Chapter 9 Enabling the Organization – Decision Making

Decision Making

Reasons for the growth of decision-making information systems

• People need to analyze large amounts of information
• People must make decisions quickly
• People must apply sophisticated analysis techniques, such as modeling and forecasting, to make good decisions
• People must protect the corporate asset of organizational information

Model – a simplified representation or abstraction of reality

IT systems in an enterprise

Transaction Processing Systems

Moving up through the organizational pyramid users move from requiring transactional information to analytical information

Transaction processing system - the basic business system that serves the operational level (analysts) in an organization 

Online transaction processing (OLTP) – the capturing of transaction and event information using technology to (1) process the information according to defined business rules, (2) store the information, (3) update existing information to reflect the new information

Online analytical processing (OLAP) – the manipulation of information to create business intelligence in support of strategic decision making

Decision Support Systems

Models information to support managers and business professionals during the decision-making process

Three quantitative models used by DSSs include:

1. Sensitivity analysis – the study of the impact that changes in one (or more) parts of the model have on other parts of the model. Eg: What will happen to the supply chain if a hurricane in South Carolina reduces holding inventory from 30% to 10%?
2. What-if analysis – checks the impact of a change in an assumption on the proposed solution. Eg: Repeatedly changing revenue in small increments to determine it effects on other variables.
3. Goal-seeking analysis – finds the inputs necessary to achieve a goal such as a desired level of output. Eg: Determine how many customers must purchase a new product to increase gross profits to $5 million

Executive Information Systems

A specialized DSS that supports senior level executives within the organization

Most EISs offering the following capabilities:

1. Consolidation – involves the aggregation of information and features simple roll-ups to complex groupings of interrelated information. Eg: Data for different sales representatives can be rolled up to an office level. Then state level, then a regional sales level.
2. Drill-down – enables users to get details, and details of details, of information. Eg: From regional sales data then drill down to each sales representatives at each office.
3. Slice-and-dice – looks at information from different perspectives. Eg: One slice of information could display all product sales during a given promotion, another slice could display a single product’s sales for all promotions.

Digital dashboard – integrates information from multiple components and presents it in a unified display

Artificial Intelligence (AI)

Intelligent system – various commercial applications of artificial intelligence

Artificial intelligence (AI) – simulates human intelligence such as the ability to reason and learn

Advantages: can check info on competitor

The ultimate goal of AI is the ability to build a system that can mimic human intelligence

Four most common categories of AI include:

*    Expert system – computerized advisory programs that imitate the reasoning processes of experts in solving difficult problems. Eg: Playing Chess.

* Neural Network – attempts to emulate the way the human brain works. Eg: Finance industry uses neural network to review loan applications and create patterns or profiles of applications that fall into two categories – approved or denied.

Fuzzy logic – a mathematical method of handling imprecise or subjective information. Eg: Washing machines that determine by themselves how much water to use or how long to wash.

Genetic algorithm – an artificial intelligent system that mimics the evolutionary, survival-of-the-fittest process to generate increasingly better solutions to a problem. 

Eg: Business executives use genetic algorithm to help them decide which combination of projects a firm should invest.

Intelligent agent – special-purposed knowledge-based information system that accomplishes specific tasks on behalf of its users

• Multi-agent systems
• Agent-based modeling

Eg:  Shopping bot: Software that will search several retailer’s websites and provide a comparison of each retailers’s offering including prive and availability.

Data Mining

Data-mining software includes many forms of AI such as neural networks and expert systems

Common forms of data-mining analysis capabilities include:

• Cluster analysis
• Association detection
• Statistical analysis

Cluster Analysis

Cluster analysis – a technique used to divide an information set into mutually exclusive groups such that the members of each group are as close together as possible to one another and the different groups are as far apart as possible

CRM systems depend on cluster analysis to segment customer information and identify behavioral traits

Eg: Consumer goods by content, brand loyalty or similarity 

Association Detection

Association detection – reveals the degree to which variables are related and the nature and frequency of these relationships in the information

Market basket analysis – analyzes such items as Web sites and checkout scanner information to detect customers’ buying behavior and predict future behavior by identifying affinities among customers’ choices of products and services

Eg: Maytag uses association detection to ensure that each generation of appliances is better than the previous generation.

Statistical Analysis

Statistical analysis – performs such functions as information correlations, distributions, calculations, and variance analysis

Forecast – predictions made on the basis of time-series information

Time-series information – time-stamped information collected at a particular frequency

Eg: Kraft uses statistical analysis to assure consistent flavor, color, aroma, texture, and appearance for all of its lines of foods

- THANK YOU -

Chapter 8 Accessing Organizational Information – Data Warehouse

History of Data Warehousing

In the 1990’s executives became less concerned with the day-to-day business operations and more concerned with overall business functions

The data warehouse provided the ability to support decision making without disrupting the day-to-day operations, because:

• Operational information is mainly current – does not include the history for better decision making
• Issue of quality information
• Without information history, it is difficult to tell how and why things change over time.

Data Warehouse Fundamentals

Data warehouse – a logical collection of information – gathered from many different operational databases – that supports business analysis activities and decision-making tasks

The primary purpose of a data warehouse is to combined information throughout an organization into a single repository for decision-making purposes – data warehouse support only analytical processing

Data Warehouse Model

Extraction, transformation, and loading (ETL) – a process that extracts information from internal and external databases, transforms the information using a common set of enterprise definitions, and loads the information into a data warehouse. 

Data warehouse  then send subsets of the information to data mart.

Data mart – contains a subset of data warehouse information

Multidimensional Analysis and Data Mining 

Cube – common term for the representation of multidimensional information

Once a cube of information is created, users can begin to slice and dice the cube to drill down into the information.

Users can analyze information in a number of different ways and with number of different dimensions.

Data mining – the process of analyzing data to extract information not offered by the raw data alone. Also known as "knowledge discovery" – computer-assisted tools and techniques for sifting through and analyzing vast data stores in order to find trends, patterns, and correlations that can guide decision making and increase understanding. 

To perform data mining users need data-mining tools

Data-mining tool – uses a variety of techniques to find patterns and relationships in large volumes of information. Eg: retailers can use knowledge of these patterns to improve the placement of items in the layout of a mail-order catalog page or Web page.

Information Cleansing or Scrubbing 

An organization must maintain high-quality data in the data warehouse

Information cleansing or scrubbing – a process that weeds out and fixes or discards inconsistent, incorrect, or incomplete information

Occur during ETL process and second on the information once if is in the data warehouse

Contact information in an operational system

Standardizing Customer name from Operational Systems

Information cleansing activities

Accurate and complete information

Business Intelligence

Business intelligence – refers to applications and technologies that are used to gather, provide access, analyze data, and information to support decision making effort.

these systems will illustrate business intelligence in the areas of customer profiling, customer support, market research, market segmentation, product profitability, statistical analysis, and inventory and distribution analysis to name a few

Eg: Excel, Access 

- THANK YOU -

Chapter 7 Storing Organizational Information

Relational Database Fundamentals

Information is everywhere in an organization

Information is stored in databases
Database – maintains information about various types of objects (inventory), events (transactions), people (employees), and places (warehouses)

Database models include:

• Hierarchical database model – information is organized into a tree-like structure (using parent/child relationships) in such a way that it cannot have too many relationships
• Network database model – a flexible way of representing objects and their relationships
• Relational database model – stores information in the form of logically related two-dimensional tables

Entities and Attributes

Entity – a person, place, thing, transaction, or event about which information is stored

• The rows in each table contain the entities
• In Figure 7.1 CUSTOMER includes Dave’s Sub Shop and Pizza Palace entities

Attributes (fields, columns) – characteristics or properties of an entity class

• The columns in each table contain the attributes
• In Figure 7.1 attributes for CUSTOMER include Customer ID, Customer Name, Contact Name

Keys and Relationships

Primary keys and foreign keys identify the various entity classes (tables) in the database

• Primary key – a field (or group of fields) that uniquely identifies a given entity in a table
• Foreign key – a primary key of one table that appears an attribute in another table and acts to provide a logical relationship among the two tables

Potential relational database for Coca-Cola

Relational Database Advantages

Database advantages from a business perspective include

• Increased flexibility
• Increased scalability and performance
• Reduced information redundancy
• Increased information integrity (quality)
• Increased information security

Increased flexibility

A well-designed database should:

• Handle changes quickly and easily
• Provide users with different views
• Have only one physical view
• Physical view – deals with the physical storage of information on a storage device
• Have multiple logical views
• Logical view – focuses on how users logically access information 

Increased scalability and performance

A database must scale to meet increased demand,  while maintaining acceptable performance levels

• Scalability – refers to how well a system can adapt to increased demands
• Performance – measures how quickly a system performs a certain process or transaction

Reduced information redundancy

• Databases reduce information redundancy. Redundancy – the duplication of information or storing the same information in multiple places 
• Inconsistency is one of the primary problems with redundant information

Increase Information Integrity (Quality)

Information integrity – measures the quality of information

Integrity constraint – rules that help ensure the quality of information

• Relational integrity constraint
• Business-critical integrity constraint 

Increased Information Security

Information is an organizational asset and must be protected

Databases offer several security features including:

• Password – provides authentication of the user
• Access level – determines who has access to the different types of information 
• Access control – determines types of user access, such as read-only access

Database Management Systems

Database management systems (DBMS) – software through which users and application programs interact with a database

DATA-DRIVEN WEB SITES

Data-driven Web sites – an interactive Web site kept constantly updated and relevant to the needs of its customers through the use of a database

Data-Driven Web Site Business Advantages

• Development
• Content Management
• Future Expandability
• Minimizing Human Error
• Cutting Production and Update Costs
• More Efficient
• Improved Stability

Data-Driven Business Intelligence

BI in a data-driven Web site

Integrating Information among Multiple Databases

Integration – allows separate systems to communicate directly with each other

• Forward integration – takes information entered into a given system and sends it automatically to all downstream systems and processes
• Backward integration – takes information entered into a given system and sends it automatically to all upstream systems and processes

Forward integration 

Backward integration

Building a central repository specifically for integrated information

- THANK YOU -

Chapter 6 Valuing Organizational Information

Organizational Information

- Information is everywhere in an organization

- Employees must be able to obtain and analyze the many different levels, formats, and granularities of organizational information to make decisions

- Successfully collecting, compiling, sorting, and analyzing information can provide tremendous insight into how an organization is performing

Levels, formats, and granularities of organizational information

The Value of Transactional and Analytical Information 

- Transactional information verses analytical information

The Value of Timely Information 

Timeliness is an aspect of information that depends on the situation

• Real-time information – immediate, up-to-date information
• Real-time system – provides real-time information in response to query requests

The Value of Quality Information 

- Business decisions are only as good as the quality of the information used to make the decisions

- You never want to find yourself using technology to help you make a bad decision faster

The Value of Quality Information 

Characteristics of high-quality information include:

• Accuracy
• Completeness
• Consistency
• Uniqueness 
• Timeliness

Chapter 5 Organizational Structures that Support Strategic Initiatives

Organizational Structures

• Organizational employees must work closely together to develop strategic initiatives that create competitive advantages
• Ethics and security are two fundamental building blocks that organizations must base their businesses upon

IT Roles and Responsibilities 

Information technology is a relatively new functional area, having only been around formally for around 40 years

Recent IT-related strategic positions:

• Chief Information Officer (CIO)
• Chief Technology Officer (CTO)
• Chief Security Officer (CSO)
• Chief Privacy Officer (CPO)
• Chief Knowledge Office (CKO)

Chief Information Officer (CIO) – oversees all uses of IT and ensures the strategic alignment of IT with business goals and objectives

Broad CIO functions include:

• Manager – ensuring the delivery of all IT projects, on time and within budget
• Leader – ensuring the strategic vision of IT is in line with the strategic vision of the organization
• Communicator – building and maintaining strong executive relationships

Average CIO compensation by industry

What concerns CIOs the most

Chief Technology Officer (CTO) – responsible for ensuring the throughput, speed, accuracy, availability, and reliability of IT

Chief Security Officer (CSO) – responsible for ensuring the security of IT systems

Chief Privacy Officer (CPO) – responsible for ensuring the ethical and legal use of information 

Chief Knowledge Office (CKO) - responsible for collecting, maintaining, and distributing the organization’s knowledge

Skills pivotal for success in executive IT roles

The Gap Between Business Personnel and IT Personnel 

• Business personnel possess expertise in functional areas such as marketing, accounting, and sales  
• IT personnel have the technological expertise  
• This typically causes a communications gap between the business personnel and IT personnel

Improving Communications

• Business personnel must seek to increase their understanding of IT
• IT personnel must seek to increase their understanding of the business
• It is the responsibility of the CIO to ensure effective communication between business personnel and IT personnel

Organizational Fundamentals – Ethics and Security

• Ethics and security are two fundamental building blocks that organizations must base their businesses on to be successful 
• In recent years, such events as the Enron and Martha Stewart, along with 9/11 have shed new light on the meaning of ethics and security

Ethics

Ethics – the principles and standards that guide our behavior toward other people

Privacy is a major ethical issue

Privacy – the right to be left alone when you want to be, to have control over your own personal possessions, and not to be observed without your consent

Issues affected by technology advances

• Intellectual property
• Copyright
• Fair use doctrine
• Pirated software
• Counterfeit software

1. Intellectual property - Intangible creative work that is embodied in physical form
2. Copyright - The legal protection afforded an expression of an idea, such as a song, video game, and some types of proprietary documents
3. Fair use doctrine - In certain situations, it is legal to use copyrighted material
4. Pirated software - The unauthorized use, duplication, distribution, or sale of copyrighted software
5. Counterfeit software - Software that is manufactured to look like the real thing and sold as such

One of the main ingredients in trust is privacy

Primary reasons privacy issues lost trust for e-business

Security

• Organizational information is intellectual capital - it must be protected 
• Information security – the protection of information from accidental or intentional misuse by persons inside or outside an organization
• E-business automatically creates tremendous information security risks for organizations

-THANK  YOU-