Qiong Wang works on problems with managerial and policy Implications
5/18/2017 11:10:46 AM
After doing research at Bell Labs for over a decade, Professor Qiong Wang joined the department of ISE in 2012. At ISE, he is carrying out a research agenda to address problems that arise from private business management and public policy development.
One area of his research involves developing control policies for assemble-to-order (ATO) inventory systems. The problem involves two related questions: how many components to order; and which customers to serve? Both decisions need to be made dynamically over time, in the absence of exact knowledge about future demands. The challenge is finding an efficient solution to balance the need to satisfy customers with the desire to reduce inventory costs.
Wang first encountered this problem at Bell Labs when he was helping its parent company, Alcatel-Lucent (now Nokia USA), to improve its supply chain performance. Optimizing an ATO system is a long-standing unsolved problem in the inventory literature.
“So the topic combines the best of two worlds.” Wang says. “On the one hand, we want to attack a difficult problem to advance the research frontier. On the other hand, solving the problem also helps to improve the practice of inventory management.”
Wang has also done research on revenue management and pricing, which, like inventory control, aims at improving the performance of enterprise systems. Not surprisingly, much of his work is pertinent to the telecommunications industry where he used to work.
“In this industry, managerial decision-making not only is a business concern, but also has profound implications on public policy.” Wang observes.
The debate over net neutrality gives a strong demonstration of this observation. The basic issue is whether internet service providers (ISPs) should be allowed to provide services at different quality levels and charge customers accordingly. Whereas from the engineering perspective, there are clear advantages to differentiating customers based on the bandwidth needs of their applications, there are also concerns about whether the ISPs will exploit this flexibility to enhance their profits at the expense of societal and consumer welfare.
“The question has been passionately debated and the answer can be rather complicated,” Wang says. “Operation research can be a great help here by building models to quantify various tradeoffs involved, capturing economic incentives of different players, and applying mathematical logic to infer likely outcomes.”
As a former employee, Wang has tremendous admiration for the scientific achievements of Bell Labs over the past century. He has also witnessed a significant change of direction of the lab in the last decade or so. What will be the future of industrial labs? How should lab managers balance resource allocation in research, which explores uncharted territories, and development, which exploits new ideas for commercial gains? To answer these intriguing questions, Wang has joined forces with Professor Debasis Mitra at Columbia University, who was both a distinguished researcher and a senior manager at Bell Labs, to develop models and analysis that help us to understand investment, structure, and sustainability of industrial labs.
While the subject matter of Wang’s research may vary, the underlying studies are united by a common theme: applying quantitative modeling and analysis to dissect and optimize real-world managerial and policy decision making. Many of his topics have traditionally been addressed by social scientists and legal scholars. Nevertheless, Wang believes that, equipped with an ever-growing arsenal of analytical tools, operation researchers and industrial engineers are in a unique position to provide novel insights and make substantial contributions in these domains.