IS 300

Bell’s Law

Describes how computer-equipment classes form, evolve, and may eventually die. Understand how businesses will be affected by digital evolution.

Functional Area Information Systems (FAIS)

a collection of application programs in a single department or functional area. (Accounting, Finance, Marketing, HR, ETC)

Enterprise Resource Planning (ERP) Systems

Provide communication among functional area ISs

Transaction Processing Systems (TPS)

Support the “real time” monitoring, collection, storage, and processing of data from the organization’s day to day operations 21

Interorganizational Information Systems (IOS)

Information systems that connect two or more organizations. Ability to Support many Interorganizational operations.

IT

any computer-based tool that people use to work with information and to support the information and information processing needs of an organization.

IS

Collects, processes, stores, analyzes, and disseminates information for a specific purpose.

Porter’s Competitive Forces Model

1. Threat of Entry of New Competitors

2. Bargaining Power of Suppliers

3. Bargaining Power of Customers/Buyers

4. Threat of Substitute Products or Services

5. Rivalry Among Existing Firms within the Industry

Buyer power

The ability of buyers to affect the price of an item

Switching cost

Manipulating costs that make customers reluctant to switch to another product

Loyalty Program

Rewards customers based on the amount of business they do with a particular organization

Supplier Power

The suppliers’ ability to influence the prices they charge for supplies

Supply Chain

Consists of all parties involved in the procurement of a product or raw material

Threat of substitute products or services

High when there are many alternatives to a product or service and low when there are few alternatives

Threat of new entrants

Entry barrier – A feature of a product or service that customers have come to expect and entering competitors must offer the same for survival

Product differentiation

Occurs when a company develops unique differences in its products or services with the intent to influence demand

Strategic Information provide Competitive Advantage by helping organization implement its strategic goals and improve performance /productivity.

1. Support for Decision Making: SIS provides valuable insights to executives and managers, helping them make informed strategic decisions.

2. Alignment with Business Strategy: These systems are closely aligned with the organization's strategic goals and objectives.

3. Integration of Data: SIS integrates data from various sources to provide a comprehensive view of the organization's performance and market conditions.

4. Competitive Advantage: By offering unique insights and capabilities, SIS can give a company a competitive edge over its rivals.

Customer Relationship Management (CRM) Systems

These systems help companies manage interactions with current and potential customers. For example, Salesforce's CRM system allows businesses to track customer interactions, sales, and preferences, enabling personalized marketing and improved customer service

Supply Chain Management (SCM) Systems

These systems optimize the flow of products, information, and finances across the supply chain. For instance, Walmart uses an advanced SCM system to manage inventory levels, supplier relationships, and logistics, ensuring products are available at the right time and place

Enterprise Resource Planning (ERP) Systems

Integrates various business processes, such as finance, HR, and manufacturing, into a single system. SAP's ERP solutions help organizations streamline operations, reduce costs, and improve efficiency

Business Intelligence (BI) Systems:

BI systems analyze data to provide actionable insights. For example, Microsoft's Power BI allows organizations to visualize data, identify trends, and make data-driven decisions

Value Chain

A sequence of activities through which the organization’s inputs are transformed into valuable outputs

Primary Activities

Relate to Production & Distribution of Products & Services

Support Activities

Support Primary Activities Contributing to Competitive Advantage

Support Activities Include:

1. Firm’s Infrastructure (accounting, finance, management)

2. Human Resources Management

3. Product & Technology Development (R&D)

4. Procurement

Business Processes

an ongoing collection of related activities that create a product or service of value to the organization, its business partners, and/or its customers

Business Process is comprised of Three elements

Inputs: Materials, services, and information that flow and are transformed as a result of a process

Resources: The people and materials that perform process activities

Outputs: The products or a service created by the process

Efficiency

Doing Things well. Less delay, less cost, less resources, etc.

Effectiveness

Doing things that matter, High Quality Product

IS’s vital role in three areas of business processes

• Executing the process

• Capturing and storing process data

• Monitoring process performance

Measures of Excellence in Executing Business Processes:

Customer Satisfaction, Cost Reduction, Cycle and fulfillment time reduction, Quality, Differentiation, and Productivity

Business Process Reengineering (BPR)

A radical redesign of an organization’s business processes to increase productivity and profitability Examines business processes with a “clean slate” approach

Business Process Improvement (BPI)

An incremental approach to move an organization toward business process centered operations. Focuses on reducing variation in process outputs by identifying the underlying cause of the variation

Five basic phases of successful BPI

Define, Measure, Analyze, Improve, Control

Business Process Management (BPM)

A management system used to support continuous BPI initiatives for core business processes over time. Important components of BPM: Process modeling and Business Activity Monitoring (BAM)

Business Process Management Suite (BPMS)

An integrated set of applications used for BPM

Difficulties in Managing Data

-Data increases exponentially with time

-Multiple sources of data

-New sources of data (video casts, RFID tags, Blogs, wireless sensors, etc.)

-Data rot, or data degradation

-Data security, quality, and integrity

-Government Regulation

Internal Sources

Corporate databases, company documents

Personal Sources

Personal thoughts, opinions, experiences

External Sources

Commercial databases, government reports, and corporate Web sites. • Clickstream data

Master Data Management

a strategy for data governance involving a process that spans all organizational business processes and applications providing companies with the ability to store, maintain, exchange, and synchronize a consistent, accurate, and timely for the company’s master data

Master Data

a set of core data (e.g., customer, product, employee, vendor, geographic location, etc.) that span the enterprise information systems

Database

maintains information about various types of objects (inventory), events (transactions), people (employees), and places (warehouses) aka a place where data is stored.

Database management system (DBMS)

Creates, reads, updates, and deletes data in a database while controlling access and security

Relational Database Model

a type of database that stores its information in the form of logically-related two-dimensional tables

Data Hierarchy

1. Bit

2. Byte

3. Field

4. Record

5. Data File or Table

6. Database

Foreign Key

a column or columns in a database that link to a primary key in another table. Used to establish and enforce relationships between tables in a relational database. Accepts duplicate values as well as null values.

What problems do Database Management Systems minimize?

Data Redundancy, Data Isolation, Data Inconsistency

What do Database Management Systems maximize?

Data Security, Data Integrity, Data Independence

What are the 5 V’s of Big Data?

Volume (data size)

Velocity (data production speed)

Variety (data oriented from various things)

Veracity (data accuracy)

Value (data value).

What does Big Data Generally Consist of?

-Traditional enterprise data

-Machine-generated/sensor data

-Social Data

-Images captured by billions of devices located around the world

What are some issues with Big Data

-Untrusted data sources

-Big Data is dirty- can be inaccurate, incomplete, duplicated, erroneous

-Big Data changes, especially in data streams

Data Warehouse

A repository of historical data that are organized by subject to support decision makers in the organization

Data Mart

A low-cost, scaled-down version of a data warehouse designed for end-user needs in a strategic business unit (SBU) or individual department.

Data Quality

quality of the data in the warehouse must meet users’ needs. Some of the data can be improved with data-cleansing software, the better, long-term solution is to improve the quality at the source system level.

Knowledge Management (KM)

The process of identifying, organizing, storing, and disseminating information within an organization.

Tacit Knowledge

Acquired through experience, intuitively understood, but challenging to articulate. Examples include language skills and leadership expertise.

Implicit Knowledge

Exists within processes, often referred to as “know-how.” It hasn’t been formally documented yet

Explicit Knowledge

Captured in documents like manuals, reports, and guides. Easily shared across teams through knowledge bases

Knowledge Management Systems

a system to manage knowledge in an organization for creating, capturing, storing, and distributing information. In simple terms, KMS are technologies supporting KM in an organization.

KMS Cycle

-Create knowledge: Knowledge is created as people determine new ways of doing things or develop know-how. Sometimes external knowledge is brought in.

-Capture knowledge: New knowledge must be identified as valuable and be represented in a reasonable way.

-Refine knowledge: New knowledge must be placed in context so that it is actionable. This is where tacit qualities (human insights) must be captured along with explicit facts.

-Store knowledge: Useful knowledge must then be stored in a reasonable format in a knowledge repository so that other people in the organization can access it.

-Manage knowledge: Like a library, the knowledge must be kept current. It must be reviewed regularly to verify that it is relevant and accurate.

-Disseminate knowledge: Knowledge must be made available in a useful format to anyone in the organization who needs it, anywhere and anytime

3 Managerial Roles

Interpersonal, Informational, and Decisional

Why managers need IT support?

-Number of alternatives is constantly increasing

-Most decisions must be made under time pressure

-Increased uncertainty in the decision environment

-Often necessary to rapidly access remote information, consult with experts, or conduct a group decision-making session

Problem Structure

where decision-making processes fall along a continuum ranging from highly structured to highly unstructured

-Structured

-Semi-structure

-Unstructured Decisions

Nature of Decisions

Three broad categories of managerial decisions

1. Operational Control: executing specific tasks efficiently and effectively.

2. Management Control: acquiring and using resources efficiently in accomplishing organizational goals.

3. Strategic Planning: the long-range goals and policies for growth and resource allocation

Business Analytics

Is the process of developing actionable decisions or recommendations for actions based on insights generated from historical data.

Descriptive Analytics

What has Happened? It uses data mining and data aggregation to discover historical data. Uses various statistical analysis techniques to slice and dice raw data into a form that allows people to see patterns, identify anomalies, improve planning, and compare things. It’s easy to employ in daily operations, and little experience is needed. Cons: It offers a limited view and doesn't go beyond the data’s surface.

Predictive Analytics

What could happen? It looks at historical data and analyzes past data trends to predict what could happen. It is a valuable forecasting tool. But it needs lots of historical data to work and it will never be 100% accurate.

Prescriptive Analytics

What should be done? Recommends one or more courses of action and shows the likely outcome of each decision It takes the conclusions gleaned from descriptive and predictive analysis and recommends the best future course of action. It offers critical insights into making the best, most informed decisions. It requires a lot of past data and often cannot account for all possible variables.

What are data mining applications used in?

Retailing and sales, Banking, Manufacturing and production, Insurance, Police work, Healthcare, Marketing, Politics, Weather, Social good

Data Mining Techniques

1. Association Rule Learning: This technique is used to discover interesting relations between variables in large databases. (Market Basket)

2. Classification: This technique is used to classify data into predefined classes or labels. For example, an email can be classified as ‘spam’ or ‘not spam’.

3. Clustering: This is similar to classification but there are no predefined classes. The data is grouped on the basis of similarity. For example, clustering can be used in customer segmentation where customers with similar behaviors are grouped together.

4. Regression: This technique is used to predict a range of numeric values (like sales, temperatures, etc.) based on a particular dataset.

5. Anomaly Detection: This technique is used to identify unusual patterns that do not conform to expected behavior, called outliers. For example, detecting fraudulent transactions in banks.

6. Sequential Patterns: This technique is used to discover or identify similar patterns, regular events or trends in transaction data over a business period.

7. Prediction: This technique uses some variables to predict unknown or future values of other

8. Decision trees are a type of model that uses a tree-like model of decisions. They adopt a top-down approach and use supervised learning to construct decision trees from a given training data set.

9. Decision rules are conditions that imply a given outcome. They can be produced from a decision tree or association. They help in understanding the data better and making informed decisions based on the patterns and associations found in the data.

10. Artificial Neural Networks These are computing systems inspired by the human brain’s biological neural networks. They are used to estimate or approximate functions that depend on a large number of inputs.

Data Mining

the practice of analyzing large databases to generate new information. Performs 2 basic operations, identifying previously unknown patterns (Descriptive Analytics) and Predicting Trends and Behaviors (Predictive Analytics)

Market Basket Analysis

Involves researching customer characteristics in respect to their purchase patterns

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

Geographic Information System (GIS)

a computer-based system for capturing, integrating, manipulating, and displaying data using digitized maps. Its most distinguishing characteristic is that every record or digital object has an identified geographical location