Chapter 12 - Integrating The Organization From The End To End - Enterprise Resource Planning

Chapter 12

Enterprise Resource Planning (ERP)

• It serves as the organization’s backbone in providing fundamental decision making support.

• It enables people in different business areas to communicate. 

• ERP system helps an organization to obtain operational efficiencies, lower costs, improve supplier and customer relations, and increase revenues and market share.

• The heart of an ERP system is a central database that collects information from and feeds information into all the ERP system’s individual application components (called modules), supporting diverse business function such as accounting, manufacturing, marketing, and human resources. 

•  ERP automates business processes such as order fulfillment- taking an order from a customer, shipping the purchase, and then billing for it. 

ERP Integration Data Flow 

ERP Process Flow 

Bringing the Organization Together 

•  ERP enables employees across the organization to share information across a single, centralized database.

• With extended portal capabilities, an organization can also involve its suppliers and customers to participate in the workflow process, allowing ERP to penetrate the entire value chain, and help the organization achieve greater operational efficiency.

Organization before ERP 

ERP- Bringing the Organization Together 

The Evolution of ERP 

Although ERP solutions were developed to deliver automation across multiple units of an organization, to help facilitate the manufacturing process and address issues such as raw materials, inventory, order entry, and distribution, ERP was unable to extend to other functional areas of the company such as sales, marketing, and shipping. It could not tie to any CRM capabilities that would allow organizations to capture customer-specific information, nor did it work with websites or portals used for customer service or order fulfillment

Integrating SCM, CRM, and ERP

Integration of SCM, CRM, and ERP is the key to success for many companies. Integration allows the unlocking of information to make it available to any user, anywhere, anytime. 2 main competitors in ERP market: 

1.    Oracle 

2.    Sap

Primary Users and Business Benefits of Strategic Initiatives.

Integration Tools

• An integrated enterprise infuses support areas, such as finance and human resources, with a strong customer orientation.

• Integration are achieved using:  

* Middleware- several different types of software that sit in the middle of and provide connectivity between two or more software applications. It translates information between disparate systems.

* Enterprise application integration (EAI) middleware- represents a new approach to middleware by packaging together commonly used functionality, such as providing prebuilt links to popular enterprise applications, which reduces the time necessary to develop solutions that integrate applications from multiple vendors.

 Integration between SCM, CRM, and ERP Applications.

• Companies run on independent applications, such as SCM, CRM, and ERP. If one application performs poorly, the entire customer value delivery system is affected.

Enterprise Resource Planning’s Explosive Growth:

Reasons of ERP being proven to be such a powerful force:

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

To qualify as a true ERP solution, the system not only must integrate various organization processes, but also must be:

•  Flexible- an ERP system should be flexible in order to respond to the changing needs of an enterprise. 
• Modular and open- an ERP system has to have open system architecture, meaning that any module can be interfaced with or detached whenever required without affecting the other modules. The system should support multiple hardware platforms for organizations that have a heterogeneous collection of systems. It must also support third- party add-on components. 
•  Comprehensive- an ERP system should be able to support a variety of organizational functions and must be suitable for a wide range of business organizations. 
•  Beyond the company- an ERP system must not be confined to organizational boundaries but rather support online connectivity to business partners or customers.

Everyone involved in sourcing, producing, delivering the company’s product works with the same information, which eliminates redundancies, cuts wasted time, and removes misinformation.

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

Chapter 11, we are learning about….

CRM enables an organization to:

W      Provide better customer service

W      Make call centers more efficient

W      Cross sell products more effectively

W      Help sales staff close deals faster

W      Simplify marketing and sales processes

W      Discover new customers

W      Increase customer revenues

Recency, Frequency, and Monetary Value

Organizations can find their most valuable customers through “RFM” –Recency, Frequency, and Monetary value

F      How recently a customer purchased items (Recency)

F      How frequently a customer purchased items (Frequency)

F      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

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:

W      Clearly communicate the CRM strategy

W      Define information needs and flows

W      Build an integrated view of the customer

W      Implement in iterations

W      Scalability for organizational growth

Chapter 10 – Extending the Organization – Supply Chain Management

BASICS OF SUPPLY CHAIN

SCM – 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 flows from suppliers and their upstream suppliers at all levels

2.       Transformation of materials into semi-finished products, or the organization’s own production processes

3.       Distribution of products to customers and their downstream customers at all levels

INFORMATION TECHNOLOGY’S ROLE IN THE SUPPLY CHAIN

 Information technology’s primary role in SCM is creating the integrations or tight process and information linkages between functions within a firm such as marketing, sales, finance, manufacturing, and distribution – and between firms, which allow the smooth, synchronized flow of both information and product between customers, suppliers and transportation providers across the supply chain

VISIBILITY

·         Supply Chain Visibility is the ability to view all areas up and down the supply chain. Changing supply chains requires a comprehensive strategy buoyed by information technology. Organizations can use technology tools that help them integrate upstream and downstream, with both customers and suppliers.

·         The bullwhip effect occurs when distorted product demand information passes from one entity to the next throughout the supply chain.

CUSTOMER BEHAVIOR

·   The behavior of customers has changed the way businesses complete. Customers will leave if a company does not continually meet their expectations. They are more demanding because they have information readily available, they know exactly what they want, and they know when and how they want it.

·        Demand planning software generates demand forecasts using statistical tools and forecasting techniques. Companies can respond faster and more effectively to consumer demands through supply chain enhancements such as demand planning software.

·      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 organization’s performance.

COMPETITION

·        Supply chain planning (SCP) software uses advanced mathematical algorithms to improve the flow and efficiency of the supply chain while reducing inventory. SCP depends entirely on information for its accuracy.

·     Supply chain execution (SCE) software automates the different steps and stages of the supply chain. This could be as simple as electronically routing orders from a manufacturer to a supplier.

SPEED

·         These systems raise the accuracy, frequency and speed of communication between suppliers and customers, as well as between internal users.

·        Another aspect of speed is the company’s ability to satisfy continually changing customer requirements efficiently, accurately and quickly.

SUPPLY CHAIN MANAGEMENT SUCCESS FACTORS

·         To succeed in today’s competitive markets, companies must align their supply chain with the demands of the markets they serve.

·     Supply chain performance is now a distinct competitive advantage for companies proficient in the SCM area.

MAKE THE SALE TO SUPPLIERS

The hardest part of any SCM system is its complexity because a large part of the system extends beyond the company’s walls. Not only will the people in the organization need to change the way they work, but also the people from each supplier that is added to the network must change. Be sure suppliers are on board with the benefits that the SCM system will provide.

WEAN EMPLOYEES OFF TRADITIONAL BUSINESS PRACTICES

Operations people typically deal with phone calls, faxes and orders scrawled on paper and will most likely want to keep it that way. Unfortunately, an organization cannot disconnect the telephones and fax machines just because it is implementing a supply chain management system. If the organization cannot convince people that using the software will be worth their time, they will easily find ways to work around it, which will quickly decrease the changes of success for the SCM system.

ENSURE THE SCM SYSTEM SUPPORTS THE ORGANIZATION GOALS

It is important to select SCM software that gives organizations an advantage in the areas most crucial to their business success. If the organizational goals support highly efficient strategies, be sure the supply chain design has the same goals.

DEPLOY IN INCREMENTAL PHASE AND MEASURE AND COMMUNICATE SUCCESS

Design the development of the SCM system in incremental phases. For instance, instead of installing a complete supply chain management system across the company and all suppliers at once, start by getting it working with a few key suppliers, and then move on to the other suppliers. Along the way, make sure each step is adding value through improvements in the supply chain’s performance. While a big-picture perspective is vital to SCM success, the incremental approach means the SCM system should be implemented in digestible bites and also measured for success one step at a time.

BE FUTURE ORIENTED

The supply chain design must anticipate the future state of the business. Because the SCM system likely will last for many more years than originally planned, managers need to explore how flexible the systems will be when (not if) changes are required in the future. The key is to be certain that the software will meet future needs, not only current needs.

Chapter 9- Enabling the Organization – Decision Making

Ø  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

Ø   Model – a simplified representation or abstraction of reality

Ø   IT systems in an enterprise'

Transaction Processing Systems(TPS)

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 (analysts) 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

Ø  Decision Support Systems(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.

Eg: What will happen to the supply chain if a tsunami 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.

Eg: 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.

Eg: Determine how many customers must purchase a new product to increase gross profits to $5 million

What-if analysis

Goal-seeking analysis

Interaction between a TPS and a DSS

Ø  Executive Information Systems

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.

 Eg: Data for different sales representatives can be rolled up to an office level. Then state level, then a regional sales level.

§        Drill-down – enables users to get details, and details of details, of information.

Eg: From regional sales data then drill down to each sales representatives at each office.

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

Eg: 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.

Interaction between a TPS and an EIS

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

Ø  Intelligent system – various commercial applications of artificial intelligence

Ø  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

Ø  Four most common categories of AI include:

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

Eg: Playing Chess.

Neural Network – attempts to emulate the way the human brain works. Eg: 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.

Eg: Washing machines that determine by themselves how much water to use or how long to wash

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

 Eg: 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

             Eg:  Shopping bot: Software that will search several retailers’ websites and provide a comparison of each retailers’ offering including prive and availability

#Common forms of data-mining analysis capabilities include:

• Cluster analysis
• Association detection
• 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

Eg: 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

Eg: 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

Eg: 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

 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