REACHING NEW HEIGHTS IN REGIONAL COMPETITIVENESS WITH VALUE-CHAIN ANALYSIS

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1 REACHING NEW HEIGHTS IN REGIONAL COMPETITIVENESS WITH VALUE-CHAIN ANALYSIS Marty Romitti, PhD, Senior Vice President CREC 1 The 2014 EMSI Leadership Conference Coeur d'alene, ID. October 21, 2014

2 WHAT DO NAPOLEON AND RAISIN BRAN HAVE IN COMMON? They both tried to make it rain! 2

3 REACHING NEW HEIGHTS IN REGIONAL COMPETITIVENESS WITH VALUE-CHAIN ANALYSIS Topic Why Clusters? Identifying Clusters from the Top Down Identifying Clusters from the Bottom Up with Value Chains Applying Value Chain Analysis in Regional Planning NW PA 3

4 WHAT IS A CLUSTER? A geographic concentration of inter-related firms and institutions that collaborate, compete, learn from one another, attract assets, and share unique talent. Emphasis is on Interdependence Economically important linkages within and between businesses and other organizations Linkages can take the form of trade, information, innovation and labor Combined, these factors reinforce the regional cluster s market advantage. 4

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6 THE BASIC LOGIC Cluster Identification Competitive Analysis -Innovation growth -Productivity growth -Income distribution Cluster Strategy Regional Economic Outcome Cluster Expansion 6

7 APPROACHING ANALYSIS: ENTERPRISE Enterprise What your region makes Goods & services created by existing and prospective industries Linkages to national and global economies Formation of new industries through new business formation. Innovation How your region renews New ideas and innovations Mechanisms to take them from concept to market, Creation of new business models, companies, or product lines Talent What your region does Human capital base Embodied in skills of existing and future workforce supply Improved through education, experience and training reflecting industry demand LOCATION ASSETS The basic conditions facing firms and innovators in the region. 7

8 APPROACHING ANALYSIS: ENTERPRISE Key Questions Measures/Techniques Which industries are largest sources of jobs and income? Absolute size Are some industries local specializations? Relative size Which industries are growing? Which are declining? Local vs. state/national growth Are new businesses being formed, leading to new industries? New business start-ups Is the mix of key industries unique? Application of cluster definitions Are related and mutually dependent industries present? Is there evidence of multiindustry specializations? 8

9 6 CONTRIBUTING FACTORS TO MAKING DATA RELEVANT Availability Ease of Extraction Making Sense of It All Relevance Findability Timeliness Accuracy 9

10 EMSI ANALYST Go to Key advantages Detailed Comprehensive Regional Current Pulling together an overview Creating a region Demographic trends Economic structure 10

11 REACHING NEW HEIGHTS IN REGIONAL COMPETITIVENESS WITH VALUE-CHAIN ANALYSIS Topic Why Clusters? Identifying Clusters from the Top Down Identifying Clusters from the Bottom Up with Value Chains Applying Value Chain Analysis in Regional Planning NW PA 11

12 CHOOSING YOUR CLUSTER DEFINITIONS There is no single best way to define clusters Off the shelf or selfdefined? Depends on your needs EMSI Analyst provides pre-defined clusters that can be used 17 clusters defined by Purdue University researchers 12

13 SETTING CRITERIA FOR TARGETING CLUSTERS Traded or Local (multiplier impact) Number of establishments in clusters Employment size of cluster Relative concentration of cluster ( Location quotient ) Average annual wage level of cluster Employment growth trends of cluster 13

14 ONE APPROACH TO CATEGORIZING CLUSTERS FOR TARGETING Growing Large employment size Growing more rapidly than the region or nation Most interested in higher wages Shrinking employment, declining faster than the nation Receding regional concentration At-Risk Stable Consistent and large employment size Close to national growth trends Emerging Continuously rising employment Growing faster than the nation Rising regional concentration in the cluster industries 14

15 KEY DATA POINTS ONTARIO S CLUSTERS Cluster Employment Average Cluster LQ 2011 Wage Type Advanced Materials 65, $48,391 At-risk Agribusiness, Food Proc & Tech 187, $38,353 Stable Apparel & Textiles 25, $37,895 At-risk Arts, Entmnt, Recreation & Visitor Ind. 191, $31,669 Stable Biomedical/Biotech (Life Sciences) 476, $44,540 Growing Business & Financial Srvcs 451, $58,775 Stable Chmls & Chml Based Pdcts 50, $65,535 Stable Comp & Elec Pdct MFG 23, $59,623 At-risk Defense & Security 79, $41,030 Emerging Education & Knowledge Creation 436, $52,791 Growing Elec Eqpt, App & Compont MFG 49, $44,428 Stable Energy (Fossil & Renewable) 169, $71,381 Growing Fabricated Metal Pdct MFG 72, $51,146 Stable Forest & Wood Pdct 164, $50,771 Stable Machinery MFG 54, $55,973 Stable IT & Telecomm 194, $69,680 Stable Printing & Publishing 36, $62,698 Stable Transportation & Logistics 196, $47,139 Growing Transp Eqpmt MFG 106, $56,672 Stable Ontario average $46,100 15

16 THE CLUSTER BUBBLE CHART 16

17 REACHING NEW HEIGHTS IN REGIONAL COMPETITIVENESS WITH VALUE-CHAIN ANALYSIS Topic Why Clusters? Identifying Clusters from the Top Down Identifying Clusters from the Bottom Up with Value Chains Applying Value Chain Analysis in Regional Planning NW PA 17

18 Value Chain Example Source: Center on Globalization, Governance & Competitiveness, Duke University. 18

19 FRAMEWORK FOR CONDUCTING VALUE CHAIN ANALYSIS Supplier 1 A Customer 1 Supplier 2 Customer 2 Supplier 3 Core Industry Customer 3 Supplier 4 Customer 4 Supplier 5 Customer 5 Backward Linkages (supplier opportunities) Core Industry Forward Linkages (market opportunities) 19

20 Value Chain Example Exports Consumers Wheels Government Rubber Tires Steel Rubber molding Automotive assembly Vehicle rental services Engines Automotive assembly s forward linkages Legal services Advertising Direction of sales Source: Edward Feser, University of Illinois. 20 Automotive assembly s backward linkages

21 BEGIN BY CONSIDERING LINKAGES Which linked industries value chains are in the region? Are the linked industries significant/competitive in the region? Where are the gaps? Which linked industries could be in the region? Which industries are not appropriate for your region? 21

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25 REACHING NEW HEIGHTS IN REGIONAL COMPETITIVENESS WITH VALUE-CHAIN ANALYSIS Topic Why Clusters? Identifying Clusters from the Top Down Identifying Clusters from the Bottom Up with Value Chains Applying Value Chain Analysis in Regional Planning NW PA 25

26 NW Pennsylvania has seen an erosion in jobs over the past decade, especially when compared to broader state and national trends NW PA PA US Employment Index for NW Pennsylvania, Pennsylvania, and US. Base Year 2001 = Source: Economic Modeling Specialists Int l., Analysis by CREC 26

27 Mapping the Shale Gas Boom 27 Gas wells (red) and oil wells (blue) Source: FracFocus chemical disclosure registry, a partnership between federal and state governments and private companies, lists more than 50,000 gas and oil wells nationwide where companies have voluntarily reported using fracking.

28 Employment Index (2001=100) Employment trends in Oil and Gas-related activities Index of Employment in Oil and Gas Related Activities* (2001=100) Northwest Pennsylvania Pennsylvania USA *Include NAICS industries: Crude Petroleum and Natural Gas Extraction (211111), Drilling Oil and Gas Wells (213111), Support Activities for Oil and Gas Operations (213112), and Natural Gas Distribution (221210) Source: Economic Modeling Specialists, Int'l 28

29 CONDUCTING A VALUE-CHAIN ANALYSIS Define Inter- Industry Linkages using NAICS Codes Identify Regional Strengths/Trends with Data Analysis Supplement Data with Interviews and Focus Groups 29

30 KEY LINKAGES FOR OIL AND GAS EXTRACTION Backward linkages Forward linkages Support activities for oil & gas operations Construction Industrial gas MFG Metal valve MFG Mining & oil & gas field machinery MFG Lessors of nonfinancial intangible assets Electric power generation, transmission, & distribution Natural gas distribution Petroleum refineries Petroleum & coal products MFG 30

31 OIL AND GAS EXTRACTION SUPPLY CHAIN Site Preparation Drilling & Extraction Midstream Exploration & Leasing Site Construction Drilling Hydraulic Fracturing Extraction & Production Transp. & Processing Storage Distribution Scientific R&D Services Architectural, Engineering, and related services Supp. Activities for oil & gas opt. Lessors Architectural, Engineering, and related services Construction Comm. & Ind. Mach. & Equip. rental & leasing Truck transp. Environ. Remediation services Drilling oil & gas wells Construction Mining & oil/gas field mach. mfg. Metalworking mach. Mfg Steel prod. Mfg. Pump & pumping equip. mfg. Metal valve & pipe mfg. Petroleum lubricating oil & grease mfg. Industrial sand mining Supp. Activities for oil & gas opt. Ind. Gas & other chem. mfg Metal valve & pipe mfg. Pump & pumping equip. mfg. Metalworkin g mach. Mfg. Steel prod. Mfg. Pipeline transp. Truck transp. Rail transp. Sensor & other detection equip. mfg. Petroleum refineries Metal valve & pipe mfg. Oil & Gas Pipeline & Related Structures Const. Pipeline transp. Metal valve & pipe mfg. Natural gas distribution Electric power generation, trans., & distr. Supp. Activities for oil & gas opt. Truck transp. Truck transp. Stable ( ) Declining faster than US ( ) Growing faster than US ( )

32 Key companies by segment of the Marcellus Shale Supply Chain 32

33 Supply Chain Issues Quality is paramount consideration and far more important than cost. Many suppliers invest in industry certification programs like ISO 9001 or the American Petroleum Institute as a way to demonstrate their product quality. Firms involved in the oil and gas industry must also demonstrate impeccable safety records, given that few industries are as scrutinized about health, environmental and safety standards. Vendors must be available 24/7 to meet client needs. Beyond short-term responsiveness, firms must be able to deliver on actual deadlines as well as their forecast planning. Financial solvency is an important consideration because payments to vendors do not turn around as quickly as in other industries.

34 34 Analyzing Data for Decision-Making

35 Thanks! Marty Romitti 35

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