Engineering Strategy for Reshoring
With the resiliency of extended global supply chains tested by COVID-19 and the increase in geopolitical risks driven by events such as armed-conflicts in various parts of the globe, the idea of reshoring manufacturing capabilities has gained momentum both in popular press and in studied business de...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Published: |
Massachusetts Institute of Technology
2024
|
| Online Access: | https://hdl.handle.net/1721.1/156024 |
| _version_ | 1811094368425082880 |
|---|---|
| author | Easley, Jack |
| author2 | Fine, Charles |
| author_facet | Fine, Charles Easley, Jack |
| author_sort | Easley, Jack |
| collection | MIT |
| description | With the resiliency of extended global supply chains tested by COVID-19 and the increase in geopolitical risks driven by events such as armed-conflicts in various parts of the globe, the idea of reshoring manufacturing capabilities has gained momentum both in popular press and in studied business decisions. In theory, reshoring decisions may be based on either new grounds of competition, such as automation to achieve lower manufacturing costs, or desire to reduce risk exposure, such as moving away from sole-source and/or geographically distant suppliers. For domestic industrial businesses looking for new growth opportunities or to re-evaluate strategic sourcing decisions, there is interest to look broadly at what the prime candidates for reshoring are, and such analysis would be more useful when viewed in the context of established strategy frameworks.
Recognizing the risks of over-reliance on offshore production, and seeing opportunities to support manufacturing with the latest breakthroughs in advanced technology such as in sustainability and mobility, Re:Build Manufacturing is a private company founded with the mission to help revitalize the American industrial base over the coming decades. Since 2020, the company has grown quickly through mergers and acquisitions, assembling a family of engineering and manufacturing businesses and mounting a platform of capabilities. As a part of the company's strategic goals, the topic of reshoring is front and center.
This research, therefore, serves to inform strategic decision making for reshoring by taking a practical view on the subject through the lens of a company looking to grow domestic manufacturing -- Re:Build Manufacturing. The study performs detailed data analysis for reshoring opportunities and proposes a unified framework for assessing ones that look promising by comparing market intelligence and company strengths and capabilities. The approach builds an independent, data-driven model that addresses: out of everything that could be reshored or built, how should a company evaluate what to focus on from a technical and competitive landscape standpoint, at least to start with? Objective criteria for characteristics of "good" reshoring candidates is established based on literature review and pairing such guidance with application of competitive strategy frameworks. A simplified narrative would be that an ideal candidate to reshore should be one that has a big market or is considered advanced technology, exhibits rewarding financial risk/return profile, and is exposed to above average level of supply chain risks from offshore operations. The competitive strengths and goals of the company serve to bound the scope of product selection. Considering macro indicators, the thesis of the study centers on the creation of a new decision-support model for reshoring assessment, proposing that publicly available data may be leveraged to drive reshoring attractiveness assessments quickly, at scale, and at product-type level detail. Broadly speaking, the study steps through macro-economic data search and analysis, reshoring ranking model construction, company capabilities inventory, and synthesis of reshoring opportunities.
Analysis on the results of the model suggests that, in aggregate and absent company unique considerations, the model provides a reasonable approximation of general reshoring attractiveness across product-types. Specifically, out of the 6 product-types selected for verification study, 67% stayed in relative ranking to each other under additional scrutiny. It is worth noting that, given macro-data as inputs, the model does not capture nuanced competitive information. As such, detailed case studies should dictate specific reshoring considerations. Further, true performance of the model will only become apparent over time as the extended life cycle of manufacturing decisions takes years to materialize. Nevertheless, the results here serve to offer a holistic starting point to help guide manufacturing businesses in both strategic positioning for product portfolio planning and opportunity screen in business scaling to inform and shape strategies in achieving long-term growth. |
| first_indexed | 2024-09-23T15:58:56Z |
| format | Thesis |
| id | mit-1721.1/156024 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T15:58:56Z |
| publishDate | 2024 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1560242024-08-13T03:04:46Z Engineering Strategy for Reshoring Easley, Jack Fine, Charles Simchi-Levi, David Sloan School of Management Massachusetts Institute of Technology. Department of Civil and Environmental Engineering With the resiliency of extended global supply chains tested by COVID-19 and the increase in geopolitical risks driven by events such as armed-conflicts in various parts of the globe, the idea of reshoring manufacturing capabilities has gained momentum both in popular press and in studied business decisions. In theory, reshoring decisions may be based on either new grounds of competition, such as automation to achieve lower manufacturing costs, or desire to reduce risk exposure, such as moving away from sole-source and/or geographically distant suppliers. For domestic industrial businesses looking for new growth opportunities or to re-evaluate strategic sourcing decisions, there is interest to look broadly at what the prime candidates for reshoring are, and such analysis would be more useful when viewed in the context of established strategy frameworks. Recognizing the risks of over-reliance on offshore production, and seeing opportunities to support manufacturing with the latest breakthroughs in advanced technology such as in sustainability and mobility, Re:Build Manufacturing is a private company founded with the mission to help revitalize the American industrial base over the coming decades. Since 2020, the company has grown quickly through mergers and acquisitions, assembling a family of engineering and manufacturing businesses and mounting a platform of capabilities. As a part of the company's strategic goals, the topic of reshoring is front and center. This research, therefore, serves to inform strategic decision making for reshoring by taking a practical view on the subject through the lens of a company looking to grow domestic manufacturing -- Re:Build Manufacturing. The study performs detailed data analysis for reshoring opportunities and proposes a unified framework for assessing ones that look promising by comparing market intelligence and company strengths and capabilities. The approach builds an independent, data-driven model that addresses: out of everything that could be reshored or built, how should a company evaluate what to focus on from a technical and competitive landscape standpoint, at least to start with? Objective criteria for characteristics of "good" reshoring candidates is established based on literature review and pairing such guidance with application of competitive strategy frameworks. A simplified narrative would be that an ideal candidate to reshore should be one that has a big market or is considered advanced technology, exhibits rewarding financial risk/return profile, and is exposed to above average level of supply chain risks from offshore operations. The competitive strengths and goals of the company serve to bound the scope of product selection. Considering macro indicators, the thesis of the study centers on the creation of a new decision-support model for reshoring assessment, proposing that publicly available data may be leveraged to drive reshoring attractiveness assessments quickly, at scale, and at product-type level detail. Broadly speaking, the study steps through macro-economic data search and analysis, reshoring ranking model construction, company capabilities inventory, and synthesis of reshoring opportunities. Analysis on the results of the model suggests that, in aggregate and absent company unique considerations, the model provides a reasonable approximation of general reshoring attractiveness across product-types. Specifically, out of the 6 product-types selected for verification study, 67% stayed in relative ranking to each other under additional scrutiny. It is worth noting that, given macro-data as inputs, the model does not capture nuanced competitive information. As such, detailed case studies should dictate specific reshoring considerations. Further, true performance of the model will only become apparent over time as the extended life cycle of manufacturing decisions takes years to materialize. Nevertheless, the results here serve to offer a holistic starting point to help guide manufacturing businesses in both strategic positioning for product portfolio planning and opportunity screen in business scaling to inform and shape strategies in achieving long-term growth. S.M. M.B.A. 2024-08-12T14:16:07Z 2024-08-12T14:16:07Z 2024-05 2024-06-25T18:11:42.559Z Thesis https://hdl.handle.net/1721.1/156024 In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology |
| spellingShingle | Easley, Jack Engineering Strategy for Reshoring |
| title | Engineering Strategy for Reshoring |
| title_full | Engineering Strategy for Reshoring |
| title_fullStr | Engineering Strategy for Reshoring |
| title_full_unstemmed | Engineering Strategy for Reshoring |
| title_short | Engineering Strategy for Reshoring |
| title_sort | engineering strategy for reshoring |
| url | https://hdl.handle.net/1721.1/156024 |
| work_keys_str_mv | AT easleyjack engineeringstrategyforreshoring |