Jonathon MoteThe George Washington University

Gretchen B Jordan360 Innovation LLC

Rosalie RueggTIA Consulting

Using Netchain Analysis to Explore the Formation ofRobust Supply Chains for Innovative Technologies

Work prepared for the U.S. Department of Energy (DOE), under contract with Lawrence Berkeley National Laboratory (LBNL). Opinions expressed do not necessarily reflect those of the U.S. DOE or LBNL.

Introduction

2

Team brought together to develop evaluation framework for specific set of the DOE’s Office of Energy Efficiency and Renewable Energy initiatives:

Includes Thomas Choi (Arizona State) and Angela Becker-Dippmann (Pacific Northwest)

Establish an evaluation framework that will guide impact and process assessments of DOE/EERE R&D and related investments aimed at accelerating innovation, advancing manufacturing and creating a domestic supply base and early markets in the U.S.

Where resulting evaluations speak to multiple audiences including program managers, senior managers, industry partners, OMB and Congress.

Evaluation perspective: focus on interim periodNet Cash Flow

Time

With DOE Initiative

Without DOE Initiative0

FOCUS

Types of initiatives – supply chainInterim Effects

CoveredBrief Description Related EERE Program Areas

and  ActivitiesAccelerated development and commercialization of energy technologies in the U.S.

New products, processes and/or business models  are introduced and accepted faster than without EERE support

BioRefinery Initiative 

Growth in U.S. manufacturing

Growth in U.S. production within the target areas

Advanced Manufacturing Office

Capabilities for continued innovation 

Flow of new ideas and invention within a supportive environment as technologies and markets change

Innovation Ecosystem Initiative

Added value to characteristics of a new product

New or better performance characteristics and functions, or costs, or both

SunShot for Photovoltaics 

More and stronger firms in the product value chain 

Development of a viable industry base in the area of the product of focus

Buildings Innovation Hub

Stronger product supply chain

An emergent supply chain begins to deliver products to early adopters.

Advanced Batteries for Vehicles 

Current evaluation guides and practices not sufficient

5

Government R&D to

develop & prototype

technology

Government encourages deployment

of a technology

Energy, environment, economic &

security benefits

Industry scales up,

validates & commerciali

zes a technology

Existing Evaluations

New Evaluation Guide

Government R&D to

develop & prototype

technology

Government encourages deployment

of a technology

Energy, environment, economic &

security benefits

Public-Private

Partnerships help Industry

scale up & commercializ

e a technology

Accelerated innovation; Domestic

suppliers & producers in the supply

chain

Retrospective Cost Benefit Studies (minimal attention to intermediate events)

Deployment Impact Studies

Evaluate Interim Impacts

Peer ReviewStage Gate ReviewTechnical Milestones

A logic model – theory of change

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A tool for evaluation planning

Describes what an intervention aims to do and how

Thus illuminates what to measure, from inputs to outcomes

This draft is high level, attempts to summarize detail

of the R&D process,

supply chain management,

netchains, and

partially, government role.

A logic model – theory of change

Growth in US manufacturing

Strengthened/ developed supply chain

Available capital for

R&D, scale up, production

EERE Investments/Activities and Collaborations(Technical, Information/Relationships, Business, Policy)

U.S. Global Competitiveness in Manufacturing Energy TechnologiesNational Energy and Economic Benefits

Added value to character-istics of new

product

Stronger networks, knowledge exchange

Accelerated new product commer-cialization, adoption

Capabilitiesfor continued

product innovation

Strengthened product value chain

O 3

O 1

O 2

C 2C 1 C 3C 4

C 5C 6 C 7

Inputs

Short & Interim Outcomes -

Conditions for Progress

Ultimate Impacts

Broader Interim

Outcomes

External Influences:Technical.

Information/ Networks, Economic,

Policy

Added capabilities (product process,business model)

Supportive supply chain practices, gov’t. policies

Supply chains, value chains and networks Previous work on supply chain networks (Choi) and

netchains (Lazzarini) suggested the use of social network analysis to assess impact on value chains for specific alternative energy industries

Focus on near-term (early stage) changes and intermediate indicators

Focus on connectedness of firms within value chain, as well as other relevant actors (R&D, finance, etc)

Is the DOE-EERE fostering networks that lead to positive outcomes?

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Network indicators Netchain – set of networks comprised of

horizontal ties between firms in an industries, such that networks (or layers) are sequentially arranged based on vertical ties between firms in different layers (Larrarini et al, 2001)

Focus primarily on the “horizonal” level of industry netchains – ties within the same layer

Also ties outside layer to other actors – financial, R&D

Three principal areas of indicators Connectivity Overall Network Health Intended Interim Outcomes/Impacts

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Network indicators - connectivity Connectivity

Does the structure enable efficient sharing of info, ideas and resources?

Is the network growing (new actors, but new links as well)?

Is the network more interconnected (more dense)? Does the network bridge clusters? How are actors connected? – suppliers, buyers,

communication, collaboration, alliances, joint ventures

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Network indicators – overall health Overall Network Health

Who are the primary leading actors (organizational leaders in horizontal networks)? What role are they playing—controllers or collaborators?

How diverse is the network? Small/large (horizontal networks), suppliers, manufacturers, distributors, R&D, universities, agencies, venture capital/private equity (netchains)

Is the network balanced and growing – able to grow more inclusive and sustain collaboration?

Is the structure appropriate for the work of the network (different horizontal networks may require different structures)? Assumed core/periphery is optimal, but may not be the case.

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Network indicators – interim impacts

Intended Outcomes/Impacts Evidence of greater coordination and collaboration –

alignment of priorities/R&D, working agreements, alliances, joint ventures, etc.

Identification of key actors (either within or outside the networks) for future network weaving.

More innovative products being developed for market and deployed – movement through the TRLs and MRLs.

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Network “Weaving”

Identifying important actors and assessing emerging network patterns could allow for network “weaving”

Strategic interventions to make connections that strengthen the network

The innovation ecosystem

R&DInstitutions Sources of

Capital, Other Resources

Other actors involved with product Component,

Sub systemSuppliers

Manufacturers/Assemblers

Distributors, Sellers Service Providers

Consumers

Raw Material Suppliers

Technical:Competing, complementary technologies…

Economic:Market characteristics, NGOs...

Government:Policies, procurement … (including EERE)

Information, Culture: Human resources, networks, beliefs…

Innovation Ecosystem

Product Value Chain

Product & Marketof Focus

Product Supply Chain firmsOther firms in the industryOther elements contributing to product, market

Supply chains, value chains and networks

Opportunities and challenges

Opportunities Network analysis able to capture complexity of

innovation ecosystem (one-mode, two-mode and multi-level)

Suggests interim indicators based on how firms are interacting (or not)

Challenges Network theory and methodology still nascent Data gathering of this magnitude

A hypothetical example – li-ion batteries for vehicles

Application of netchain analysis to real-world Hypothetical dataset based on parameters of li-ion

battery industry and the EERE li-ion batteries for vehicles initiative

Utilized existing industry analysis conducted by Marcy Lowe at Center on Globalization Governance & Competitiveness (Duke University)

Constructed a hypothetical value chain with linkages that attempted to mirror real-world linkages

Hypothetical Value ChainFirm Type by Category

Number of Firms

OEM 7Supplier – Battery Pack

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Supplier - Anode 9Supplier - Cathode 8Supplier - Lithium 4Supplier – Other 41

Li-ion value chain, firms and recipients

Li-ion value chain, firms and recipients – time 1

Li-ion value chain, firms and recipients – time 2

Network Measures Over TimeMeasures Time 1 Time 2Size 75 74Network Density .024 .025Network Centralization .323 .322Network Closeness .016 .083Degree Centrality (individual firms)

Top 5.338 Firm 43 (Supplier-Battery).189 Firm 17 (Supplier-Battery).135 Firm 33 (OEM).122 Firm 1 (OEM).068 Firm 9 (Supplier-Battery)

Top 5.338 Firm 43 (Supplier-Battery).196 Firm 17 (Supplier-Battery).135 Firm 33 (OEM).122 Firm 1 (OEM).074 Firm 9 (Supplier-Battery)

Closeness (individual firms)

Top 5.039 Firm 38 (Supplier-Lithium).039 Firm 33 (OEM).039 Firm 43 (Supplier-Battery).038 Firm 17 (Supplier-Lithium).038 Firm 34 (Supplier-Anode)

Top 5.111 Firm 73 (Supplier-Lithium).107 Firm 17 (Supplier-Battery).103 Firm 33 (OEM).102 Firm 19 (Supplier-Anode).101 Firm 38 (Supplier-Lithium)

Betweenness (individual firms)

Top 5.333 Firm 43 (Supplier-Battery).289 Firm 33 (OEM).232 Firm 17 (Supplier-Battery).231 Firm 38 (Supplier-Lithium).039 Firm 1 (OEM)

Top 5.409 Firm 43 (Supplier-Battery).391 Firm 17 (Supplier-Battery).326 Firm 33 (OEM).244 Firm 38 (Supplier-Lithium).193 Firm 1 (OEM)

Isolates 7 4

Conclusion

Need for interim indicators suggested new methodology

Development of new products in emerging industries does not happen in isolation – supply chains

Netchain analysis (network analysis across product value chains) offers one potential avenue

Questions?

Gretchen Jordan – Gretchen.Jordan@Comcast.net

Jonathon Mote – jmote@gwu.edu

Thanks for your time!