Supply Chain Management

supply chain managements

• 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 product 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 chain

visibility

• 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

consumer behavior

• companies can respond faster and more effectively to consumer demands through supply chain enhances
• demand planning software - generates demand forecasts using statiscal 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

speed

• there factors fostering speed
1. pleasing customers has become something of a corporate obsession. serving the customer in the best, most efficient, and most effective manner has become critical, and informaion about issues such as order status, product availability, delivery schedules, and invoices has become a necessary a part of the total customer service experience.
2. information is crucial to managers' abilities to reduce inventory and human resource requirements to a competitive level.
3. information flows are essential to strategic planning for and deployment of resources.

supply chain management success factors

seven principles of supply chain management

1. segment customers by service needs, regardless of industry and then tailor services to those particular segments
2. customize the logistics network and focus intensively on the service requirements and on the profitability of the preidentified customer segments
3. listen to signals of market demand and plan accordingly. planning must span the entire chain to detect signals and changing demand.
4. differentiate products closer to the customer, since companies can no longer afford to hold inventory to compensate for poor demand forecasting.
5. strategically manage sources of supply, by working with key suppliers to reduce overall costs of owning materials and sevices
6. develop a supply chain information technology strategy that supports different levels of decision making and provides a clear view (visibility) of the flow of products, services and information.
7. adopt performances evaluation measures that apply to every link in the supply chain and measure true profitability at every stage.

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

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 intergrated 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
• companies using supply chain to drive operations
• dull
• nokia
• procter & gamble
• wal-mart stores
• toyota motor 
• the home deposit
• best buy
• marks & spencer

Enabling the Organization- Decision Making

Decision Making

• reasons for the growth of decision making information system
• people need to analyze large amounts of information
• people must make decision quickly
• people must apply sophisticated analysis techniques, such as modelling and forecasting, to make good decision
• people must protect the corporate asset of organizational information
• model- a simplified representation of abstraction of reality
• IT system in an enterprise
• moving up through the organizational pyramid users move from requiring transactional information to analytical 

Transaction Processing System

• transaction processing system - the basic business system that serves the operational level (analysis) in an organization
• online transaction processing (OLTP) - the capturer of transaction and event information using technology to (1)process 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

• decision support system (DSS) - 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
2. what-if analysis - checks the impact of a change in an assumption on the proposed solution
3. goal seeking analysis - finds the inputs necessary to achieve a goal such as a desired level of output 

Executive Information System

• executive information system (EIS) - a specialize DSS that supports senior level executives within the organization
• most EIS 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 perspective
• 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 systems
• artificial intelligence (AI) - stimulates human intelligence such as the ability to reason and learn
• advantages : can check info on competitor
• the ultimate goal of AI is teh ability to build a system that can mimic human intelligence
• four most common categories of AI include:
1. expert system - computerized advisory programs that initiate the reasoning processes of experts in solving difficult problems
2. neural network - attempts to emulate the way the human brain works
• fuzzy logic - a mathematical method of handling imprecise or subjective information
3. genetic aigorithm - an artificial intelligent system that mimics the evolutionary, survival of the fittest process to generate increasingly better solutions to a problem
4. intelligent agent - special purposed knowledge based information system that accomplishes specific tasks on behalf of its users
• multi-agent systems
• agent-based modelling

Data Mining

• data mining software includes many forms of AI such as neural networks and expert 
• common forms of data mining analysis capabilities:
• cluster analysis
• cluster analysis is a technique used to divide an information set into mutually exclusive groups such that the members of each group are so close together as possible ti 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   
• association detection
• association detection reveals the degree to which variables are related and the nature and frequency of these relationship in the information
• market basket analysis - analyzes such items as Web sites and checkout scanner information to detect customer's buying behavior and predict future behavior by identifying affinities among customers' choices of products and services
• statistical analysis
• statistical analysis performs such function 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

Viewing and Protection Organizational Information

history of data warehousing

• data ware house 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 marking without disrupting the day- to-day operations

data warehouse fundamentals

• data warehouse - a logical collection of information, gathered from different operational database that support business analysis activities and decision making task
• the primary purpose of a data warehouse is to aggregate information throughout an organization into a single repository for decision making purpose
• extraction, transformation, and loading (ETL) - a process that extracts information from internal and external databases, transform 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 minig

• databases contain information in a series of two-dimensioanl tables
• in a data warehouse and data mart, information is multidimensional, it contais 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 to dat 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

• 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

business intelligence

• business intelligence - information that people use to support their decision making efforts
• principle BI enblers include:
• technology
• people
• culture

Storing Organizational Information Databases

relational database fundamentals

• information is everywhere in an organization
• information is stored in databases
• databases - maintains information about various types of objects (inventory), events (transaction), people )employee), and places (warehouse)
• database includes includes:
• hierarchical database model - information is organized into a tree-like structure (using parent/child relationships) in such way that it cannot have too many relationships
• network database model - a flexible way of representing object 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 column in each table contains 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 tables
• 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 database

• database advantage 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 views
• have multiple logical views
• logical view - focuses on how users logically access information
• eg: a mail-order buss-2 people view diff format (logical views) but same 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 demand
• 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
• difficult to decide which is most current and most accurate

increased information integrity (quality)

• information integrity - measures the quality of information
• integrity constraints - rules that help ensure the quality of information
• relational integrity constraint - rule that enforces basic and fundamental information-based constraints
• Eg. users cannot create an order for a nonexistent customer, provide a markup percentage that was negative etc.
• business critical integrity constraint - rule that enforce business rules vital to an organization's success and often require more insight and knowledge than relational integrity constraints
• Eg. product returns are not accepted for fresh product 15 days after purchase

increased information security

• information is an organization asset and must be protected
• database offer several security features including:
• password - provide 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 system

• database management system (DBMS) - software through which user and application programs interact with a database

Data driven web sites

• data driven websites - an interactive web site kept constantly updated and relevant to the needs of its customers through the use of a database
• advantages
• development: allows the websites owner to make changes anytime - all without to rely on a developer or knowing HTML programming. a well-structured, data web site enables updating with little or no training.
• content management: a static web site requires a programmer to make updates. this adds an unnecessary layer between the business and its wen contract, which can lead to misunderstanding and slow turnarounds for desired changes.
• future expandability: having a data driven web site enables the site to grow faster than would be possible with a static site, changing the layout, displays, and functionality of the site (adding more features and section) is easier with a data driven solution
• minimizing human error: even the most competent programmer charged with the task of maintaining many pages will overlook things and make mistakes. this will lead to bugs and inconsistencies that can be time consuming and expensive to track down and fix. unfortunately, uses who come across these bugs will likely become irritated and may leave the site. a well-designed, data driven web site will have "error trapping" mechanisms to ensure that required information is filled out correctly and that content is entered and displayed in its correct format.
• cutting production and update costs: a data driven web site can be updated and "published" by any competent data entry or administrative person. in addition to being convenient and more affordable, changes and updates will tak a fraction of time that they would with a static site. while training a competent programmer can take months or even a years, training a data entry person can be done in 30-60 minutes
• more efficient: by their very nature, computers are excellent as keeping volumes of information intact. with a data driven solution, the system keeps track of the templates, so users do not have to. global changes to layout, navigation, or site structure would need to be programmed only once, in one place, and the site itself will take care of propagating those changes to the appropriate pages and areas.
• improved stability: any programmer who has to update a web site from "static" templates must be very organized to keep track of all the sources files. if a programmer leaves unexpectedly, it could involve re-creating existing work if those source file cannot be found.
• plus. if there were any changes to the templates, the new programmer must be careful to use only the latest version. with a data driven web site, there is peace of mind, knowing the content is never lost.

integration information among multiple database

• integration - allows separate system to communication 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.
• building a central repository specifically for integrated information
• 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.