NSF Award # 0747779

Integrating Project and Supply Chain Management

Yao Zhao, PhD

Professor in

Supply Chain Management

News & Events

Talk at MIT –SDM on 787 Dreamliner:




Over the last three to four decades, advances in technology and the networked economy have led to the evolution of the business models in many project driven industries, from the one-company-does-all approach to a more collaborative and decentralized one on a global basis. While this has brought tremendous benefits in the areas of market expansion, technological innovations and cost reduction, it also led to significant challenges in the coordination and management of the project (driven) supply chains. Indeed, with the outsourced work accounting for 50% or more of the revenue for projects in these industries, supply chain management has never been so important.


The problems studied in this NSF-funded project share a common feature – project management and supply chain management decisions are intertwined. In practice, they are typically managed as projects without taking the supply chain perspective into account. In academia, the connections and interactions between the projects and their supply chains are yet fully recognized and understood. We studied these problems by an interdisciplinary approach, which combines mathematical modeling with empirical studies. Our objective is to develop new insights and solutions beyond conventional wisdom, and reconcile the discovery with practice to demonstrate its economic or social impact.

Research Streams:

1. Development Chain Coordination: One-of-a-kind development projects with an extensive workload outsourced (found in the aerospace and defense industries).

2.  Clinical Trial Supply Management: Clinical trial projects with a global network of testing sites and investigative drug distribution (found in the pharmaceutical and biotech industries).

3.    Recurrent projects subject to random material delays (found in the construction industry).


1. Development Chain Coordination

Motivation: This stream of work is motivated by recent practice in the Aerospace and Defense industies. Product development programs (e.g., the Dreamliner, Airbus 380, China 919, F35 and Global Hawk) outsourced a signifcant amount of workload in design and/or fabriaction to a global network of suppliers. While outsourcing offers irresistible benefits in market expansion, utilization of the best-in-class technologies, and cost/cycle-time reduction, it poses a significant challenge for the project supply chains, which are increasingly more complex, more risky and involve more organziations with diverse strategic motivations. Indeed, many of these programs have experienced or are experiencing significant delays and cost overrun. Naturally, people asked, what caused those delays? How to avoid them the next time?

Summary of our work:

1.  We wrote a case study, Build-to-Performance: The Boeing 787 Dreamliner, to thoroughly document the facts, events and data of the 787 development program by collecting information from publically available sources such as, the new medias, web commentaries, case studies and financial reports.

2.  We conducted an empirical study, Why 787 Slips Were Inevitable?, to identify the real causes for a majority of the 787 delays, and to reveal the rationale behind many irrational behaviors that delayed this program.

3. We constructed a game theoretical model, Incentives and Alignment in Collaborative Projects, to analyze the firms‘ strategic motivation and economic incentives under the risk sharing partnership, and to propose a new partnership, fair sharing, that can align the firms‘ best interest with that of the program.

·     Case Study: “Build-to-Performance –The Boeing 787 Dreamliner

The Story: In September 2011, the first Dreamliner was finally delivered to All Nippon Airways, Japan, the launching customer of the Boeing 787 program, after 40 months of agonizing delays. Boeing’s executives, in particular, the 3rd manager of the 787 program, Scott Fancher (he replaced Pat Shanahan who replaced Mike Bair), finally got a relief from the huge pressure imposed by the share-holders, suppliers and customers. Looking back at the delays and the damages to the company’s reputation and standing in the market place, as well as the profitability of this program, Scott felt lucky, as the situation could have been much worse. 

Reviewing the 787 development process, Scott can hardly believe how many delays there were and how long they took, how many embarrassing mistakes were made, and how much effort and expense that Boeing had to pay to bring the program back on track. Although the pain is almost over, he cannot help but thinking how such problems could have been avoided in the first place?

·     Empirical Study – “Why 787 slips were inevitable?”

Abstract: Boeing 787, the Dreamliner, was the fastest-selling plane ever in the commercial aviation industry. However, its development was a nightmare – the first flight was delayed by 26 months, and the first delivery was delayed by 40 months with a cost overrun of at least $11 billion. By a comprehensive empirical study of the actual events and facts, we find strong evidence to suggest that a majority of the delays were intentional. An economic analysis of incentives and gaming behaviors in joint development projects discovers that the 787’s risk-sharing partnership forced Boeing and its partners to share the “wrong” risk. This led the firms into a Prisoner’s Dilemma, where delays were in the best interests of these firms, although doing so drove them into a disaster. We reconcile the economic analysis with the empirical evidence to reveal the rationale behind many seemingly irrational behaviors that delayed this program. Finally, we suggest a new “fair sharing” partnership to share the “right” risk and greatly alleviate delays for development programs of this kind.

·  Mathematical Modeling – Xu, X., Y. Zhao (2014). “Incentives and Alignment in Collaborative Projects.” Working Paper. Rutgers Business School. NJ

Abstract: Collaboration and partnership are the way of life for many projects in diverse industries where the outcome depends on the joint efforts of multiple firms. Although partnership (teamwork) and externality are well studied in the economics literature, their explicit expressions and implications in project management are not. Specifically, it remains unclear as how collaboration may change firms' behaviors in project execution and impact the overall project performance in time and cost. Utilizing a novel model that integrates the economic theory of teamwork with project management specifics, we study incentives and strategic behaviors of firms under the popular loss-sharing partnership. For a typical project network with both parallel and sequential tasks where each firm faces a time-cost trade-off, we reveal an inherent conflict of interests between individual firms and the project. Depending on the cost and network structures, we discover explicit forms of externality in the content of project operations, such as, the Prisoners' Dilemma in project execution, the Supplier's Dilemma, and the Coauthors' Dilemma. These dilemmas reveal how individual firms can be driven by selfish motives to deliberately delay tasks against the best interest of the project and exactly how collaboration can deteriorate project performance. As a remedy, we suggest a new ``fair-sharing" partnership and prove its effectiveness in handling the externalities in collaborative projects.

2. Clincial Trial Supply Management

Motivation: Clinical trial supply management offers a substantial opportunity to cut costs and improve efficiency as the cost of clinical supplies could account for 20 per cent or more of a company’s R&D spending. The opportunity lies in the fact that companies typically manage clinical trials as projects, and set up the trials without considering supply chain issues. However, the project and supply decisions are tightly coupled; for instance, globalisation improves significantly project metrics (for example, patient recruitment), but imposes a huge challenge on supply metrics (cost and drug availability). Thus, integrating clinical trial project decisions (country and site selection, protocol design) with supply decisions (inventory levels, logistics network) offers a significant opportunity for companies to do more with less.

Summary of Our Work:

1. We wrote a case study, CTR Clinical Research – Clinical Trial Supply Management, to understand some of the key issues in clinical trial supply chains.

2.       We conducted an empirical study, Contract Development and Manufacturing Costs During Clinical Development of A New Drug, to estimate the financial impact of supplies on clinical trials by collecting data from companies‘ SEC filings.

3.    We present various mathematical models to help firms streamline their clinical supply operations, such as production planning and inventory management, and integrate with their clinical project operations.

·     Case Study: “CTR Clinical Research – Clinical Trial Supply Management”

The Story: James Collins is a project manager at SPRI Pharmaceuticals Inc. supervising clinical trials. One of the current clinical trials under his supervision is on the experimental medicine SPRINT-HC for treating Hepatitis C. The clinical trial commenced on Oct. 1st 2009, and now it has been six months into the study.  A third party company CTR-PHONE, a subsidiary of CTR Clinical Research, tracks and manages drug inventory for this trial.

Since the beginning of this clinical trial, James has received a number of complaints from the research sites, while some said that CTR-PHONE sent shipments quantities that overwhelm their storage space, others said that CTR-PHONE is not supplying enough medicine. Insufficient inventory at research sites is of great concern to James as it risks slowing down patient recruitment and invalidating the trial. However, too much inventory at the sites risks leftover at the end of the trial and thus a waste of precious materials. James notices that similar complaints are filed in other clinical trials that he and his colleagues supervised. He wonders what can be done to eliminate these problems encountered by CTR-PHONE.

· Empirical Study – Fleischhacker, A., Y. Zhao (2013). “Contract Development and Manufacturing Costs DuringClinical Development of A New Drug.” Working Paper. Rutgers Business School.

Abstract: Clinical trial supply is an area often ignored by pharmaceutical and bio-tech companies partially due to a lack of understanding of its financial impact. Through a study of several 
firms’ expenditures on clinical supply and manufacturing activities, we estimate the magnitude of R&D budgets devoted to these activities. In these examples, roughly 30% - 40% of clinical trial spending is attributable to supplying the investigational drugs and developing the production process.

·  Analytical Modeling 1 – Fleischhacker, A., A. Ninh, Y. Zhao (2012). “Positioning Inventory in Clinical Trial Supply Chains.” To appear in Production and Operations Management.

Abstract: As a result of slow patient recruitment and high patient costs in the United States, clinical trials are increasingly going global. While recruitment efforts benefit from a larger global footprint, the supply chain has to work harder at getting the right drug supply, to the right place, at the right time. Certain clinical trial supply chains, especially those supplying biologics, have a combination of unique attributes that have yet to be addressed by existing supply chain models. These attributes include a fixed patient horizon, an inflexible supply process, a unique set of service-level requirements, and an inability to transfer drug supplies among testing sites. In this paper, we provide a new class of multi-echelon inventory models to address these unique aspects. The resulting mathematical program is a nonlinear integer programming problem with chance constraints. Despite this complexity, we develop a solution method that transforms the original formulation into a linear integer equivalent. By analyzing special cases and numerically studying a hypothetical real-life example, we develop novel insights into inventory positioning in clinical trial supply chains. We also study the impact of site network on the supply chain cost and the trade-off between inventory overage and the expected recruitment time.

·     Analytical Modeling 2 – Fleischhacker, A., Y. Zhao (2011). “The Dynamic Economic Lot-size Model for Clinical Trial Supply Chains: Planning for Demand Failure. European Journal of Operational Research 211: 496-506

Abstract: This paper examines the optimal production lot size decisions for clinical trial supply chains. One unique aspect of clinical trial supply chains is the risk of failure, meaning that the investigational drug is proven unsafe or ineffective during human testing and the trial is halted. Upon failure, any unused inventory is essentially wasted and needs to be destroyed. To avoid waste, manufacturers could produce small lot sizes. However, high production setup costs lead manufacturers to opt for large lot sizes and few setups. To optimally balance this tradeoff of waste and destruction versus production inefficiency, this paper generalizes the Wagner-Whitin model (W-W model) to incorporate the risk of failure. We show that this stochastic model, referred to as the failure-risk model, is equivalent to the deterministic W-W model if one adjusts the cost parameters properly to reflect failure and destruction costs. We find that increasing failure rates lead to reduced lot sizes and that properly incorporating the risk of failure into clinical trial drug production can lead to substantial cost savings as compared to the W-W model without the properly adjusted parameters.

·   Analytical Modeling 3 – Fleischhacker, A., Y. Zhao (2013). “Balancing Learning and Economies of Scale for Adaptive Clinical Trials.” Operations Research for Health Care 2: 42-51

AbstractPrior to the start of an adaptive clinical trial, demand for an investigational drug can be highly uncertain. Both recommended dosages and forecasted patient recruitment can fluctuate in response to early trial results. While initial demand forecasts can be very wrong, the factors influencing future demand can be learned during the trial. To take advantage of this learning, intra-trial production and/or packaging can be leveraged, but this is done at the expense of scale economies. In this paper, we study the balance between learning and economies of scale for adaptive clinical trials. We characterize the optimal production (or packaging) decisions and through analytical and numerical studies, we develop insights on the impact of 
fixed costs, learning rates in terms of forecasting future demand, inventory overage costs, and inventory underage costs on the value of having intra-trial flexibility and on decisions regarding quantity and timing of drug supply.

3. Recurrent Projects With Random Material Delays

Motivation: Today, construction projects frequently spend a significant portion of their budgets (more than 50 per cent) on materials sourced from an extended supply network. However, projects and their material supply chains are often managed in separation despite the fact that they are tightly coupled, for instance, lean supply practice often leads to long and variable material lead-times which may ruin the project schedule and result in expediting cost and/or delay penalties.

Summary of Our Work:

1.       We wrote a case study, ICM Inc. – Construction Resource Management, to understand the current practice of material management in construction projects.

2.   We conducted an empirical study, Some Economic Facts on Prefabricated housing”, to illustrate the connections between project and supply chain operations in the real life practice.

3.      We established a class of mathematical models to study the connections and quantify the impact of the integrating project and supply chain operations in the construction industry.

·     Case study: “ICM Inc. – Construction Resource Management”

The storyMihir is a new assistant project manager at Intercontinental Construction Management Inc (ICM), a New Jersey based engineering/construction company. As his first task, he assists in managing and planning for the west point project which starts in January.  In February, he got a call from the structural steel supplier that delivery to one of new buildings at the site will be delayed by one week. This means one week delay of the new building if no action is taken.  Usually, ICM expedites some tasks to avoid project delay at the cost of construction labor.

Looking at past projects, Mihir noticed that the same kind of structural steel is used in all ICM’s military projects. Given about 25 weeks of total project duration, the lead time of structural steel is relatively long (4-6 weeks) and varies quite significantly. Mihir wonders what else he can do to better match material delivery with project schedule except passively expediting tasks when a material delay occurs. Mihir also realizes that this problem is connected to a more challenging issue: A few major competitors are bidding against ICM on several construction projects. The customer, US Military, has made it clear that the winner must provide superior project schedule and competitive cost structure.

·     Empirical study – “Some Economic Facts on Prefabricated housing

Abstract: We compare and contrast the current practice of the prefabricated housing among three countries: the U.S., Japan and China, to illustrate the advantages and challenges of this relatively new approach in the construction industry. We also exemplify the operations management practice through real-world practice for the prefabricated housing and point out the future trends.

·    Analytical Modeling – Xu, X., Y. Zhao, C. Chen (2012). “Project-Driven Supply Chains: Integrating Safety-Stock and Crashing Decisions for Recurrent Projects.” To appear in Annals of Operations Research.

Abstract: We study a new class of problems -- recurrent projects with random material delays, at the interface between project and supply chain management. Recurrent projects are those similar in schedule and material requirements. We present the model of project-driven supply chain (PDSC) to jointly optimize the safety-stock decisions in material supply chains and the crashing decisions in projects. We prove certain convexity properties which allow us to characterize the optimal crashing policy. We study the interaction between supply chain inventory decisions and project crashing decisions, and demonstrate the impact of the PDSC model using examples inspired by real-world practice.