Location analysis and data quality

The impact of accurate data on site selection

In location analysis and site selection, data choices drive outcomes. But data without insights or experience can yield the wrong results.

Endless information—with the swipe of a finger

We're in a time of easily accessible location data, with more sources, maps, and visualizations available to everyone—often for free. For companies evaluating new locations for their operations or considering a change in footprint, it seems to be the golden age of data. Wages, demographics, real estate, tax conditions, and other location factors are available to all. With smartphones and tablets, it's increasingly easy to pull information on every county and major city in the US with just the swipe of a finger.

This availability of data makes it possible for anyone to make location decisions. Unfortunately, while the sources of location data are numerous and readily accessible, not all data is of equal value or accuracy. In addition, when it comes to screening locations for a particular investment, setting the appropriate boundary conditions or screening thresholds is essential to narrow the field to locations that can support a thriving operation.

Understanding which location variables make a difference, and which don't, requires a deep understanding of the criteria that drive success for any given asset type. These complicating factors often lead what might otherwise be a straightforward screening process to very different results, depending on the data sources chosen, the data elements analyzed, and the boundary conditions used to perform the location analysis.

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Gathering the right data—and how to evaluate it

Prior to engaging in any site selection process, a hypothesis-based approach that defines the key success factors for the operation is essential. These success factors should, in turn, drive the data that should be leveraged in the screening process.

The data inputs used to conduct a location analysis often come from government agencies, such as the Bureau of Labor Statistics (BLS) or the US Department of Labor. Other common sources include the US Census, state and local governmental data, and even crowdsourced information and other free online resources. These sources can have highly variable levels of accuracy. Even in the case of typically reliable data from a source like the BLS, there are important assumptions that need to be accounted for in a location evaluation.

First and foremost, it's important to understand the coverage and level of detail in any given piece of data that's being analyzed. Second, the establishment of boundary conditions—or screening thresholds—is critical to realize results that are relevant to a particular site-selection evaluation. Even slightly different boundary conditions can result in vastly different outcomes. Finally, the data itself needs to be sourced thoroughly to vet its accuracy and timeliness—there are numerous sources available in the public domain that rely on outdated or unreliable information. A test of data quality is essential to ensure that the results of a location screening are based on accurate data.

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Finding a successful location that's right for you

Knowing what drives a successful location for an investment is critical. It's important to assess whether the results emerging from a screening process align with the hypothesis established at the outset of the process and whether the specific results either confirm or refute the hypothesis.

Understanding what type of data to use, what boundary conditions to set, and then how to interpret the results is a critical part of the site-selection process. We’ve found, over time, that when the wrong location data is used—or when the right data is used with the wrong boundary conditions—the resulting screen of locations is often suboptimal.

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to learn more about the importance of combining the right data with experience and insight when making site-selection decisions.

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