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The growth–share matrix [2] (also known as the product portfolio matrix, [3] Boston Box, BCG-matrix, Boston matrix, Boston Consulting Group portfolio analysis and portfolio diagram) is a matrix used to help corporations to analyze their business units, that is, their product lines.
After its well-known growth-share matrix, the Boston Consulting Group developed another, much less widely reported, matrix which approached the economies of scale decision rather more directly. This is known as their Advantage Matrix. The matrix was published in a 1981 Perspective titled "Strategy in the 1980s" by Richard Lochridge. [1]
The growth-share matrix—or BCG Matrix, as it came to be known—is a managerial tool used to visually represent a company's portfolio. It is a two-by-two matrix, which divides the dimensions of relative market share (x-axis) and market growth (y-axis) into four quadrants.
Like in BCG analysis, a two-dimensional portfolio matrix is created. However, with the GE model the dimensions are multi factorial. One dimension comprises nine industry attractiveness measures; the other comprises twelve internal business strength measures. The GE matrix helps a strategic business unit evaluate its overall strength.
In the BCG study, participants using OpenAI’s GPT-4 for solving business problems actually performed 23% worse than those doing the task without GPT-4. Read more here . Other news below.
The DICE framework, or Duration, Integrity, Commitment, and Effort framework is a tool for evaluating projects, [1] predicting project outcomes, and allocating resources strategically to maximize delivery of a program or portfolio of initiatives, aiming for consistency in evaluating projects with subjective inputs.
The concept of the corporation as a portfolio of business units, with each plotted graphically based on its market share (a measure of its competitive position relative to its peers) and industry growth rate (a measure of industry attractiveness), was summarized in the growth–share matrix developed by the Boston Consulting Group around 1970.
A bivariate correlation is a measure of whether and how two variables covary linearly, that is, whether the variance of one changes in a linear fashion as the variance of the other changes. Covariance can be difficult to interpret across studies because it depends on the scale or level of measurement used.