R Shiny Applications at TVA

  

Region

☐ West

☐ Midwest

☐ Northeast

☒ Southeast

 

Utility Class

☐ IOU

☐ Municipally owned

☐ Cooperative

☒ Government owned

 

Size

☐ <10,000

☐ 10,001-100,000

☐ 100,001-1,000,000

☒ >1,000,001

 

ANALYTICS AREAS

 

  1. Which of the following analytics areas apply to your project (see definitions at end of document)? Place an “X” in the appropriate boxes.

 

 

Implementation underway

 

 

Project completed

Future

 

Meter data analytics

_______

 

 

_______

_______

Credit and collections

_______

 

 

_______

_______

Call center optimization

_______

 

 

_______

_______

Fraud detection

_______

 

 

_______

_______

Campaign management

_______

 

 

_______

_______

Customer segmentation

_______

 

 

_______

_______

Pricing optimization

_______

 

 

_______

_______

Demand response programs

_______

 

 

_______

_______

Energy efficiency programs

_______

 

 

_______

_______

Distributed generation management programs, including electric vehicles

_______

 

 

_______

_______

Transformer management

_______

 

 

_______

_______

Substation equipment management

_______

 

 

_______

_______

Overall transmission & distribution management

_______

 

 

_______

_______

Outage management

_______

 

 

_______

_______

System modeling

_______

 

 

_______

_______

Power quality optimization

_______

 

 

_______

_______

Advanced distribution management

_______

 

 

_______

_______

Analytics for real-time network operations

_______

 

 

_______

_______

 

Other:  analytics architecture

 

 

PROJECT OVERVIEW

 

  1. In two or three sentences or a short paragraph, please describe this project (include business drivers, how project aligns with utility’s corporate strategy, project goals, results achieved/desired outcomes).

 

R is one of the most prevalent tools used for data science and advanced analytics. Shiny is an R package that allows analysts to develop and deploy interactive web apps using R with little to no web development experience. TVA deployed a Shiny server internally that allows analysts throughout the business to create, publish, and maintain Shiny applications. Current use cases include predictive analytics, optimization modeling, and risk simulation (across various business units).



BUSINESS VALUE

 

  1. Describe actual and/or anticipated QUALITATIVE (e.g. better customer service) and QUANTITATIVE (e.g. ROI, cost savings, revenue increases) benefits of this project.
    • Note: Any and all quantification of benefits helpful including estimates, ranges, percentage increases or decreases in costs, resources, etc.

 

  • Increase the success and productivity of analysts through the self-service infrastructure and ability to publish and maintain applications without having to bring in IT or outside consultants
  • Models have interfaces as opposed to reporting dashboards, which allows users and viewers to more easily manage and present information


BUSINESS PROCESS IMPACTS

 

  1. List the key business processes impacted (or expected to be impacted) and describe the nature of those impacts.

 

  • Able to tweak models and data inputs with ease
  • Easier deployment means that business units can benefit from analytics with significantly more ease than in the past
  • Can comply with data governance/privacy protocols by limiting data seen by the user

 

TECHNOLOGY

 

  1. Identify the PRIMARY TECHNOLOGY COMPONENTS associated with this project including the technologies used (or expected to be used) for: 1) data collection/integration 2) data analysis 3) data presentation and 4) data storage.
    • Notes: Identify the solution providers and products by name if possible

 

  • R Shiny Server Pro

 

 

  1. Identify the PRIMARY DATA INPUTS/ELEMENTS utilized and their sources.


- N/A; depends on application/use case

PEOPLE

 

  1. Identify the following individuals by job title (as applicable):

 

  • Business-side Project Leader: Manager of Advanced Analytics

 

  • Technology-side Project Leader: Senior Manager, Information & Analytics Solutions

 

  • Executive Sponsor: Director of Enterprise Analytics

 

 

  1. Identify and describe the role of external providers (e.g. strategy, consultant, design, development, implementation, ongoing operations).

 

N/A

 

  1. Describe the investments required to implement and provide ongoing support for this initiative.

 

  • Internal resources (identify type of internal resources, e.g. job titles and quantities of each (e.g. # of full time/# of part time, total FTEs):

 

Implementation:

2 software engineers + 1 database administrator at 25% for 3 months to install software and develop infrastructure for managing data access for the server and application access for end users

 

Ongoing support:

4 data scientists regularly developing and deploying individual apps

1 software engineer for occasional maintenance (installing packages, updating licenses, etc.)

 

 

  • Technology investments (estimate/provide ranges for one time and recurring costs if possible or indicate that existing technologies were leveraged):

 

Annual license fees of $15k/year

 

 




BEST PRACTICIES/LESSONS LEARNED

 

  1. What advice would you share with those either planning or implementing a similar initiative (e.g. best practices, lessons learned, what to do, what not to do)?

 

Clearly differentiate R Shiny use cases (interfaces to advanced models) from Tableau/PowerBI (descriptive analytics/reporting)

 

Install RStudio Server, even if you plan to primarily develop apps on workstations. It’s very helpful for debugging errors when deploying to the Shiny Server

 


 

CONTACT INFORMATION:

Name:

Matt Kocoloski

Title:

Manager of Advanced Analytics, TVA

Company name:

Tennessee Valley Authority

Email:

mlkocoloski@tva.gov

Phone:             

(423) 751-7520


 

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