EXTENDING THE ORGANIZATION- SUPPLY CHAIN MANAGEMENT

CHAPTER 10 :

EXTENDING THE ORGANIZATION- SUPPLY CHAIN MANAGEMENT 

 

LEARNING OUTCOMES CHAPTER 10

List and describe the component of a typical supply chain

• PLAN : REFER TO THE OVERALL STRATEGY OF SCM PROGRAM INCLUDING THE DEVELOPMENT OF SCM METRIC TO MONITOR.
• SOURCE: REFER TO THE SUPPLIER WHO WILL PROVIDE OF GOODS AND SERVICE NECESSARY FOR TO RUN BUSINESS.
• MANUFACTURING COMPONENT: EXECUTION OF PROCESSES NEEDED TO PRODUCED, TEST AND PACKAGE PRODUCT OR SERVICE.
• DELIVERY: REFER TO THE SYSTEM FOR RECEIVING ORDERS FROM CUSTOMER, DEVELOPING A NETWORK PF WAREHOUSES GETTING THE PRODUCT TO THE CUSTOMER AND RECEIVING PAYMENT FROM THEM.
• RETURN: SYSTEM OF PROCESSING CUSTOMER RETURN OR SUPPORTING CUSTOMER PROBLEM WITH THE PRODUCT THEY RECEIVED.

Describe the four changes resulting from advances in IT that are driving supply chain

 

visibility

• ABILITY TO VIEW ALL AREAS UP AND DOWN THE SUPPLY CHAIN
• BULL WHIP EFFECT OCCURS WHEN DISTORTED PRODUCT DEMAND INFORMATION PASSES FROM ONE ENTITY TO THE NEXT THROUGH THE SUPPLY CHAIN
• INFORMATION TECHNOLOGY ALLOWS ADDITIONAL VISIBILITY IN THE SUPPLY CHAIN.

Consumer behavior

• DEMAND PLANNING SOFTWARE GENERATES DEMAND FORECAST USING STATITICAL TOOLS AND FORECASTING TECHNIQUES
• ONES AN ORGANIZATION UNDERSTAND CUSTOMER DEMAND ITS EFFECT ON THE SUPPLY CHAIN IT CAN BEGGING TO ESTIMATE THE IMPACT THAT ITS SUPPLY CHAIN WILL HAVE ON ITS CUSTOMER AND ULTIMATELY THE ORGANIZATIONS PERFORMANCE

Competition

• SUPPLY CHAIN PLANNING SOFTWARE, USES ADVANCED MATHEMATICAL ALGORITHM TO IMPROVE THE FLOW AND EFFICIENCY OF THE SUPPLY CHAIN WHILE REDUCING INVENTORY.
• SUPPLY CHAIN EXECUTIVE (SCE) SOFTWARE AUTOMATES THE DIFFERENT SYSTEM AND STAGE OF THE SUPPLY CHAIN.

Speed

• NEW FORM OF SERVE, TELECOMMUNICATION ENABLING COMPANIES TO PERFORM ACTIVITIES THAT WERE ONCE NEVER THOUGHT POSSIBLE.
• ABILITY TO SATISFY CONTINUALLY CHANGING CUSTOMER REQUIREMENT EFFICIENCY, ACCURATELY AND QUICKLY.

Summarize the best practice for implementing a successful supply chain management system.

• MAKE THE SALE TO SUPPLIER: SCM IS IT COMPLEXITY BECAUSE A LARGE PART OF   THE SYSTEM EXTENDS BEYOND THE COMPANY WALLS
• WEAN EMPLOYEES OF TRADITIONAL BUSINESS PRACTICES: OPERATION PEOPLE TYPICALLY DEAL WITH PHONE CALLS, FAXES AND ORDERS SCRAWLED ON PAPER AND WILL MOST LIKELY WANT TO KEEP IT THAT WAY.
• ENSURE THE SCM SYSTEM SUPPORT THE ORGANIZATIONAL GOALS: SCM SOFTWARE THAT GIVE ORGANIZATION AND ADVANTAGE IN THE AREAS MOST CRUCIAL TO THEIR BUSINESS SUCCESS.
• DEPLOY IN INCREMENTAL PHASES AND MEASURE COMMUNICATE SUCCESS:  DESIGN THE DEPLOYMENT OF SCM SYSTEM IN INCREMENTAL PHASES.
• BE FUTURE ORIENTED: THE SUPPLY CHAIN DESIGN MUST ANTICIPATE THE FUTURE STATE OF THE BUSINESS.

CHAPTER 9 -> Enabling The Organization ( Decision Making)

CHAPTER 9 -> Enabling The Organization ( Decision Making)

The categories of Artificial Intelligence systems are:

*EXPERT SYSTEM*

Expert systems are used for problems where there is incomplete data about a subject, and insufficient theory available for the creation of an algorithmic solution. Some problems, such as medical diagnosis, are not easily solved with an algorithm, but instead require reasoning and induction.

Numerical algorithms are more efficient then expert systems, and are typically more exact. However, many problems are not suited to being easily modeled mathematically, and in these cases numerical algorithms are not possible. Other AI techniques, such as artificial neural networks are suited for problems where there is very little theory but a wealth of experimental data.

Expert systems tend to be slow, and often require extensive human interaction. However, well-designed expert systems can be very rigorous, and some expert systems have been shown to outperform the human experts that helped to develop them.

*INTELLIGENT AGENTS*

Intelligent agents are applied as automated online assistants, where they function to perceive the needs of customers in order to perform individualized customer service. Such an agent may basically consist of a dialog system, an avatar, as well an expert system to provide specific expertise to the user.

An example of an automated online assistant providing automated customer service on a webpage. *GENETIC ALGORITHMS*

As the power of evolution gains increasingly widespread recognition, genetic algorithms 
have been used to tackle a broad variety of problems in an extremely diverse array of fields, clearly showing their power and their potential. 

An example using Genetic Algorithms is Robotics company.
The international RoboCup tournament is a project to promote advances in robotics, artificial intelligence, and related fields by providing a standard problem where new technologies can be tried out it is an annual soccer tournament between teams of autonomous robots. The programs that control the robotic team members must display complex behavior, deciding when to block, when to kick, how to move, when to pass the ball to teammates, how to coordinate defense and offense, and so on. In the simulator league of the 1997 competition, David Andre and Astro Teller entered a team named Darwin United whose control programs had been developed automatically from the ground up by genetic programming, a challenge to the conventional wisdom that this problem is just too difficult for such a technique.

*VIRTUAL REALITY*

Virtual reality is often used to describe a wide variety of applications commonly associated with immersive, highly visual, 3D environments. To develop a real time virtual environment, a computer graphics library can be used as embedded resource coupled with a common programming language, such as C++, Perl, Java, or Python. Some of the most popular computer graphic libraries are OpenGL,Direct3D, Java3D, and VRML, and their use are directly influenced by the system demands in terms of performance, program purpose, and hardware platform. The use of multithreading can also accelerate 3D performance and enable cluster computing with multi-userinteractivity.

CHAPTER 8 : ACCESSING ORGANIZATIONAL INFORMATION(DATA WAREHOUSE)

1. ROLES AND PURPOSES OF DATA WAREHOUSES AND DATA MART IN ORGANIZATION 

The purpose of the Data Warehouse in the overall Data Warehousing Architecture is to integrate corporate data.  It contains the "single version of truth" for the organization that has been carefully constructed from data stored in disparate internal and external operational databases.

The amount of data in the Data Warehouse is massive.  Data is stored at a very granular level of detail.  For example, every "sale" that has ever occurred in the organization is recorded and related to dimensions of interest.  This allows data to be sliced and diced, summed and grouped in unimaginable ways. 

Typical Data Warehousing Environment

Contrary to popular opinion, the Data Warehouses does not contain all the data in the organization.  It's purpose is to provide key business metrics that are needed by the organization for strategic and tactical decision making.

Decision makers don't access the Data Warehouse directly.  This is done through various front-end Data Warehouse Tools that read data from subject specific Data Marts.

The Data Warehouse can be either "relational" or "dimensional".  This depends on how the business intends to use the information.

2. The relationship of business intelligence and data warehousing 

 changing data into information and knowledge.

Many of the tool vendors who sell their products or software call it business Intelligence software rather than Data warehousing software. so what is it? 

Business Intelligence is a term commonly associated with data warehousing. Business Intelligence is a generalized term where a company initiates various activities to gather today's market information which also includes about their competitor. Today's business Intelligence systems are contrasted to more classical way of information gathering in mining and crunching the data in the most optimal manner. In short we can say BI simplifies information discovery and analysis. 

In this way the company will have a competitive advantage of business and intelligently using the available data in strategic and effective decision making. it has the ability to bring disparate data under one roof  with a meaningful information and ready for analysis.

so what has Data warehousing to do with Business Intelligence?

Business intelligence usually refers to the information that is available for the enterprise to make decisions on. A data warehousing (or data mart) system is the backed  or the infrastructural, component for achieving business intelligence. Business intelligence also includes the insight gained from doing data mining analysis, as well as unstructured data.

Example, data warehousing. All the source data from disparate sources are used to load/Stage data. Different sources can be flat files, another database or some other process. The starting point of the Data warehouse should extract the data in order to load into its environment.This is extracting. This data may not be the expected format or size. your business demands are different or your organization business requirements are different. So the business process has to modify the data or better word is to transform the incoming data to meet requirements and objectives. This is called Transformation. 

Once every slicing and dicing of the data is done along with applied business rules, this data is ready for loading into the target tables. This process is called Loading. So overall till now we have done Extraction, Transformation and Loading. In short we call this ETL. There are lot of tools available in today's market which does help in achieving the ETL process. Once this data is loaded in to the database, this is ready for next processing. We call that database as Data warehouse database. 

The next process could be building of data marts or directly reporting from it. There are lot of tools or software available for reporting/analysis. Some call it business reporting or analysis tool. But if you see the whole process has intelligence involved in business. we can call this or the gurus call it Data warehousing and the system involved from end to end is called business intelligence system. 

enabling business intelligence