Chapter 11: Building a Customer- Centric Organozation- Customer relationship Management

CUSTOMER RELATIONSHIP MANAGEMENT (CRM)

•          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

•          An organization can find its most valuable customers by using a formula that industry insiders call RFM:

–      How recently a customer purchased items (recency)

–      How frequently a customer purchases items (frequency)

–      How much a customer spends on each purchase (monetary value)

THE EVOLUTION OF CRM

THE UGLY SIDE OF CRM: WHY CRM MATTERS
MORE NOW THAN EVER BEFORE

CUSTOMER RELATIONSHIP MANAGEMENT’S EXPLOSIVE GROWTH

•          CRM Business Drivers

 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

•          Operational CRM and analytical CRM

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

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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

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

•          Organizations must embrace technologies that can effectively manage supply chains

INFORMATION TECHNOLOGY’S ROLE IN THE SUPPLY CHAIN

•          IT’s primary role is to create integrations or tight process and information linkages between functions within a firm

•        Factors Driving SCM

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 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 in the supply chain

 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

•          Top reasons why more and more executives are turning to SCM to manage their extended enterprises

•          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 Organization Decision Making

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Decision Making

•          Model – a simplified representation or abstraction of reality

•          IT systems in an enterprise

TRANSACTION PROCESSING SYSTEMS

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

•          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 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

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 get details, and details of details, of information

–      Slice-and-dice – looks at information from different perspectives

•          Digital dashboard – integrates information from multiple components and presents it in a unified display

 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

•          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

•          Neural Network – attempts to emulate the way the human brain works

                         - Fuzzy logic – a mathematical method of handling imprecise or subjective information

•          Genetic algorithm – an artificial intelligent system that mimics the evolutionary, survival-of-the-fittest process to generate increasingly better solutions to a problem

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

          DATA MINING

•          Data-mining software includes many forms of AI such as neural networks and expert systems

Common Forms of data analysis capabilities include:                                                                        

• Cluster analysis
• Association detection
• Statistical analysis

Chapter 8: Accessing Organizational Information

Hi, we meet again, in new chapter. This Chapter is one of my favourite chapter. Okay, lets go through this!!!

Data Warehouse                                                            

First thing you should know is :

    What is Data Warehouse ?

History of Data Warehousing

    v  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

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

v  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

v  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.

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

v  Data mart – contains a subset of data warehouse information

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

•    In a data warehouse and data mart, information is multidimensional, it contains layers 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.

v  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.

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

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

                                                        Information cleansing activities

                                                                                                  Accurate and complete information

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

v  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

Eg: Excel, Access

Chapter 7: Storing Organizational Information- Databases

Hi, okay this is my entry for mgt300 which is chapter 7 about Storing Organizational Information- databases. This chapter quiet fun & interesting. Let me share you this.

• Information is stored in databases

  Database – maintains information about various types of objects (inventory), events (transactions), people    (employees), and places (warehouses)

• Database models include:

1. Hierarchical database model – information is organized into a tree-like structure (using parent/child relationships) in such a way that it cannot have too many relationships
2. Network database model – a flexible way of representing objects and their relationships
3. Relational database model – stores information in the form of logically related two-dimensional tables

Entities and Attributes 

•    Entity – a person, place, thing, transaction, or event about which information is stored

          The rows in each table contain the entities

          In Figure 7.1 CUSTOMER includes Dave’s Sub Shop and Pizza Palace entities

• Attributes (fields, columns) – characteristics or properties of an entity class

         The columns in each table contain the attributes

         In Figure 7.1 attributes for CUSTOMER include Customer ID, Customer Name, Contact Name

RELATIONAL DATABASE ADVANTAGES

Database advantages from a business perspective include:

• Increased flexibility
• Increased scalability and performance
• Reduced information redundancy
• Increased information integrity (quality)
• Increased information security

1. Increased flexibility

A well-designed database should:

• Handle changes quickly and easily
• Provide users with different views
• Have only one physical view

              -   Physical view – deals with the physical storage of information on a storage device

• Have multiple logical views

              - Logical view – focuses on how users logically access information

2. Increased scalability and performance

A database must scale to meet increased demand, while maintaining acceptable performance levels

• Scalability – refers to how well a system can adapt to increased demands
• Performance – measures how quickly a system performs a certain process or transaction

3. Reduced Information Redundancy

Redundancy – the duplication of information or storing the same information in multiple places.

4. Increase Information Integrity (Quality)

• Information integrity – measures the quality of information
•  Integrity constraint – rules that help ensure the quality of information

                 - Relational integrity constraint

                 - Business-critical integrity constraint

5. Increased Information Security

• Information is an organizational asset and must be protected
• Databases offer several security features including:

                - Password – provides authentication of the user

                - Access level – determines who has access to the different types of information

                - Access control – determines types of user access, such as read-only access

DATABASE MANAGEMENT SYSTEMS

- Database management systems (DBMS) – software through which users and application programs interact with a database.

Data-Driven Websites

- Data-driven websites – an interactive website kept constantly updated and relevant to the needs of its customers through the use of a database

Data-Driven Website Business Advantages

Integrating Information among Multiple Databases

•        Integration – allows separate systems to communicate directly with each other

–       Forward integration – takes information entered into a given system and sends it automatically to all downstream systems and processes

–       Backward integration – takes information entered into a given system and sends it automatically to all upstream systems and processes

Forward integration and backward integration

•           Building a central repository specifically for integrated information