CHAPTER 9 ENABLING THE ORGANIZATION - DECISION MAKING

CHAPTER NINE
ENABLING THE ORGANIZATION
DECISION MAKING.

Today, I want to share the subtopic MGT 300 about the chapter 9. This chapter is Enabling Organizational Information - Decision Making. Chop Chop!

1. DECISION MAKING

ü Reasons for 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.

ü Model - a simplified representation or abstraction of reality.

ü IT system is an enterprise.

2. TRANSACTION PROCESSING SYSTEMS

ü Moving up through the organizational pyramid users move from requiring transaction information to analytically information.

ü  Transaction Processing System - The basic business system that serves the operational level (analysts) in an organization.

ü  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. more to save the information.

ü  Online Analytically Processing (OLAP) - The manipulation of information to create business intelligence in support of strategic decision making. do the information for decision making. more to analysis.

3. DECISION SUPPORT SYSTEMS (DSS)

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

ü Three quantitative models used by DSS's include:

• Sensitivity analysis. - A special case of what-if analysis, is the study of the impact on the other variables when one variables is changed repeatedly.
• What-if analysis. - Checks the impacts of a change in a variable or assumption on that model.
• Goal - seeking analysis. - Finds the inputs necessary to achieve goal such as a desired level of output.

4. EXECUTIVE INFORMATION SYSTEMS

A specialized DSS that supports senior level executives within the organization (EXECUTIVES)

ü  Most EISs offering the following capabilities:

• Consolidation - The aggregation of data from simple-\ roll-ups to complex groupings of interrelated information.
• Drill-down - Enables users to view details, and details of details, of information.
• Slice-and-dice -  The ability to look at information from different perspectives.

ü  Digital dashboard - integrates information from multiple components and present it in a unified display.

5. ARTIFICAL INTELLIGENCE (AI)

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

ü Four most common categories of AI include;

• Expert System – Computerised 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.

1. 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;

1. Multi-agent systems
2. Agent-based modelings

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

6. DATA MINING 

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

ü Common forms of data-mining analysis capabilities include;

• Cluster Analysis.
• Association Detection.
• Statistical Analysis.

7. CLUSTER ANALYSIS.

ü 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.

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

Eg: Consumer goods by content, brand loyalty or similarity.

8. ASSOCIATION DETECTION

ü 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.

9. STATISTICAL ANLYSIS

ü 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.

Niaathirah c:

CHAPTER 8 ACCESSING ORGANIZATIONAL INFORMATION - DATA WAREHOUSE

8.1 Describe the roles and puposes of Data Warehouse and Data Marts.
8.2 Compare the multidimensional nature of  Data Warehouse and Data Marts.
8.3 Identify the importance if ensuring the cleanliness of information throughout an organization.
8.4 Explain the relationship between the business intelligence and a data warehouse.

1. HISTORY OF DATA WAREHOUSE

• 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;

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

2. DATA WAREHOUSE FUNDAMENTALS

•  A Data Warehouse is a logical collection of information-gathered from many different operational database - that supports business analysis activities and decision-making tasks.
• The primary purpose of a data warehouse is to aggregate information throughout an organization into a single repository in such a way that employees can make decisions and undertake business analysis activities.
• A Data Mart contains a subsets of data warehouse information.
  
• The Data Warehouse then send subsets of the information to data mart.
  
• Extraction, Transformation, and Loading (ETL) - process that extracts information from internal and external database, transforms the information using a common set of enterprise definitions, and loads the information into a data warehouse.

3. MULTIDIMENSIONAL ANALYSIS AND DATA MINING.

• Database contains information in a series of two-dimensional tables.
  In a data warehouse and data mart, information is multidimensional, it contains layers of columns and rows.

>  Dimension – A particular attribute of information.

• A cube is the common term for the representation of multidimensional information.

• Data Mining is the process of analyzing data to extract information not to offered by the raw data alone. It is known as 'knowledge discovery.
• To perform data mining user needs data mining tools.

1. Data Mining Tools use a variety of techniques to find patterns and relationships in large volumes in information and infer rules from them that predict future behaviour and guide decision making. 

4. INFORMATION CLEANSING OR SCRUBBING.

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

Contact information in an operational system.

Standardizing Customer name from Operational Systems

Information Cleansing Activities

Accurate and complete information.

5. BUSINESS INTELLIGENCE

• Business Intelligence refers to application and technologies that are use to gather, provide access to, and analyze data and information to support decision-making efforts. 
• Enabling Business Intelligence

1. Technology.
2. People.
3. Culture.

niaathirah xx

CHAPTER 7 STORING ORGANIZATIONAL INFORMATION - DATABASES.

* Learning Outcomes
7.1 Define the fundamental concepts of the relational database mode.
7.2 Evaluate the advantage of the relational database model.
7.3 Compare relational integrity constraints and business-critical integrity constraints
7.4 Describe the benefits of a data driven web site.
7.5 Describe the two primary methods for integrating information. 

  1. RELATIONAL DATABASES FUNDAMENTALS.

• Information is everywhere in an organization.
• Information is stored in databases.

A database maintains information about various types of objects (inventory), events (transaction), people (employees) and place (warehouses).

• Database models include;

> Hierarchical database model is information is organized into tree-like structure that allows repeating information using parent/child relationships in such a way that it cannot have too many relationships.

> The network database model is a flexible way of representing objects and their relationships.

> The relational database model is a type of database that stores information in the form of logically related two-dimensional tables.

Hierarchical Structure

Network Structure

Relational Structure

 3. ENTITIES AND ATTRIBUTES.

• A entity in the relational database model is a person, place, thing, transaction or event about which information is stored.
• Attributes called fields or columns are characteristics or properties of an entity class.

4.  KEYS AND RELATIONSHIP.

• A primary key is a field (group/fields) that uniquely identifies a given entity in a table.
• A foreign key is a primary key of one table that appears as an attributes in another table and acts to provide a logical relationships between the two tables.
  

  

5. RELATIONAL DATABASE ADVANTAGES

• Databases advantages from a business perspective include;

1. Increased Flexibility.
2. Increased scability and performance.
3. Reduced Information Redundancy.
4. Increased Information Integrity (Quality)
5. Increased Information Security.

6. DATABASES MANAGEMENT SYSTEMS

• A database management systems (DBMS) is software through which users and application programs interact with a database.

7. DATA DRIVEN WEB SITES

• A data-driven website is an interactive website keep constantly updated and relevant to the needs of its costumer through the use of a database.

• Data Driven Web Sites Business Advantages.

1. Development : Allows the website owner to make changes any time
2. Content management;  A static website requires a programmer to make updates.
3. Future expandability; Having a data-driven website enables the site to grow faster than would be possible with a static site.
4. Minimizing human error .
5. Cutting production and update costs.
6. More efficient.
7. Improved stability.

• Data Driven Business Intelligence.
• Integrating Information among Multiple Databases.

An integration allows separate systems to communicate directly with each other.

> A forward integration takes information entered into a given system and sends it automatically to all downstream processes.

 > A backward integration - takes information entered into a given systems and sends it automatically to all upstream systems and processes.

> Without integration, an organization will;

• Spend considerable time entering the same info in multiple system.
• Suffer from the low quality and inconsistency typically embedded in redundant info.

niaathirah xx

CHAPTER 6 VALUING ORGANIZATIONAL INFORMATION

*Learning Outcomes.
6.1 Describe the broad levels, formats and granulities of information
6.2 Differentiate between transactional and analytical information
6.3 List, Describe and provide an example for each five characteristics.
6.4 Assess the impact of low quality information on an organizational.

  1. ORGANIZATIONAL INFORMATION.

• Information is everywhere in an organization.
• Employees must be able to obtain and analyze the many different levels, formats and granularity 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 granularity of organizational information.

2. THE VALUE OF TRANSACTIONAL AND ANALYTICAL INFORMATION.

• Timeliness is an aspect of information that depends on the situation.

Real- time Information - Immediate, up-to-date information (weather forecast, touch and go).

Real- time System - Provides real times information in response to query requests (using internet).

• Business decisions are only as good as the quality of the information used to make the decisions.
• Characteristics of high-quality information include;

  3. THE VALUE OF QUALITY INFORMATION.

• Low quality information example.

 

 4. UNDERSTANDING THE COSTS OF POOR INFORMATION.

• The four primary sources of low quality information include;

1. Online customers intentionally enter inaccurate information to protect their privacy.
2. Information from different systems have different entry standards and formats.
3. Call center operators enter abbreviated or erroneous information by accident or to save time .
4. Third party and external information contains inconsistencies, inaccuracies and errors.

• Potential business effect resulting from low quality information include;

1. Inability to accurately track customers.
2. Difficulty identifying valuable customers.
3. Inability to identify selling opportunities.
4. Marketing to nonexistent customers.
5. Difficulty tracking revenue due to inaccurate invoices.
6. Inability to build strong customer relationships.

• High quality information can significantly improve the chances of making a good decision.
• Good decisions can directly impact an organization's bottom line.

Niaathirah xx

UNIT TWO EXPLORING BUSINESS INITIATIVES

Exploring Business Iniatives

CHAPTER 5 ORGANIZATIONAL STRUCTURES THAT SUPPORT STRATEGIC INITIATIVES

5.1 Compare the responsibilities.

 5.2 Explain the gap between IT people and business people & the primary reason this gap exists

 5.3 Define the relationship.

  

 1. 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.

  2. INFORMATION TECHNOLOGY 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 Officer (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;

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

• 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 Officer (CKO) – responsible for collecting, maintaining and distributing the organization’s knowledge.

 3. 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 businesspersonnel and IT personnel.

 4. 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.

 5. 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 event as the 9/11 have shed new light on the meaning of ethics and security.

6. ETHICS

• Ethics – the principles and standards that guide our behavior toward other people.
• Privacy is a major ethical issues;

Privacy – the right to be left alone when you want to be to have control ever your own personnel possessions and not to be observed without your consent.

• Issues affected by technology advances.

Intelligent property	Intangible creative work that is embodied in physical form
Copyright	The legal protection afforded an expression of an idea, such as a song, video game and some types of proprietary documents
Fair use doctrine	In certain situations, it is legal to use copyrighted material
Pirated software	The unauthorized use, duplication, distribution or sale of copyrighted software
Counterfeit software	Software that is manufactured to lock 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.

1.	Loss of personnel privacy is a top concern for Americans in the 21st century
2.	Among Internet users, 37 percent would be “a lot” more inclined to purchase a product on a websites that had a privacy policy
3.	Privacy/security is the number one factors that would convert Internet researchers into Internet buyers

End of chapter 5 by Niaathirah xx

CHAPTER 4 MEASURING THE SUCCESS OF STRATEGIC INITIATIVES

Assalamualaikum, I would like to share to my readers about new chapter, Chapter 4 Measuring the success of strategic initiatives. Sorry for the late entry post because this week is a busy week for me, so let's start!

*Learning outcomes

4.1 Compare efficiency IT metrics and effectiveness IT metrics.

4.2 List and describe five common types of efficiency IT metrics.

4.3 List and describe four types effectiveness IT metrics.

4.4 Explain customer metrics and their importance to an organization.

1. MEASURING INFORMATION TECHNOLOGY's SUCCESS

• Key Performance Indicator - measures that are tied to business drivers.
• Metrics are detailed measures that feed KPIs.

      2. EFFICIENCY AND EFFECTIVENESS

• Effectiveness IT metrics - measure the impact IT has on business processes and activities including customer satisfaction, conversion rates, and sell-through increases.
• Efficiency IT metrics - measure the performance of the IT system itself including throughput, speed, and availability.

      3. BENCHMARKING - Baseline Metrics.

• Benchmarking - a process continuously measuring systems results, comparing those results to optimal system performance, and identifying steps and procedures to improve systems performance.

 

    4. EFFICIENCY IT METRICS.

• Common types of efficiency IT metrics.

• Common types of effectiveness IT metrics.

Focus on an organization's goals, strategies and objectives.

   5. THE INTERRELATIONSHIP OF EFFICIENCY AND EFFECTIVENESS IT METRICS.

• Security is an issues for any organization offering products or services over the Internet. When we use security in our system, the system can be slower.
•  It is inefficient for an organization to implement Internet security, since it slows down processing.
• To be effective it must implement Internet security.
• Secure Internet connections must offer encryption and Secure Sockets Layers (SSL denoted by the lock symbol in the lower right corner of a browser).
• It can be slow because have a security and effectiveness but customer feeling happy because all information can be more safely.

 

   6. METRICS FOR STRATEGIC INITIATIVES

Metrics for measuring and managing strategies.

   7. SUPPLY CHAIN MANAGEMENT METRICS

   8. CUSTOMER RELATIONSHIP MANAGEMENT METRICS

   9. BPR AND ERP METRICS

The balanced scorecard enables organizations to measure and manage strategic initiatives.

 

End of the chapter 4, Thank you. Niaathirah xx