Fourth Year 2020-21
DSS
Part 2
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Fourth Year 2020-21
DSS
Quick Review on (Part 1) [Section]
1. Which of the following is an organizational response to a business environmental factor?
A) customer demand
C) new business models
B) government regulations
D) globalization
2. One of the major objectives of ________ is to facilitate closing the gap between the current
performance of an organization and its desired performance, as expressed in its mission, objectives,
and goals.
A) business alliances
B) customer relationships
C) business model
D) computerized decision support
3. Management is a process by which organizational goals are achieved by using resources. The
resources are considered ________, and attainment of goals is viewed as the ________ of the
process.
A) expenses; profits
B) inputs; output
C) pressures; opportunities
D) scarce; success
4. Mintzberg's (1980) classic study of top managers suggests that managers perform ten major roles
that can be classified into three major categories. Each of the following is one of those major
categories except:
A) relational
B) interpersonal
C) decisional
D) informational
5. Today's computerized systems possess capabilities that can facilitate decision support in a
number of ways, including each of the following except:
A) Increased productivity of group members B) Improved communication and collaboration
C) Agility support
D) Reduced environmental pressures
Answers: 5: D 4: A 3: B 2: D 1: C
TRUE & FALSE
1. Globalization has significantly reduced the complexity of the business environment. For example,
companies can find suppliers and customers in many countries where materials are cheaper, which
reduces competition and complexity. (…..)
2. One of the major objectives of computerized decision support is to minimize the gap between the
current performance of an organization and its desired performance. (….)
3. Computerized systems enable people to overcome their cognitive limits by quickly accessing and
processing vast amounts of stored information. (….)
4. Accounts receivable and accounts payable processes are highly structured, which makes them
easy to program. (….)
5. Research and development (R & D) planning and social responsibility planning are unstructured
decisions, which cannot be supported by computerized decision support systems.(….)
6. Automated decision systems (ADS) are rule-based systems that provide solutions to repetitive
managerial problems, usually in one functional area (e.g., finance, manufacturing). (….)
Answers: 6: TRUE 5: FALSE 4: TRUE 3: TRUE 2: TRUE 1: FALSE
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Fourth Year 2020-21
DSS
Structured Problem
◼ Structured problems: encountered repeatedly, have a high level of structure
It is possible to abstract, analyze, and classify them into specific categories
For each category a solution approach is developed => Management Science (or
Operation Research) (Quantitative Analysis QA)
e.g., make-or-buy decisions, capital budgeting, resource allocation, distribution,
procurement, and inventory control
Management Science
◼ In solving problems, managers should follow the five-step MS approach
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
Automated Decision Making
◼ A relatively new approach to supporting decision making
◼ Applies to highly structures decisions
◼ Automated decision systems (ADS) (or decision automation systems)
◼ 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
UN-Structured Problem
◼ Unstructured problems can be only partially supported by standard computerized
quantitative methods
◼ They often require customized solutions
◼ They benefit from data and information
◼ Intuition and judgment may play a role
◼ Computerized communication and collaboration technologies along with knowledge
management is often used
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DSS
Simi-Structured Problem
◼ Solving semi-structured problems may involve a combination of standard solution
procedures and human judgment
◼ MS handles the structured parts
◼ DSS deals with the unstructured parts
◼ With proper data and information, a range of alternative solutions, along with their
potential impacts
DSS (Decision Support System)
◼ In a narrow sense DSS refers to a process for building customized applications for
unstructured or semi-structured problems
◼ Components of the DSS Architecture
◼ Data, Model, Knowledge/Intelligence, User, Interface (API and/or user
interface)
From DSS to BI : Evolution of DSS into Business Intelligence
◼ Use of DSS moved from specialist to managers, and then whomever,
whenever, wherever
◼ Enabling tools like OLAP, data warehousing, data mining, intelligent systems,
delivered via Web technology have collectively led to the term “business
intelligence” (BI) and “business analytics”
BI (Business Intelligence) History
◼ BI is an evolution of decision support concepts over time
◼ Then: Executive Information System
◼ Now: Everybody’s Information System (BI)
◼ The term BI was coined by the Gartner Group 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 -> coining of the term
“BI” (The term BI emerged from industry)
◼ 2010s - Inclusion of AI and Data/Text Mining capabilities; Web-based
Portals/Dashboards, Big Data, Social Media, Analytics
◼ 2020s - yet to be seen
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BI (Business Intelligence)
◼ BI is an umbrella term that combines architectures, tools, databases, analytical tools,
applications, and methodologies
◼ 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 action
◼ BI systems are enhanced with additional visualizations, alerts, and performance
measurement capabilities
Architecture (Components):
1. a data warehouse, with its source data
2. business analytics, a collection of tools for manipulating, mining, and analyzing the data in
the data warehouse
3. business performance management (BPM) for monitoring and analyzing performance
4. a user interface (e.g., dashboard)
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Styles of BI:
1. report delivery and alerting
2. enterprise reporting (using dashboards and scorecards)
3. cube analysis (also known as slice-and-dice analysis)
4. ad-hoc queries
5. statistics and data mining
The Benefits of BI:
◼ The ability to provide accurate information when needed, including a real-time view of the
corporate performance and its parts
◼ A survey by Thompson (2004)
◼ Faster, more accurate reporting (81%)
◼ Improved decision making (78%)
◼ Improved customer service (56%)
◼ Increased revenue (49%)
The DSS–BI Connection:
◼ First, their architectures are very similar because BI evolved from DSS
◼ Second, DSS directly support specific decision making,
while, BI provides accurate and timely information, and indirectly support decision making
◼ Third, BI has an executive and strategy orientation, especially in its BPM and dashboard
components, while DSS, in contrast, is oriented toward analysts
◼ Fourth, most BI systems are constructed with commercially available tools and
components, while DSS is often built from scratch
◼ Fifth, DSS methodologies and even some tools were developed mostly in the academic
world, while BI methodologies and tools were developed mostly by software companies
◼ Sixth, many of the tools that BI uses are also considered DSS tools (e.g., data mining and
predictive analysis are core tools in both)
◼ Although some people equate DSS with BI, these systems are not, at present, the same
◼ some people believe that DSS is a part of BI—one of its analytical tools
◼ others think that BI is a special case of DSS that deals mostly with reporting, communication,
and collaboration (a form of data-oriented DSS)
◼ BI is a result of a continuous revolution and, as such, DSS is one of BI's original elements
◼ In this book, we separate DSS from BI
◼ MSS = BI and/or DSS
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◼ A Simple Taxonomy of Analytics
◼ Descriptive Analytics
◼ Predictive Analytics
◼ Prescriptive Analytics
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