Systems Analysis, Data Analytics, and Management Accounting Course

Lesson 1 • Introduction to Process Modeling

Introduces flowcharts and basic process diagrams as tools for visualizing system behavior. Prepares students for more advanced modeling techniques in later chapters.

Lesson 2 • Core Concepts of Systems Theory

Introduces open vs. closed systems, entropy, and emergence as applied to organizations. Establishes vocabulary used throughout all subsequent chapters.

Lesson 3 • Problem Identification and Scoping

Teaches structured techniques for defining business problems before analysis begins. Prevents scope creep by establishing clear problem boundaries early.

Lesson 1 • Data Flow and Entity Modeling

Introduces data flow diagrams and entity-relationship models as complementary analysis tools. Links data structures to business processes identified in Chapter 1.

Lesson 2 • Functional and Non-Functional Requirements

Distinguishes between what a system must do and how well it must perform. Teaches writing precise, testable requirement statements.

Lesson 3 • Use Case and User Story Development

Teaches use case diagrams and agile user stories as user-centered specification tools. Bridges traditional and agile analysis approaches.

Lesson 4 • Requirements Elicitation Techniques

Covers interviews, workshops, surveys, and observation as methods for gathering system requirements. Emphasizes selecting the right technique for each stakeholder context.

Lesson 1 • Database Structures and Data Storage

Explains relational database design, normalization, and the role of data warehouses. Connects storage architecture to retrieval efficiency for analytics.

Lesson 2 • Data Types and Measurement Scales

Classifies data as nominal, ordinal, interval, or ratio and explains analytical implications of each. Grounds subsequent statistical and visualization work in correct data handling.

Lesson 3 • Data Quality Assessment and Cleansing

Identifies common data quality issues including missing values, duplicates, and inconsistencies. Applies systematic cleansing procedures to produce analysis-ready datasets.

Lesson 1 • Root Cause Diagnostic Techniques

Applies Pareto analysis, fishbone diagrams, and drill-down techniques to identify performance drivers. Bridges descriptive findings to actionable management insights.

Lesson 2 • Descriptive Statistics for Business

Covers measures of central tendency, dispersion, and distribution shape applied to business datasets. Provides the statistical foundation for all subsequent analytical techniques.

Lesson 3 • Correlation and Trend Analysis

Introduces correlation coefficients, scatter plots, and time-series trend identification. Connects pattern recognition to diagnostic questions about business performance.

Lesson 4 • Data Visualization Principles

Teaches chart selection, design principles, and visual encoding for accurate communication. Prevents common visualization errors that mislead decision-makers.

Lesson 1 • Classification and Segmentation Methods

Introduces logistic regression, decision trees, and cluster analysis for categorizing business entities. Connects segmentation outputs to targeted management decisions.

Lesson 2 • Model Evaluation and Selection

Teaches cross-validation, overfitting detection, and model comparison metrics. Ensures students select the most appropriate model for each business context.

Lesson 3 • Regression Analysis for Prediction

Covers simple and multiple linear regression, model assumptions, and interpretation of outputs. Applies regression to cost estimation and revenue forecasting scenarios.

Lesson 1 • Cost Classification and Behavior

Distinguishes fixed, variable, semi-variable, and step costs and explains their behavior across output levels. Establishes cost vocabulary essential for all subsequent accounting topics.

Lesson 2 • Cost-Volume-Profit Analysis

Applies CVP relationships to calculate break-even points, margin of safety, and profit targets. Connects cost behavior to pricing and volume decisions.

Lesson 3 • Performance Measurement Frameworks

Introduces responsibility accounting, divisional performance metrics, and the balanced scorecard. Aligns financial and non-financial measures to strategic objectives.

Lesson 4 • Budgeting and Variance Analysis

Covers master budget construction, flexible budgeting, and variance calculation for materials, labor, and overhead. Links budget deviations to corrective management actions.

Lesson 1 • Analytical Budgeting and Forecasting

Replaces static budget assumptions with data-driven forecasts using time-series and regression models. Produces rolling forecasts that adapt to changing business conditions.

Lesson 2 • Working Capital and Cash Flow Analytics

Uses analytical tools to monitor receivables, payables, and inventory cycles. Connects operational efficiency metrics to cash flow forecasting.

Lesson 3 • Profitability and Segment Analysis

Applies contribution analysis and customer profitability techniques using transactional data. Identifies high-value and loss-making segments for strategic resource allocation.

Lesson 4 • Integrated Management Reporting

Designs management reports that combine financial results with operational and analytical insights. Applies storytelling principles from Chapter 4 to accounting report design.

Lesson 1 • Capstone Integration Project

Synthesizes all course competencies in a comprehensive case study requiring systems analysis, data analytics, and management accounting outputs. Develops professional-grade deliverables for portfolio use.

Lesson 2 • Pricing Strategy and Decision Analysis

Evaluates pricing approaches including cost-plus, target costing, and value-based pricing using analytical data. Applies decision trees and expected value to pricing under uncertainty.

Lesson 3 • Capital Investment Appraisal

Applies net present value, internal rate of return, and payback methods to evaluate long-term investments. Incorporates risk analysis and sensitivity testing into investment decisions.

Lesson 4 • Strategic Performance and Value Creation

Connects management accounting and analytics outputs to long-term value creation and competitive strategy. Evaluates organizational performance using economic value added and strategic scorecards.