GEOP 4355 Supply Networks: Decision Models

Slides:



Advertisements
Similar presentations
Slides 8a: Introduction
Advertisements

Decision Theory.
To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-1 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Prepared by.
Lesson 9.1 Decision Theory with Unknown State Probabilities.
20- 1 Chapter Twenty McGraw-Hill/Irwin © 2005 The McGraw-Hill Companies, Inc., All Rights Reserved.
Chapter 3 Decision Analysis.
Decision Theory.
Decision Process Identify the Problem
Chapter 3 Decision Analysis.
Ch 7 Decision theory Learning objectives: After completing this chapter, you should be able to: 1.Outline the characteristics of a decision theory approach.
Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Chapter Twenty An Introduction to Decision Making GOALS.
©The McGraw-Hill Companies, Inc. 2008McGraw-Hill/Irwin An Introduction to Decision Making Chapter 20.
Dr. C. Lightner Fayetteville State University
Chapter 7 Decision Analysis
Decision Analysis Chapter 13.
Decision Theory is a body of knowledge and related analytical techniques Decision is an action to be taken by the Decision Maker Decision maker is a person,
Part 3 Probabilistic Decision Models
1 1 Slide Decision Analysis Professor Ahmadi. 2 2 Slide Decision Analysis Chapter Outline n Structuring the Decision Problem n Decision Making Without.
Topic 2. DECISION-MAKING TOOLS
ISMT 161: Introduction to Operations Management
Decision Making Under Uncertainty and Under Risk
Decision Analysis Introduction Chapter 6. What kinds of problems ? Decision Alternatives (“what ifs”) are known States of Nature and their probabilities.
To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 3-1 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ Chapter 3 Fundamentals.
Operations Management Decision-Making Tools Module A
Decision Making Under Uncertainty Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing.
1 1 Slide © 2005 Thomson/South-Western EMGT 501 HW Solutions Chapter 12 - SELF TEST 9 Chapter 12 - SELF TEST 18.
Chapter 12: Inventory Control Models
Chapter 8 Decision Analysis n Problem Formulation n Decision Making without Probabilities n Decision Making with Probabilities n Risk Analysis and Sensitivity.
Module 5 Part 2: Decision Theory
“ The one word that makes a good manager – decisiveness.”
An Introduction to Decision Theory (web only)
3-1 Quantitative Analysis for Management Chapter 3 Fundamentals of Decision Theory Models.
1 1 Slide Decision Theory Professor Ahmadi. 2 2 Slide Learning Objectives n Structuring the decision problem and decision trees n Types of decision making.
Decision Making Under Uncertainty and Risk 1 By Isuru Manawadu B.Sc in Accounting Sp. (USJP), ACA, AFM
Chapter 9 - Decision Analysis - Part I
Decision Analysis Steps in Decision making
Copyright 2006 John Wiley & Sons, Inc. OPIM 3104: Lecture #1 Introduction to OM Instructor: Jose M. Cruz.
Welcome Unit 4 Seminar MM305 Wednesday 8:00 PM ET Quantitative Analysis for Management Delfina Isaac.
Decision Theory McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved.
Models for Strategic Marketing Decision Making. Market Entry Decisions To enter first or to wait Sources of First-Mover Advantages –Technological leadership.
Data Analysis and Decision Making (Albrigth, Winston and Zappe)
TM 732 Engr. Economics for Managers Decision Analysis.
Decision Analysis.
1 1 © 2003 Thomson  /South-Western Slide Slides Prepared by JOHN S. LOUCKS St. Edward’s University.
Decision Theory Copyright © 2015 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of McGraw-Hill.
Chapter 12 Decision Analysis. Components of Decision Making (D.M.) F Decision alternatives - for managers to choose from. F States of nature - that may.
DECISION MODELS. Decision models The types of decision models: – Decision making under certainty The future state of nature is assumed known. – Decision.
Chapter 8 Decision Analysis n Problem Formulation n Decision Making without Probabilities n Decision Making with Probabilities n Risk Analysis and Sensitivity.
1 1 Slide © 2005 Thomson/South-Western Chapter 13 Decision Analysis n Problem Formulation n Decision Making without Probabilities n Decision Making with.
Problems Decision Making under Uncertainty Rahul Chandra.
Part Three: Information for decision-making Chapter Twelve: Decision-making under conditions of risk and uncertainty Use with Management and Cost Accounting.
DECISION THEORY & DECISION TREE
Chapter 5 Supplement Decision Theory.
Chapter 5 Capacity Planning.
Chapter Twenty McGraw-Hill/Irwin
The nature and character of the exchange process
Tools for Decision Analysis: Analysis of Risky Decisions
Welcome to MM305 Unit 4 Seminar Larry Musolino
Slides 8a: Introduction
FORECASTING.
Chapter 5 Capacity Planning.
MANAGEMENT AND COST ACCOUNTING
Supplement: Decision Making
Supply Chain Management (SCM) Basics
GEOP 4355 Supply Networks: Supplier management
Marketing Management Module 1
Decision Theory.
Modeling T.Reema T.Rawan.
Making Decisions Under Uncertainty
Decision Making without State Probabilities
Presentation transcript:

GEOP 4355 Supply Networks: Decision Models Outline Supplier decision models Supply decision models Sources/references used in the preparation of this presentation are listed in the Introduction presentation

Supplier decision models Decision Analysis Theory models Based on the concept of relating multiple alternatives to multiple possible futures. DA = Decision alternatives SN = states of nature = possible futures. Each relation is called a payoff. Assumptions All alternatives are considered All futures are considered

Supplier decision models Alternatives: Supplier A = high quality but low capacity Supplier B = high technology and expensive Supplier C = high capacity and moderate costs Future (SN = States of Nature) Two elements: Competition focus and market trend Market trend: up, down (Up, Down) Competition: focuses on new technology (T) or focuses on efficiency (E) Four SNs: Up/T; Up/E; Down/T; Down/E Market Competition Up T E Down Probability 35% 30% 25% 10%

Supplier decision models The table presents the effect on Market Share given each supplier and state of nature combination. We want the highest market share possible. States of Nature (SNs) Market Competition Up T E Down Supplier A 5% 12% -3% -9% Supplier B 11% 4% 6% Supplier C 1% 3% Alternatives For example. If we select supplier B and the Market is Up, and the competition focuses on Technology our market share will increase by 11%

Supplier decision models What supplier should be selected? Four decision models (called decision theory models). Optimistic Conservative Minimize Maximum Regret (Regret = Error) Expected value

Supplier decision models Optimistic. Select alternative provides the best result across all possible futures. Market Competition Up T E Down Supplier A 5% 12% -3% -9% Supplier B 11% 4% 6% Supplier C 1% 3% The optimistic decision is to select Supplier A

Supplier decision models The conservative decision aims to minimize risk. Selects the best of the worst. Add a column with the worst for each alternative. Market Competition Up T E Down Worst Supplier A 5% 12% -3% -9% Supplier B 11% 4% 6% Supplier C 1% 3%

Supplier decision models The conservative decision aims to minimize risk. Selects the best of the worst. Market Competition Up T E Down Worst Supplier A 5% 12% -3% -9% Supplier B 11% 4% 6% Supplier C 1% 3% The conservative decision is to select Supplier C

Supplier decision models The minimize maximum regret (error) method considers the effect of a wrong selection. It minimizes the maximum error. A “middle” of the road recommendation. Process has 3 steps.

Supplier decisions models Step 1. Add a row with the best payoff for each possible SN Market Competition Up T E Down Supplier A 5% 12% -3% -9% Supplier B 11% 4% 6% Supplier C 1% 3% Best

Supplier decision models Step 2. Create an error (regret) table. Difference between each payoff and the best payoff for that SN. Market Competition Up T E Down Supplier A 5% 12% -3% -9% Supplier B 11% 4% 6% Supplier C 1% 3% Best 6% - - 3% = 9% 11% - 5% = 6% 12% - 12% = 0% Market Competition Up T E Down Supplier A 6% 0% 9% 15% Supplier B 8% Supplier C 10% 2%

Supplier decision models Step 3. Add a column with the maximum value for each alternative (for the error table!). Market Competition Up T E Down Max Error Supplier A 6% 0% 9% 15% Supplier B 8% Supplier C 10% 2%

Supplier decision models The min-max regret solution has the smallest maximum error. Market Competition Up T E Down Max Error Supplier A 6% 0% 9% 15% Supplier B 8% Supplier C 10% 2% The min-max regret decision is to select Supplier B

Supplier decision models Expected value is based on the weighted average of payoffs EV(X) = 𝑦= 𝑎𝑙𝑙 𝑆𝑁 𝑝𝑟𝑜𝑏𝑎𝑏𝑖𝑙𝑖𝑡𝑦 𝑦 ×𝑝𝑎𝑦𝑜𝑓𝑓(𝑦,𝑋) Market Competition Up T E Down Probability 35% 30% 25% 10% Market Competition Up T E Down Supplier A 5% 12% -3% -9% Supplier B 11% 4% 6% Supplier C 1% 3% EV(Supplier A) = 35% × 5% + 30% × 12% + 25% × -3%+ 10% × -9% = 3.7% EV(Supplier B) = 35% ×11% + 30% × 4% + 25% × 6%+ 10% × -3% = 6.25% EV(Supplier C) = 35% × 1% + 30% × 3% + 25% × 4%+ 10% × 6% = 2.85% The EV decision is to select Supplier B

Supplier decision models Thus different models have different recommendations. Optimistic: Supplier A Conservative: Supplier C Min-max regret: Supplier B EV: Supplier B Which model to use depends on the decision maker’s attitude towards risk, and the confidence on any probability estimates available.

Supply decision models A purchasing manager must determine the amount of a key raw material to buy for a new product. This is a made to order raw material with a long lead time, thus additional material cannot be procured in this cycle. They must buy the raw material in lots of 400 and each lot costs $10,000. Raw material not used is lost due to a fast deterioration. Cost to produce and deliver the final product is $10/unit and will be based only on the demand.

Supply decision models Demand for the new product is not known. However the sales department has provided three estimates of how much they will sell and the price customers will be willing to pay for it. Low demand, low prices: Market for about 1,220 at an average of $45/each. P = 60% Medium demand/ medium prices: Market for about 1,530 at an average of $55/each. P = 20% High demand/ high prices: Market for about 2,250 at an average of $60/each. P = 20% States of nature: the demand and prices Decision alternatives: how much raw material to order from the supplier ahead of the production cycle.