac.comTrusted intelligence
Develop a data architecture that is extensible, and select a foundational tool set
How we structure and maintain our customer, asset, and systems data models will only matter more with time
Customer Asset Systems
Other public data examples
Weather Census Social media
Financial
(ex. creditworthiness)

14. woodmac.comTrusted intelligence
Develop minimum viable product (MVP), iterate, and productize.
The process is cyclical
1. Engage users early and often
• Get feedback from end users and SME
before, during, and after the MVP to ensure
adoption and reduce iterations
• For process projects, consider shadowing
users
2. Hand-off the application to the BU and IT
• Turn over support for hardware and
software to IT
• Turn over software ownership to the
business unit

15. woodmac.comTrusted intelligence
A. In planning phases
B. Initial digital roles are hired
C. Data architecture in place
D. Developing initial use cases
E. Productized use cases are in production
F. Digital transformation team efforts are a key part of our business unit’s performance
Poll Question: How far has your organization come along in your analytics
strategy?
Poll

16. 15
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Thank
You
Ben Kellison
Director, Grid Edge