MCS2020

1. DATA, ANALYTICS & SYSTEM BASICS

Data Layers

  • 1st-party: collected directly by company (e.g., Nike Run Club).

  • 2nd-party: another firm’s 1st-party data.

  • 3rd-party: purchased aggregated data.

Types of Analytics

  • Descriptive (what happened)

  • Diagnostic (why it happened)

  • Predictive (what will happen)

  • Prescriptive (what should we do)

System Types

  • TPS: daily transactions (operational).

  • MIS: routine summary reports.

  • DSS: non-routine analytics (“what-if”).

  • ESS: strategic dashboards (executives).

2. FOUNDATIONS (Ch. 1–4)

Data vs Information

  • Data: raw facts

  • Information: processed, meaningful data

Six Strategic Business Objectives

  1. Operational excellence

  2. New products/services

  3. Customer/supplier intimacy

  4. Improved decision-making

  5. Competitive advantage

  6. Survival

Firm Levels

  • Operational → Middle → Senior Management

Porter’s Five Forces

  • Competitors

  • New entrants

  • Substitutes

  • Supplier power

  • Buyer power

Key Theories

  • Transaction Cost Theory: IT lowers coordination cost → more outsourcing

  • Agency Theory: IT lowers monitoring cost → fewer managers needed

Ethics

  • Responsibility, Accountability, Liability, Due Process

  • Opt-in vs Opt-out (GDPR vs US)

  • No-Free-Lunch Rule: creators deserve compensation (e.g., AI using artist’s work)

3. TECH + DATABASES (Ch. 5–8)

Database Errors

  • Redundancy: duplicate data

  • Inconsistency: conflicting values

  • Primary key: unique

  • Foreign key: links tables

Database Operations

  • Select (rows), Project (columns), Join (merge tables)

Networks & Marketing

  • SEO: organic ranking

  • SEM: paid search ads

Security (Essentials Only)

  • Systems vulnerable due to complexity, user error, network exposure

  • Safeguards: encryption, firewalls, authentication

4. BUSINESS APPLICATIONS (Ch. 9–14)

Supply Chain Management

  • Upstream: suppliers

  • Downstream: customers

  • Bullwhip Effect: minor demand changes → large supply variation

CRM

  • Operational CRM: sales/service interactions

  • Analytical CRM: customer data insights

AI

  • Supervised learning: labeled data (digit recognition)

  • Unsupervised learning: pattern discovery, no labels

Decision Types

  • Structured: routine, operational (TPS)

  • Unstructured: strategic, executive (ESS)

SDLC Activities

  • Planning → Analysis → Design → Implementation → Maintenance

Conversion Strategies

  • Direct, Parallel, Phased, Pilot

IT Business Case

  • Tangible benefits: cost savings, efficiency

  • Intangible benefits: satisfaction, insight, reputation

5. HIGH-YIELD EXAMPLES (Guaranteed Test Topics)

  • Nike Run Club = 1st-party data

  • Point-of-sale system updating inventory = TPS

  • Artist’s work in AI dataset = No-Free-Lunch violation

  • Duplicate customer files + different spellings = Redundancy + Inconsistency

  • Handwritten digit model = Supervised Learning

  • Outsourcing increases due to Transaction Cost Theory

  • MIS needs raw data from TPS

  • ESS used for strategic, unstructured decisions