CHAPTER 10: EXTENDING THE ORGANIZATION – SUPPLY CHAIN MANAGEMENT

BASICS OF SUPPLY CHAIN

• Three main links:

• Materials flow from suppliers and their “upstream” suppliers at all levels
• Transformation of materials into semi-finished and finished products through the organization’s own production process
• Distribution of products to customers and their “downstream” customers at all levels

• 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 (Logistics)
• Companies must be able to receive orders from customers, fulfil 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.

IT's Roles in the Supply Chain

• 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
• 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 in the supply chain







• Speed
• Three factors fostering speed

• Supply Chain Management 


• Success Factors

• SCM industry best practices include:
• Make the sale to suppliers
• Wean employees off traditional business practices
• Ensure the SCM system supports the organizational goals
• Deploy in incremental phases and measure and communicate success
• Be future oriented
• SCM Success Stories
• Top reasons why more and more executives are turning to SCM to manage their extended enterprises
• Numerous decision support systems (DSSs) are being built to assist decision makers in the design and operation of integrated supply chains
• DSSs allow managers to examine performance and relationships over the supply chain and among:
• Suppliers
• Manufacturers
• Distributors
• Other factors that optimize supply chain performance

CHAPTER 9: ENABLING THE ORGANIZATION – DECISION MAKING

•   Reasons for the growth of decision-making information systems:

• Model – a simplified representation or abstraction of reality.
• IT systems in an enterprise:

 Transaction Processing Systems(TPS)

• 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(DSS)

• Models information to support managers and business professionals during the decision-making process.
• Three quantitative models used by DSSs include:
• Sensitivity analysis – the study of the impact that changes in one (or more) parts of the model have on other parts of the model. 
• What-if analysis – checks the impact of a change in an assumption on the proposed solution.
• Goal-seeking analysis – finds the inputs necessary to achieve a goal such as a desired level of output. 
• Interaction between TPS and DSS

Executive Information Systems

• A specialized DSS that supports senior level executives within the organization
• Most EISs offering the following capabilities:
• Consolidation – involves the aggregation of information and features simple roll-ups to complex groupings of interrelated information.
• Drill-down – enables users to get details, and details of details, of information. 
• Slice-and-dice – looks at information from different perspectives.
• Interaction between a TPS and an EIS

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

• Intelligent system – various commercial applications of artificial intelligence
• Artificial intelligence (AI) – simulates human intelligence such as the ability to reason and learn

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

• Data Mining - includes many forms of AI such as neural networks and expert systems.

- END OF CHAPTER 9-

CHAPTER 8: ACCESSING ORGANIZATIONAL INFORMATION DATA—WAREHOUSE

HISTORY OF DATA WAREHOUSING

• Data warehouses extend the transformation of data into information
• 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

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 aggregate information throughout an organization into a single repository for decision-making purposes
• 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 mart – contains a subset of data warehouse information

MULTIDIMENSIONAL ANALYSIS AND DATA MINING

Databases contain information in a series of two-dimensional tables
In a data warehouse and data mart, information is multi-dimensional; it contains layers of columns and rows

• Dimension – a particular attribute of information
• Cube – common term for the representation of multidimensional information
• Data mining – the process of analyzing data to extract information not offered by the raw data alone
• 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 and infers rules that predict future behavior and guide decision making

INFORMATION CLEANSING OR SCRUBBING

Information cleansing or scrubbing – 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 System
• 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

• Principle BI enablers include:
• Technology
• People
• Culture

CHAPTER 7: STORING ORGANIZATIONAL INFORMATION—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)

RELATIONAL DATABASE FUNDAMENTALS

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
• Attributes (fields, columns) – characteristics or properties of an entity class
• The columns in each table contain the attributes
• 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

RELATIONAL DATABASE ADVANTAGES

Database advantages from a business perspective include

• Increased flexibility
• Increased scaleability 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

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

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 WEBSITES

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

DATA-DRIVEN WEBSITE 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 website

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 and backward integration

Building a central repository specifically for integrated information

-END OF CHAPTER 7-