Nursuhada Bt Abd Ghafar 4C BM111.

Nursuhada Bt Abd Ghafar 4C BM111.

Chapter 12 ~ Integrating the Organization from End to End-Enterprise Resource Planning ..

Enterprise Resource Planning (ERP)

- enterprise resource planning systems serve as the organization's backbone

 in providing fundamental decision-making supports.

*Bringing the organizational together

- information has traditionally been isolated within specific departments,

 whether on an individual database, in a file cabinet, or on an employee's.

- ERP enables employees across the organization to share information across 

a single, centralized database.

*Evolution of ERP

- ERP solutions were developed to deliver automation across multiple units of 

an organization, yo help facilitate the manufacturing process and address issues

 such a raw materials, inventory, order entry, and distribution.

- ERP handle document management, such as cataloging contracts and purchase orders.

*Integrating SCM, CRM and ERP

- this application are the backbone of ebusiness.

- is the key success of the company.

- allows unlocking of information to make it available to any user, anywhere, anytime.

*Integrating tools

- achieved using middleware- several different types of software that sit in the

 middle of and provide connectivity between two or more software applications.

- enterprise application integration (EAI) middleware represents a new approach

 to middleware by packaging together commonly used functionality.

- if one applications performs poorly, the entire customers value delivery systems will affected.

Nursuhada Bt Abd Ghafar 4C BM111.

Nursuhada Bt Abd Ghafar 4C BM111.

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

CUSTOMER RELATIONSHIP MANAGEMENT

- Customers relationship management(CRM) - managing all aspects of a customer's relationship with an organization to increase customer loyalty and retention and an organization's profitability.
- for example checking online orders twice daily, shipping online orders within 24 hours.
THE BENEFITS OF CRM

• allows the company to operate more efficiently and effectively in the area of supporting customer needs.
• enables a firm to treat customers as individuals, gaining important insights into their buying preferences and shopping behaviors.
• firm can find their most valuable customers by using RFM formula -recently, frequently and monetary value.

EVOLUTION OF CRM.

 

CRM repoting technologies helps organizations identify their customers across other applications

CRM analysis technologies helps organizations segment their customers  into categories.

CRM predicting technologies helps organization predict customers behaviors.

OPERATIONAL AND ANALYTICAL CRM

Operational CRM- supports traditional transactional processing for day-to-day front office operations or systems that deal directly with the consumer.

Analytical CRM- supports back-office operations and strategic analysis and include all systems that do not deal directly with the consumers.

Nursuhada Bt Abd Ghafar 4C BM111.

Nursuhada Bt Abd Ghafar 4C BM111.

CHAPTER 10 EXTENDING THE ORGANIZATION- SUPPLY CHAIN MANAGEMENT

BASICS OF SUPPLY CHAIN 

• Supply chain consists of all parties involved, directly or indirectly, in the procurement of a product or raw material.
• Supply chain management(SCM) involves the management of information flows between and among stages in a supply chain to maximize total supply chain effectiveness and profitability. 
• the supply chain has three main links:

1. materials flow from suppliers and their upstream suppliers at all levels.
2. transformation of materials into semi-finished and finished products, or the organization's own production processes. 
3. distribution of products to customers and their downstream customers at all levels.     

                                             

                                                                                    A TYPICAL SUPPLY CHAIN

                                                 

                                                     FIVE BASIC SUPPLY CHAIN MANAGEMENT

INFORMATION TECHNOLOGY'S ROLE IN THE SUPPLY CHAIN

Factor driving supply chain management

1. VISIBILITY

 -supply chain visibility-is 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.
   

  2.  CONSUMER BEHAVIOUR 

- demand planning software-  generates demand forecasts using statistical tools and forecasting techniques.

3.  COMPETITION

- supply chain planning(SCP) software-  uses advanced mathematical algorithms to improve the flow and efficiency of the supply chain while reducing inventory.

-supply chain execution (SCE) software automates the different stages and steps of the supply chain.

                                            

4. SPEED

-these systems raise the accuracy, frequency, and speed of communication between suppliers and customers.

                                                 

SUPPLY CHAIN MANAGEMENT SUCCESS FACTORS.

Seven principles of supply chain management.

                                          

Keys to SCM success.

• make the sale to suppliers
• wean employes off traditional business practices
• ensure the SCM systems support the organizational goals
• deploy in incremental phass and measure and communicate success
• be future oriented.

Chapter 9 : Enabling the Organization - Decision Making.

Nursuhada Bt Abd Ghafar 4C BM111.

Decision Making.
* Reasons for the growth of decision-making information systems
- people need to analyze large amounts of information
- people must make decision 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.

* Model - a simplified representation or abstraction of reality
* IT system in an enterprise
                                                      Executive      > Executive information systems ( EIS)                                               Managers       > Decision support systems (DSS)
                                    Analysis         > Transaction Processing Systems (TPS)
                                                                                 Organizational Levels
Transaction Processing Systems
* Moving up through the organizational pyramid users move from requiring transaction information to                analytical.


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 Analysts Processing (OLAP) - the manipulation of information to create business intelligence in support of strategic decision making.

Decision Support System
> Decision Support System (DSS) - models information to support managers and business professional 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

Interaction between in a TPS and a DSS

* 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 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
> Advantages: can check info on competitor.
* The ultimate goal of AI is the ability to build a system that can mimic human intelligence
* Four most common categories of AI include: 
1. Expert system - computerized advisory programs that imitate the reasoning processes of expert 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 alogrithm - an artificial intelligent system that mimics the evolutionary, survival of the fittest process    to generate increasingly better solution to a promblem
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 software includes many forms of AI such as neural networks and expert system

Data mining 
* Common forms of data-mining analysis capabilities include:
    i) 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 systems depend on cluster analysis to segment customer information and        identify behavioral traits.
    ii) 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.
    iii) Statistical analysis - performs such function as information correlations, distributions, calculations, and           variance analysis
       1. Forecast- predictions made on the basis of time-series information
       2. Time-series information- time-stamped information collected at a particular frequency.

Chapter 8: Accessing Organizational Information – Data Warehouse.

Nursuhada Bt Abd Ghafar 4C BM111.

                              

                                      History of Data Warehousing.

I In the 1990’s executives became less concerned with the day-to-day business operations and more concerned with overall business functions

I The data warehouse provided the ability to support decision making without disrupting the day-to-day operations, because:

§Operational information is mainly current – does not include the history for better decision making

§Issue of quality information

§Without information history, it is difficult to tell how and why things change over time.

                        Data Warehouse Fundamentals.

T Data warehouse – a logical collection of information – gathered from many different operational databases – that supports business analysis activities and decision-making tasks

T The primary purpose of a data warehouse is to combined information throughout an organization into a single repository for decision-making purposes – data warehouse support only analytical processing.

                             Data Warehouse Model.

B 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.

B Data warehouse  then send subsets of the information to data mart.

B Data mart – contains a subset of data warehouse information

                Multidimensional Analysis and Data Mining.

M Relational Database contain information in a series of two-dimensional tables.

M In a data warehouse and data mart, information is multidimensional, it contains layers of columns and rows

§Dimension –

a particular attribute

of information. 

M Cube – common term for the representation of multidimensional information

Q Once a cube of information is created, users can begin to slice and dice the cube to drill down into the information.

Q Users can analyze information in a number of different ways and with number of different dimensions.

Q Data mining – the process of analyzing data to extract information not offered by the raw data alone. Also known as "knowledge discovery" – computer-assisted tools and techniques for sifting through and analyzing vast data stores in order to find trends, patterns, and correlations that can guide decision making and increase understanding.

Q 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. E.g: retailers can use knowledge of these patterns to improve the placement of items in the layout of a mail-order catalog page or Web page.

         Information Cleansing or Scrubbing.

I An organization must maintain high-quality data in the data warehouse

I Information cleansing or scrubbing – a process that weeds out and fixes or discards inconsistent, incorrect, or incomplete information

I Occur during E.T.L process and second on the information once if is in the data warehouse

I Contact information in an operational system

Y Standardizing Customer name from Operational Systems

Y Information cleansing activities

S Accurate and complete information

                             Business Intelligence.

S Business intelligence – refers to applications and technologies that are used to gather, provide access, analyze data, and information to support decision making effort.

S 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

Y E.g: Excel, Access