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Economic Geography's Vital Role in America's Alternative Energy Manufacturing Sector

For the renewable energy industry, site selection optimization goes well beyond incentives.

March 2011
(page 2 of 3)
Harnessing Strengths of Economic Geography: Wind
The United States has become a global leader in installed wind turbine capacity and annual installations, according to the U.S. International Trade Commission (USITC). Likewise, the number of wind industry original equipment manufacturers (OEMs) in the U.S. grew from one (General Electric) in 2004 to five in 2008. Several more are planned or in progress as manufacturers seek to deliver unique systems to the Midwest, California, and offshore sites near the East Coast.

Texas leads America in wind power production and is the fifth largest in the world, at 9,528 megawatts of installed capacity. The state accomplished this feat largely without European-style subsidies and incentives. Conventional wisdom suggests that new manufacturing facilities should relocate in or near Texas to serve its proven demand for wind energy products and services.

When a federally-backed turbine manufacturer approached Newmark Knight Frank for a site selection recommendation, the company explored three regions. Texas was an immediate standout, but the economic geography analysis of the three leading contenders found that the Great Plains and Midwest also offered tremendous potential to maximize financial returns. More importantly, they showed the ability to develop a sustainable, competitive business model.

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Location Optimization and Decision Analytics
The goal of Newmark Knight Frank's wind client was to find a community with a suitable business environment for a substantial new manufacturing assembly and corporate office facility, centrally located to U.S. regions that could best use small wind farms or single, on-site wind turbines.

Newmark Knight Frank's decision-making process incorporates expert input within a robust framework:
Risk - Balancing short-term and long-term requirements
Cost and revenue implications - Capital allocations and evaluating CapEx mitigation through strategic cost reduction and economic development incentive offsets, i.e. can the investment and the location provide the opportunity to drive demand and create relationships that enhance the top line
Complex decision criteria - Optimizing multiple factors (suppliers and customers, labor market, site quality, cost) and ensuring that location decision-making is aligned with the entire value chain
Infrastructure and industry dynamics - Assessing the implications of industry presence, competition, and geographic concentrations of infrastructure (physical and non-physical) and their impact on the scalability and sustainability of desired operations
Labor market and talent base - Targeting appropriate markets, skills availability, work force productivity, R&D, and innovation capacity, and evaluating talent supply-and-demand balance across multiple options and markets.

At the wind project's outset, the client's headquarters was in Northern California, providing access to venture capitalists from whom they had secured investment. Its assembly operations were in the Mountain West, and its engineering design unit was based in Europe. The client's leadership and board decided to consolidate their operations into a single optimal location.

Because of the size of its turbines (nacelles), the company assumed transportation costs would drive the location decision. So Newmark Knight Frank developed a logistics network optimization model to quantify inbound and outbound costs. According to the model, all of the candidate locations under consideration were on par with the exception of its current Mountain West assembly operation. This was a significant discovery and represented a departure from conventional thinking. Because of the client's willingness to explore preconceived notions, the process could focus on identifying the best overall business environment, as opposed to optimizing for logistics only, an important distinction for long-term business success.

Comparative analysis of real estate alternatives, airport proximity, logistics, operating cost, and incentives narrowed down the candidate locations to Kansas City, Missouri, and Denton, Texas. At this stage, the consulting team usually expects to begin negotiating with the two finalists. However, since the available facilities did not accommodate the client's unique needs, the company decided that a build-to-suit facility would be the only feasible alternative.

Newmark Knight Frank's extensive operations analysis and supply chain modeling resulted in a series of small compromises and creative solutions that appeased both client and real estate partners. Through strategic cost reductions and capital generation, the client was able to use monetized incentives as equity in the building in Kansas City.

Missouri Governor Jay Nixon authorized a $5.6 million incentive package through community development block grants, jobs training, employee recruitment, and sales tax exemptions for equipment and machinery, which lowered the risk to the developer. The developer agreed to put in the remaining amount for the construction cost after some concessions from the company on overall facility layout and customization. Although each project change and creative solution seemed minimal, they collectively helped to advance a strategic target industry for the Kansas City region, and foster an environment where the project could realize its potential.

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