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    • Introduction to Managerial Economics >
      • Basic Techniques
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  • What is Cluster Analysis
  • Preparing Data and Measuring Dissimilarities
  • Data Reduction and Unsupervised Learning
  • Hierarchical and k-Means Clustering
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  • Adding Uncertainty to a Spreadsheet Model
  • Defining Output Variables and Analyzing the Results
  • Using Historical Data to Model Uncertainty
  • Models with Correlated Uncertain Variables
  • Creating and Interpreting Charts
  • Using Average Values versus Simulation
  • Optimization and Decision Making
  • Formulating an Optimization Problem
  • Developing a Spreadsheet Model
  • Adding Optimization to a Spreadsheet Model
  • What-if Analysis and the Sensitivity Report
  • Evaluating Scenarios and Visualizing Results to Gain Practical Insights
  • Digital Marketing Application of Optimization
  • Advanced Models for Better Decisions
  • Business Problems with Yes/No Decisions
  • Formulation and Solution of Binary Optimization Problems
  • Metaheuristic Optimization
  • Chance Constraints and Value At Risk
  • Simulation Optimization
  • Marketing Analytics and Customer Satisfaction
  • Customer Satisfaction
  • Measurements and Scaling Techniques – Introduction
  • Primary Scales of Measurement
  • Comparative Scaling
  • Non-Comparative Scaling
  • Experiment Design: Controlling for Experimental Errors

Picture

BCG GROWTH-SHARE MATRIX

Companies that are large enough to be organized into strategic business units face the challenge ofallocating resources among those business units. In the early 1970, the Boston Consulting Group developeda model for managing a portfolio of different business units (or major product lines). The BCG growthsharematrix displays the various business units on a graph of the market growth rate vs. market sharerelative to competitors:
Resources are allocated to business units according to where they are situated on the grid as follows:

1. Cash Cows - business units that have a large market share in mature, slow growing industries. Cash cows
require little investment and generate cash that can be used to invest in other business units.

2. Stars - business units that have a large market share in a fast growing industry. Stars may generate cash, but
because the market is growing rapidly, they require investment to maintain their lead. If successful, a star
will become a cash cow when its industry matures.

3. Problem Child or Question Mark - business units that have a small market share in a high growth market.
These business units require resources to grow market share, but whether they will succeed and become
stars is unknown.

4. Dogs - business units that have small market share in a mature industry. A dog may not require substantial
cash, but it ties up capital that could better be deployed elsewhere. Unless a dog has some other strategic
purpose, it should be liquidated if there is little prospect for it to gain market share.
The BCG matrix provides a framework for allocating resources among different business units and allows
one to compare many business units at a glance. However, the approach has received some negative
criticism for the following reasons:

1. The link between market share and profitability is questionable since increasing market share can be very
expensive.
2. The approach may overemphasize high growth, since it ignores the potential of declining markets.
3. The model considers market growth rate to be a given. In practice, the firm may be able to grow the market.
Picture
The size of the circle indicates the amount of revenue the product/brand/sbu contributes to company
turnover
JBDON © 2009-2021 All rights reserved . E-learning Initiative by Applied Cloud Computing www.acc.ltd
  • Home
  • New Page
  • Soft Skills
    • Adaptability
    • Confidence
    • Change Management
    • Unlearning and Learning
    • Collaboration and Teamwork
    • Cultural Sensitivity
  • Marketing
  • Finance
  • Economics
    • Introduction to Managerial Economics >
      • Basic Techniques
      • The firm: Stakeholders, Objectives and Decision Issues
      • Scope of Managerial Economics
    • Demand and Revenue Analysis >
      • Demand Estimation and Forecasting
      • Demand Elasticity
      • Demand Concepts and Analysis
    • Prodution and Cost Analysis >
      • Production Function
      • Estimation of Production and Cost Functions
      • Cost Concepts and Analysis I
      • Cost Concepts and Analysis II
    • Pricing Decisions >
      • Pricing strategies
      • Market structure and microbes barriers to entry
      • Pricing under pure competition and pure monopoly
      • Pricing under monopolistic and oligopolistic competition
    • Narendra Modi Development Model of Gujarat
  • JBDON Golf
  • Let's Talk
  • MBA Project Sharing
  • About Us
  • CET Knowledge Zone
    • Tips From JBIMS Students >
      • Prasad Sawant
      • Chandan Roy
      • Ram
      • Ashmant Tiwari
      • Rajesh Rikame
      • Ami Kothari
      • Ankeet Adani
      • Sonam Jain
      • Mitesh Thakker
      • Tresa Sankoorikal
    • Speed Techniques
    • CET Workshops
  • What is Cluster Analysis
  • Preparing Data and Measuring Dissimilarities
  • Data Reduction and Unsupervised Learning
  • Hierarchical and k-Means Clustering
  • Cluster analysis using excel and excel miner
  • Adding Uncertainty to a Spreadsheet Model
  • Defining Output Variables and Analyzing the Results
  • Using Historical Data to Model Uncertainty
  • Models with Correlated Uncertain Variables
  • Creating and Interpreting Charts
  • Using Average Values versus Simulation
  • Optimization and Decision Making
  • Formulating an Optimization Problem
  • Developing a Spreadsheet Model
  • Adding Optimization to a Spreadsheet Model
  • What-if Analysis and the Sensitivity Report
  • Evaluating Scenarios and Visualizing Results to Gain Practical Insights
  • Digital Marketing Application of Optimization
  • Advanced Models for Better Decisions
  • Business Problems with Yes/No Decisions
  • Formulation and Solution of Binary Optimization Problems
  • Metaheuristic Optimization
  • Chance Constraints and Value At Risk
  • Simulation Optimization
  • Marketing Analytics and Customer Satisfaction
  • Customer Satisfaction
  • Measurements and Scaling Techniques – Introduction
  • Primary Scales of Measurement
  • Comparative Scaling
  • Non-Comparative Scaling
  • Experiment Design: Controlling for Experimental Errors