CHAPTER ELEVEN - BUILDING A CUSTOMER-CENTRIC ORGANIZATION - CRM

CHAPTER ELEVEN - BUILDING A CUSTOMER-CENTRIC ORGANIZATION - CRM

CUSTOMER RELATIONSHIP MANAGEMENT

Customer Relationship Management (CRM) is a means of managing all aspects of a customer’s relationship with an organization to increase customer loyalty and retention and an organization’s profitability.

RECENCY, FREQUENCY AND MONETARY VALUE

Organizations can find their most valuable customers through “RFM” 

- How recently a customer purchased item.

- How frequently a customer purchased item.

- How much a customer spends on each purchase. 

EVOLUTION OF CRM

Three phase in evolution of CRM:

- Reporting

- Analyzing

- Predicting

OPERATIONAL AND ANALYTICAL CRM

Operational CRM – support traditional processing day-to-day front-office operation or system that deal directly with the customers.

Analytical CRM – support back-office operation and strategic analysis and includes all systems that do not deal directly to 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.

CHAPTER TEN - EXTENDING THE ORGANIZATION - SCM

CHAPTER TEN - EXTENDING THE ORGANIZATION - SCM

 

SUPPLY CHAIN MANAGEMENT

The supply chain has three main links:

-  Materials flow from suppliers and their “upstream” suppliers at all levels.

-  Transformation of materials into semifinished and finished products through the organization’s own production process.

-  Distribution of products to customers and their “downstream” customers at all levels.

Organizations must embrace technologies that can effectively manage supply chains.

Supply chain management improves ways for companies to find the raw components they need to make a product or service, manufacture that product or service, and deliver it to customers.

Plan – This is the strategic portion of supply chain management. A company must have a plan for managing all the resources that go toward meeting customer demand for products or services.

Source – Companies must carefully choose reliable suppliers that will deliver goods and services required for making products.

Make – This is the step where companies manufacture their products or services. This can include scheduling the activities necessary for production, testing, packaging, and preparing for delivery.

Deliver – This step is commonly referred to as logistics. Logistics is the set of processes that plans for and controls the efficient and effective transportation and storage of supplies from suppliers to customers. 

Return – This is typically the most problematic step in the supply chain. Companies must create a network for receiving defective and excess products and support customers who have problems with delivered products.

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

- 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 must respond to demanding customers through supply chain enhancements.

- 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

-  increased competition makes any organization that is ignoring its supply chain at risk of becoming obsolete.

- 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.

Speed

- These system raise the accuracy, frequency, and speed of communication between supplier and customers, as well as between internal users.

CHAPTER NINE - ENABLING THE ORGANIZATION - DECISION MAKING

CHAPTER NINE - ENABLING THE ORGANIZATION - 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

TRANSACTION PROCESSING SYSTEM

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 SYSTEM

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

Three quantitative models used by DSSs include:

--       Sensitivity analysis

--       What-if analysis

--       Goal-seeking analysis

Interaction between a TPS and a DSS

EXECUTIVE INFORMATION SYSTEM

 Executive information system (EIS) - a specialized DSS that supports senior level executives within the organization.

Interaction between a TPS and an EIS

ARTIFICIAL INTELLIGENCE

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.

Four most common categories of AI include:

--       Expert system

--       Neural Network

--       Genetic algorithm

--       Intelligent agent

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

--       Statistical analysis

CLUSTER ANALYSIS

Cluster analysis – a technique used to divide 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 behavioural traits.

ASSOCIATION PROTECTION 

Association detection – reveals the degree to which variables are related and the nature and frequency of these relationships in the information.

  Market basket analysis – analyses such items as Web sites and checkout scanner information to detect customers’ buying behaviour and predict future behaviour by identifying affinities among customers’ choices of products and services.

STATISTICAL ANALYSIS

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.

CHAPTER EIGHT - ACCESSING ORGANIZATIONAL INFORMATION - DATA WAREHOUSE

CHAPTER EIGHT - ACCESSING ORGANIZATIONAL INFORMATION - DATA WAREHOUSE

Accessing Organizational Information

The company uses data warehouse information to perform the following :

Base labor budgets on actual number of guests served per hour.

Develop promotional sale item analysis to help avoid losses from overstocking or under stocking inventory.

Determine theoretical and actual cost of food and the use of ingredients.

History of Data Warehousing

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

A data warehouse is a logical collection of information – gathered from many different operational databases – that supports business analysis activities and decision making tasks.

Purpose of a data warehouse is to aggregate information throughout an organization into a single repository in such way that employees can make decisions and undertake business analysis activities.

Extraction, transformation, and loading (ETL) is 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.

Model of Typical Data Warehouse

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 layers of columns and rows.

Dimension – a particular attribute of information.

Cube – common term for the representation of multidimensional information.

Data mining is the process of analyzing data to extract information not offered by the raw data alone.

Data-mining tool – uses a variety of techniques to find patterns and relationships in large volumes of information. 

INFORMATION CLEANSING OR SCRUBBING

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

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

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

Contact information in an operational system.

Standardizing Customer name from Operational Systems.

Information cleansing activities.

Accurate and complete information.

Business Intelligence

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

ENABLING BUSINESS INTELLIGENCE

Competitive organizations accumulate business intelligence to gain sustainable competitive advantage, and they may regard such intelligence as a valuable core competence in some instances.

The principal BI enablers are technology, people, and culture.