A Data-Driven Approach to Managing Food Security in Global Supply Chains

A Data-Driven Approach to Managing Food Security in Global Supply Chains
Retsef Levi, Spencer Standish (1945) Professor of Management, Professor of Operations Management
Tauhid Zaman, Assistant Professor of Operations Management
Yanchong Zheng, Associate Professor of Operations Management

Period of performance: 

September 2015 to August 2017


It is estimated that 15% of all food products consumed in the U.S. are imported, whereas in some product categories, such as seafood, more than 80% is imported. The global scale of food supply chains implies that food supplies can be susceptible to changing socio-economic and environmental conditions in regions that are very distant from the end market. In 2011, President Obama signed into law the FDA Food Safety Modernization Act, giving the FDA new authorities to regulate the ways foods are grown, harvested, and processed. The Act also holds companies responsible to guarantee the quality of their supply chains. This Act reflects the increasing concerns of governments and firms regarding global supply chain-related security and safety threats. In the meantime, the disproportionate imbalance between rapid growth of regulated food imports and marginal increase in inspection and port sampling capabilities makes it almost mandatory to develop more systematic and data-driven approaches to identify ‘risky’ products and allocate the scarce inspection resources in the most effective way. The proposed research will focus on studying two major parts of global food supply chains: (i) farming supply chains that connect farmers who grow plants and animals with food manufacturers; (ii) shipping supply chains that connect food manufacturers with markets of consumers.

In particular, the focus will be on understanding how the structure and dynamics of these supply chains are correlated with and impact disruption (food security) and quality (food safety) related risks. The expected outcomes of the proposed research are: (i) qualitative and quantitative measures of what structural features and characteristics of farming and shipping food supply chains are correlated with increased levels of disruption and safety risks; (ii) predictive models to dynamically identify evolving disruption and safety risks based on supply chain structures and dynamics.

We expect that these outcomes will inform various decisions faced by firms and regulatory bodies, such as (i) regulation of global supply chains; (ii) assessment of risky food supply chains and recommended designs with increased security and safety levels; (iii) real-time risk management strategies to monitor food supply chains, dynamically assess and prioritize risks and employ appropriate interventions; (iv) development of technical and technological solutions to better monitor and trace food supply chains. Our research methodologies will integrate qualitative analysis of case studies and field data to derive hypotheses with mathematical modeling, big data analytics, and state-of-the-art statistical analysis of large-scale networks.