Title

Essays at the interface of operations and risk management

Date of Completion

January 2010

Keywords

Business Administration, Management

Degree

Ph.D.

Abstract

Successful implementation of business strategy requires proper integration of operations and financial management. This dissertation is aimed at applying optimization techniques to solve real-life problems that are at the interface of operations and working capital management. The first essay focuses on different outsourcing arrangements for back-office operations between a financial services firm and an outsourcing vendor. To meet dynamic and stochastic demand requirements, the financial services firm complements in-house operations with outsourcing. The second essay analyzes inventory and advertising policies of a start-up firm. Risk exposure is a critical aspect in start-up operations. It is imperative for the management to have a perception of the risks involved in any decision they plan to implement. We develop a heuristic that provides us a mechanism to construct efficient risk-reward curves in a stochastic dynamic setting. Important managerial insights are deduced based on the risk-reward for a set of policies. The third essay explores the emerging field of Supply Chain Finance (SCF). The physical side of supply chains has been a subject of much research. However, when it comes to their trade operations, the goals of the buyer and their suppliers, in many cases, are not aligned. This leads to suboptimal decisions for the supply chain as a whole. Recently financial intermediaries have come up with innovative trade solutions that are providing financial win-wins for all the supply chain partners. Here we examine the payables management problem of a buying firm in a supply chain scenario with SCF enabled Early Payment Program in place. Finally, the fourth essay studies risk-reward trade-offs in finite-horizon stochastic dynamic programming models. The objective in these models is to deduce optimal policies based on expected reward criteria. However, in many cases, managers are concerned about the risks or the variability associated with a set of policies and not just the expected reward. Here we develop heuristics that systematically track the variance and the average reward for a set of policies in a stochastic dynamic setting, and instead of identifying one policy to achieve the stated objective, finds the set of policies that form the efficient frontier. ^