Recovery of Business and Supply Chains Post-Hurricane Maria - Project Leader: Jennifer Helgeson - Objective: Characterize SME Recovery in Puerto Rico

Q: What two-part plan does the project use to produce its analysis outcomes?

It combines (1) sampling and surveying individual SMEs in manufacturing, retail, and services, and (2) full supply chain modeling based on infrastructure—especially transportation—for key Puerto Rico-based industries.

Q: How are study regions and samples selected for the surveys?

Study units are selected by ZIP code, with municipios chosen within shaded regions. A combined sample design integrates this project with a Social Functions NWIRP task and uses random distribution proportional to NAICS counts within in-scope ZIP codes.

Sep 12, 2026

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Recovery planning for Puerto Rico small- and medium-sized businesses after Hurricane Maria focuses on manufacturing, retail, and service sectors, emphasizing business continuity resilience and supply chain continuity. The study links business functions with physical systems while accounting for social systems and decision-making. It builds a two-part plan: sampling and surveying SMEs and modeling full supply chains using infrastructure, especially transportation, across selected ZIP-code regions and hospital-linking strata.

LanguageEnglish

CategoryPresentations

FormatPDF

Pages12

Reading Time4 min

AccessFree to download

NCST Advisory Committee Meeting

NWIRP study scope and objectives

Background and motivation

Study area and ZIP-code sampling

Project plan overview

Sample design (2/3)

Sample design (3/3)

Recent progress (1/3)

Recent progress (2/3)

Recent progress (3/3)

NCST Advisory Committee Meeting, June 10-11, 2021 NWIRP Research Study of Recovery from Hurricane Maria’s Impacts on Puerto Rico Recovery of Business and Supply Chains Post-Hurricane Maria Project Leader: Jennifer Helgeson Objective: To characterize the recovery of small- and medium-sized businesses, including manufacturing, retail, and service sectors in Puerto Rico to provide greater understanding of business continuity resilience planning and supply chain continuity and how these may differ between industries/affected regions. Background and Motivation 2 • This project falls under the NWIRP study of the NIST Hurricane Maria Program . • There are supply chain linkages between Puerto Rico and the rest of the U.S. in critical sectors (e.g., healthcare) (NAS, 2020) . • Businesses are a critical part of community functions and community-level resilience and recovery capacity. • 99.7 % of businesses in Puerto Rico qualify as “small”(<500 employees at a location); 68 % of which have annual reported revenues of $250K or less; 75 % are micro-enterprises (less than 10 employees) (SBA, 2018, 2019) • Project outcomes will support development of methods to assess community-level resilience . • Focus is on empirical relationships between business functions and physical systems with regard for social systems and decision-making. National Academies of Sciences, Engineering, and Medicine. 2020. Strengthening Post-Hurricane Supply Chain Resilience: Observations from Hurricanes Harvey, Irma, and Maria. Washington, DC: The National Academies Press. [https://doi.org/10.17226/25490](https://doi.org/10.17226/25490) . Importance of small-and medium-sized businesses in the U.S. (Small Business Administration-Office of Advocacy 2018, 2019) Background and Motivation: Study Area • Regions by ZIP code selected as the study unit (NWIRP Projects) • Municipios selected within the six shaded regions shown below – Four common across all NIST projects – Addition of Mayagüez and Ponce (concentration of manufacturers) 3 4 Project Plan – Overview Two-part plan and analysis outcomes: 1. Sampling and Surveying individual small-and medium-sized enterprises (SMEs): • Small-and medium-size manufacturers (SMMs) and • Small-and medium-sized businesses in the retail and services sectors (e.g., grocery, clothing, and restaurants) (Contractor supported effort, in progress) 2. Full supply chain modeling (based upon infrastructure, specifically transportation) for key Puerto Rico-based industries: • Medical Device Manufacturing • Food Preparation Manufacturing (Use of Complex Network Theory and Discrete Event Simulation techniques discussed at the June 2020 NCSTAC Meeting) Project Plans: Sample Design (2/3) Slide 6 5/7/21 ZIP codes without hospitals ZIP codes with hospitals ZIP codes selected Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z ZZ + 71 ZIP codes without hospitals ZIP codes selected |
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H | | --- | --- | --- | --- | --- | H H H H H H H H H H 10 ZIP codes for the"linking” hospitals 20 ZIP codes with other hospitals 6 Project Plan: Sample Design (3/3) ● Combined sample design for this project and Social Functions NWIRP project. Integrated to allow for a combined analysis with sufficient sample units within the same geographic area from both tasks . ● Random distribution of businesses proportional to the count of specified NAICS codes in a given ZIP code compared to those business types in ALL in-scope ZIP codes | | \# ZIP code areas | “Linking”Hospitals | Other Hospitals | Schools | Manufacturers | Retail/S

FAQs

What is the main objective of the project on business recovery after Hurricane Maria?

To characterize the recovery of small- and medium-sized businesses in Puerto Rico, supporting understanding of business continuity resilience planning and supply chain continuity across industries and affected regions.

What two-part plan does the project use to produce its analysis outcomes?

It combines (1) sampling and surveying individual SMEs in manufacturing, retail, and services, and (2) full supply chain modeling based on infrastructure—especially transportation—for key Puerto Rico-based industries.

How are study regions and samples selected for the surveys?

Study units are selected by ZIP code, with municipios chosen within shaded regions. A combined sample design integrates this project with a Social Functions NWIRP task and uses random distribution proportional to NAICS counts within in-scope ZIP codes.

Sep 12, 2026

Upload by Ben