Week 1: Chapter 1, Section 1: Management Information Systems: Business Driven MIS

Key notes outlining concepts

The 4th Industrial Revolution

From (2006–present) represents the blending of the digital, physical, and biological worlds, with rates of change operating at hypervelocity. This revolution is driven by connected devices. Includes IoT & M2M

Internet of Things (IoT)

• Any device connected to the Internet with the goal of enhancing performance without human intervention.

  • Devices typically use smaller volumes of data (under 1 gigabyte).

  • The ultimate goal is the analysis of data to create better performing products and services.

  • Examples include smart watches, yoga mats, frying pans, and fridges.

Machine-to-Machine (M2M)

• Two or more connected devices interacting via wireless or wired connections with the goal of data sharing and analytics without human intervention.

  • Devices use large amounts of data, ranging in the terabytes.

  • Operates in systems like smart grids and is used for things such as asset tracking and banking transaction monitoring.

Key difference of IoT and M2M

IoT connects one or more devices wirelessly to achieve better performance, while M2M connects two or more devices (wired or wirelessly) primarily for data sharing and performing advanced analytics for continuous business monitoring.

Data, Information, Business Intelligence, Knowledge

These four concepts represent the core drivers of the information age. Progressing from data to knowledge involves including more variables for analysis, resulting in better, more precise support for decision making and problem solving.

• Data: Defined as raw facts that describe the characteristics of an event or object.

• Information: Data converted into a meaningful and useful context. Information provides context and structure to analyzed data, making it insightful for humans when making informed business decisions.

• Business Intelligence (BI): Information collected from multiple sources (suppliers, customers, competitors, partners, and industries) that analyzes patterns, trends, and relationships for strategic decision making. BI can manipulate multiple variables, such as weather conditions and interest rates, to anticipate business performance.

• Knowledge: Includes the skills, experience, and expertise, coupled with information and intelligence, that create a person's intellectual resources. People who use BI along with personal experience to make decisions are referred to as knowledge workers.

Data

Defined as raw facts that describe the characteristics of an event or object.

Information

Data converted into a meaningful and useful context. Information provides context and structure to analyzed data, making it insightful for humans when making informed business decisions.

Business Intelligence (BI)

Information collected from multiple sources (suppliers, customers, competitors, partners, and industries) that analyzes patterns, trends, and relationships for strategic decision making. BI can manipulate multiple variables, such as weather conditions and interest rates, to anticipate business performance.

Knowledge

Includes the skills, experience, and expertise, coupled with information and intelligence, that create a person's intellectual resources. People who use BI along with personal experience to make decisions are referred to as knowledge workers.

Data Characteristics - Big Data

Described as large volumes of data—both structured and unstructured—containing greater variety, increased veracity, and more velocity.

• Variety: Refers to the different forms of structured and unstructured data, such as spreadsheets, databases, email, videos, photos, and PDFs, all requiring analysis.

• Veracity: Relates to the uncertainty or trustworthiness of data, including biases, noise, and abnormalities. Data must be meaningful and clean to prevent dirty data from accumulating in systems.

• Volume: Represents the scale of data, encompassing enormous volumes generated daily, requiring specialized tools to analyze zettabytes and brontobytes.

• Velocity: Involves the analysis of streaming data as it travels around the internet. Massive volume is created by machines and networks, necessitating rapid analysis.

Variety

Refers to the different forms of structured and unstructured data, such as spreadsheets, databases, email, videos, photos, and PDFs, all requiring analysis.

Veracity

Relates to the uncertainty or trustworthiness of data, including biases, noise, and abnormalities. Data must be meaningful and clean to prevent dirty data from accumulating in systems.

Volume

Represents the scale of data, encompassing enormous volumes generated daily, requiring specialized tools to analyze zettabytes and brontobytes.

Velocity

Involves the analysis of streaming data as it travels around the internet. Massive volume is created by machines and networks, necessitating rapid analysis.

Structured Data

Data that has a defined length, type, and format, such as numbers, dates, or strings (e.g., Customer Address).

• It accounts for about 20 percent of the data surrounding us and is typically stored in traditional systems like relational databases or spreadsheets.

• Sources include human-generated structured data (e.g., keyboard input) and machine-generated structured data (e.g., sensor data).

Unstructured Data

Data that is not defined and does not follow a specified format, typically appearing as free-form text (e.g., emails, Twitter tweets, and text messages).

• It accounts for about 80 percent of the data surrounding us.

• Sources include human-generated unstructured data (e.g., text messages, social media data) and machine-generated unstructured data (e.g., satellite images, radar data).

System

A collection of parts that link to achieve a common purpose.

Systems Thinking

A method for monitoring the entire system by viewing multiple inputs being processed or transformed to produce outputs while continuously gathering feedback on each part.

Input, Process, Output

Systems thinking involves taking inputs (e.g., lettuce, patty, bun for a hamburger), processing or transforming them (e.g., cooking the patty, assembling the ingredients), to produce an output (e.g., the final hamburger).

Feedback

Information that returns to its original transmitter (input, process, or output) and modifies the transmitter’s actions, helping the system maintain stability.

Systems Thinking Process

• System

• Systems Thinking 

• Input, Process, Output

• Feedback

Management Information Systems (MIS)

A business function (like accounting or HR) that moves information about people, products, and processes across the company to facilitate decision making and problem solving.

Enabling Communications

MIS incorporates systems thinking to help companies operate cross-functionally. For example, an MIS for sales moves a single customer order across all functional areas (sales, order fulfillment, shipping, billing, and customer service), ensuring that the sale appears as one continuous process to the customer, even though different departments handle different parts. This helps eliminate data silos, which occur when departments cannot freely communicate or share data.

MIS Department

The MIS department performs vital roles and responsibilities in the organization, often including senior executive positions at the strategic level.

• Chief Information Officer (CIO): Responsible for (1) overseeing all uses of MIS and (2) ensuring that MIS strategically aligns with business goals and objectives.

• Chief Technology Officer (CTO): Responsible for ensuring the throughput, speed, accuracy, availability, and reliability of an organization’s information technology.

• Chief Security Officer (CSO): Responsible for ensuring the security of MIS systems and developing strategies and safeguards against attacks from hackers and viruses.

• Chief Data Officer (CDO): Responsible for determining the types of information the enterprise will capture, retain, analyze, and share; this role focuses specifically on the data, regardless of the system used.

• Chief Privacy Officer (CPO): Responsible for ensuring the ethical and legal use of information within an organization.

• Chief Knowledge Officer (CKO): Responsible for collecting, maintaining, and distributing the organization’s knowledge.

Chief Information Officer (CIO)

• Responsible for (1) overseeing all uses of MIS and (2) ensuring that MIS strategically aligns with business goals and objectives.

Chief Technology Officer (CTO)

Responsible for ensuring the throughput, speed, accuracy, availability, and reliability of an organization’s information technology.

Chief Security Officer (CSO)

Responsible for ensuring the security of MIS systems and developing strategies and safeguards against attacks from hackers and viruses.

Chief Data Officer (CDO)

Responsible for determining the types of information the enterprise will capture, retain, analyze, and share; this role focuses specifically on the data, regardless of the system used.

Chief Privacy Officer (CPO)

Responsible for ensuring the ethical and legal use of information within an organization.

Chief Knowledge Officer (CKO)

Responsible for collecting, maintaining, and distributing the organization’s knowledge.