week 1 lecture dss

CSE4DSS Lecture 1CSE4DSS Lecture 1Decision Support and Business Decision Support and Business IntelligenceIntelligence

Based on material from Chapter 1

Decision Support and Business Intelligence

Turban, Sharda and Delen, 9th edition.

• The Business Pressures-Responses-Support Model• The managerial decision making process• The Gorry and Scott-Morton framework• Simon’s phases of decision making• Framework for managerial decision-making• Definition of a decision support system • Decision Support Systems and Business Intelligence

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ContentsContents

Business Pressures – Responses – Support Business Pressures – Responses – Support ModelModel

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• Companies are moving aggressively to computerized support of their operations.

• This can be explained by the Business Pressures–Responses–Support Model.– Today's competitive business climate creates

pressures for businesses– In order to remain competitive businesses must

respond to those pressures – This response process can be better facilitated

through the use of computerized support.

• The (business) environment in which organizations operate today is becoming more and more complex, creating problems, but also opportunities.

• Business environment factors: – Markets– Consumer demands– Technology– Societal

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FACTOR DESCRIPTION

Markets Strong competition

Expanding global markets

Blooming electronic markets on the Internet

Innovative marketing methods

Opportunities for outsourcing with IT support

Need for real-time, on-demand transactions

Consumer Desire for customization

demand Desire for quality, diversity of products, and speed of delivery

Customers getting powerful and less loyal

Technology More innovations, new products, and new services

Increasing obsolescence rate

Increasing information overload

Social networking, Web 2.0 and beyond

Societal Growing government regulations and deregulation

Workforce more diversified, older, and composed of more women

Increasing social responsibility of companies

Greater emphasis on sustainability


• In response to these pressures, managers may take actions, such as

– Employ strategic planning– Use new and innovative business models– Restructure business processes– Participate in business alliances and partnership relationships– Improve corporate information systems– Encourage innovation and creativity– Improve customer service and relationships– Move to make-to-order production and on-demand manufacturing and services

– Use new IT to improve communication, data access (discovery of information), and collaboration

– Respond quickly to competitors' actions (e.g., in pricing, promotions, new products and services)

– Automate many tasks of white-collar employees– Improve decision making by employing analytics– Automate certain decision processes

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Managerial Decision MakingManagerial Decision Making

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• Management is a process by which organizational goals are achieved by using resources– Inputs: resources (e.g., people, capital, equipment)– Output: attainment of goals– Measure of success: outputs / inputs

• Managers are involved in a continuous process of making decisions

goalsgoalsresourcesresources processprocess

managementmanagement


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What is a decision?•A decision is a reasoned choice among alternatives•Making decisions is part of the broader subject of problem solving•Its purpose is to solve problems by closing the gaps between reality and a more desirable situation

What is decision-making?•selecting the best solution from two or more alternatives


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Decision Making is difficult because:– Technology, information systems, advanced search engines,

and globalization result in more and more alternatives from

which to choose

– Government regulations and the need for compliance, political

instability and terrorism, competition, and changing consumer

demands produce more uncertainty, making it more difficult to

predict consequences and the future

– Need to make rapid decisions

– Frequent and unpredictable changes that make trial-and-

error learning difficult

– Potential costs of making mistakes

The 4-step Decision-MakingThe 4-step Decision-Making Process Process

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The 4-step Decision-MakingThe 4-step Decision-Making Process Process

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Managers usually make decisions by following a four-step process:

1. Define the problem (or opportunity)

2. Construct a model that describes the real-world problem

3. Identify possible solutions to the modeled problem and evaluate the solutions

4. Compare, choose, and recommend a potential solution to the problem

Computerized Support for Decision MakingComputerized Support for Decision Making

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Why Use Computerized Decision Support Systems?

Computerized Support for Decision MakingComputerized Support for Decision Making

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• Computerized DSS can facilitate decision making via:– Fast computations– Improved communication and collaboration– Increased productivity of group members– Improved data management– Managing giant data warehouses– Overcoming cognitive limits – Using Web– Anywhere, anytime support– …

A Framework for Computerized Decision SupportA Framework for Computerized Decision Support

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• Gorry and Scott-Morton proposed a framework that is a 3-by-3 matrix. One dimension describes how structured the problem is; the other dimension describes the scope of the decision.

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Type of Decisions

• Structured decision– A well defined decision making procedure

– Standard solutions exist

– Could be given to a computer program

• Unstructured decision– Fuzzy, complex problems for which there are no cut-and-dried

solution methods

– Uncertainty involving human judgement

• Semi-structured decision– Lies somewhere between structured and un-structured decisions

– Most decisions are of this type


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Scope of Decisions• Strategic Planning

– Defining long-range goals and policies for resource allocation– High level decisions that will affect entire organizational

objectives and policies

• Managerial Control– Acquisition and efficient use of resources in the

accomplishment of organizational goals– Decisions affect some part or parts of the organization, and are

made by middle-level managers

• Operational– Efficient and effective execution of specific tasks– Lower-level managers


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Categorize each of the following decisions along the dimensions of Type and Scope.

1.Determining the location for a new warehouse

2.Determining whether to build a new plant

3.Determining whether to make or buy a component for a new product

4.Selecting a cover for the monthly advertising brochure

5.Reward system design

6.Recruiting an executive

Class ExerciseClass Exercise


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(scope of decision)

• Gorry and Scott-Morton framework, with examples

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Phases of Decision-MakingPhases of Decision-Making

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Simon’s four Phases of Decision-Making

1. Intelligence: involves Searching for conditions that call for decisions

2. Design: involves inventing, developing, and analyzing possible alternative courses of action (solutions)

3. Choice: involves selecting a course of action from those available

4. Implementation: involves adapting the selected course of action to the decision situation (i.e., problem solving or opportunity exploiting).


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Computer Support for Computer Support for StructuredStructured Decisions Decisions

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• Structured problems are encountered repeatedly, and have a high level of structure. It is possible to abstract, analyze, and classify them into specific categories; e.g., – make-or-buy decisions– capital budgeting– resource allocation– distribution– procurement– inventory control

• For each category, easy-to-apply prescribed models and solutions have been developed.

• This approach is commonly known as Management Science, or Operations Research

Computer Support for Computer Support for StructuredStructured Decisions Decisions

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1. Define the problem

2. Classify the problem into a standard category

3. Construct a model that describes the real-world problem

4. Identify possible solutions to the modeled problem and evaluate the solutions

5. Compare, choose, and recommend a potential solution to the problem

Computer Support for Computer Support for StructuredStructured Decisions DecisionsManagement Science (Operations Research) ApproachManagement Science (Operations Research) Approach

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• The Management Science approach is based on mathematical modeling (i.e., algebraic expressions that describe problems)

• Modeling involves transforming a real-world problem into an appropriate prototype structure (i.e., model)

• Computerized methodologies (e.g., linear programming) can then be used to find solutions to the standard category models quickly and efficiently

Computer Support for Computer Support for StructuredStructured Decisions DecisionsManagement Science (Operations Research) ApproachManagement Science (Operations Research) Approach

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• Automated Decision Systems (ADSs) are a relatively new approach to supporting structured decision making

• An ADS is a rule-based system that provides a solution to a repetitive managerial problem in a specific area – e.g., simple-loan approval system

• Expert Systems (to be covered in Week 10 ) are an example of automated decision systems

Computer Support for Computer Support for StructuredStructured Decisions DecisionsAutomated Decision System (ADS) ApproachAutomated Decision System (ADS) Approach

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Computer Support for Computer Support for UnUnstructuredstructured Decisions Decisions

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• Unstructured problems can be only partially supported by standard computerized quantitative methods

• They often require customized solutions• They benefit from data and information generated from

external sources• Intuition and judgment may play a role• Computerized communication and collaboration

technologies, along with knowledge management, is often used

Computer Support for Computer Support for UnUnstructuredstructured Decisions Decisions

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Computer Support for Computer Support for SemiSemi-structured-structured Decisions Decisions

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• Solving semi-structured problems may involve a combination of standard solution procedures and human judgment

• Management Science handles the structured parts while DSS deals with the unstructured parts

• With proper data and information, a range of alternative solutions can be considered, along with their potential impacts

Computer Support for Computer Support for SemiSemi-structured-structured Decisions Decisions

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The Concept of Decision Support Systems (DSS)The Concept of Decision Support Systems (DSS)

• “Decision Support Systems are computer‑based information systems that use data and models to support unstructured and semi-structured decisions made by managers” (Gorry and Scott-Morton, 1971)

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• “Decision Support Systems are computer‑based information systems that use data and models to support unstructured and semi-structured decisions made by managers” (Gorry and Scott-Morton, 1971)

• “Decision support systems couple the intellectual resources of individuals with the capabilities of the computer to improve quality of decisions. It is a computer-based support system for management decision makers who deal with semi-structured problems” (Keen and Scott-Morton, 1978)

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Basic architecture of a DSS

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DSS as an Umbrella term• Describes any computerized system that supports

decision making in an organization

DSS as a specific application• Although DSS usually refers to the umbrella term,

sometimes it is used in a narrower scope to refer to a process for building specific customized applications for unstructured or semi-structured problems.

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Types of DSS• model-oriented DSS: quantitative models used to

generate a recommended solution to a problem • data-oriented DSS: support ad-hoc reporting and

queries


Business Intelligence (BI)Business Intelligence (BI)

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Business Intelligence (BI)Business Intelligence (BI)

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• Business Intelligence (BI) is an umbrella term that combines architectures, tools, databases, analytical tools, applications, and methodologies

• Like DSS, BI means different things to different people• BI's major objective is to enable easy access to data

(and models) to provide business managers with the ability to conduct analysis

• BI helps transform data to information (and knowledge), to decisions, and finally to actions

A Framework for Business Intelligence (BI)A Framework for Business Intelligence (BI)

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A Brief History of BI• The term BI was coined in the mid-1990s• However, the concept is much older

– 1970s - MIS reporting - static/periodic reports

– 1980s - Executive Information Systems (EIS)

– 1990s - OLAP, dynamic, multidimensional, ad-hoc reporting

– 2005+ Inclusion of AI and Data/Text Mining capabilities; Web-

based Portals/Dashboards

– 2010s - Big data, social network analysis, …


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General BI Architecture


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The Benefits of BIThe Benefits of BI

• The ability to provide accurate information when needed, including a real-time view of the corporate performance and its parts

• Faster, more accurate reporting• Improved decision making• Improved customer service• Increased revenue

Business value of BI Analytical ApplicationsBusiness value of BI Analytical Applications

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Analytic Application

Business Question

Business Value

Customer segmentation What market segments do my customers fall into, and what are their characteristics?

Personalize customer relationships for higher satisfaction and retention.

Propensity to buy Which customers are most likely to respond to my promotion?

Customer targeting. Increase advertising campaign profitability by focussing on the most likely to buy.

Customer profitability What is the lifetime profitability of my customer?

Make individual business interaction decisions based on the overall profitability of customers.

Fraud detection How can I tell which transactions are most likely to be fraudulent?

Quickly determine fraud and take immediate action to minimize cost.

Customer attrition Which customer is at risk of leaving? Prevent loss of high-value customers and let go of lower-values customers.

Channel optimization What is my best channel to reach my customer in each segment?

Interact with customers based on their preference and your need to manage cost.

Some Examples…Some Examples…

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National Australia BankNational Australia Bank• NAB uses data mining to aid its predictive marketing. NAB uses data mining to aid its predictive marketing. • The tools are used to extract and analyse data stored in The tools are used to extract and analyse data stored in

the bank’s Oracle database. the bank’s Oracle database. • Data mining tools are used to generate market analysis Data mining tools are used to generate market analysis

models from historical data. models from historical data. • The bank considers these initiatives to be crucial to The bank considers these initiatives to be crucial to

maintaining an edge in the increasingly competitive maintaining an edge in the increasingly competitive financial services marketplace.financial services marketplace.

Some Examples…Some Examples…

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FAI Insurance GroupFAI Insurance Group• FAI Insurance Group uses its data mining to reassess FAI Insurance Group uses its data mining to reassess

the relationship between historical risk from insurance the relationship between historical risk from insurance policies and the pricing structure used by its policies and the pricing structure used by its underwriters. underwriters.

• The data analysis capabilities allow FAI to better serve The data analysis capabilities allow FAI to better serve its customers by more accurately assessing the its customers by more accurately assessing the insurance risk associated with a customer request. insurance risk associated with a customer request.

• Through the use of neural networks and business Through the use of neural networks and business statistics, the analysts comb the data for trends and statistics, the analysts comb the data for trends and relationships.relationships.


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The DSS–BI ConnectionThe DSS–BI Connection1. Similar architectures because BI evolved from DSS

2. DSS directly supports specific decision making, while BI provides accurate and timely information, and indirectly supports decision making

3. BI has an executive and strategy orientation, while DSS tend to be more oriented toward analysis

4. Most BI systems are constructed with commercially available tools and components, while DSS are often built from scratch

5. DSS methodologies and even some tools were developed mostly in the academic world, while BI methodologies and tools were developed mostly by software companies

6. Many of the tools that BI uses are also considered DSS tools (e.g., data mining and predictive analysis are core tools in both)


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Management Support SystemsManagement Support Systems

• Due to the lack of crisp and universal definition of DSS and BI, some people refer to DSS and BI, either independently, or collectively, as Management Support Systems (MSS)

• MSS = BI and/or DSS

• Chapter 1 from Turban, Sharda, Delen, Decision Support and Business Intelligence Systems, Ninth Edition.

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Homework ReadingHomework Reading

• After you have completed the reading, attempt the Week 1 Quiz (which you will find on the LMS under ‘Quizzes’).

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Weekly QuizWeekly Quiz

1. What are structured, unstructured, and semi-structured decisions? Provide two examples of each, and indicate their position in the Gorry and Scott-Morton framework.

2. Think of an organization with which you are familiar. List three decisions it makes in each of the following categories: strategic planning, management control, and operational control. For each decision, is it best described as structured, unstructured, or semi-structured?

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Homework QuestionsHomework Questions

week 1 lecture dss

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