Cambridge, MA – The MIT Center for Transportation & Logistics (CTL) and AWESOME (Achieving Women’s Excellence in Supply Chain Operations, Management, and Education), an industry-leading organization of senior-level women in supply chain, are pleased to announce the opening of applications for the Advancing Women through Education (AWE) MIT Fellowship for the MIT Supply Chain Management (SCM) Master’s Program Class of 2026. This prestigious fellowship will provide full tuition funding for two outstanding students: one from the residential MIT SCM student cohort and one from the blended MIT SCM student cohort.
All eligible applicants to the program for the MIT SCM Master’s Program Class of 2026 are considered for this award upon completion of their program application. Those hoping to be considered are encouraged to apply by the round two deadline of January 31, 2025, for the residential cohort, and the round one deadline of January 10, 2025, for the blended cohort. This fellowship is designed to support and empower women in the supply chain and logistics field who are applying to the MIT SCM Master’s Program.
“We are excited to once again launch the AWE MIT Fellowship for the MIT SCM Master’s Program applicants. This fellowship not only supports those advancing their careers but also fosters diversity and innovation in the supply chain field,” says Maria Jesus Saenz, Executive Director of the MIT SCM Master’s Program.

The MIT SCM Master’s Program offers specialized training for early-career professionals seeking advanced education in supply chain management. The residential program is tailored for those who prefer an in-person learning experience, and is offered over a course of 10 months on the MIT campus in Cambridge, while the blended program offers a combination of online and on-campus coursework with 5 months on campus. Both tracks are designed to prepare students for leadership roles in the global supply chain industry.

To be eligible for the AWE MIT Fellowship, applicants must meet the following criteria:
Apply to the MIT SCM Master’s Program.
Have a minimum of two years of relevant work experience (3-7 years preferred).
Demonstrate strong quantitative skills and leadership potential.

Prospective candidates must indicate their interest in the AWE MIT Fellowship within their MIT SCM Master’s Program application. MIT will review all eligible applications and forward the top finalists to AWESOME for final selection.

“Our collaboration with MIT CTL through the AWE MIT Fellowship aims to develop and empower the next generation of female supply chain talent. This initiative directly aligns with our mission to advance and transform the future of supply chain leadership, and we are so honored to partner with an institution like MIT,” says Michelle Dilley, CEO of AWESOME.

Olivia Morton, a recipient of the AWE MIT Fellowship for the blended cohort class of 2025, shared her experience: “Collaborating with and learning from other female supply chain leaders in cross-functional roles is an incredible opportunity and will foster critical dialogue, interaction, and community. Being a recipient of the AWE MIT Fellowship Award serves as a catalyst for leading global organizational change in a cohesive supportive environment.”

The recipients of the fellowship will be announced in early 2025, and the awardees will commence their SCM studies in August 2025. They will also attend the AWESOME Symposium in 2026 to share their experiences and future aspirations in the supply chain field.

For More Information:
MIT SCM Master’s Program admission requirements and process: MIT SCM Admissions
The Advancing Women through Education (AWE) Fellowship: Details

About the MIT Center for Transportation & Logistics
Founded in 1973, MIT CTL is one of the world’s leading supply chain education and research centers. MIT CTL coordinates more than 100 supply chain research efforts across the MIT campus and around the globe. The center also educates students and corporate leaders in the essential principles of supply chain management and helps organizations to increase productivity and improve their environmental performance.

About AWESOME
AWESOME (Achieving Women’s Excellence in Supply Chain Operations, Management and Education) is the pre-eminent professional organization for senior women leaders in supply chain. Our mission is to advance and transform the future of supply chain leadership by bringing together senior women leaders in this vitally important industry for connecting, learning, collaboration, recognition, and inspiration. At our core, AWESOME is an organization built by passionate women leaders for passionate women leaders. We are a platform for women to be seen and heard and to operate as catalysts for positive progress in their organizations, the supply chain industry, and the world. To learn more and review the criteria for network membership, visit awesomeleaders.org.

About the MIT Supply Chain Management Master’s Program (MIT SCM)
Founded in 1998 by the MIT Center for Transportation & Logistics (MIT CTL), MIT SCM attracts a diverse group of talented and motivated students from across the globe. Students work directly with researchers and industry experts on complex and challenging problems in all aspects of supply chain management. MIT SCM students propel their classroom and laboratory learning straight into industry. They graduate from our programs as thought leaders ready to engage in an international, highly competitive marketplace.
 
Media Contact: Lisa Kim, lisahuh@mit.edu

Editor’s Note: The SCM thesis Profit-Driven Network Redesign Through Value-Creation Services was authored by Morgan DeHaan and Yujia Ke and supervised by Dr. Milena Janjevic (mjanjevi@mit.edu). For more information on the research, please contact the thesis supervisor.

Network design is a key strategic decision in supply chain management. Traditional network design concentrates on cost savings. However, can we utilize these facilities to create profit, given that there are value-creation services that facilities can undertake? In our capstone project, we worked with a logistics service provider to restaurant chains across the United States. The company envisions a redesign of its service network based on two components: (1) the addition of new flexible distribution centers (referred to as iDCs) located closer to high-volume demand areas and (2) the value-creating services offered from the iDCs to restaurants beyond deliveries (such as inventory reserves, food preparation, and reverse materials handling).

With the context of network redesign with iDCs and focus on profits, we aimed to give a comprehensive technical approach to answer three questions: (1) how to identify urban clusters in the current demand areas, (2) how to infer/impute missing transportation cost data, and (3) how to determine the best locations of future iDCs.

Editor’s Note: The SCM thesis Developing a Dynamic S&OP Process for Third-Party Logistics was authored by Richard A. Elmquist and Luis Dávila and supervised by Dr. Ilya Jackson (ilyajack@mit.edu) and Dr. Jafar Namdar (jnamdar@mit.edu). For more information on the research, please contact the thesis supervisors.

The preservation of food characteristics and quality within a temperature-controlled environment presents a complex challenge in the food supply chain. Third-party logistics (3PL) companies have a significant opportunity to assist producers, wholesalers, and retailers in managing this complexity. Cold chain warehousing providers face the task of determining appropriate capacity requirements in terms of time and location, which entails allocating capital expenditures to construct the necessary infrastructure. Furthermore, accurate prediction of client needs enables the allocation of operational expenses to manage flexible and cost-effective supply chains.

Our research was initiated by a challenging question posed by the second-largest cold chain 3PL provider worldwide: How can the company balance operational costs and service levels while meeting both present and future demand? This project aimed to establish a dynamic sales and operations planning (S&OP) process by developing a scalable and accurate warehouse inventory forecast. The forecast is utilized as an input in the proposed S&OP process, where subject matter expertise is employed to enhance forecast accuracy through a deep understanding of the business.

To answer the question, we leveraged a comprehensive dataset spanning a duration of four years, encompassing inventory positions for each customer and product within a designated warehousing facility belonging to the company. The significant number of possible combinations between customers and products, coupled with customer churn, posed a challenge in determining the appropriate level of granularity and data grouping. To address this, we developed a segmentation model based on a two-by-two matrix that incorporated average inventory on the y-axis and ease of business on the x-axis. Additionally, we established discrete segments based on temperature ranges for product storage: freezer, cooler, and ambient. This allowed for better forecasting at a level of granularity that was actionable for the company.

After segmenting the data, we generated reliable forecasts using different forecasting models, such as SARIMA and Facebook Prophet, that provided key information for the company. Our forecasts revealed the need for additional freezer capacity in the next six months, as well as underutilized space in the cooler segments that could be repurposed in the next six months. Converting a room from cooler to freezer can add significant benefits to the bottom line of the site, but expert judgment is required before any actual decision can be made.

Finally, we recommended an S&OP framework that enables the company to scale efficiently across its 240-plus facilities globally, including the integration of subject matter experts and the establishment of a feedback loop for forecasts. In the specific warehouse, it was deemed necessary to execute the changes identified by our forecasts. This framework at scale allows 3PL companies to better understand their customers and proactively make changes to their network to ensure reliability and reduce cost of operations.

Supply Chain Management Review

Every year, approximately 80 students in the MIT Center for Transportation & Logistics’s (MIT CTL) Master of Supply Chain Management (SCM) program complete approximately 45 one-year research projects.

These students are early-career business professionals from multiple countries, with two to 10 years of experience in the industry. Most of the research projects are chosen, sponsored by, and carried out in collaboration with multinational corporations. Joint teams that include MIT SCM students and MIT CTL faculty work on real-world problems. In this series, they summarize a selection of the latest SCM research.

Editor’s Note: The SCM thesis Procurement Control Tower: Proof of Concept Through Machine Learning and Natural Language Processing was authored by Bishwajit Kumar and Pablo Barros Gomez, and supervised by Dr. Elenna Dugundji (elenna_d@mit.edu) and Dr. Thomas Koch (thakoch@mit.edu). For more information on the research, please contact the thesis supervisors.

Our capstone project sponsor, a global pharmaceutical company, faces significant challenges in its procurement processes due to its large procurement spending, diverse product needs, extensive supplier base, and divergent software insights. The company recognizes that to remain competitive in today’s volatile, uncertain, complex, and ambiguous (VUCA) market, it will be imperative to gain insights faster, enhance decision-making capabilities, and optimize exception management. As a potential solution, the company wants to explore the value proposition of implementing a procurement “control tower:” a centralized platform that offers end-to-end visibility and control over procurement processes.

To address our sponsor’s objectives, our study aimed to answer two key questions:

1. Would a procurement control tower create measurable value for the sponsor’s procurement functions?

2. Could we demonstrate the proof of value of a procurement control tower by creating a prototype of one of its use cases?

Editor’s Note: The SCM thesis The Green Route: An Analysis of Mode Change as a Strategy for Carbon Emission Reduction was authored by Elizabeth Bruttomesso and Shruti Pant and supervised by Dr. Elenna Dugundji (elenna_d@mit.edu) and Dr. Thomas Koch (thakoch@mit.edu). For more information on the research, please contact the thesis supervisors.

Faced with the pressing imperatives of pursuing net-zero emissions targets and promoting sustainable development, the marine transportation sector is actively seeking innovative ways to achieve these goals. One promising solution is to establish green intermodal corridors that reduce carbon emissions. For a route to be viable as a green corridor, it must have the potential for significant decarbonization while also providing economic benefits. We believe inland drayage transportation is a strong candidate for applying this approach. We therefore conducted feasibility assessments for three drayage corridors from an East Coast seaport, exploring different scenarios for each of these routes and comparing them with current operations in terms of operating costs and carbon emissions.

Exploring the route less traveled

Currently, the marine transportation industry predominantly utilizes diesel trucks for the delivery of cargo from the port to the warehouse. However, this method is associated with high carbon emissions. There is a need to explore alternate routes and modes of transport that can efficiently balance costs and emissions, guiding companies in making decisions about future infrastructure and routing.

In this study, we sought to find out if using an electric barge and a hybrid barge in combination with an electric truck (Route 1), an electric truck alone (Route 2), or an electric train in combination with an electric truck (Route 3) would be viable alternatives to traditional diesel trucks. To evaluate these routes, we considered the cost of transportation, necessary infrastructure improvements, and carbon emissions for both the proposed options and the current diesel truck operations.

Carbon emissions were a crucial component of our calculations. For each mode of transportation, we took into account not only the direct emissions but also the emissions associated with generating electricity used by electric vehicles. Emission factors were sourced from The Green Freight Handbook and converted to metric tons per TEU mile. Additionally, we considered the national average price for diesel as reported by the U.S. Department of Energy for Oct. 1–15, 2022, to estimate fuel costs.

Opening a corridor to net zero

Our analysis revealed specific findings regarding the costs and carbon emissions of the proposed green intermodal corridors. Electric trucks (Route 2) emerged as the most cost-efficient alternative. Compared to traditional diesel trucks, adopting electric trucks can reduce operational costs by 60% and carbon emissions by 89% per year. The payback period for the initial investment in electric trucks was estimated to be 17 years.

In contrast, Route 1 (electric barge + electric truck) and Route 3 (electric train + electric truck) presented higher costs and longer payback periods, making them unsuitable investments in the short term. Specifically, Route 1 showed a 10% increase in operational costs compared to diesel trucks and a 170% increase in carbon emissions. Route 1 with a hybrid barge has 5% decrease in operating cost and a 78% decrease in carbon emission but has a payback period over 100 years.  Route 3 showed a 25% decrease in operational costs but has an 80% increase in carbon emissions.

Despite the higher costs associated with electric barges and trains, companies should not disregard these options entirely. There is potential for costs to be reduced through advancements in battery technology and economies of scale. Moreover, collaboration among stakeholders to develop reliable electricity supply sources and charging infrastructure is vital for these alternatives to become viable in the future.

For a successful transition to green corridors, the transportation industry, government, and stakeholders need to share risks and burdens. Together, they can bridge the total cost of ownership gap that arises with adopting these alternate pathways, thereby contributing to the establishment of sustainable green routes with lower carbon emissions.

Supply Chain Management Review

About the Capstone projects

Every year, approximately 80 students in the MIT Center for Transportation & Logistics’s (MIT CTL) Master of Supply Chain Management (SCM) program complete approximately 45 one-year research projects.

These students are early-career business professionals from multiple countries, with two to 10 years of experience in the industry. Most of the research projects are chosen, sponsored by, and carried out in collaboration with multinational corporations. Joint teams that include MIT SCM students and MIT CTL faculty work on real-world problems. In this series, they summarize a selection of the latest SCM research.

The Massachusetts Institute of Technology (MIT) proudly announces that its Supply Chain Management (SCM) Master’s Program, housed within the MIT Center for Transportation & Logistics (MIT CTL) at the Institute’s Engineering School, has received the title of top master’s program for supply chain management for 2024. This recognition comes from three leading global rankings institutions, including QS World University Rankings, Eduniversal, and Supply Chain Digital.

QS World University Rankings, recognized for its thorough evaluation of over 1,500 institutions across 104 locations worldwide, has singled out MIT SCM as the premier program in the field. QS considers five main facets in determining rankings: (1) Employability of degree recipients, (2) Alumni CEO & Executive Outcomes, (3) Tuition, Alumni salaries, and Return on Investment, (4) Thought Leadership and Research Impact, and (5) Class & Faculty Diversity. With an emphasis on career sustainability and growth, QS’s acknowledgment reflects MIT’s commitment to preparing students for success in today’s dynamic business landscape.

Eduniversal, known for its exhaustive review of over 5,800 Masters and MBA programs across 50+ fields of study spanning 150+ countries, also bestowed the #1 ranking upon MIT’s SCM program. Eduniversal’s assessment takes into consideration the MIT Global SCALE Network of six innovation centers (MIT CTL, Ningbo China Institute for Supply Chain Innovation, Zaragoza Logistics Center, Center for Latin-American Logistics Innovation, the Malaysia Institute for Supply Chain Innovation, and Luxembourg Center for Logistics and Supply Chain Management), underscoring MIT’s global impact and leadership in real-world applications in supply chain education.

Supply Chain Digital, a leading industry publication with an audience of global logistics executives, recently honored the MIT Center for Transportation & Logistics as the provider of the #1 supply chain program globally. This recognition highlights MIT’s influence in shaping the future of supply chain from the perspective of company leadership and management.

In addition to its Master’s program, MIT CTL offers an online MicroMasters® program, which registered its one-millionth learner in late 2022. After finishing the online program, certificate holders can apply to MIT (and other universities) and obtain a full master’s degree in a single semester.

“Our program prides itself on its interdisciplinary curriculum and close collaboration with industry leaders,” said Dr. Maria Jesús Saénz, Executive Director of the MIT SCM Masters Programs, “so that our graduates can emerge equipped with the skills, knowledge, and mindset needed to tackle the complex and dynamic challenges facing modern supply chains. We are as committed as ever to fostering excellence and driving positive, real-world challenges.”

MIT CTL has been a world leader in supply chain management education and research for more than five decades. The center has made significant contributions to supply chain and logistics and has helped numerous companies gain competitive advantage from its cutting-edge research.

“We are thrilled by the recognition of the SCM program by these esteemed organizations,” said Dr. Yossi Sheffi, Director of the MIT Center for Transportation & Logistics. “This achievement reflects the dedication of our faculty, staff, and students in serving as a world leader in supply chain management education and research by driving supply chain innovation into practice.”

Links of Interest:

MIT SCM: https://scm.mit.edu/

MIT CTL: https://ctl.mit.edu/

QS World University Rankings in SCM: https://www.topuniversities.com/business-masters-rankings/supply-chain-management

Eduniversal SCM rankings: https://www.best-masters.com/ranking-master-supply-chain-and-logistics.html

Supply Chain Digital Top Supply Chain Schools: https://supplychaindigital.com/operations/top-10-supply-chain-schools

MIT MicroMasters Program in Supply Chain Management: https://micromasters.mit.edu/scm/

MIT Global SCALE Network: https://scale.mit.edu/

Cambridge, MA – The MIT Supply Chain Management Master’s Program has recognized thirty-five exceptional students from eight renowned undergraduate programs specializing in supply chain management and engineering across the United States.

Presented annually, the MIT Supply Chain Excellence Awards honor undergraduate students who have demonstrated outstanding talent in supply chain management or industrial engineering. These students originate from institutions that have partnered with the MIT Center for Transportation and Logistics’s Supply Chain Management master’s program to expand opportunities for graduate study and advance the field of supply chain and logistics.

In this year’s awards, the MIT SCM Master’s Program has provided over $900,000 in fellowship funding to 35 deserving recipients. These students come from respected schools like Arizona State University, University of Illinois Urbana-Champaign, Lehigh University, Michigan State University, Monterrey Institute of Technology and Higher Education (Mexico), Penn State University, Purdue University, and Texas A&M University.

Recipients can use their awards by applying to the SCM program after gaining two to five years of professional experience post-graduation. The fellowship funds can be applied towards tuition fees for the SCM master’s program at MIT or at MIT Supply Chain and Logistics Excellence (SCALE) network centers in Spain, Malaysia, Luxembourg, or China.

For more information about the MIT Supply Chain Excellence Awards, please visit here.

___________________________

About the MIT Center for Transportation & Logistics

Founded in 1973, MIT CTL is one of the world’s leading supply chain education and research centers. MIT CTL coordinates more than 100 supply chain research efforts across the MIT campus and around the globe. The center also educates students and corporate leaders in the essential principles of supply chain management and helps organizations to increase productivity and improve their environmental performance.

About the MIT Supply Chain Management Master’s Program (MIT SCM)

Founded in 1998 by the MIT Center for Transportation & Logistics (MIT CTL), MIT SCM attracts a diverse group of talented and motivated students from across the globe. Students work directly with researchers and industry experts on complex and challenging problems in all aspects of supply chain management. MIT SCM students propel their classroom and laboratory learning straight into industry. They graduate from our programs as thought leaders ready to engage in an international, highly competitive marketplace.

Supply Chain Excellence Contact: Kate Padilla kpadilla@mit.edu

Cambridge, MA – The AWESOME award represents a significant commitment by the MIT Supply Chain Management Master’s Program, the MIT Center for Transportation & Logistics, and AWESOME (Achieving Women’s Excellence in Supply Chain Operations, Management, and Education) to encourage students to prepare for and perform successfully in supply chain leadership roles. This fellowship was awarded to two students each year: one from the residential cohort and one from the blended.

Editor’s Note: The SCM capstone Case Fill Rate Prediction was authored by Madeleine Lee and Kamran Iqbal Siddiqui, and supervised by Dr. Elenna Dugundji (elenna_d@mit.edu) and Dr. Thomas Koch (thakoch@mit.edu). For more information on the capstone, please contact the thesis supervisors.

The fast-moving consumer goods (FMCG) industry, currently valued at $10 trillion, is poised for exponential growth, projected to reach $15 trillion by 2025. However, the industry’s complex supply chains and unpredictable demand patterns have been further complicated by recent disruptions such as the COVID-19 pandemic, the Suez Canal blockade, and port congestion. These challenges have highlighted the vulnerability of the FMCG sector, leading to unmet customer demands and jeopardizing business resilience.

To address these issues, our capstone project set out to identify the key factors contributing to low case fill rates (CFR) in an FMCG company and develop predictive models to improve future CFR. By harnessing data-driven insights, this project offers a transformative approach to managing CFR, ultimately enhancing sales, customer loyalty, and overall resilience within the FMCG landscape.

Common struggles

Consumer product companies, with diverse product portfolios, face the common struggle of maintaining optimal CFR in a dynamic business environment. CFR, calculated by dividing total shipments by total customer orders, serves as an indicator of a company’s ability to fulfill customer demands. A decline in CFR can result in lost sales, eroded customer loyalty, and even potential contract breaches. As little as a 1% drop in sales can translate into millions in lost net profit margin, underscoring the criticality of maintaining an optimal CFR.

Our project followed a robust three-phase methodology: business understanding, modeling, and validation. Extensive datasets, including sales transactions, customer purchase history, inventory levels, and manufacturing plans, were compiled to gain a holistic understanding of business operations and customer behavior. Rigorous data preprocessing techniques were employed to ensure data integrity, integrate diverse datatypes, and enhance data quality. And descriptive analytics, such as ACF (autocorrelation function) and PACF (partial autocorrelation function), were applied to identify autocorrelation in the time series dataset.

In the modeling phase, various techniques were employed to uncover patterns and forecast future CFR. Time series analysis enabled the isolation of the impact of single and multiple variables on CFR. Statistical methods, including decision tree matrices, were utilized to identify major drivers of low CFR. Two distinct approaches were taken: a hybrid model to predict cut quantities and, to forecast inventory availability and order quantity, advanced deep learning techniques, including XGBoost, LSTM, and multistep LSTM.

Improving forecast accuracy

The project yielded valuable insights into the factors influencing CFR. It was found that forecast accuracy and demand variability were the primary drivers impacting CFR. Inaccuracies between predicted and actual customer demands significantly influenced the CFR, underscoring the importance of improving forecast accuracy and maintaining adequate inventory levels.

The hybrid model, incorporating logistic regression, random forest regression, and support vector machine (SVM), demonstrated impressive precision and accuracy in predicting cut quantities and CFR. In the second approach, advanced time series machine learning models like XGBoost, LSTM, and multi-step-LSTM showed potential for short-term forecasting. While long-term predictions posed challenges, these models provided valuable insights for inventory optimization.

The project’s findings hold immense significance for the FMCG industry. By identifying forecast error and demand variability as critical factors impacting CFR, the project highlights the need for improved forecast accuracy and inventory optimization. Integrating exogenous factors, such as promotions and market indices, into forecasting models can further enhance accuracy and reliability.

Though challenges remain, such as inventory variability and irregular order patterns, the project lays a strong foundation for future research. Employing a combination of machine learning and deep learning techniques, exploring reinforcement learning, and incorporating additional data inputs like promotional activities and competitor pricing can lead to superior predictive accuracy. By adopting these data-driven insights, FMCG companies can proactively mitigate stockouts, enhance CFR, and thrive in an ever-changing business landscape.

Supply Chain Management Review

Every year, approximately 80 students in the MIT Center for Transportation & Logistics’s (MIT CTL) Master of Supply Chain Management (SCM) program complete approximately 45 one-year research projects.

These students are early-career business professionals from multiple countries, with two to 10 years of experience in the industry. Most of the research projects are chosen, sponsored by, and carried out in collaboration with multinational corporations. Joint teams that include MIT SCM students and MIT CTL faculty work on real-world problems. In this series, they summarize a selection of the latest SCM research.