CHAPTER 13 : E-BUSINESS

E-BUSINESS
The Internet is  a powerful channel that presents new opportunities for an organization to :

• Touch customers
• Enrich products and services with information
• Reduce costs

E-COMMERCE & E-BUSINESS

How do e-commerce and e-business differ?

• E-commerce - the buying and selling of goods and services over the Internet (online transactions).
• E-business - the conducting of business on the Internet including, not only buying and selling, but also serving customers and collaborating with business partners (online transactions, serving customers and collaborating with business partners)

E-BUSINESS MODEL

• An approach to conducting electronic business on the Internet.

*BUSINESS-TO-BUSINESS (B2B)

• Electronic marketplace (e-marketplace) - interactive business communities providing a central market where multiple buyers and sellers can engage in e-business activities.
• Electronic marketplaces, or e-marketplaces, present structures for conducting commercial exchange, consolidating supply chains and creating new sales channels.
• Their primary goal is to increase market efficiency by tightening and automating the relationship between buyers and sellers.
• Existing e-marketplaces allow access to various mechanisms in which to buy and sell almost anything, from services to direct materials.

Search Engine Marketing

*BUSINESS-TO-CONSUMER (B2C)

Common B2C e-business models include :

• e-shop - a version of a retail store where customers can shop at any hour of the day without leaving their home or office.
• e-mall - consists of a number of e-shops : it serves as  a gateway through which a visitor can access other e-shops.

e-shop

e-mall

-Business types :

• Brick-and-mortar business - operates in a physical store without an Internet presence. Eg : Bata.
• Pure-play business - a business that operates on the Internet only without physical store. Example : Amazon.com
• Click-and-mortar business - a business that operates in a physical store and on the Internet. Eg : Hijabs by Hanami.

Amazon.com

*CONSUMER-TO-BUSINESS (C2B)

• Priceline.com is an example of a C2B e-business model.
• The demand for C2B e-business will increase over the next few years due to customer's desire for greater convenience and lower prices.

*CONSUMER-TO-CONSUMER (C2C)

- Online auctions 

• Electronic auction (e-auction)- Sellers and buyers solicit consecutive bids from each other and prices are determined dynamically.
• Forward auction - Sellers use as a selling channel to many buyers and the highest bid wins.
• Reverse auction - Buyers use to purchase a product or service, selecting the seller with the lowest bid.

-C2C communities include :

• Communities of interest - People interact with each other on specific topics, such as golfing and stamp collecting.
• Communities of relations - People come together to share certain life experiences, such as cancer patients, senior citizens and car enthusiasts.
• Communities of fantasy - People participate in imaginary environments, such as fantasy football teams and playing one-on-one with Michael Jordan.

E-bay

mudah.my

E-BUSINESS BENEFITS

E-business benefits include :

• Highly accessible

- Businesses can operate 24 hours a day, 7 days a week, 365 days a year.

• Increased customer loyalty

- Additional channels to contact, respond to, and access customers helps contribute to customer loyalty.

• Improved information contact

- In the past, customers had to order catalogs or travel to a physical facility before they could compare price and product attributes. Electronic catalogs and Web pages present customers with updated information in real-time about goods, services and prices.

• Increased convenience 

- E-business automates and improves many of the activities that make up a buying experience.

• Increased global reach

- Businesses, both small and large, can reach new markets.

• Decreased cost

- The cost of conducting business on the Internet is substantially smaller than traditional forms of business communication.

E-BUSINESS CHALLENGES

E-business challenges include : 

• Identifying Limited Market Segments

- The main challenge of e-business is the lack of growth in some sectors due to product or service limitation.

• Managing Consumer Trust

- Internet marketers must develop a trustworthy relationship to make that initial sale and generate customer loyalty.

• Ensuring Consumer Protection 

- Implement Internet Security, protect from misuse of customer information.

• Managing Consumer Trust

- Companies that operate online must obey a patchwork of rules about which customers are subject to sales tax on their purchase and which are not.

E-BUSINESS BENEFITS AND CHALLENGES

There are numerous advantages and limitations in e-business  revenue models including :

• Transaction fees
• License fees
• Subscription fees 
• Value-added fees
• Advertising fees

MASHUPS

Web mashup - a Web site or Web application that uses content from more than one source to create a completely new service.

• Application programming interface (API) - a set of routines, protocols, and tools for building software applications.
• Mashup editor -  WYSIWYGs ( What You See Is What You Get) for mashups.

WEB MASHUPS

CHAPTER 12 : INTEGRATING THE ORGANIZATION FROM END TO END - ENTERPRISE RESOURCE PLANNING (ERP)

ENTERPRISE RESOURCE PLANNING (ERP)

• Integrates all departments and functions throughout an organization into a single IT system so that employees can make decisions by viewing enterprisewide information on all business operations.
• At the heart of all ERP systems is a database, when a user enters or updates information in one module, it is immediately and automatically updated throughout the entire system.

• ERP systems automate business processes

BRINGING THE ORGANIZATION TOGETHER

• ERP - bringing the organization together

THE EVOLUTION OF ERP

INTEGRATING SCM, CRM AND ERP

• SCM, CRM and ERP are the backbone of e-business.
• Integration of these applications is the key to success for many companies.
• Integration allows the unlocking of information to make it available to any user, anywhere, anytime.
• SCM and CRM market overviews 

• General audience and purpose of SCM, CRM and ERP

INTEGRATION TOOLS

Many companies purchase modules from an ERP vendor, an SCM vendor and a CRM vendor and must integrate the different modules together.

• Middleware - several different types of software which sit in the middle of and provide connectivity between two or more software applications.
• Enterprise application integration (EAI) middleware - packages together commonly used functionality which reduced the time necessary to develop solutions that integrate applications from multiple vendors.
• Data points where SCM, CRM and ERP integrates 

ENTERPRISE RESOURCE PLANNING (ERP)

ERP systems must integrate various organization processes and be :

• Flexible - must be able to quickly respond to the changing needs of the organization.
• Modular and open - must have an open system architecture, meaning that any module can be interface, with or detached whenever required without affecting the other modules.
• Comprehensive - must be able to support a variety of organizational functions for a wide range of businesses.
• Beyond the company - must support external partnerships and collaboration efforts.

ENTERPRISE RESOURCE PLANNING'S EXPLOSIVE GROWTH

• SAP boasts 20,000 installations and 10 millions users worldwide.
• ERP solutions are growing because :

1. ERP is a logical solution to the mess of incompatible applications that had sprung up in most  businesses.
2. ERP addresses the need for global information sharing and reporting.
3. ERP is used to avoid the pain and expense of fixing legacy systems.  

CHAPTER 11 : BUILDING A CUSTOMER-CENTRIC ORGANIZATION - CUSTOMER RELATIONSHIP MANAGEMENT (CRM)

CUSTOMER RELATIONSHIP MANAGEMENT
- Involves managing all aspects of a customer's relationship with an organization to increase customer loyalty and retention an organization's profitability.

- CRM enables an organization to :

• Provide better customer service
• Make call centers more efficient
• Cross sell products more effectively
• Help sales staff close deals faster
• Simplify marketing and sales processes
• Discover new customers
• Increase customer revenues

RECENCY, FREQUENCY AND MONETARY VALUE

Organizations can find their most valuable customers through "RFM"- Recency, Frequency and Monetary value.

• How recently a customer purchased items (Recency)
• How frequently a customer purchased items (Frequency)
• How much a customer spends on each purchase (Monetary Value)

THE EVOLUTION OF CRM

• CRM reporting technology -  help organizations identify their customers across other applications.
• CRM analysis technologies - help organization segment their customers into categories such as best and worst customers.
• CRM predicting technologies - help organizations make predictions regarding customer behavior such as which customers are at risk of leaving.
• Three phases in the evolution of CRM include reporting, analyzing and predicting.

CUSTOMER RELATIONSHIP MANAGEMENT'S EXPLOSIVE GROWTH

USING ANALYTICAL CRM TO ENHANCE DECISIONS

• Operational CRM - supports traditional transactional processing for day-to-day front-office operations or systems that deal directly with the customers.
• Analytical CRM - supports back-office operations and strategic analysis and includes all systems that do not deal directly with the customers.

CUSTOMER RELATIONSHIP MANAGEMENT SUCCESS FACTORS

CRM success factors include :

1. Clearly communicate the CRM strategy.
2. Define information needs and flows.
3. Build an integrated view of the customer.
4. Implement in iterations.
5. Scalability for organizational growth.

CHAPTER 10 : EXTENDING THE ORGANIZATION - SUPPLY CHAIN MANAGEMENT (SCM)

SUPPLY CHAIN MANAGEMENT
 - The management of information flows between and among stages in a supply chain to maximize
    total supply chain effectiveness and profitability.

BASIC 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 products through the organization's own production process.
3. Distribution of products to customers and their "downstream" customers at all levels.

INFORMATION TECHNOLOGY'S ROLE IN THE SUPPLY CHAIN

Factors Driving SCM 

• Visibility
• Consumer Behavior
• Competition
• Speed

VISIBILITY

• Visibility - more visible models of different ways to do things in the supply chain have emerged. High visibility in the supply chain is changing industries, as Wal-Mart demonstrated.
• 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.
• Once an organization understands customer demand and its effect on the supply chain it can begin to estimate the impact that its supply chain will have on its customers and ultimately the organizations performance.
• Demand planning software - generates demand forecasts using statistical 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.
• SCP and SCE both increase a company's ability to compete.
• SCP depends entirely on information for its accuracy.
• SCE can be as simple as electronically routing orders from a manufacturer to a supplier.

SPEED

• Three factors fostering speed

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

• 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 integrated supply chains.
• DSSs allow managers to examine performance and relationships over the supply chain and among :

1. Suppliers
2. Manufacturers
3. Distributors
4. 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.
• MODEL - A simplified representation or abstraction of reality.
• IT systems in an enterprise

•  Moving up through the organizational pyramid users move from requiring transactional information to analytical information.

  

TRANSACTION PROCESSING SYSTEMS (TPS)

•  Transaction processing system - the basic business system that serves the operational level (analysts) in an organization. 
•  A transaction processing systems (TPS) is an information processing system for business transactions involving the collection, modification and retrieval of all transaction data.
• Transaction processing systems consist of computer hardware and software hosting a transaction-oriented application that perform the routine transactions necessary to conduct business.
• Examples, include systems that manage sales order entry, airline reservations, payroll,employee records, manufacturing and shipping.

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 (DSS)

• A computer-based information system that supports business or organizational decision-making activities.
• DSS serve the management, operations and planning levels of an organization (usually middle management) and help people make decisions about problems that may be rapidly changing and not easily specified in advance.
• Three quantitative models used by DSS include sensitivity analysis, what-if analysis and goal-seeking analysis.

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. Example : What will happen to the supply chain if a stunami in Sabah reduces holding inventory from 30% to 10%?
2. What-if analysis - checks the impact of a change in an assumption on the proposed solution. Example : Repeatedly changing revenue in small increments to determine it effects on other variables.
3. Goal-seeking analysis - finds the inputs necessary to achieve a goal such as a desired level of output. Example : Determine how many customers must purchase a new product  to increase gross profits to $5 million.

 EXECUTIVE INFORMATION SYSTEMS (EIS)

• A decision support system (DSS) used to assist senior executives in the decision-making process. 
• It does this by providing easy access to important data needed to achieve strategic goals in an organization.
• An EIS normally features graphical displays on an easy-to-use interface. 
• Executive information systems can be used in many different types of organizations to monitor enterprise performance as well as to identify opportunities and problems.
• Most EIS offering the following capabilities :

1. Consolidation - involves the aggregation of information and features simple roll-ups to complex groupings of interrelated information. Example : Data for different sales representatives can be rolled up to an office level. Then state level, then a regional sales level.
2. Drill-down - enables users to get details, and details of details, of information. Example : From regional representatives at each  office.
3. Slice-and-dice - looks at information from different perspectives. Example : One slice of information could display all product sales during a given promotion, another slice could display a single product's sales for all promotions.

• Digital dashboard

 

ARTIFICIAL INTELLIGENCE (AI)

• 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 computer

• The ultimate goal of AI is the ability to build a system that can mimic human intelligence.

Four most common categories of AI include :

• Expert system - computerized advisory programs that imitate the reasoning processes of experts in solving difficult problems. Example : Playing Chess.
• Neural Network - attempts to emulate the way the human brain works. Example : Finance industry uses neural network to review loan applications and create patterns or profiles of applications that fall into two categories - approved or denied.

      * Fuzzy logic - a mathematical method of handling imprecise or subjective information.
         Example : Washing machines that determine by themselves how much water to
          use or how long to wash.

•  Genetic algorithm - an artificial intelligent that mimics the evolutionary, survival-of-the-fittest process to generate increasingly better solutions to a problem. Example : Business executives use genetic algorithm to help them decide which combination of projects a firm should invest. 

• Intelligent agent - special-purposed knowledge-based information system that accomplishes specific tasks on behalf of its users.

               * Multi-agent systems
               * Agent-based modeling

•  Example : Shopping bot : Software that will search several retailer's website and provide a comparison of each retailer's offering including price and  availability.

DATA MINING

• Data-mining software includes many forms of AI such  as neural networks and expert systems.
• Common forms of data-mining analysis capabilities include cluster analysis, association detection and statistical 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 systems depend on cluster analysis to segment customer information and identify behavioral traits.
• Example : Consumer goods by content, brand loyalty or similarity.

• 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 - 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.
• Example : Kraft uses statistical analysis to assure consistent flavor, color, aroma,texture and appearance for all of its lines of foods.

CHAPTER 8 : ACCESSING ORGANIZATIONAL INFORMATION - DATA WAREHOUSE

HISTORY OF DATA WAREHOUSE

• 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 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

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

•  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.
• Data warehouse then send subsets of the information to data mart.
• Data mart - contains a subset of data warehouse information 

MULTIDIMENSIONAL ANALYSIS AND DATA MINING

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

 

• In a data warehouse and data mart, information is multidimensional, it contains layer of columns and rows

             *Dimension - a particular attribute of information

• Cube - common term for the representation of multidimensional information.

•  Once a cube of information is created, users can begin to slice and dice the cube to drill down into the information.
• Users can analyze information in a number of different ways and with number of different dimensions.
• 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.
• 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 informations. Eg : retailers can use knowledge of these
                                                 patterns to improve the placement of the items in the layout of a mail-
                                                 order catalog page or Web page.


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.
• Occur during ETL process and second on the information once if is in the data warehouse.

 

BUSINESS INTELLIGENCE

• Business intelligence -  refers to applications and technologies that are used to gather, provide access, analyze data and information to support decision making effort.
• 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.
• Example : Excel, Access