Amazon’s recent announcement it will seek a second company headquarters is an ideal opportunity to apply the Value Ratings method. Using publicly available data, Value Ratings show why accounting for preferences is critical when ranking complex choices.
In addition to preferences, methods matter, too. The New York Times’ approach — which concluded Denver is the ideal locale — illustrates a pitfall of “sequential filtering.” With each added restriction, the pool of remaining options shrinks, making choice less taxing. The price, however, is we lose sight of excluded options for the rest of the process.
In contrast, the Value Ratings method never discards an option because of weak performance in a single area. After all, weak performance in an area of little importance to you could still result in a strong Value Rating.
Amazon identified four specific attributes it valued in a metropolitan location for its HQ2:
- Metropolitan areas with more than one million people
- A stable and business-friendly environment
- Urban or suburban locations with the potential to attract and retain strong technical talent
- Communities that think big and creatively when considering locations and real estate options
Of course, we cannot precisely know Amazon’s preferences across these four attributes. Instead, we will imagine two possible “corporate personas” to illustrate the critical role played by preferences.
Persona #1: Satisfy the Investors
In this persona, we complete the Preference Survey as if we were an organization primarily concerned with making Amazon stockholders wealthier. Such an organization’s Preference Profile might look like this:
Based on these preferences, the fifteen cities with the highest Value Ratings are:
Persona #2: Good Corporate Citizen
In the second persona, we complete the Preference Survey as if we were an organization seeking to cultivate an urban working/living district that will benefit not only investors but also customers, suppliers, and the community at large. Such an organization’s Preference Profile might look like this:
Based on these preferences, the fifteen cities with the highest Value Ratings are:
Comparing the Top Performers from Each List
We expect that cities performing strongly across the board would rate highly in any case. We see this for Atlanta and San Francisco. Seattle is included as point of reference because, according to Jeff Bezos, Amazon founder and CEO, “We expect HQ2 to be a full equal to our Seattle headquarters.”
Beginning with 4th place, however, the lists diverge.
Some cities appear only in the Satisfy the Investors list:
- Dallas-Fort Worth-Arlington, TX
- Miami-Fort Lauderdale-West Palm Beach, FL
- Riverside-San Bernardino-Ontario, CA
- Houston-The Woodlands-Sugar Land, TX
- Tampa-St. Petersburg-Clearwater, FL
- Orlando-Kissimmee-Sanford, FL
Other cities appear only in the Good Corporate Citizen list:
- Philadelphia-Camden-Wilmington, PA-NJ-DE-MD
- New York-Newark-Jersey City, NY-NJ-PA
- San Diego-Carlsbad, CA
- Chicago-Naperville-Elgin, IL-IN-WI
- Baltimore-Columbia-Towson, MD
- Austin-Round Rock, TX
Notice the range of Value Ratings for the top fifteen cities differs in each list. Corporate persona #1 ranges from 76.7% to 99.8%, while persona #2 runs from 62.7% to 98.8%. This suggests that the Preference Profile of persona #2, with the wider range, skews toward attributes for which strong performance is less common.
Finally, some cities appear on both lists, usually in different positions:
- Atlanta-Sandy Springs-Roswell, GA
- San Francisco-Oakland-Hayward, CA
- Portland-Vancouver-Hillsboro, OR-WA
- Boston-Cambridge-Newton, MA-NH
- Raleigh, NC
- Washington-Arlington-Alexandria, DC-VA-MD-WV
- Minneapolis-St. Paul-Bloomington, MN-WI
- Denver-Aurora-Lakewood, CO
Preferences and Methods Matter
To summarize, Value Ratings give a personalized prioritization of all the choices you face. Shortly after Amazon’s announcement, many media outlets presented their evaluations of the deserving cities. These appeals either ignored Amazon’s preferences or presumed to know what they are (or ought to be). As shown above, the pool of better choices is highly dependent on the decision-maker’s preferences.