Information Age, Connected Devices, and Business Strategies

COMPETING IN THE INFORMATION AGE Fact - The confirmation or validation of an event or object Information age – the present time, during which infinite quantities of facts are widely available to anyone who can use a computer The impact of information Technology on the global business e...

COMPETING IN THE INFORMATION AGE Fact - The confirmation or validation of an event or object Information age – the present time, during which infinite quantities of facts are widely available to anyone who can use a computer The impact of information Technology on the global business environment is equivalent to the printing press’s impact on electronics' publishing and productivity CONNECTED DEVICES DRIVING THE FOURTH INDUSTRIAL REVOLUTION Internet of Things (IoT) - Any device connected to the Internet (collect and share data ) for enhancing performance without human. (e.g. Smart Home Devices, Connected Vehicles) 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 (e.g. Industrial Automation - Smart Meters) COMPETING IN THE INFORMATION AGE The core drivers of the information age Data Information Business intelligence Knowledge CORE DRIVER 1: DATA Data - Raw facts that describe the characteristics of an event or object Big data - Large, volumes of data—both structured and unstructured—containing greater variety, increased veracity, and more velocity Variety - Different forms of structured and unstructured data (e.g. spreadsheets, documents, emails, videos, photos, voices and PDFs) Veracity - The uncertainty of data, including biases, noise, and abnormalities (e.g. social media platforms; fake accounts, spam, and misinformation) Volume - The scale of data (e-commerce companies: process millions of transactions per day such as like customer ID, product ID, price, quantity, shipping and billing) Velocity -: The analysis of streaming data as it travels around the Internet (e.g. financial trading firms that makes investment decisions based on real-time market data. Stock prices, trading volumes, news headlines) CORE DRIVER 1: DATA Structured data – Has a defined length, type, and format and includes numbers, dates, or strings such as Customer Address format Machine-generated structured data – Created by a machine without human intervention (e.g. Smart meters automatically record electricity, gas, or water consumption) Human-generated structured data – Data that humans, in interaction with computers, generate (e.g. fill out online surveys such as multiple-choice questions or rating scales)  CORE DRIVER 2: INFORMATION Information - Data converted into a meaningful and useful context Variable - A data characteristic that stands for a value that changes or varies over time CORE DRIVER 2: INFORMATION Report - A document containing data organized in a table, matrix, or graphical format allowing users to easily comprehend and understand information Dynamic report - Changes automatically during creation Static report - Created once based on data that does not change  CORE DRIVER 3: BUSINESS INTELLIGENCE Business intelligence - Information collected from multiple sources such as suppliers, customers, competitors, partners, and industries that analyzes patterns, trends, and relationships for strategic decision making CORE DRIVER 3: BUSINESS INTELLIGENCE Business analytics – The scientific process of transforming data into information for making data-driven business decision  CORE DRIVER 3: BUSINESS INTELLIGENCE Descriptive analytics – Describes past performance and history (e.g. A clothing store analyzes its sales data and discovers that jackets sell best in the fall) It summarizes historical sales data to provide insights into past performance, helping the store understand seasonal trends and customer preferences. Diagnostic analytics – Examines data or content to answer the questions, “Why did it happen?” (e.g. A restaurant notices a sudden drop in customer visits last month. They will analyze customer feedback to know the reason) It examines data to determine why the drop in visits occurred, identifying the negative impact of the new menu on customer satisfaction  CORE DRIVER 3: BUSINESS INTELLIGENCE Predictive analytics – Extracts information from past data and uses it to predict future trends and identify behavioral patterns (e.g. An online retailer uses past purchase data to predict that a particular product will see increased demand during the holiday season) It analyzes historical data to forecast future trends, allowing the retailer to prepare inventory and marketing strategies accordingly. Prescriptive analytics – Creates models including the best decision to make course of action to take (e.g. A logistics company uses data models to determine the most efficient delivery routes based on traffic patterns and fuel costs) It provides recommendations for the best course of action, helping the company optimize its delivery processes and reduce costs. THE MIS SOLUTION Common departments working interdependently Democratization - The action of making something accessible to everyone Data democratization - The ability for data to be collected, analyzed, and accessible to all users  Successful companies operate cross-functionally, integrating the operations of all departments.  Systems are the primary enabler of cross-functional operations.  SYSTEMS THINKING Production - The process where a business takes raw materials and processes them or converts them into a finished product for its goods or services  SYSTEMS THINKING Systems thinking – A way of monitoring the entire system by viewing multiple inputs being processed or transformed to produce outputs while continuously gathering feedback on each part SYSTEMS THINKING Management Information Systems (MIS) – A business function, like accounting and human resources, which moves information about people, products, and processes across the company to facilitate decision-making and problem-solving The MIS department is responsible for gathering, storing, cleaning, and analyzing all data from all of the transaction processing systems MIS DEPARTMENT: ROLES AND RESPONSIBILITIES Chief information officer (CIO) – Overseeing information and ensures the strategic alignment of MIS with business goals and objectives Chief data officer (CDO) – Responsible for determining the types of information the enterprise will capture, retain, analyze, and share Chief technology officer (CTO) – Responsible for ensuring the throughput, speed, accuracy, availability, and reliability of information Chief security officer (CSO) Chief privacy officer (CPO) Chief knowledge officer (CKO)  IDENTIFYING COMPETITIVE ADVANTAGES Stakeholder’s Interests IDENTIFYING COMPETITIVE ADVANTAGES Competitive advantage – A product or service that an organization’s customers place a greater value on than similar offerings from a competitor (e.g. Apple vs. Other Smartphone Brands) First-mover advantage – Occurs when an organization can significantly impact its market share by being first to market with a competitive advantage that lead to market share, brand recognition, and customer loyalty (e.g. Amazon’s Online Marketplace)  SWOT ANALYSIS A SWOT analysis evaluates an organization’s Strengths, Weaknesses, Opportunities, and Threats to identify significant influences that work for or against business strategies SWOT ANALYSIS STRUCTURE  THE FIVE FORCES MODEL – EVALUATING INDUSTRY ATTRACTIVENESS Five Forces Model BUYER POWER Buyer power (Customer 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 Attract customers to buy from us than from our competitors SUPPLIER POWER Supplier power – The suppliers’ ability to influence the prices they charge for supplies Supply chain – Consists of all parties involved in If supplier power is high, the supplier can the procurement of a influence the industry by: product or raw material  Charging higher prices  Limiting quality or services  Shifting costs to industry participants  THREAT OF SUBSTITUTE PRODUCTS OR SERVICES 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 Threat of new entrants – High when it is easy for new competitors to enter a market and low when there are significant entry barriers Entry barrier – A feature of a product or service that customers have come to expect and entering competitors must offer the same for survival What is an industry that has a high entry barrier? What is an industry that has a low entry barrier? RIVALRY AMONG EXISTING COMPETITORS Rivalry among existing competitors – High when competition is fierce (Severe) in a market and low when competitors are more complacent Product differentiation – Occurs when a company develops unique differences in its products or services with the intent to influence demand (e.g. Additional features on a cell phone)  THE THREE GENERIC STRATEGIES CHOOSING A BUSINESS FOCUS Porter’s Three Generic Strategies Provide a framework for businesses to gain a competitive advantage in their industry  THE THREE GENERIC STRATEGIES CHOOSING A BUSINESS FOCUS Porter’s Three Generic Strategies Provide a framework for businesses to gain a competitive advantage in their industry  DECISION-MAKING LEVELS Organizational Decision- Making Levels  OPERATIONAL DECISION-MAKING LEVELS Operational level - Employees develop, control, and maintain core business activities required to run the day-to-day operations (e.g. Employees in a retail store are responsible for tasks such as rearranging shelves, managing the cash, and assisting customers.) Operational decisions - Affect how the firm is run from day to day (e.g. Daily changes on the menu based on the availability of ingredients and customer preferences.) OPERATIONAL Structured decisions - Situations where established processes offer potential solutions (e.g. Conducting regular maintenance checks on machinery follows a structured process. )  OPERATIONAL DECISION-MAKING LEVELS Employee Type: lower management, analysts, staff Focus: Internal, functional Time Frame: Short term, day-to-day operations Decision Types: Structured, repetitive MIS Type: Information OPERATIONAL  MANAGERIAL DECISION-MAKING LEVELS Managerial level – Employees evaluate company operations to identify, adapt to, and leverage change (e.g. A regional sales manager analyzes sales data to identify trends in customer preferences to make adjustments to the sales strategy) Managerial decisions - These concern how the organization should achieve the goals and objectives set by its strategy (e.g. Marketing department head decides to allocate a larger budget to digital MANAGERIAL advertising campaigns instead of traditional media to of increase online sales ) Semistructured decisions – Occur in situations in which a few established processes help to evaluate potential solutions, but not enough to lead to a definite recommended decision (e.g. A manager faces a situation where a key supplier has delayed delivery of materials, he should find alternative suppliers)  MANAGERIAL DECISION-MAKING LEVELS Employee Type: Middle mgmt., managers, directors Focus: Internal, cross-functional Time Frame: Short term, daily, monthly, yearly MANAGERIAL Decision Types: Semi structured, reporting MIS Type: Business Intelligence  STRATEGIC DECISION-MAKING LEVELS Strategic level – Managers develop overall strategies, goals, and objectives (e.g. The executive team at a company decides to focus on developing artificial intelligence (AI) solutions as a core part of their business strategy as a long-term goals) STRATEGIC Strategic decisions - Involve higher-level issues concerned with the overall direction of the organization (e.g. A retail chain's board of directors decides to expand internationally by entering the Europe market) Unstructured decisions – Occurs in situations in which no procedures or rules exist to guide decision makers toward the correct choice (e.g. A startup founder faces a sudden opportunity to collaborate with a well-known influencer for a marketing campaign) STRATEGIC DECISION-MAKING LEVELS Employee Type: Senior management, presidents Focus: external, industry, cross company STRATEGIC Time Frame: Long term, yearly, multi-year Decision Types: Unstructured, nonrecurring, one time MIS Type: Knowledge MEASURING ORGANIZATIONAL BUSINESS DECISIONS Project – A temporary activity a company undertakes to create a unique product, service, or result Metrics – Measurements that evaluate results (track and assess the performance) to determine whether a project is meeting its goals E.g. Revenue Growth: Measures the percentage increase or decrease in revenue over a specific period.  MEASURING ORGANIZATIONAL BUSINESS DECISIONS Critical success factors (CSFs) – The crucial steps companies make to perform to achieve their goals and objectives and implement strategies Create high-quality products Retain competitive advantages Reduce product costs Increase customer satisfaction Hire and retain the best professionals Personal CSFs (e.g. Earn a Degree - E-commerce Business CSF: Effective digital marketing. Exercising and Practicing Healthy They will invest in targeted advertising and search engine optimization Habits (SEO) to increase website traffic and conversion rates for driving sales and brand awareness.  MEASURING ORGANIZATIONAL BUSINESS DECISIONS Key performance indicators (KPIs) – The quantifiable metrics a company uses to evaluate progress toward critical success factors Turnover rates of employees Number of product returns Number of new customers Average customer spending E-commerce Business - CSF: Driving online sales and revenue growth KPI: Conversion rate : (The percentage of website visitors who make a purchase) This KPI helps the marketing team optimize the website's user experience, product offerings, and promotional campaigns to drive more sales.  EFFICIENCY AND EFFECTIVENESS METRICS Efficiency MIS metrics – Measure the performance of MIS itself, such as throughput, transaction speed, and system availability Focuses on the extent to which a firm is using its resources in an optimal way. Doing things right – getting the most from each resource. Effectiveness MIS metrics – Measures the impact MIS has on business processes and activities, including customer satisfaction and customer conversation rates Focuses on how well a firm is achieving its goals and objectives Doing the right things – setting the right goals and objectives and ensuring they are accomplished EFFICIENCY AND EFFECTIVENESS METRICS THE INTERRELATIONSHIP BETWEEN EFFICIENCY AND EFFECTIVENESS METRICS Benchmark – Standards or baseline values the system seeks to achieve (e.g. A coffee shop sets a benchmark of serving customers within 5 minutes during peak hours) Benchmarking – A process of continuously measuring system results, comparing those results to optimal system performance (benchmark values), and identifying steps and procedures to improve system performance (e.g. A manufacturing company produces a product in 60 minutes. They find that a competitor produces the same product in 45 minutes (the benchmark)) Benchmarks are the targets businesses strive for. Benchmarking is the ongoing process of measuring and improving performance of those targets. USING MIS TO MAKE BUSINESS DECISIONS Model – A simplified version or abstraction of reality that helps businesses understand complex situations and make informed decisions (e.g. A clay model of a new car design) Models help managers to  Calculate risks (changes in interest rates)  Understand uncertainty (forecasting sales & inventory)  Change variables (advertising budgets)  Manipulate time to make decisions (visualize project schedule)  OPERATIONAL SUPPORT SYSTEMS Transactional Data – all the collected and processed data within a single business process or unit of work, and its primary purpose is to support the performing of daily operational or structured decisions (e.g. customer's name, address, items bought, quantity, price, and payment details) Transaction processing system (TPS) – Basic business system (computerized) that serves the operational level (records, processes, and stores business transactions) and assists in making structured decisions (e.g. Payroll system (Tracking hourly employees), Course registration system, Human resources systems (tracking vacation, sick days)) Online transaction processing (OLTP) - Capturing in real-time of transaction and event data using technology to process, store, and update (e.g. Booking a hotel room online) Source document – The original transaction record, serve as inputs a business activity. (e.g. invoice; includes the customer's name, items purchased, quantities, prices, and total amount)  OPERATIONAL SUPPORT SYSTEMS Systems Thinking View of a Transaction processing system (TPS) Create, read, update, and delete (CRUD)  MANAGERIAL SUPPORT SYSTEMS Analytical Information - all organizational data (various sources), and its primary purpose is to support the performing of managerial analysis or semistructured decisions (e.g. sales data, customer feedback, and inventory levels) Online analytical processing (OLAP) – Manipulation of information to create business intelligence in support of strategic decision making (e.g. analyze sales data by region, product line, and time period) Decision support system (DSS) – Models information to support managers and business professionals during the decision-making process by analyzing large amounts of data and presenting useful information (e.g. help doctors decide on treatment plans for patients) STRATEGIC SUPPORT SYSTEMS Digital dashboard - Tracks KPIs and CSFs by compiling information from multiple sources and tailoring it to meet user needs  MANAGING BUSINESS PROCESSES Customer facing process - Results Business facing process - Invisible in a product or service that is to the external customer but received by an organization’s essential to the effective external customer management of the business  BUSINESS PROCESS MODELING Business process model - A graphic description of a process, showing the sequence of process tasks, which is developed for a specific process Business process modeling (or mapping) - The activity of creating a detailed flow chart or process map of a work process showing its inputs, tasks, and activities, in a structured sequence As-Is process model - Represent the current state of the operation that has been mapped, without any specific improvements or changes to existing processes To-Be process model - Shows the results of applying change improvement opportunities to the current (As-Is) process model  BUSINESS PROCESS MODELING Example: A restaurant process model for table reservation system As-Is process model might include: Customer calls to make a reservation - Staff checks availability on a paper calendar - Staff writes down the reservation - Customer arrives and checks in at the host stand To-Be process model might include: Customer visits the restaurant's website to make a reservation - System automatically checks availability - Confirmation email is sent to the customer - Customer arrives and checks in using a digital system E.g. Flight Seats Reservation, Course Registration BUSINESS PROCESS MODELING BUSINESS PROCESS BEST PRACTICES Workflow – Includes the tasks, activities, and responsibilities required to execute each step in a business process Digitization - The automation of existing manual and paper-based processes and workflows to a digital format  OPERATIONAL BUSINESS PROCESSES - AUTOMATION Operational business processes - Static, routine, daily business processes such as stocking inventory, checking out customers, or daily opening and closing processes Business process improvement - Attempts to understand and measure the current process and make performance improvements accordingly Automation - The process of computerizing manual tasks, making them more efficient and effective, and dramatically lowering operational costs Can you name an organization, product, or service that does not require any improvement? MANAGERIAL BUSINESS PROCESSES STREAMLINING Managerial business processes - Semidynamic, semiroutine, monthly business processes such as resource allocation, sales strategy, or manufacturing process improvements Streamlining – Improves business process efficiencies by simplifying or eliminating unnecessary steps Bottleneck – Occur when resources reach full capacity and cannot handle any additional demands Redundancy – Occurs when a task or activity is unnecessarily repeated  STRATEGIC BUSINESS PROCESSES REENGINEERING Strategic business processes - Dynamic, nonroutine, long-term business processes such as financial planning, expansion strategies, and stakeholder interactions (e.g. Market Research, Financial Planning, Partnership Development, Implementation Plan) Business process reengineering (BPR) - Analysis and redesign of workflow within and between enterprises (e.g. Current Process Analysis, Process Redesign, Training Staff) USING AI TO MAKE BUSINESS DECISIONS AND DRIVE DIGITAL TRANSFORMATION Artificial intelligence (AI) – Simulates human intelligence such as the ability to reason and learn, focusing on three cognitive skills: learning, reasoning, and self-correction Digital transformation - The process of using digital technologies to fundamentally transform business processes, operations, and customer experiences.  ALGORITHM BASICS Black box algorithm - Decision-making process that cannot be easily understood or explained by the computer or researcher - Mysterious Machine - (e.g. A credit scoring system uses a complex black box algorithm to evaluate loan applications. The algorithm analyzes numerous factors (like credit history, income, and spending patterns)) Genetic algorithm - An artificial intelligence system that mimics the survival-of-the-fittest process to generate increasingly better solutions to a problem (e.g. A company wants to optimize the layout of its factory floor for maximum efficiency.) ?  TYPES OF ARTIFICIAL INTELLIGENCE Weak AI (also called narrow AI) - Artificial intelligence systems that simulate human reasoning can perform a specific task with a true purpose (e.g. Siri or Alexa) Strong AI (called Artificial General Intelligence) - A type of artificial intelligence that can perform any intellectual task that a human can perform (e.g. play chess, engage in a real conversation, cook a meal) – understand and learn specific knowledge Generalized AI, also known as Artificial General Intelligence (AGI) - Refers to AI systems that possess human-level intelligence and are capable of understanding, learning, and performing any intellectual task a human being can do (e.g. manage your calendar, make travel arrangements, negotiate contracts, and provide emotional support by understanding your feelings) - learn new skills on its own  AI TYPE 1: MACHINE LEARNING Machine learning - A type of artificial intelligence that enables computers to understand concepts in the environment and to learn Virtual Personal Assistants: Apple's Siri, Amazon's Alexa, and Google Assistant Recommendation Systems: Netflix, Amazon, and Spotify Healthcare Diagnostics: (e.g., X-rays, MRIs) to detect diseases like cancer, predict patient outcomes, and suggest personalized treatment plans. AI TYPE 1: MACHINE LEARNING Overfitting - Occurs when a machine learning model matches the training data so closely that the model fails to make correct predictions on new data (the model performs well on the training data but poorly on new data) – memorizes/understands answer Underfitting - Occurs when a machine learning model has poor predictive abilities because it did not learn the complexity in the training data- Algebra and Calculus  AI TYPE 2: NEURAL NETWORKS Neural Network – Attempts to emulate the way the human brain works Fuzzy logic – A mathematical method of handling imprecise or subjective information (e.g. patterns or image recognition) Deep learning – A process that employs specialized algorithms to model and study complex datasets; the method is also used to establish relationships among data and datasets (e.g. toddler learns process) Used in the finance industry to discover credit card fraud by analyzing individual spending behavior  AI TYPE 3: NATURAL LANGUAGE PROCESSING Natural language processing (NLP) - Refers to the development of algorithms that can analyze and understand human language, including text and speech AI TYPE 4: COMPUTER VISION Computer Vision - Refers to the development of algorithms that can interpret and analyze visual information, including images and videos E.g. Object detection, image classification, facial recognition, auto driving cars, medical image analysis  AI TYPE 5: EXPERT SYSTEMS Expert Systems - Computerized advisory programs that imitate the reasoning processes of experts in solving difficult problems E.g. MYCIN is an early expert system designed specifically for identifying bacterial infections and recommending antibiotics.  AI TYPE 6: ROBOTICS Robotics - Focuses on creating artificial intelligence devices that can move and react automatically to sensory input 1. Industrial Robots: car manufacturing plant 2. Service Robots: vacuum cleaner 3. Humanoid Robots: Sophia 4. Medical Robots: Surgical robots 5. Agricultural Robots: Drones used in farming to monitor crop health 6. Exploration Robots: NASA’s Mars rovers  THE BIGGEST PROBLEM WITH AI AND ML: BIAS IN THE TRAINING DATA Bias - A disproportionate weight in favor of or against an idea or thing, usually in a way that is closed-minded, prejudicial, or unfair Affinity bias - A tendency to connect with, hire, and promote those with similar interests, experiences, or backgrounds Conformity bias - Acting similarly, or conforming to those around you, regardless of your own views Confirmation bias - Actively looking for evidence that backs up preconceived ideas about someone Name bias - The tendency to prefer certain types of name