Applied Information Economics (AIE): Not just calculate, scientifically MEASURE IT

1

Enterprise Architecture is stymied by the lack of a framework to measure its benefits. Can Applied Information Economics (AIE) solve this problem?

Introduction

The economic benefit analysis of an Enterprise Architecture Integration program is directly related to the success of an Enterprise Architecture program. However, the benefits of Enterprise Architecture cannot be measured in a meaningful way. Therefore, the result is that Enterprise Architecture is not as widely adopted as it otherwise would be. This article explains how Applied Information Economics (AIE), a revolutionary methodology invented by Douglus Hubbard of Hubbard Decision Research, fills in those unanswered gaps that act as a dangerous trap for enterprise investment decision makers. This article explains why AIE is so important in helping organizations realize the actual benefits of an Enterprise Architecture Program and all other subsequent projects executed under the hood of this Enterprise Architecture program.

Applied Information Economics: A brief overview

Applied Information Economics (AIE) is the practical application of mathematical and scientific methods to the enterprise decision and valuation process. AIE distinguishes itself from all other decision making methodologies by its synthesis of a variety of scientific and mathematical fields which makes possible everything measurable. AIE uses advanced methods from decision theory, portfolio optimization methods, operations research, statistics, and many other areas to solve even the most difficult IT valuation issues. It also uses the same methods that actuaries, financial analysts or statisticians use. AIE can measure any IT benefit or risk including faster communication, better quality data, or customer satisfaction.

The tools of economics, financial theory, and statistics are all major contributors to AIE. In addition to these more familiar fields, AIE includes Decision Theory - the formulation of decisions into a mathematical framework - and Information Theory - the mathematical modeling of the transmission and reception of information. It is important to emphasize, however, that even though AIE is a theoretically well-founded set of techniques, it is a very practical approach. Every proper application of AIE keeps the bottom line squarely in mind. All output from the AIE project is in support of specific practical business objectives.

Figure 1: AIE Foundation Blocks. Source: Hubbard Decision Research. Used with permission of Douglas W. Hubbard.