Decision-Making and the Information System

Maryse Salles

• Publisher: Wiley-ISTE
• Year: 2015
• Print ISBN: 9781848217539
• eBook ISBN: 9781119102984
• Edition: 1
• Topic: Computer Science
• Subtopic: Information Technology
• Index: Computer Science

The purpose of this book is to question the relationships involved in decision making and the systems designed to support it: decision support systems (DSS). The focus is on how these systems are engineered; to stop and think about the questions to be asked throughout the engineering process and, in particular, about the impact designers' choices have on these systems.

1
Decision-Making

Introduction: decision-making, the central issue of decision support

In an engineering approach to decision support systems (DSS), the technical aspects, however complex, must never forget that decision-making is the central issue of decision support. This chapter will explore the different dimensions of decision-making so that we can understand its content, its sense.

It is worth reiterating that decision-making is the prerogative of mankind and that a “decision” made by a digital machine is not a decision (however, complex, it is nothing but the result of a line of calculations).

Every human being, in their personal and professional life and in their life as a citizen, is almost constantly making decisions of varying degrees of importance. To illustrate (basic) decision-making, let us consider the following: a pedestrian walking from one place to another will decide which route to take, during the journey they will choose which pavement to walk on, where and when to cross the road, how fast to walk, etc., until they decide to stop when they think they have arrived at their destination.

Similarly, decision-making is an integral part of the life of human organizations (authorities, enterprises, the State, etc.). Complex systems are immersed in moving environments, and they must indeed be managed. Managing takes various forms, but in the end it always results in individuals or groups making decisions. Enterprises must, for example, choose suppliers, organize production, set the price of products, define a client segment, redistribute the tasks of an absent worker, recruit employees and define the axes of research and development, and so on.

This book will focus on the decisions made within organizations, and not those made in individuals’ private lives.

Section 1.1 will present two different and opposing approaches to decision-making. The first approach is based on a rational view of decision-making and aims to optimize the final choice. The second approach, taken from research by Simon [SIM 60, SIM 77], takes the limitations of the decision maker’s rationality into account and seeks to help them make the most satisfactory decision for them.

In the domain of DSS, decision-making is understood in several dimensions, which can be split into two categories: the first category concerns the individuals making the decisions (the decision makers) and the second category concerns the methods and the roles of decision-making in the life of organizations.

Section 1.2 will focus on the decision maker (or a group of decision makers). First, the decision-making process modeled by Simon [SIM 60] will be studied. Given that the process is partially determined by the degree of formalization of the problems being asked to the decision maker, we will then discuss how decisions are structured (including the specific case of undefined or “wicked” problems). Some specificities of group decision-making will conclude this section.

This book discusses decision-making within organizations; section 1.3 will focus on the organizational context of decision-making. Organizations can be seen as complex systems. Systems theory has presented a management model, which we will describe in detail. Out of its components, indicators play a vital role. A definition of indicators will be provided and then a typology will be presented. We will then reflect on the distinction that must be drawn between decisions that have an impact on the definition of the management system and decisions that operate within the framework of this system (action decisions). The section will conclude with an important dimension of decision-making within organizations: the level of management (operational, tactical or strategic).

Organizations are immersed in an environment and they interact with it. It has often been said that this environment has been constantly changing for the past 20 years. Section 1.4 is dedicated to analyzing these changes and their impact on the content of decisions. The different dimensions of these changes will be studied with regard to organizations: their connection with the environment, establishing their boundaries and their needs in terms of the information system (IS). Public institutions and their evolution will specifically be discussed.

1.1. Normative theory versus engineering theory

Economics, management sciences and computer sciences are interested in decision support design (whichever forms these supports take). These areas have taken two main approaches to decision-making. The first approach, which we will call normative decision theory [ALC 04], mostly comes from economic sciences and is based on a rational view of decision-making (for more details, see [KAS 93]). Decision-making is assimilated to calculations determining the best possible action (i.e. optimum). This approach is based on what Simon [SIM 76] calls substantive rationality:

Behavior is substantively rational when it is appropriate to the achievement of given goals within the limits imposed by given conditions and constraints.

Defining the pursued objectives, defining the problem the decision needs to solve, choosing the relevant perimeter, identifying the necessary information, etc., are seen as exogenous to the decision-making process and as given. Simon et al. [SIM 86] wrote the following about subjective expected utility (SEU):

SEU theory defines the conditions of perfect utility-maximizing rationality in a world of certainty or in a world in which the probability distributions of all relevant variables can be provided by the decision makers. (…) SEU theory deals only with decision making; it has nothing to say about how to frame problems, set goals, or develop new alternatives.

Lévine and Pomerol [LÉV 89] summarized the hypotheses based on normative theory as follows:

1. – all possible actions are identified before the start of the decision-making process;
2. – there is a total preorder for actions, which can be represented by an explicit utility function and can be given a mathematical expression;
3. – input (parameters and data) is digital and contains all useful information;
4. – the best decision is that which maximizes the utility function.

Normative decision theory has been undeniably successful for repetitive and well-defined problems, for which all the useful information is available. These situations most often correspond with operational decisions, rarely with tactical decisions and never with strategic decisions.

We can even question the decisional nature of the activities carried out in this context. For a decision maker, choosing the optimum, i.e. only accepting the best choice, is not really decision-making (which would imply a set of possible choices), but rather the ratification of what is essentially the result of a calculation. It should be noted that using normative theory to deal with strategic decision-making generates excessive risks of reducing complexity and losing diversity (this will be discussed in Chapter 3).

A large number of decision-making situations come out of the very restricted context of normative theory. These situations are characterized by the limitations of the decision maker’s (substantive) rationality. These limitations are particularly visible in situations perceived to be complex by the decision maker.

Alcaras [ALC 11] shows that three types of factors contribute to this complexity, which he calls informational, teleological and computational, respectively:

1. – informational factors: information required for decision-making is difficult to define, collect or process in the time available;
2. – teleological factors: the end purpose pursued in decision-making is not always clear, nor shared by everyone involved in making the decision; consequently, the selection criteria are not very easy to set;
3. – computational factors: humans’ computational skills are limited: attention span, calculation skills, short- and long-term memory, etc.

Following Simon, another approach was developed, which is based on procedural rationality rather than substantive rationality. The main focus shifted, therefore, from the result of the decision-making (which should “simply” be optimized) to the process of decision-making, which concludes not when the optimum is achieved, but according to the criterion of satisficing (see se...

Table of contents

• Cover
• Table of Contents
• Title
• Copyright
• Introduction
• 1: Decision-Making
• 2: Decision Support Systems
• 3: The Influence of DSS on Decision-Making and Associated Risks
• 4: Elements for Ethical DSS Design
• General Conclusion
• Bibliography
• Index
• End User License Agreement