Decision Making: Support Systems and Disciplines

Characteristics of Decision Making

• Groupthink and evaluating "what-if" scenarios factor into decision-making.
• Decision-making involves experimenting with a real system.
• The decision-making environment faces continuous changes.
• Decision-makers often face time constraints.
• Analyzing a problem involves incurring time and monetary costs.

Decision Support Systems (DSS)

• DSS dissects into main concepts: support, system, and decision-making
• Building a successful DSS requires a thorough understanding of these concepts and models and data.

Decision Making Defined

• Decision making describes a process of choosing between two or more options to attain a goal
• Managerial decision making describes the entire management process.
• Planning involves contemplating what needs to be done by whom, when, where, why, and how.

Decision-Making Disciplines

• Behavioral disciplines: anthropology, law, philosophy, political science, psychology, social psychology, and sociology.
• Scientific disciplines: computer science, decision analysis, economics, engineering, the hard sciences (e.g., biology, chemistry, physics), management science/operations research, mathematics, and statistics.
• Each discipline has its own assumptions and contributions to how people make decisions.
• Better decisions require tradeoffs between accuracy and speed.
• Fast decisions may be detrimental and many areas suffer from them.
• "Effectiveness" means "goodness" or "accuracy" while "efficiency" means "speed" using "less resources."
• A fine balance between effectiveness and efficiency is needed.

Decision Style

• Decision style defines the manner in which decision-makers think and react to problems including perceiving a problem, cognitive response, values, and beliefs.
• When making decisions, people follow different steps in a particular sequence, and emphasis, time allotment, and priority to each step.

Decision Makers

• Small organizations are often run by individuals, who can face conflicting objectives.
• Medium-to-large organizations are often run by groups comprised of different styles, backgrounds, and expectations.
• Large organizations face conflicting objectives, where consensus is often difficult to reach.
• Computer support and GSS help with decision making in larger organizations.

Phases of Decision-Making Process

• Humans consciously or subconsciously follow a systematic decision-making process.
• The decision-making process involves intelligence, design, choice, implementation, and monitoring.
• Simon (1977) describes the decision-making structure.

Simon's Decision-Making Process

• Organization objectives, search and scanning procedures, data collection, problem identification, problem ownership, problem classification, and problem statement are all examples related to intelligence
• Formulating a model, setting choice criteria, searching for alternatives, and predicting/measuring outcomes are all examples related to design
• Solution to the model, sensitivity analysis, selecting the best alternative(s), and planning for implementation are all examples related to choice
• During implementation the solution can result in success or failure

How Decisions are Supported

• Intelligence: ANN, MIS, Data Mining, OLAP, ES, and ERP
• Design: ESS, ES, SCM
• Choice: CRM, ERP, KVS, Management Science, and ANN
• Implementation: ESS, ES, KMS, and ERP
• DSS and ES are examples of Phase
• CRM and SCM are examples of Implementation

DSS Capabilities

• DSS are intended to support managerial decisions in semistructured and unstructured decision situations.
• DSS are designed as adjuncts to decision-makers that extend their capabilities.
• DSS are computer-based, operate interactively online, and have graphical output capabilities.
• Current-day DSS is simplified via Web browsers and mobile devices.
• DSS systems may be semistructured or unstructured.
• DSS help support managers at all levels.
• DSS helps support individuals and groups.
• DSS allows interdependent or sequential decisions.
• DSS supports intelligence, design, choice and implementation.
• DSS supports a variety of decision processes and styles.
• DSS is designed to be adaptable and flexible.
• DSS gives the user interactive ease of use.
• DSS should have effectiveness and efficiency.
• DSS gives humans control of the process.
• DSS improves the ease of development by end users.
• DSS allows data access.
• DSS allows modeling and analysis.
• DSS can be standalone, integrated, and web-based.

DSS Classifications

• AIS SIGDSS classifies DSS into communication-driven and group DSS, data-driven DSS, document-driven DSS, knowledge-driven DSS, and model-driven DSS.
• Generally, DSS is a hybrid of many classes.

Components of DSS

• Data: can be internal and/or external.
• The process involves Organizational Knowledgebase, manager (user), user interface, knowledge-based subsystems, legacy web interfaces, external models, Model Management, and Data Management.
• There are other computer-based systems, internet, intranet, and extranet systems involved.
• Data Management Subsystem: includes the database that contains the data.
• A database management system (DBMS) can be connected to a data warehouse.
• Model Management Subsystem: Model base management system (MBMS)
• User Interface Subsystem.
• Knowledgebase Management Subsystem: Organizational knowledge base.