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How Data Analysis can be used to Address an RFE
Successfully – A Case Study
Soon after the May Memo was released, many regional centers
received an RFE challenging their tenant occupancy-based job
projection based methodologies. Most regional centers gave up
“tenant occupancy” jobs, but one in particular felt a favorable
decision was within reach. Their persistence paid off with an
eventual approval, but it did not come easily. By providing a
comprehensive list of data for all the prospective tenants, this
regional center showed that there was excess demand for their
project. Although USCIS rejected the conclusions of their
analysis, it was apparent that the methodology of this analysis
was accepted. By the time the last RFE arrived, this regional
center was able to sign up tenants and provided concrete proof
of their s pecific industries. Fortunately for this regional center,
the developer was smart about the types of tenant businesses
that they were bringing into the development. In response to the
RFE, the data was updated with a more specific list of prospective tenants and the irrelevant industries were thrown out. What
ensued was basically a chess match with the data. The discarded
industries were ones that displayed no excess demand and the
updated analysis now proved to be credible. The project thus
was approved with tenant occupancy jobs. This example shows
that proper use of data may be the only solution for approval
with difficult project requirements.
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The Proper Role of Third-Party Data
The evolving EB-5 environment has changed the priority of
third-party data and the role of the business plans today. When
preparing an exemplar EB-5 project, a project developer must
start with the correct foundation. While the goal is to find the
correct amount of EB-5 funds in the capital stack, the process
needs to start with relevant data. This can either be done by
purchasing a feasibility study or by engaging a company that
will correctly identify the relevant data and use it to model out
the financials and any construction costs. As long as the data
can be shown to be credible, these conclusions can become
the proper basis for economic model inputs. The economist
should be able to easily take those inputs and model out the job
creation numbers to determine the maximum projected raise of
EB-5 capital. By incorporating the proper third-party data (with
source attribution) into a business plan, a separate feasibility
study is usually not required for I-526 approval of a project. The
case where a feasibility study may be needed is when a project is
unique and has insufficient data points or the data is proprietary
and unattainable. When opening a new business location for
an existing brand, the feasibility study can include regression
analysis by plotting the data of existing locations.
Without properly analyzing and identifying both the
maximum raise potential and the expected minimum raise of
EB-5 funds in the capital stack, it is very difficult to fully commit to a plan. Project details may have to be tweaked according
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