What Virginia’s winning Amazon HQ2 bid teaches us about approaching a location search

This brief case study presents important lessons learned from the Amazon HQ2 process and offers constructive, practical advice about how to approach a location search. Though many articles have explored high-level takeaways from the process (for examples, see Brookings, CCIM Institute, or Governing), few (if any) discuss how stakeholders—businesses, site selection consultants, or economic developers—can apply these lessons in practice…until now.



Amazon’s search for its second headquarters was unique not just in its public nature and accompanying bidding war among states but also in the way it was conducted. The reams of economic, demographic, fiscal, real estate, and other types of data—both quantitative and qualitative—submitted by nearly 250 communities across the US and Canada will benefit Amazon for years to come as it continues to expand its physical and economic footprint across the continent.

As the Vice President of Economic Competitiveness at Virginia’s state economic development organization and the lead author of the state’s 900-page second-round RFI response, I worked with dozens of colleagues, partners, and stakeholders at all levels of government to deliver a compelling, data-driven narrative that not only successfully addressed Amazon’s specific requests for information but also sold the region’s story to one of the most advanced companies in the world.

In many ways EDai, and our LocatEDTM portal specifically, was born out of this experience, finding a way for these same stakeholders to replicate the breadth and depth of Amazon’s location search process easily and efficiently.


The selection process—from 238 contenders to 2 finalists

The Amazon HQ2 process was announced in September 2017 and unfolded in two phases.

Initially promising to create upwards of 50,000 new jobs and invest $5B in capital expenditures, the project award was eventually split into two, with Northern Virginia and New York City emerging as the winning communities (though only one embraced the victory).

The first phase was a general request for proposals (RFP) from communities in North America. Amazon received 238 proposals from communities pitching why they were Amazon’s best bet for its second headquarters.

In January 2018, Amazon announced a shortlist of 20 locations accompanied by a nearly 30-page request for information.

At a very high level, the second-round proposal (request for information – “RFI”) requested information across five categories:


  • Will there be enough workers now to sustain Amazon’s known operations?
  • What is the community doing to ensure there will be enough workers to drive Amazon’s future but unknown operations?
  • Will Amazon’s workers be happy living in the community in which they work?
Real Estate
  • Does the community have the real estate product (i.e., commercial office space) to meet Amazon’s needs?
  • Just as importantly, who controls that real estate and will that company(ies) be a good, supportive partner with Amazon?
Taxes and Tax Policy
  • Does the community have a stable policy environment that supports businesses, encourages and protects diverse individuals and communities, and maintains sound fiscal conditions?
  • How committed is the community to winning this very competitive project? *notably, Amazon’s final selections were not the communities with the highest incentives offers


Alfried Braumann’s article, “Amazon’s HQ2 Site Selection Criteria: The New ‘Gold Standard’ in FDI Decision-Making,” provides the most detailed exploration of Amazon’s RFI process I’ve encountered to date. The article’s Supplemental File 2 includes a version of the second-round request pulled from New York City’s proposal. These questions are similar to the ones we responded to on behalf of Virginia.


Top three takeaways for businesses, consultants, and economic developers

The breadth of topics covered, depth of detail requested, and nuance required to answer Amazon’s questions required considerable effort and coordination across stakeholders. But many companies request the same type of information from prospective economic development partners as Amazon did. We can take three lessons from this:


1.   Ask the “why” (storytelling) in addition to the “what” (quantitative data)

The most difficult part of preparing our response to Amazon’s second-round RFI was not gathering the extensive data—it was comprehensively answering the “why” questions.

For example, fulfilling Amazon’s request for college attainment rates or the numbers of local machine learning specialists was straightforward: we pulled Census numbers for attainment rates and job postings data from the data provider, EMSI. It was much more difficult to describe what was driving the growth in those numbers, including the companies that accounted for most of the hiring now and in the future.

After reviewing a number of other first- and second-round proposals that have become publicly available (for example, see Georgia’s round 1 and 2 proposals, Boston’s first round proposal, Toronto’s first round proposal), I discovered that most economic developers used the same data sources to answer the same sets of questions.

Amazon with its vast resources could have pulled the same data. But it would not have had access to the narrative explaining why a location had a dense concentration of workers with a particular skillset, what that community was doing to increase its future pipeline, or how the community was working with businesses to increase access to STEM opportunities for under-represented populations.

In an unrelated effort, my Economic Competitiveness team at the Virginia Economic Development Partnership reviewed over 100 RFP/RFIs to identify the most commonly requested data. Most of these requests asked quantitative “what” questions about the talent pool, available real estate, or incentives. While Amazon asked for narratives in both rounds of its process, very few of the other requests we reviewed asked “why” questions.

In Amazon’s case, the RFI forced respondents to provide intimate analysis of their community only they could provide. As just one example, Amazon included a very general question that turned out to be one of the hardest to answer: “Describe any places where you feel that the raw data does not tell the full story for your community. Tell us the full story.

For example, if your software developer location quotient is low enough to suggest that a tech employer might struggle to recruit, but it is rapidly increasing and employers are having great success recruiting to your community right now, tell us that. Perhaps your housing supply is low but your community has implemented innovative programs to address this in the future.” We had to decide which aspect of Northern Virginia to highlight (how the region’s public-private sector tech ecosystem was a strength), how to describe it, and why it mattered to Amazon.


Actionable takeaways:

  • For businesses and consultants, include a few “why” questions to push economic developers to describe what the numbers cannot.
  • For economic developers, find ways to describe what the data misrepresents or misses completely.


How LocatED helps:

We make the same types of data and insights requested by Amazon available to businesses, consultants, and economic developers at the click of a few buttons, freeing up decision makers to focus on the “why” rather than the “what.”


2.   Make information a competitive advantage, now and in the future

Storytelling is an important part of making your case, but don’t discount hard data and numbers. When all was said and done, Amazon gained an unprecedented level of insight and granularity into two vital topics: economic development incentives and commercial real estate:

  • Comprehensive catalog of economic development incentives: Amazon is now armed with nearly 240 communities’ best incentives offers that can be leveraged for future projects and negotiations.
  • Robust perspective on local commercial real estate: Each community, working with the property developers who owned and/or managed its prime commercial real estate, compiled reams of data on each property, the regulations that governed what could be built and when, and the economics (e.g., price to rent, costs to renovate, costs to build new) of location-specific property development.


I would bet very few, if any, site selection companies, no other companies, and certainly no economic developers have access to this amount of detailed information on incentives and real estate.

Currently,  information on each state’s portfolio of incentives and available real estate is spread across multiple agencies and portals (public and private); is offered in a variety of formats, from word documents and pdfs to interactive portals; and leaves it to the searcher to analyze the information.

The sheer time that it would take to compile the information and the capacity and capabilities needed to turn it into actionable insights would be too much for a one-time search process or even a small consulting shop.


Actionable takeaways:

  • For businesses and consultants, think beyond the project at hand. Ask communities to provide a few additional questions that may be relevant for future projects. Leverage that data for the future.
  • For economic developers, identify the most common data requests and the most impactful data that you can offer to prospects, even if unprompted.


How LocatED helps:

EDai took Amazon’s incentives advantage one step further with its Incentives Profitability Model, modeling out eligibility and profitability impact of nearly 300 incentives programs across the Lower 48 US states for businesses of any size and type. The Real-time Real Estate Portal compiles all of the real estate data that economic developers see in their own portal and more.


3.   Balancing breadth and depth with speed

Despite the negative press, Amazon’s approach was incredibly efficient, at least for Amazon: communities did the legwork of developing narratives to pitch their stories, assembling detailed information on available real estate, and providing creative and detailed incentives offers to Amazon. All within six or so weeks.

Sure, Amazon’s site visits to the 20 finalist locations were likely incredibly exhausting, but their deep insight into nearly 240 communities’ economies and economic development strategies will pay dividends for years to come.

Many of the larger companies and site selection consultants replicate Amazon’s RFI process on a smaller scale, requesting specific pieces of information from economic developers to aid in their location shortlist selection process (aka filtering process).

However, this RFI approach is beyond the capacity of small- to medium-sized companies given that it takes a significant amount of time; creates complexity in both selecting the information to request and then processing that information; and requires in-house capacity and capabilities to analyze the information.

Due to their smaller staff size and comparatively limited resources, small and mid-sized companies have to condense the scope of their search, likely leaving money and opportunities on the table.

Furthermore, companies expect speed. A 2015 presentation by Timmons Group highlighted several major project announcements from the past decade that moved from initial contact with economic developers to announcement in less than a year.

It should come as no surprise that 64% of corporate executives in Development Counsellors International’s recent “Winning Strategies in Economic Development Marketing” noted they planned to outsource a portion of their next site selection process. Interestingly, the same survey noted that nearly half of respondents said the most time-strapped executive—the Chairman/CEO/President—is the most likely executive to lead location decisions.


Actionable takeaways:

Time is money.

  • For businesses, identify who will lead your search process internally and be realistic about the time constraints on that individual(s) time—external support can save time and often lead to better decisions.
  • For consultants, identifying the location shortlist sooner allows more time for you and your clients to get to site and location visits sooner and focus on core decision factors earlier, saving time, money, and stress.
  • For economic developers, businesses want speedy responses. Investing in tools and resources to turn around easily replicable data requests saves you capacity to focus on higher value-added activities like hosting prospects on visits.


How LocatED helps:

EDai replicates Amazon’s “all-in-one” approach, combining 15+ categories (location competitiveness, incentives eligibility and profitability, real estate supply, talent supply and demand) into one simple, clean, and intuitive portal that is “client-“ or “proposal-“ ready out-of-the-box. With this tool, decision-makers can save time, reduce complexity, and create capacity to make better, faster decisions.


Storytelling and data at speed

Amazon’s HQ2 search was unique in its comprehensiveness, efficiency, and novelty, creating a national competition that captured international attention. However, most companies don’t have the resources and heft needed to can replicate Amazon’s process.

Nonetheless, anyone involved in economic development can apply lessons like integrating the “why” with the “what,” making information a competitive advantage now and in the future, and balancing depth and breadth efficiently.

EDai’s LocatEDTM portal overcomes many of the challenges identified in this case study by providing businesses, consultants, and economic developers with the same set of comprehensive information Amazon received, delivered at the click of just a few buttons.

If you’re looking to improve your location search with data-driven insights and reduce the information mismatch, EDai is here for you. Learn more about our services.

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