DSS Chapter 1

[Virtual Presenter] Good morning everyone. Today we are going to be discussing Decision Support and Business Intelligence Systems and the ninth edition of the book from Prentice Hall. We'll be covering topics such as rationality, bounded rationality, making choices, and establishing principles of choice as well as the role of Decision Support Systems to support decision making processes. This edition of the book also focuses on decision modeling at HP using Spreadsheets and other technologies. So let's dive right into it!.

[Audio] In this chapter we will explore the conceptual foundations for decision making, and the need for and nature of models in relation to this. We will learn about Simon’s four phases of decision making - intelligence, design, choice and implementation - and how they contribute to the process. By the end of the chapter, you will have a greater understanding of the theories and concepts behind the decision-making process..

[Audio] This chapter examines decision making and systems modeling as they pertain to decision support systems. It covers how rationality and bounded rationality apply to decision making, the difference between making a choice and setting a principle of choice, how decision support systems are used to facilitate decision making, and provides an overview of the systems approach..

[Audio] Decision making and support systems are an essential part of business operations today. This slide presents the opening vignette of Chapter 2 of the Decision Support and Business Intelligence Systems book, which touches upon the use of spreadsheets as a decision-making tool. Specifically, it focuses on the case study of HP and the problem they faced when trying to make decisions. It also describes the proposed solution they developed and the results they achieved. Finally, the slide provides case questions which help us analyse the case study and gain knowledge from its results..

[Audio] Decision support systems, or DSS, are a type of software designed to assist decision-makers in their decision-making process. By breaking down DSS into its main concepts, such as decision making and systems modeling, we can gain a thorough understanding of what goes into building a successful DSS. Understanding these concepts is key in being able to effectively utilize DSS to its fullest potential..

[Audio] This chapter of Decision Support and Business Intelligence Systems will provide an overview of decision making and its characteristics. Groupthink, what-if scenarios evaluation, and experimentation with a real system will be analyzed. We will also examine how changes in the decision-making environment can be fluid and how time pressure and lack of resources can have a bearing on decision making. Additionally, we will look into how having too little or too much information can influence decision making..

[Audio] This chapter examines the characteristics of decision making, with particular focus on the balance between accuracy and speed. Evidence suggests that personnel/human resources, budgeting and finance, organizational structuring, quality and productivity, IT selections and installation, and process improvement are particularly affected by hurried decisions. We will explore strategies to negotiate these decisions more effectively..

[Audio] Decision making is a process of choosing among two or more alternative courses of action with the purpose of attaining a goal. According to Simon, decision making is synonymous with the entire management process. Examining the planning process can help us look at it by considering what should be done, when, where, why, how, and by whom. Discussion today will cover decision making, systems, modeling, and support within the context of Decision Support and Business Intelligence Systems..

[Audio] We will be discussing Decision Support and Business Intelligence Systems, focusing on Decision Making and Problem Solving from Chapter 2. A problem can arise when a system doesn't live up to its established goals, or fails to produce the wanted results or doesn't work as intended. Problem solving requires figuring out the gap between intended and actual outcome, and also recognizing new potential opportunities. Let's take a closer look at these topics..

[Audio] The topic is Decision Making and Problem Solving. Are they related or different? The four phases of the decision-making process are Intelligence, Design, Choice and Implementation. The first three phases are considered decision-making, while phase four is problem-solving. Additionally, this book discusses decision-making as being synonymous with problem-solving. Each of these four phases will be explored in more detail in the coming slides..

[Audio] In this slide we look at the various disciplines useful for decision-making, which fall into three categories - Behavioral, Scientific, and Hybrid. The Behavioral disciplines are anthropology, law, philosophy, political science, psychology, social psychology, and sociology. The Scientific disciplines are computer science, decision analysis, economics, engineering, hard sciences, management science, operations research, maths, and statistics. Each of these disciplines gives us a valid perspective on how people come to decisions..

[Audio] Decision making is a key component for operating a successful business. Chapter 2 of "Decision Support and Business Intelligence Systems (9th Ed., Prentice Hall)" examines the distinct methods decision makers apply when tackling issues. It includes grasping how morals and convictions are relevant to the decision-making process. Additionally, it looks at how various individuals undertake various steps and attach different importance and precedence to each phase. All of these aspects are significant when forming business decisions..

[Audio] Personality temperament tests can be an effective way to measure decision styles, although there are various such tests available. Examples of these include Meyers/Briggs, True Colors and the Keirsey Temperament Theory, each of which has its own focus and should not be used interchangeably..

[Audio] We will examine decision making styles and the necessity of selecting the correct style for a given circumstance. We will take into consideration heuristic and analytic decision making, autocratic and democratic decision making, and consultative decision making. It is critical for a computerized system to be successful that it is compatible with the user's decision style and decision situation. Subsequently, it should be able to modify to various users and scenarios..

[Audio] We will analyze decision making in small and medium-to-large organizations, examining how a combination of different perspectives, experiences and expectations can make consensus difficult to achieve. To aid in this process, computer support and Group Support Systems can be utilized..

[Audio] A model is a simplified representation of reality, which is often too complex to describe. Modeling is an integral part of Decision Support and Business Intelligence Systems, as it allows for focusing on the relevant details necessary to solve the problem. This offers the ability to represent systems and problems at various levels of ion..

[Audio] We can divide models into various categories based on their degree of ion. Iconic models, also known as scale models, analog models, mental models, and mathematical or quantitative models are all examples of such models. Mathematical or quantitative models utilize the greatest degree of ion, while iconic models are the least . Models are used to simplify complex and real-world problems, situations and objects, and the degree of ion decreases from mathematical models to iconic models..

[Audio] Modeling provides a cost-efficient approach to manipulate information when researching business solutions. It aids in assessing multiple possibilities, allowing us to confidently settle on the best solution. Models also aid in comprehending risk and uncertainty, as well as reinforce teaching and training. The web opens up access to numerous resources, and also grants us the capability to publish models to the web..

[Audio] The authors of this chapter discuss the decision-making process and divide it into five phases. Intelligence involves gathering and analyzing information relevant to the decision. Design is creating an action plan. Choice is picking one option from the alternatives created. Implementation is the process of carrying out the chosen decision. Lastly, monitoring is assessing outcomes to determine if the decision was successful, allowing one to learn from mistakes and make better future decisions..

[Audio] Herbert Simon proposed in the 1950s that decision makers rarely examine all alternatives and their consequences before deciding. He argued that decisions are made by a four-step process composed of intelligence, design, choice and implementation. This process is illustrated in Figure 2.7. The stages of Simon's decision-making process are intelligence, design, choice and implementation, as depicted in the figure..

[Audio] In this chapter on Decision Making, Systems, Modeling, and Support we address ways to identify, analyze and address problems or opportunities. Our goal is to facilitate the detection of problems before they become too big to handle. We start by looking at the environment - both the internal and external environment - and scan for opportunities or problems. After the problem is identified, we can model how to identify an appropriate solution, and the end result is the implementation and monitoring of the solution. We place a strong emphasis on timely identification of opportunities, which is just as important as identifying problems..

[Audio] In this chapter, we will focus our attention on the challenges of making decisions in the presence of incomplete, inaccurate, or otherwise unreliable data. We will discuss the potential issues in data collection and estimation, which can include lack of data, cost of data collection, inaccurate and/or imprecise data, data estimation being subjective, data insecurity, data being qualitative, and data change over time. We will also look at ways to improve the reliability of the data to help make more accurate and informed decisions..

[Audio] In this slide we are going to take a look at the intelligence phase of decision making. The intelligence phase starts with problem classification in which problems are classified according to the degree of structure they have. We then move on to problem decomposition to break down complex problems into simpler parts. This is beneficial since it adds more structure to the problem, making it easier to solve. Lastly, problem ownership enables us to evaluate the problem and create a formal problem statement. This is the end of the intelligence phase, so let's get started!.

[Audio] For the design phase of decision making, various courses of action should be found, developed, and analyzed. Modeling involves combining the art and science of conceptualizing a problem and ing it into a quantitative or qualitative form- by making a few assumptions to simplify it. Cost and benefit trade-offs determine the level of ion to use..

[Audio] We are discussing the design phase of decision-making, which involves selecting a principle of choice to serve as a criterion describing the acceptability of a solution approach. This is often reflected in the result variable of a model. When making the decision, one should consider if to choose a high-risk versus low-risk approach or to optimize versus satisfice. It is worth noting that the criterion is not the same as a constraint..

[Audio] During the design phase of decision-making, a normative model - a process of optimization - is usually employed to identify the most favorable alternative. People make decisions as economic agents with the purpose of getting the most from their objectives. It is presumed that all the possible options and their effects are known in this situation and that the decision-makers have an ordered like or dislike that assists them in rating the effects of their decisions..

[Audio] Heuristic models in the design phase of decision making involve selecting the best of a subset of possible alternatives, which is known as sub-optimization. This is commonly used when it is not feasible to optimize problems that are of large size or complexity. Moreover, sub-optimization can help to eliminate unrealistic assumptions present in a model, which can lead to a good enough solution more quickly..

[Audio] Descriptive models are used to describe things as they are or as they are believed to be. They are mathematical based and don't provide a solution, instead they offer information that may lead to a solution. Simulation is the most widely used descriptive modeling method and is a mathematical portrayal of systems in a computer environment, giving us the ability to experiment with the descriptive model of a system. In this chapter, we explore the design phase of decision-making..

[Audio] When making decisions, it may be beneficial to consider whether to choose a 'good enough' or 'satisficing' option instead of aiming for the best possible outcome. This type of suboptimization seeks to attain a specific level of performance, rather than the highest possible, and can be a time-saving endeavor. The concept of satisficing was originally posed by Herbert Simon's notion of bounded rationality..

[Audio] Discussing the design phase of decision-making, this includes generating alternatives, and measuring and ranking the outcomes. In most instances, one has to generate alternatives manually. Nevertheless, group support systems may prove useful for this task. Additionally, the principle of choice is critical when making a decision..

[Audio] In this section of the presentation we will be looking at the design phase of the decision making process. We will be exploring the concept of risk and the lack of precise knowledge as well as how to measure the risk using probability. Additionally, we will overview the concept of a scenario, which is a statement of assumptions, about the operating environment of a particular system. We will look at four possible scenarios, best, worst, most likely and average, as well as custom intervals..

[Audio] In this slide, we are looking at the choice phase of decision making. Here, the actual decision and the commitment to follow a certain course of action are made. There is often a boundary between the design and choice phases, but it can be a bit overlapping. It is important to both generate alternatives and perform evaluations while making a decision. This includes the search, evaluation, and recommendation of an appropriate solution to the model. And finally, remember to not get lost in solving the model but to focus on solving the actual problem..

[Audio] In this chapter, we will explore decision making, systems, modeling, and support. We will focus on the search approaches, analytic techniques, algorithms, heuristics, and blind search. We will also discuss additional activities such as sensitivity analysis, what-if analysis, and goal seeking. These topics will enable us to gain an understanding of decision making in the business intelligence context..

[Audio] Reaching the final chapter of our course, we come to the most interesting part: decision implementation. Change is always challenging, but if done correctly, it can be highly rewarding. This course covers the implementation phase of the decision-making process in detail, investigating change management, how to tackle implementation, and the key elements needed for success. With this edition of Decision Support and Business Intelligence Systems, we explore an exciting area together. As Machiavelli wrote centuries ago, nothing is more difficult to carry out, nor more doubtful of success, nor more dangerous to handle, than to initiate a new order of things..

[Audio] Decision support systems, executive information systems, and other business intelligence (BI) systems provide support for more informed decisions. BI technologies integrate large volumes of internal and external data into meaningful information for managers to make better decisions and solve their problems. The speech should be: In this section of the presentation, we will look at how decisions are supported in decision support systems, executive information systems, and other business intelligence systems. These systems mine large volumes of internal and external data, combining it in meaningful ways to provide managers with information to aid them in their decision-making and problem-solving. Understanding how these systems work will help us understand how best to make use of the data available to us..

[Audio] This chapter focused on Decision-Making, Systems, Modeling and Support, providing insight into how decisions are supported. Leveraging the power of decision support systems, decision makers need support for the intelligence phase. Continuous scanning of external and internal information sources can help detect potential problems or opportunities. Technologies such as web-based ES systems, OLAP, data warehousing, data/text/web mining, EIS/Dashboards, KMS, GSS, GIS are used to facilitate the decision-making process. Additionally, Business activity monitoring, Business process management and Product life-cycle management provide further assistance in the decision-making process..

[Audio] Using various methods to generate alternative courses of action and determine criteria for choice is a key part of making decisions. Standards and special models, consisting of human experts, decision support systems, knowledge management systems, brainstorming or group support systems, on-line analytical processing (OLAP), and data or text mining, can all be helpful in this process. Careful consideration must be given to which criteria will best support the decision making process..

[Audio] We will be discussing how decisions can be supported in this slide. During the choice phase, it is important to select the best alternative out of a complex constraint structure. To do this, sensitivity analyses, what-if analyses, and goal seeking may be utilized. Additionally, resources such as knowledge management systems, customer relationship management systems, enterprise resource planning systems, supply chain management systems, and simulation or other descriptive models can be taken into account..

[Audio] During the implementation phase, methods to enable implementation and deployment of the chosen solution, communicate and justify decisions to reduce resistance to change, as well as utilizing resources like corporate portals, web tools, brainstorming and knowledge management systems will be examined..

[Audio] I'm going to discuss the new technologies that can facilitate decision-making. Web-based systems, m-commerce, PDA's, Cell phones, and Tablet PCs are all useful tools to support decisions. GSS with visual and immersive presence, RFID and other wireless technologies, as well as faster computers with better algorithms, are also effective decision-making tools. Such technologies can help process large amounts of different data quickly and precisely..

[Audio] At the conclusion of this chapter on decision support and business intelligence systems, I trust that you have acquired knowledge on how decisions are made, the various systems employed to make them, and the principle of modeling and bolstering the decisions made. Should you have any queries or opinions, please do not hesitate to voice them..

[Audio] No part of this publication can be reproduced, stored in a retrieval system or transmitted in any form or by any means without prior written permission of the publisher. We are taking a look at the 9th edition of the book "Decision Support and Business Intelligence Systems" and more specifically in chapter 2 which covers the topics of Decision Making, System, Modeling and Support. Thank you all for your attention and wish you a great afternoon..