Skip to main content Skip to main navigation Skip to search Skip to footer

A Systematic Approach to Comparative Decision-Making Using Pseudo inverses

A Systematic Approach to Comparative Decision-Making Using Pseudo inverses

There exist a number of circumstances in businesses where we make comparative decisions. Whether it be a set of ideas, concepts, or people, what we essentially assume is that there exists some "potential" associated with each one of them, and we assign values to those potentials by comparing them with one another. This is a very difficult problem if the number of “substances under comparison” is large. Here it is beneficial to split the problem into small, simpler problems and solve them all at once. It is also beneficial to get a quantitative measure of our understanding about the problem we are solving. Here, in this paper, we show how to take the bigger problem, split it into smaller problems, form a set of linear equations and solve these equations using standard techniques from linear algebra. The method here also evaluates our understanding about the problem and the requirement for a thorough evaluation.

In essence, this whitepaper provides a systematic approach to effectively compare options by reducing the subjectivity and noise which hinders effective “present-day decision making.”

DOWNLOAD THE WHITEPAPER

Contact Us
Maximum character limit is 10,000 including new lines.

HCL Technologies Ltd. will treat any information you submit with us as private and confidential. We will not share your personal information with any third party, except where disclosure is made at your request or with your consent or where required by law. Please read our Privacy statement for additional information.

HCL Technologies Ltd. will treat any information you submit with us as private and confidential. We will not share your personal information with any third party, except where disclosure is made at your request or with your consent or where required by law. Please read our Privacy statement for additional information.