Chapter 10 - Extnding the Organization - Suppy Chain Management

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

T    2.   Transformation of materials into semi-finished products, or the organization’s own production processes

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

Basic of 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 forecast using statistical tools and forecasting tecniques

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

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

SCM Success Stories

• 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

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

Transaction Processing Systems

• 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

• Decision support system (DSS) - models information to support managers and business professionals during the decision-making process
• Three quantitative models used by DSS's 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 impacts of a change in a variable or assumption on that model.
  3.  Goal - seeking analysis - finds the inputs necessary to achieve goal such as a desired level of output
   

Executive Information Systems

• Executive information system (EIS) - 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 view details, and details of details, of information.

          - Slice-and-dice -  The ability to look at information from different perspectives

Artificial Intelligence (A)

• Intelligence system - various commercial applications of artificial intelligence
• Artificial intelligence (A) - stimulates human intelligence such as the ability to reason and learn

- Advantages: can check info on competitor

Four most common categories of AI include:

1. Expert system - computerized advisory programs that imitate 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 algorithm - 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 modeling

Data Mining

• 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 system depends on cluster analysis to segment customer information and identify behavioral traits.

• Example: 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

          - Example: 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.