Jonathon Mote The George Washington University Gretchen B Jordan 360 Innovation LLC Rosalie Ruegg TIA 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 period Net Cash Flow Time With DOE Initiative Without DOE Initiative 0 FOCUS

Types of initiatives – supply chain Interim Effects CoveredBrief Description Related EERE Program Areas and Activities Accelerated 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 & commercializes 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 & commercialize 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 Review Stage Gate Review Technical Milestones

A logic model – theory of change 6 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

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?

9 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

10 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

11 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.

12 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.

13 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 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 Chain Firm Type by CategoryNumber of Firms OEM7 Supplier – Battery Pack6 Supplier - Anode9 Supplier - Cathode8 Supplier - Lithium4 Supplier – Other41

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 Time MeasuresTime 1Time 2 Size7574 Network Density Network Centralization Network Closeness Degree Centrality (individual firms) Top Firm 43 (Supplier-Battery).189 Firm 17 (Supplier-Battery).135 Firm 33 (OEM).122 Firm 1 (OEM).068 Firm 9 (Supplier-Battery) Top 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 Firm 38 (Supplier-Lithium).039 Firm 33 (OEM).039 Firm 43 (Supplier-Battery).038 Firm 17 (Supplier-Lithium).038 Firm 34 (Supplier-Anode) Top 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 Firm 43 (Supplier-Battery).289 Firm 33 (OEM).232 Firm 17 (Supplier-Battery).231 Firm 38 (Supplier-Lithium).039 Firm 1 (OEM) Top Firm 43 (Supplier-Battery).391 Firm 17 (Supplier-Battery).326 Firm 33 (OEM).244 Firm 38 (Supplier-Lithium).193 Firm 1 (OEM) Isolates74

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 – Jonathon Mote – Thanks for your time!