CHAPTER 10:EXTENDING THE ORGANIZATION-SUPPLY CHAIN MANAGEMENT

LEARNING OUTCOMES

1)LIST AND DESRIBE THE COMPONENTS OF A TYPICAL SUPPLY CHAIN.

SUPPLIER'S SUPPLIER ==> SUPPLIER ==> MANUFACTURER ==> DISTRIBUTOR ==> RETAILER ==> CUSTOMER ==> CUSTOMER'S CUSTOMER

2)DEFINE THE RELATIONSHIP BETWEEN DECISION MAKING AND SUPPLY CHAIN MANAGEMENT.

SUPPLY CHAIN MANAGEMENT (SCM) INVOLVES THE MANAGEMENT OF INFORMATION FLOWS BETWEEN AND AMONG STAGES IN A STAGES IN A SUPPLY CHAIN TO MAXIMIZE TOTAL SUPPLY CHAIN EFFECTIVENESS AND PROFITABILITY.WITHOUT  SCM,DECISON MAKING CANNOT BE MADE.IT IS BECAUSE SCM HAVE A MAIN ROLES IN DECISION .MORE INFORMATION BEFORE DO THE DECISION MAKING MUST DEPENDS ON SCM.

3)DESCRIBE THE FOUR CHANGES RESULTING FROM ADVANCES IN IT THAT ARE DRIVING SUPPLY CHAINS.

INFORMATION TECHNOLOGY'S PRIMARY ROLE IN SCM IS CREATING THE INTEGRATIONS OR TIGHTR PROCESS AND INFORMATION LINKAGES BETWEEN FUNCTIONS WITHIN A FIRM SUCH AS MARKETING,SALES AND FINANCE.INFORMATION TECHNOLOGY INTEGRATES PLANNING,DECION MAKING PROCESSES,BUSINESS OPERATING PROCESSES AND INFORMATION SHARING FOR BUSINESS PERFORMANCE MANAGEMENT.

4)SUMMARIZE THE BEST PRACTICES FOR IMPLEMENTING A SUCCESSFUL SUPPLY CHAIN MANAGEMENT SYSTEM.

-MAKE THE SALE TO SUPPLIER, BE SURE SUPPLY ARE ON BOARD WITH THE BENEFITS THAT THE SCM SYSTEM WILL PROVIDE.
-WEAN EMPLOYEES OFF TRADITIONAL BUSINESS PRACTICES,IF THE ORGANIZATIONS CANNOT CONVINCE PEOPLE THAT USING THAT USING SOFTWARE WILL BE WORTH THEIR TIME,THEY WILL EASILY FIND WAYS TO WORK AROUND IT,WHICH WILL QUICKLY DECREASE THE CHANCES OF SUCCESS FOR THE SCM SYSTEM.
-ENSURE THE SCM SYSTEM SUPPORTS THE ORGANIZATIONAL GOALS,IF THE ORAGNIZATIONAL GOALS SUPPORTS HIGHLY EFFICIENT STRATEGIES, BE SURE THE SUPPLY CHAIN DESIGN HAS THE SAME GOALS.
-DEPLOY IN INCREMENTAL PHASES AND MEASURE AND COMMUNICATE SUCCESS,A BIG PICTURE PERSPECTIVE IS VITAL TO SCM SUCCESS,TEH INCREMENTAL APPROACH MEANS THE SCM SYSTEM SHOULD BE IMPLEMENTED IN DIGESTIBLE BITES,AND ALSO MEASURED FOR SUCCESS ONE STEP AT A TIME.
-BE FUTIRED ORIENTED,THE KEY IS TO BE CERTAIN THAT THE SOFTWARE WILL MET FUTURE NEEDS,NOT ONLY CURRENT NEEDS.

CHAPTER 11:BUILDING A CUSTOMER-CENTRIC ORGANIZATION-CUSTOMER RELATIONSHIP MANAGEMENT

OPENING CASE STUDY QUESTIONS

1)WHY IS IT IMPORTANT FOR ANY COMPANY TO USE CRM STRATEGIES TO MANAGE CUSTOMER INFORMATION?

-PROVIDE BETTER CUSTOMER SERVICE
-MAKE CALL CENTERS MORE EFFICIENT
-CROSS SELL PRODUCTS MORE EFFECTIVELY
-HELP SALES STAFF CLOSE DEALS FASTER


2)IF THE VIRTUAL WORLD IS THE FIRST POINT OF CONTACT BETWEEN A COMPANY AND ITS CUSTOMERS, HOW MIGHT THAT TRANSFORM THE ENTIRE SHOPPING EXPERIENCE?

-EASY TO BUY ANYTHING AND DO TRANSACTION OF PURCHASING
-FASTER, NOT WASTE TIME AND SAVE ENERGY
-EASY TO GET GOODS
-SPEND MONEY

CHAPTER 9:ENABLING THE ORGANIZATION-DECISION MAKIING

EXAMPLE OF EXPERT SYSTEM

An example of the application of expert systems in the financial field is expert system for mortgages.. Loan departments are interested in expert systems for mortgages because of the growing cost of labour, which makes the handling and acceptance of relatively small loans less profitable. They also see a possibility for standardized, efficient handling of mortgages loan by applying expert systems, appreciating that for the acceptance of mortgages there are hard and fast rules which do not always exist with other types of loans.

 

 

 

 

 

EXAMPLE OF NEURAL NETWORKS

Example OF NEURAL NETWORKS: Real Estate Appraisal
Consider a real estate appraiser whose job is to predict the sale price of residential houses. As with the Bank Loans example, the input pattern consists of a group of numbers. (For example: number of bedrooms, number of stories, floor area, age of construction, neighborhood prices, size of lot, distance to schools, etc.). This problem is similar to the Bank Loans example, because it has many non-linearities, and is subject to millions of possible inputs patterns. The difference here is that the output prediction will consist of a calculated value -- the selling price of the house.
It is possible to train the neural network to simulate the opinion of an expert appraiser, or to predict the actual selling price.



 

EXAMPLE OF GENETIC ALGORITHMS 

Genetic Algorithms -An artificial intelligent system that mimics the evolutionary, survival-of-the-fittest process to generate increasingly better solutions to a problem.It essentially an optimizing system, it finds the combination of inputs that give the best outputs.Useful when search space very large or too complex for analytic treatment.In each iteration (generation) possible solutions or individuals represented as strings of numbers.



 


EXAMPLE OF INTELLIGENT AGENTS
  

Intelligent Agents - is an autonomous entity which observes through sensors and acts upon an environment using actuators and directs its activity towards achieving goals . Intelligent agents may also learn or use knowledge to achieve their goals. They may be very simple or very complex, a reflex machine such as a thermostat is an intelligent agent, as is a human being, as is a community of human beings working together towards a goal.