Determining Supply Requirement in the Sales-and-Operations-Planning (S&OP) Process Under Demand Uncertainty: A Stochastic Programming Formulation and a Spreadsheet Implementation

Journal of the Operational Research Society, Forthcoming

26 Pages Posted: 16 Jul 2010

See all articles by ManMohan S. Sodhi

ManMohan S. Sodhi

City University London - Sir John Cass Business School

Christopher S. Tang

University of California, Los Angeles (UCLA) - Decisions, Operations, and Technology Management (DOTM) Area

Date Written: May 5, 2010

Abstract

We show how to extend the demand planning stage of the sales-and-operations-planning (S&OP) process with a spreadsheet implementation of a stochastic programming model that determines the supply requirement while optimally trading off risks of unmet demand, excess inventory and inadequate liquidity in the presence of demand uncertainty. We first present the model that minimizes the weighted sum of respective conditional value-at-risk (cVaR) metrics over demand scenarios in the form of a binomial tree. The output of this model is the supply requirement to be used in the supply planning stage of the S&OP process. Next we show how row-and-column aggregation of the model reduces its size from exponential (2^T) in the number of time periods T in the planning horizon to merely square (T^2). Finally, we demonstrate the tractability of this aggregated model in an Excel spreadsheet implementation with a numerical example with 26 time periods.

Keywords: Supply Chain Risk Management, Risk Models, Stochastic Programming, Supply-Chain Planning, Demand Planning, Demand Uncertainty, Sales-and-Operations Planning (S&OP), Risk Metrics, Conditional Value-at-Risk (Cvar), Spreadsheet, Newsvendor Problem

Suggested Citation

Sodhi, ManMohan S. and Tang, Christopher S., Determining Supply Requirement in the Sales-and-Operations-Planning (S&OP) Process Under Demand Uncertainty: A Stochastic Programming Formulation and a Spreadsheet Implementation (May 5, 2010). Journal of the Operational Research Society, Forthcoming, Available at SSRN: https://ssrn.com/abstract=1639873

ManMohan S. Sodhi (Contact Author)

City University London - Sir John Cass Business School ( email )

106 Bunhill Row
London, EC1Y 8TZ
United Kingdom

Christopher S. Tang

University of California, Los Angeles (UCLA) - Decisions, Operations, and Technology Management (DOTM) Area ( email )

110 Westwood Plaza
Los Angeles, CA 90095-1481
United States

HOME PAGE: http://www.anderson.ucla.edu/x980.xml

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