Chapter 11> Building a Customer-Centric Organization – Customer Relationship Management

>CUSTOMER RELATIONSHIP MANAGEMENT (CRM)

CRM enables an organization to;

 *  Provide better customer service

 *   Make call centers more effici

*   Cross sell products more effectively

*   Helps 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 FRM;

* How recently a customer purchased items (recency)

* How frequently a customer purchased items (frequency)

* How much a customer speeds on each purchased (monetary value)

>THE EVALUATION OF CRM

CRM reporting technologies help organizations identify their customers across other applications. CRM analysis technologies help organizations segment their customers into categories such as best and worst customers. CRM predicting technologies help organizations predict customer behavior, such as which customers are at risk of leaving.

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

Recall that Business 2.0 ranked "You - the customer" as one of the 50 people who matter now for 2006. Why You Matter according to Business 2.0: They have long said the customer is always right. But they never really meant it. Now they have no choice. You - or rather, the collaborative intelligence of tens of millions of people, the networked you - continually create and filter new forms of content, anointing the useful, the relevant, and the amusing and rejecting the rest. You do it on Web sites like Amazon, Flickr, and YouTube, via podcasts and SMS polling, and on millions of self-published blogs.

In every case, you have become an integral part of the action as a member of the aggregated, interactive, self-organizing, auto-entertaining audience. But the You Revolution goes well beyond user-generated content. Companies as diverse as Delta Air Lines and T-Mobile are turning to you to create their ad slogans. Procter & Gamble and Lego are incorporating your ideas into new products. You constructed open-source and are its customer and its caretaker. None of this should be a surprise, since it was you - your crazy passions and hobbies and obsessions - that built out the Web in the first place. And somewhere out there, you are building Web 3.0. We do not yet know what that is, but one thing is for sure: It will matter.

There are numerous examples of customers having power on the Web. A few sites include www.ihatedell.com and www.donotbuydodge.ca. Customers are using YouTube, MySpace, blogs, and a number of other Web tools to slam or praise companies.

>CUSTOMER RELATIONSHIP MANAGEMENT’S EXPLOSIVE GROWTH

USING ANALYTICAL CRM TO ENHANCE DECISION

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

- Analytical CRM – supports back-office operations and strategic analysis and includes all system that do not deal directly with the customers

>CUSTOMER RELATIONSHIP MANAGEMENT SUCCESS FACTORS

CRM success factors include;

* Clearly communicate the CRM strategy

*Define information needs and flows

*Build an integrated view of the customer

*Implement in iterations

*Scalability for organizational growth

>USING ANALYTICAL CRM TO ENHANCE DECISION

CRM applications were developed to cope with the challenge of integrating information that has been scattered throughout the entire organization or across the supply chain. Customer interactions take place anytime and anywhere. Information collected at each customer interaction point has limited value unless integrated into the total system. CRM application is added to enterprise systems to address marketing opportunities in downstream supply chains.

A comprehensive CRM system includes three major components: (1) Operational CRM, (2) Analytical CRM, and (3) Collaborative CRM. Operational CRM can resolve problems related to sales force automation, customer service and support, and enterprise marketing automation. Analytical CRM systems provide intelligence based on the data collected and accumulated from all customer interaction points over time. Collaborative CRM systems assist the communication process between customers and organizational functions. Customers can choose any channel to communicate with service representatives via their preference channels, such as face to face, Internet, telephone, fax, mobile phone, and instant messaging (Richard, 2010).

Operational CRM and analytical CRM

CHAPTER 10 -> EXTENDING THE ORGANIZATION- SUPPLY CHAIN MANAGEMENT

>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

Decision Making

Ø  Reasons for Growth of Decision Making Information System

-  People need to analyze large amounts of information – Improvements in technology itself,                innovations in communication, and globalization have resulted in a dramatic increase in the                alternatives and dimensions people need to consider when making a decision or appraising an            opportunity .

-  People must make decisions quickly – Time is of the essence and people simply do not have time to     sift through all the information manually

-  People must apply sophisticated analysis techniques, such as modeling and forecasting, to  make good    decisions – Information systems substantially reduce the time required to perform these                    sophisticated analysis techniques

-  People must protect the corporate asset of organizational information – Information systems offer       the security required to ensure organizational information remains safe.

Ø  Model – A simplified representation or abstraction of reality

Ø  IT systems in an enterprise

Transaction Processing System

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

Ø  Transaction processing system – the basic business system that serves the operational level (analysis)      in an organization

Ø  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

Ø  Online analytical processing (OLAP) – the manipulation of information to create business                  intelligence in support of strategic decision making

Decision support systems

Ø  Decision support system (DSS) – models information to support managers and business                      professionals during the decision-making process

Ø  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 outputs

What-if analysis

Goal-seeking analysis

Executive information system

Ø  Executive information system (EIS) – A specialized DSS that supports senior level executives within     the organization

Ø  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 information

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

Ø  Interaction between a TPS and an EIS

Ø  Interaction between a TPS and a DSS

Ø  Digital dashboard – integrates information from multiple components and presents it in a united          display

Artificial intelligence (AI)

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

Ø  Intelligent system – various commercial applications of artificial intelligence

Ø  Artificial intelligence (AI) – simulates human intelligence such as the ability to reason and learn

Ø  Four most common categories of AI include;

1. Expert system – computerized advisory programs that imitate the reasoning processes of experts in solving difficult problems

2. Neural network – attempts to emulate the way the human brain works

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

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

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

Data Mining

Ø  Data-mining software includes many forms of AI such as neutral networks and expert systems

Chapter 8 – Accessing Organizational Information – Data Warehouse

What is Data Warehouse?

Ø  Defined in many different ways, but not rigorously

-  A decision support database that is maintained separately from the                organization’s operational database.

-  A consistent database source that bring together information from                  multiple sources for decision support queries.

-  Support information processing by providing a solid platform of                          consolidated, historical data for analysis.

History of Data Warehousing

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

Ø  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

-  Issues of quality information

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

Data warehouse fundamentals

Ø  Data warehouse – A logical collection of information – gathered from             many different operational databases – that supports business analysis       activities and decision-making takes

Ø  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

Ø  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.

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

Ø  Data mart – contains a subset of data warehouse information.

Multidimensional Analysis and Data Mining

Ø  Relational Database contains information in a series of two-dimensional       tables.

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

                    -  Dimension – A particular attribute of information

Ø  Cube – common term for the representation of multidimensional                              information

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

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

Ø  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 finds trends, patterns and                      correlations that can guide decision making and increase understanding

Ø  To perform data mining users need data-mining tools

-  Data-mining tool – uses a variety of techniques to finds patterns and                relationships in large volumes of information. Eg: retailers and 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

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

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

Ø  Occurs during ETL process and second on the information once if is in the           data warehouse

Ø  Contract information in an operational system

Ø  Standardizing Customer  name from Operational Systems

Ø  Information cleansing activities

-  Missing Records or Attributes

-  Redundant Records

-  Missing Keys or Other Required Data

-  Erroneous Relationships or References

-  Inaccurate Data

Ø  Accurate and complete information

Business Intelligence

Ø  Business Intelligence – refers to applications and technologies that are        used to gather, provides access, analyze data and information to                      support decision making efforts

Ø  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

Ø  Eg; Excel, Access

STORING ORGANIZATIONAL INFORMATION - DATABASE

RELATIONAL DATABASE FUNDAMENTALS

-  Information is everywhere in an organization

-  Information is stored in databases

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

    Ø   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.

    Ø  Network database model – a flexible way of representing objects and their relationships.

Ø  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

  Ø  The rows in each table contains the entities

- Attributes (fields, columns) – characteristics or properties of an entity class                                           Ø  The columns in each table contain the attributes

KEYS AND RELATIONSHIPS

- Primary keys and foreign keys identity the various entity classes (tables) in the database

     Ø  Primary key – a fields (or group of fields) that uniquely identities a given entity in a table

     Ø  Foreign key – a primary key of one table that appears an attribute in another table and acts to               provide a logical relationships among the two tables.

RELATIONAL DATABASE ADVANTAGES

-Database advantages from a business perspective include;

Ø  Increased flexibility

Ø  Increased scalability and performance

Ø  Reduced information redundancy

Ø  Increased information integrity (quality)

Ø  Increased information security

INCREASED FLEXIBILITY

- A well-designed database should;

Ø  Handle changes quickly and easily

Ø  Provide users with different views

Ø  Have only one physical views

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

Ø  Have multiple logical views

§  Logical view – focuses on how users logically access information

INCREASED SCALABILITY AND PERFORMANCE

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

Ø  Scalability – refers to how well a system can adapt to increased demands

Ø  Performance – measures how quickly a system performs a certain process or transaction

REDUCED INFORMATION REDUNDANCY

- Databases reduce information redundancy

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

- Inconsistency is one of the primary problems with redundant information

INCREASED INFORMATION SECURITY

- Information is an organization asset and must be protected

- Databases offer several security features including;

Ø  Password – provides authentication of the user

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

Ø  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 WEB SITES

- Data-driven Web sites – an interactive Web site kept constantly updated and relevant to the needs of    its  customers through the use of database

DATA-DRIVEN WEB SITE BUSINESS ADVANTAGES

-  Development

-  Content Management

-  Future Expandability

-  Minimizing Human Error

-  Cutting Production and Update Costs

-  More Efficient

-  Improved Stability

DATA-DRIVEN BUSINESS INTELLIGENT

- BI in a data-driven Web site

INTEGRATING INFORMATION AMONG MULTIPLE DATABASES

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

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

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

- Building a central repository specifically for integrated information