energy intelligence

Peter Evans, PhDVice PresidentCenter for Global Enterprise

Photo by Maria Carrasco Rodriguez

Rise of the Data Layer

2015 SEEA & AESP Southeast ConferenceAtlanta, GAOctober 28-30th, 2015

What do these items have in common?

2

Essential items… but lack ecosystems not strategic

3

> 8,500 apps

How about these items?

>11,000 developers have accessed Nest’s APIs

> Billions of calls

Essential items… growing ecosystems strategic

IoT is changing the fundamental nature of certain products

From Necessary but Mundane Strategic

4

Path to the Internet of Things (IoT)

MainframePC

Web

Connected Client/ APIs

Standard narrative of evolutionary change

Energy: Complex forces of change

Age of

Platforms

New business models that achieve that leverage

networks and intelligence

Age of

Networks

Mesh networks linking physical, digital and social

Digital Age

Surge in information about energy for

insight and improved decision-making

Energy

Source: Rahul Basole and Peter Evans, API Economy Visualized, Center for Global Enterprise, 2015

Rise of the API Economy

7

API Economy: Amazon vs. Walmart

Source: Peter Evans and Rahul Basole, with data from ProgrammableWeb, Center for Global Enterprise, 2015

Social media / web

Job search / work

E-commerce

Tools / analytics / big data

Payments

API Clusters

Messaging services

Walmart

Amazon

Companies

Enterprise

Amazon SNS

Alexa Web Inform

Amazon Marketplace

Amazon SimpleDB

Amazon Product Advertising

Amazon CloudWatch

Amazon Flexible

Amazon Redshift

Amazon SC2

Amazon S3 Amazon Mechanical TurkAmazon RDS

Amazon DynamoDB Amazon Queue Service

Walmart

8

Rise of IoTInformation Infrastructure Companies

9

IoT information infra companiesNew locus of value creation, capture and competition

Agriculture

Physical Layer

Energy

Physical Layer

Healthcare

Physical Layer

Digital Layer Digital Layer Digital Layer Digital Layer

Transportation

IoT information infrastructure companies

Physical Layer

Energy and the data layerIntelligence about energy is dramatically expanding

Source: John Canny, “Designing with Data”, UC Berkeley, EECS, July 2013

11

1. Volume and velocity of data growing at

- machine level - facility level- fleet level - network level

New dynamics

2. Expanded monitoring/automation

3. Shift from the reactive to the predictive

4. Experimentation with app stores

5. Many more players in the ecosystem

Open API mashups

Source: Peter Evans and Rahul Basole with data from ProgrammableWeb, Center for Global Enterprise, 2015

Energy and sustainability APIs lag social, mapping and images

Social Mapping Images Energy Sustainability

Currently there are very few open API mashups focused on energy and sustainability

Age of Platforms

13

Business Models—PlatformsPlatform companies are found in a growing number of industries

Source: CGE Platform Database, 2014

Companies Sectors

Power of network effects

1connection

Value of the system increases with more users

2 phones

10 connections

5 phones

66 connections

12 phones

Platform business

16

Expanding value through matching, interaction and innovation

Platform

Innovation

Software developers MatchingSupply +

Demand

Interaction

Ecosystem

Street lighting applications platform

Building efficiency platform

Emerging energy platforms

17

18

Race to build new platform ecosystems

Apr Jul Oct Jan Apr Jul Oct Jan Apr

2013 2014 2015

Austin Energy*

Green Mountain*

National Grid*

Reliant*

Southern California Edison*

Infinite Energy

Columbia Gas Ohio

ComEd

Npower

CPS Energy

Direct Energy

CamHydro

Essent

Lampiris

Electric Ireland

Hydro One

Bounce Energy

ConEd

SolarCity

Source: Media, press releases and Nest website: https://nest.com/energy-partners/

* Subsidiaries of NRG

**Rush Hour Rewards and Seasonal Savings

Nest Labs grows its utility partnerships**

$5.8 billion

Innovation on the energy data layer

Startups… energy data layer players

Energy supply/ management

Home automation

Distributed energy management

Data/ Analytics

Energy Intelligence

Building automation

Startup Clusters

Source: P. Evans, CGE with data and visualization powered by Quid, 2015

Top 50 Companies-- $5.8 Billion… VC funding, IPOs and M&A

OpTerra Energy Group

Crowd ComfortBuildingIQ

Wave of “energy intelligence” startupsCompanies building value with energy information

Source: P. Evans, CGE, 2015

Applications

23

Macro approaches

1Determine key building parameters

and begin load disaggregation.

DETECT ATTRIBUTES

Generate unique models of how the buildings is, and could be, performing.

2 CREATE ENERGY MODELS

Compare building to efficient model.

3 COMPARE PERFORMANCE

Target best prospects, automate audits and track efficiency savings

Data Sources: Meter + Weather + Building info

Source: Retroficiency, MIT Platform Strategy Summit, July 2014

Analytic steps

Micro approaches

New platform solutions are emerging that can efficiently gather the sensor data from humans, improving information flows between building occupants and facility managers, boosting comfort and productivity.

Building occupants report conditions

Source: CrowdComfort, MIT Platform Strategy Summit, July 2014

Tapping “human-based” sensor technology

Facility managers receive aggregated “comfort reports”

Energy efficiency’s new golden age?

Admonishment

Shift from …. Automation

1970s

Today

Yesterday and today…

IoT speed and scale

Jeff Immelt, GE Minds & Machines conference, San Francisco, Nov. 2012

Tim Cook, Apple Special Event, San Francisco, Sept 2014

Consumer Internet is ahead… Will the Industrial Internet Catch up? When?

Platforms and the 21st Century Enterprise

Examplecompanies

Platformecosystem

Hierarchalorganization +

physical assets*Structure

Asset Heavy

Daimler MoovelJohnson Controls PanopixGE PredixSamsung Tizen

Asset LightGoogle Google PlayUber Uber appAirbnb Airbnb appSalesforce AppExchange

* Includes HQ, other rooftops, retail outlets, manufacturing plants, service shops, etc.

Platform

Age of networks, digital and platforms

Revenue $ 30 trillion

Assets $121 trillion

# Employees 64.8 million

Source: Fortune Global 500 2013 and Center for Global Enterprise.

Countries

Collective Size

Uncertain implications for the world’s 500 largest firms

Future of energy

1. Growing importance of the energy data layer

2. Shift in value capture from assets to data

3. Ability to scale across markets/ service territories

4. Power of platforms to harness growth

Harness the forces of change…

31

Nov. 10th, 2015

Book Launch Event

Columbia Business School

from 9:30am to 11am New York City

Growing Global examines the challenges and opportunities in today’s global economy and offers practical lessons that will help prepare present and future business leaders for the next phase of the new enterprise.

Growing Global book launch

energy intelligence

Peter Evans, PhDVice PresidentCenter for Global Enterprise

Photo by Maria Carrasco Rodriguez

Rise of the Data Layer

2015 SEEA & AESP Southeast ConferenceAtlanta, GAOctober 28-30th, 2015