CHAPTER 10 : EXTENDING THE ORGANIZATION - SUPPLY CHAIN MANAGEMENT

Learning Outcomes

1. List and describe the components of a typical supply chain
2. Define the relationship between decision making and supply chain management
3. Describe the four changes resulting from advances in IT that are driving supply chains
4. Summarize the best practices for implementing a successful supply chain management system

Supply Chain Management

- The average company spends nearly half of every dollar that it earns on production

-In the past, companies focused primarily on manufacturing and quality improvements to 

influence their supply chains

Basics of Supply Chain

- The supply chain has three main links:

1.Materials flow from suppliers and their “upstream” suppliers at all levels

2.Transformation of materials into semifinished and finished products through the 

organization’s own production process

3.Distribution of products to customers and their “downstream” customers at all levels

- Organizations must embrace technologies that can effectively manage supply chains

 Plan

§A company must have a plan for managing all the resources that go toward meeting

customer demand for products or services.

Source

§Companies must carefully choose reliable suppliers that will deliver goods and

services required for making products. 

Make

§This is the step where companies manufacture their products or services. This can 

include scheduling the activities necessary for production, testing, packaging, and 

preparing for delivery.

Deliver (Logistic)

§Companies must be able to receive orders from customers, fulfill the orders via a 

network of warehouses, pick transportation companies to deliver the products, and 

implement a billing and invoicing system to facilitate payments.

Return

§This is typically the most problematic step in the supply chain. Companies must 

create a network for receiving defective and excess products and support customers 

who have problems with delivered products.

Information Technology’s Role in the Supply Chain

- Factors Driving SCM

          Visibility

- Visibility – more visible models of different ways to do things in the supply chain 

have emerged.  High visibility in the supply chain is changing industries, as Wal-Mart 

demonstrated

- Supply chain visibility – the ability to view all areas up and down the supply chain

- Bullwhip effect – occurs when distorted product demand information passes from 

one entity to the next throughout the supply chain

- Supply chain visibility allows organizations to eliminate the bullwhip effect

§To explain the bullwhip effect to your students discuss a product that demand does 

not change, such as diapers.  The need for diapers is constant, it does not increase at 

Christmas or in the summer, diapers are in demand all year long.  The number of 

newborn babies determines diaper demand, and that number is constant.

§Retailers order diapers from distributors when their inventory level falls below a 

certain level, they might order a few extra just to be safe

§Distributors order diapers from manufacturers when their inventory level falls below a 

certain level, they might order a few extra just to be safe

§Manufacturers order diapers from suppliers when their inventory level falls below a 

certain level, they might order a few extra just to be safe

§Eventually the one or two extra boxes ordered from a few retailers becomes several 

thousand boxes for the manufacturer.  This is the bullwhip effect, a small ripple at one 

end makes a large wave at the other end of the whip.

Consumer Behavior

- Companies can respond faster and more effectively to consumer demands through 

supply chain enhances

- Once an organization understands customer demand and its effect on the supply 

chain it can begin to estimate the impact that its supply chain will have on its 

customers and ultimately the organizations performance

- Demand planning software – generates demand forecasts using statistical tools 

and forecasting techniques

Competition

- Supply chain planning (SCP) software– uses advanced mathematical algorithms 

to improve the flow and efficiency of the supply chain

- Supply chain execution (SCE) software – automates the different steps and 

stages of the supply chain

- SCP and SCE both increase a company’s ability to compete

- SCP depends entirely on information for its accuracy

- SCE can be as simple as electronically routing orders from a manufacturer to a 

supplier

- SCP and SCE in the supply chain

Speed

- Three factors fostering speed

Supply Chain Management Success Factors

- SCM industry best practices include:

1.Make the sale to suppliers

2.Wean employees off traditional business practices

3.Ensure the SCM system supports the organizational goals

4.Deploy in incremental phases and measure and communicate success

5.Be future oriented

CHAPTER 9 : ENABLING THE ORGANIZATION - DECISION MAKING

Learning Outcomes

1. Define the systems organizations use to make decisions and gain competitive advantages
2. Describe the three quantitative models typically used by decision support systems
3. Describe the relationship between digital dashboards and executive information system
4. List and describe four types of artificial intelligence system
5. Describe three types of data-mining analysis capabilities

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 tsunami in Sabah 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.

•              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 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

CHAPTER 8 : ACCESSING ORGANIZATIONAL INFORMATION – DATA WEREHOUSE

Learning Outcome

1. Describe the roles and purposes of data warehouses and data marts in an organization
2. Compare the multidimensional nature of data warehouses (and data marts) with the two-dimensional nature of databases
3. Identify the importance of ensuring the cleanliness of information throughout an organization
4. Explain the relationship between business intelligence and a data warehouse

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 

Relational Database contain 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.

- 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 

CHAPTER 7 : STORING ORGANIZATIONAL INFORMATION

Learning Outcomes

1.  Define the fundamental concepts of the relational database model
2. Evaluate the advantages of the relational database model
3. Compare relational integrity constraints and business-critical integrity constraints
4. Describe the benefits of a data driven Web site
5. Describe the two primary methods for integrating information across multiple databases

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:

1. 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
2. Network database model – a flexible way of representing objects and their relationships
3. 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:

1.        Handle changes quickly and easily
2.        Provide users with different views
3.        Have only one physical view

•      Physical view – deals with the physical storage of information on a storage device

       4. 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

1.        Relational integrity constraint
2.        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