Description
TABLE OF CONTENTS
1 Cost Accounting Has Purpose 1-1
1.1 Companies Know Their Purpose: Do You Know Yours? 1-2
Purpose Is Meaningful 1-2
Company Strategy: Turning Purpose into Action 1-2
Your Own Strategy 1-4
Measures, Targets, and Results on the Balanced Scorecard 1-5
1.2 The Purpose of Cost Accounting 1-9
Data Analytics in Action: Data Analytics Isn’t New 1-9
Big Picture Thinking and Decision-Making 1-10
Using Data Analytics to Problem-Solve 1-14
Data Analytics in Action: Keeping Score 1-14
The Value Chain 1-15
1.3 What Guides Our Purpose? 1-17
The Importance of Ethics in Business 1-17
Governing Bodies Within Accounting 1-18
Appendix 1A: Why You Should Learn to Learn 1-23
Your Role as a Lifelong Learner 1-23
Fixed versus Growth Mindset 1-23
Purposeful Pedagogy 1-24
How This Text Can Help You Learn 1-25
Data Analytics Activities 1-35
2 Refresher on Cost Terms 2-1
2.1 Overview of Costs 2-2
Using Financial Statements to Interpret Revenues and Expenses 2-2
Costs versus Expenses: Let’s Get Specific 2-3
Opportunity Costs and Sunk Costs 2-4
2.2 Costs for Service Providers, Merchandisers, and Manufacturers 2-7
Service Providers 2-7
Data Analytics in Action: Cutting Corners 2-8
Merchandisers 2-8
Manufacturers 2-10
2.3 Defining and Assigning Costs 2-11
Product and Period Costs 2-12
Manufacturing and Nonmanufacturing Costs 2-12
The Cost Object, Direct Costs, and Indirect Costs 2-14
Prime Costs and Conversion Costs 2-15
2.4 Variable and Fixed Costs and the Relevant Range 2-16
Variable Costs 2-16
Managing Variable Costs 2-17
Data Analytics in Action: It’s a Snap! 2-17
Fixed Costs 2-17
Managing Fixed Costs 2-18
Relevant Range and Costs of Capacity 2-19
Fixed Costs on a Per-Unit Basis: Be Careful 2-20
2.5 Tracing Product Costs from the Balance Sheet to the Income Statement 2-21
Inventoriable Costs 2-22
Raw Materials Inventory on the Balance Sheet 2-22
Work-in-Process Inventory on the Balance Sheet 2-23
Finished Goods Inventory on the Balance Sheet 2-24
Cost of Goods Manufactured 2-25
Cost of Goods Sold 2-26
2.6 Comparing Gross Margin and Contribution Margin Income Statements 2-28
Gross Margin versus Contribution Margin 2-28
Full Costs 2-30
Data Analytics Activities 2-49
3 Cost Behavior and Cost Estimation 3-1
3.1 The Basics of Cost Behavior 3-2
Selecting Cost Drivers 3-2
Data Analytics in Action: Counting Cars 3-2
The Relevant Range, and Costs Within It 3-3
3.2 Estimating Costs Is Crucial: Here’s How 3-9
Account Analysis Method 3-9
High-Low Method 3-10
Data Analytics in Action: Scatter to Avoid Slacking? 3-12
Excel Tutorial: The Scatter Plot 3-12
3.3 Sophisticated Cost Estimation with Regression 3-15
Overview of the Regression Method 3-15
Excel Tutorial: Regression Analysis 3-17
Evaluating Regression Output 3-21
Assumptions of Regression 3-23
Multiple Regression 3-25
3.4 When Costs Are Nonlinear: The Learning Curve 3-29
Applying the Learning Curve 3-30
Learning Curve Impacts on Costs and Prices 3-31
Data Analytics Activities 3-54
4 Cost-Volume-Profit Analysis 4-1
4.1 Contribution Margin and the Break-Even Sales Point 4-2
Data Analytics in Action: Consuming Coffee and Trends 4-2
Contribution Margin 4-2
Numbers of Sales in Units to Break Even 4-4
Sales in Dollars to Break Even 4-5
What Happens After Break-Even Analysis? 4-6
4.2 Cost-Volume-Profit (CVP) Analysis 4-8
It’s Graphic: Understanding CVP Relationships 4-9
The Relevant Range: Quite Relevant 4-10
Margin of Safety 4-10
4.3 Break-Even with Target Profit and Taxes 4-12
Modifying the Break-Even to Include Target Profit 4-12
Modifying the Break-Even to Include Target Profit After[1]Tax 4-13
4.4 Break-Even with Multiple Products 4-14
Data Analytics in Action: Big Data for Bigger Sales 4-15
4.5 Operating Leverage and Sensitivity Analysis 4-17
Sensitivity Analysis Shows the Effects of Operating Leverage 4-17
Using the Degree of Operating Leverage Multiplier 4-18
4.6 CVP Analysis for Service and Nonprofit Organizations 4-21
Data Analytics in Action: More Service, Fewer Costs 4-21
Data Analytics Activities 4-35
5 Relevant Costs for the Decision[1]Maker 5-1
5.1 Decision-Making Made Easier 5-2
Data Analytics in Action: Don’t Succumb to Analysis Paralysis 5-2
5.2 What Are Relevant Costs and Relevant Information? 5-4
How Relevant Information Supports Decision-Making 5-4
Sunk Costs 5-5
The Total Cost Approach versus the Relevant Cost Approach 5-6
5.3 Management Decisions Requiring Use of Relevant Costs 5-7
Insource versus Outsource 5-7
Keep versus Drop 5-11
Excel Tutorial: Goal Seek 5-12
Product-Mix Decisions 5-14
Data Analytics in Action: Tasty, Fast, or Both? 5-15
Excel Tutorial: Solver 5-17
Special Orders 5-20
5.4 Decision-Making and Opportunity Costs 5-22
5.5 Fixed Costs and Decision-Making 5-25
Direct Fixed Costs 5-25
Common Fixed Costs 5-26
Allocated Fixed Costs 5-27
Data Analytics Activities 5-44
6 Mastering the Master Budget 6-1
6.1 Why Budget? 6-2
Budgeting and Behavior Modification 6-2
Data Analytics in Action: Budgeting Made Fun? 6-2
Types of Budgets 6-3
Budgeting and Ethical Considerations 6-5
6.2 The Master Budget 6-7
Revisiting the Strategic Planning Process 6-7
Organizational Structure and Responsibility Centers 6-8
The Master Budget Inputs and Outputs 6-10
Follow-Up and Feedback 6-11
6.3 The Operating Budget and the Budgeted Income Statement 6-12
Sales Forecast: It All Starts Here 6-13
Production Budget 6-14
Direct Materials Purchases Budget 6-16
Direct Labor Budget 6-17
Manufacturing Overhead Budget 6-18
Cost of Goods Sold and Cost of Goods Manufactured Budgets 6-20
Selling, General, and Administrative Expenses Budget 6-21
Non-Operating Expenses Budget 6-23
6.4 The Financial Budget and the Budgeted Balance Sheet 6-24
Budgeted Inventory Balance 6-25
Cash Receipts, Cash Collections, and the Budgeted Accounts Receivable Balance 6-26
Data Analytics in Action: Banks Expedite Loan Collections 6-27
Cash Disbursements and Budgeted Accounts Payable Balance 6-29
Budgeted Cash Balance 6-31
6.5 Budgeting in Retail and Service Organizations 6-35
Budgeting for Retailers 6-35
Budgeting for Service Providers and Nonprofit Organizations 6-36
Data Analytics Activities 6-57
7 Capital Budgeting Choices and Decisions 7-1
7.1 Capital Budgeting: The Point and the Context 7-2
Data Analytics in Action: Using Data to Scout a Location 7-2
The Circle of Life of Businesses 7-2
Return on Investment (ROI) 7-4
7.2 Elements of Capital Budgeting Decisions 7-6
Timeliness 7-6
Time Value of Money 7-7
Cash Flows: Lump Sums and Annuities 7-9
Discount Rate 7-13
Tax Rate 7-14
Depreciation Tax Shield: Yes You Can! 7-15
Data Analytics in Action: Data Informs Decision[1]Making 7-15
7.3 Tools to Evaluate Capital Budgeting Choices 7-17
Net Present Value (NPV): A Powerful Machine 7-17
Internal Rate of Return (IRR) 7-20
Payback Period 7-22
Accounting Rate of Return (ARR) 7-24
Profitability Index 7-25
7.4 Sensitivity Analysis 7-27
7.5 Making the Decision 7-29
7.6 The Follow-Up 7-33
Post-Investment Audit 7-33
Performance Evaluation 7-33
Data Analytics Activities 7-50
Time Value of Money Tables 7-52
8 Job Costing Visualized 8-1
8.1 Job Costing: An Overview 8-2
Defining Jobs and Job Costing 8-2
Revisiting Product Costs 8-2
Actual versus Normal Costing 8-4
Data Analytics in Action: Is It Hot in Here? 8-4
How Job Costing Is Organized 8-6
8.2 Actual and Applied Manufacturing Overhead 8-10
Accounting for Actual and Applied Manufacturing Overhead 8-10
Calculating Applied Manufacturing Overhead 8-12
Budgeting Manufacturing Overhead for a Specific Job 8-13
8.3 Putting It Together: Costing Jobs and Units 8-15
Cost Flows, Accounts, and Journal Entries 8-16
Year-End Adjustments 8-22
Income Statement Impacts of Job Costing 8-23
8.4 Job Costing and Decision-Making 8-26
Job Costing’s Impacts on Decision 8-26
Data Analytics in Action: Information or Invasion? 8-26
Ethical Considerations Related to Job Costing 8-27
8.5 Job Costing in Service Organizations 8-30
Data Analytics Activities 8-51
9 Activity-Based Costing 9-1
9.1 Traditional Job Costing and ABC Compared 9-1
Drawbacks of Traditional Costing 9-2
The Advantage of Activity-Based Costing 9-3
A Better Cost with Activity-Based Costing 9-4
Data Analytics in Action: A Sweet Outcome 9-5
9.2 The Cost Hierarchy, Activities, and Cost Drivers 9-7
Identifying Activities as Cost Pools 9-7
Cost Drivers 9-9
The Cost Hierarchy 9-10
9.3 Using Activity-Based Costing for Product Costing 9-13
Step 1: Identify Direct Costs 9-14
Step 2: Identify Activities and Cost Drivers 9-15
Step 3: Calculate Cost Driver Rates and Assign MOH 9-15
Step 4: Record MOH Costs 9-16
9.4 Decision-Making Outcomes, Including Time-Driven Activity-Based Costing (TDABC) 9-19
Impacts of Activity-Based Costing on Product and Service Costs 9-19
Who Should Use Activity-Based Costing? 9-19
Broader Outcomes of Using Activity-Based Costing 9-21
Time-Driven Activity-Based Costing: A Time-Saving Alternative 9-22
Data Analytics in Action: An Impressive By[1]Product 9-24
Data Analytics Activities 9-43
10 Variance Analysis and Standard Costing 10-1
10.1 A Variety of Purposes for Budgets and Variance Analysis 10-2
Motivate and Benchmark 10-2
Plan and Control 10-3
Evaluate Performance and Troubleshoot 10-4
Data Analytics in Action: Process Improvements at Nike 10-4
10.2 Master Budget and Flexible Budget Variances 10-6
Limitations of the Master Budget 10-6
The Flexible Budget 10-7
10.3 Standard Costing 10-11
The Purpose of Standard Costing 10-11
Setting and Updating Standards 10-13
Data Analytics in Action: A New Way of Checking Out the Competition 10-13
10.4 Direct Materials and Direct Labor Variances 10-15
Overview of Production Variances 10-16
Direct Materials Variances 10-17
Direct Labor Variances 10-22
10.5 Variable-MOH and Fixed-MOH with Journal Entries 10-24
Variable-MOH: Price and Efficiency Variances 10-24
Data Analytics in Action: Calculate All the Variances 10-24
Fixed-MOH: Price and Volume Variances 10-26
Journal Entries to Close Variances 10-28
10.6 Sales Variances 10-31
Master Budget Sales Variances: Sales Price Variance and Simplified Sales Activity Variance 10-31
Comprehensive Sales Activity Variance: Sales Mix Variance and Sales Quantity Variance 10-33
Sales Quantity Variance: Market Size Variance and Market Share 10-38
11 Process Costing 11-1
11.1 Process Costing: An Overview 11-2
Data Analytics in Action: Mining Data for Mining Real 11-3
Job Costing versus Process Costing 11-3
The Importance of Determining WIP Inventory Correctly 11-4
The Steps of Process Costing 11-5
11.2 Step 1: Verify Physical Units in the Period and Identify Degree of Completion 11-7
No Beginning or Ending WIP Inventory 11-7
With Only Ending WIP Inventory 11-8
With Beginning and Ending WIP Inventory 11-8
11.3 Step 2: Determine Status of Physical Units and Convert to Equivalent Units 11-13
Using the FIFO Method to Determine Status of Physical Units 11-14
Using the Weighted-Average Method to Determine Status of Physical Units 11-15
11.4 Steps 3 and 4: Account for Costs and Calculate Cost per Equivalent Unit 11-17
Using the FIFO Method to Calculate Cost per Equivalent Unit 11-18
Using the Weighted-Average Method to Calculate Cost per Equivalent Unit 11-18
11.5 Step 5: Assign Costs to WIP Inventory and FG Inventory with Journal Entries 11-21
Assigning Costs Using the FIFO Method with Corresponding Journal Entries 11-22
Assigning Costs Using the Weighted-Average Method with Corresponding Journal Entries 11-24
Applications of Determining Product Costs 11-25
11.6 Costs Transferred-In from Another Department 11-26
Transferred-In Costs Using the FIFO Method 11-26
Transferred-In Costs Using the Weighted-Average Method 11-29
11.7 Operation Costing 11-31
Data Analytics Activities 11-51
12 Absorption versus Variable Costing 12-1
12.1 Absorption Costing: An Overview 12-2
The Purpose of Absorption Costing and How It Works 12-3
Management Decision-Making and Absorption Costing 12-6
Data Analytics in Action: This Machine Is Learning! 12-7
Balance Sheet and Income Statement Impacts of Absorption Costing 12-8
12.2 Variable Costing: An Overview 12-10
The Purpose of Variable Costing and How It Works 12-10
Balance Sheet and Income Statement Impacts of Variable Costing 12-11
12.3 Side-by-Side: Comparing Absorption Costing and Variable Costing 12-13
The Two Methods Compared: Inventory Costs and Balance Sheet Impacts 12-13
The Two Methods Compared: COGS, Operating Income, and Income Statement Impacts 12-14
12.4 Determining Denominator Volumes for Fixed[1]MOH 12-17
Managing Capacity 12-18
Denominator Volume Choices 12-18
Further Outcomes of Denominator Decisions 12-20
13 Data Analytics 13-1
13.1 Big Data? Data Analytics? Challenges and Opportunities 13-2
Overview of Data 13-2
Big Data and Data Analytics in Cost Accounting 13-3
Challenges and Opportunities 13-3
Data Analytics in Action: Meeting the Challenges 13-4
13.2 Sourcing and Storing Data 13-6
The Role of Data Analytics in Decision-Making 13-6
Data Sources and Data Storage 13-7
The Cost of Data and Its Ethical Considerations 13-10
Data Analytics in Action: When Data Is Especially Costly 13-11
13.3 Categories of Data Analytics Techniques 13-13
Overview of Data Analytics Categories 13-14
Descriptive Analytics 13-15
Diagnostic Analytics 13-18
Predictive Analytics 13-19
Prescriptive Analytics 13-20
Data Analytics in Action: Price Check on Aisle 3 13-20
13.4 Your Role in Solving Business Problems with Data Analytics 13-23
Data Analytics Outcomes in Cost Accounting 13-23
Being Career-Ready 13-25
14 Support Department Costing 14-1
14.1 Support Department Costing: An Overview 14-1
Types of Support Departments and Their Costs 14-2
Allocating Support Department Costs 14-4
Data Analytics in Action: Keep or Drop? 14-5
Cost Allocation Bases for Support Departments 14-6
14.2 Methods of Allocating Support Department Costs 14-8
The Direct Method Illustrated 14-8
Step Method Illustrated 14-10
Reciprocal Method Illustrated 14-12
Excel Tutorial: The Reciprocal Method 14-13
Comparing the Three Methods 14-16
Data Analytics in Action: This Call May Be Analyzed 14-16
14.3 Allocating Common Costs and Bundled Revenues 14-20
Stand-Alone Cost Allocation Method 14-20
Incremental Cost Allocation Method 14-21
Allocating Revenue from Sales of Bundled Products/Services 14-22
15 Joint Costs and Decision[1]Making 15-1
15.1 Joint Costs: Description and Illustration 15-2
15.2 Methods of Allocating Joint Costs 15-4
Sales Value at Split-Off Method 15-4
Net Realizable Value (NRV) Method 15-5
Physical Quantities Method 15-6
Choosing an Allocation Method 15-8
15.3 Joint Costs and Decision-Making: Should We Sell or Process Further? 15-10
Relevance of Joint Costs to Sell-or-Process-Further Decisions 15-10
Sell-or-Process-Further Decision Factors 15-10
Data Analytics in Action: More Fresh Options 15-11
Decision-Making and Performance Evaluation 15-12
15.4 A Decision: How Should We Account for By-Product and Scrap? 15-13
By-Products Revisited 15-13
Data Analytics in Action: Analysis Reduces Waste 15-14
The Production Method 15-14
The Sales Method: By-Products and Scrap Recognized at Time of Sale 15-17
Production Method versus Sales Method 15-19
16 The Art and Science of Pricing to Optimize Revenue 16-1
16.1 Pricing: Art + Science + Psychology 16-2
Truths About Pricing 16-2
Consider the Context: Customers, Costs, and Competitors 16-3
16.2 Special-Order Pricing: Be Opportunistic 16-5
Lowest Acceptable Special-Order Price 16-6
Relationship to Relevant Costs for the Decision[1]Maker 16-7
16.3 Cost-Plus Pricing: If You Can Sell the Plus, Charge It 16-9
Overview of the Cost-Plus Method 16-10
The Calculation: A Starting Point 16-10
Data Analytics in Action: Using Data to Set Prices 16-10
Comparing Special-Order Pricing to Cost-Plus Pricing 16-13
16.4 Target Costing for Target Pricing—Backward but Brilliant 16-14
Steps to Implement Target Costing for Target Pricing 16-15
The Value in Value Engineering 16-16
Data Analytics in Action: Ensuring the Value of Business Activities 16-16
16.5 Consumers and Pricing Practices 16-17
Consumer Perceptions and Pricing 16-17
Other Pricing Practices: Fair or Illegal? 16-18
Data Analytics in Action: No Free Parking 16-19
Data Analytics Activities 16-33
17 Management Control Systems and Transfer Pricing 17-1
17.1 The Need for an Effective Management Control System 17-2
Centralized versus Decentralized Organizations 17-2
Goal Congruence 17-4
Components of a Management Control System 17-5
17.2 How Responsibility Centers Work 17-6
Characteristics of Responsibility Centers 17-6
Cost Centers 17-8
Revenue Centers 17-9
Profit Centers 17-10
Investment Centers 17-10
Data Analytics in Action: Major League Baseball Invests in Data 17-11
17.3 How to Measure Performance of Investment Centers 17-13
Return on Investment and Its Components 17-13
Residual Income (RI) 17-16
Economic Value Added (EVA®) 17-16
17.4 Transfer Pricing: An Overview 17-18
The Genesis of Transfer Pricing 17-19
Determining the Optimal Transfer Price Range 17-21
How Companies Set Transfer Prices 17-23
Management and Transfer Pricing 17-27
Transfer Pricing in Multinational Companies 17-28
18 Business Strategy, Performance Measurement, and the Balanced Scorecard 18-1
18.1 An Overview of Business Strategy 18-1
The Strategic Planning Process 18-2
A Closer Look at Business Strategy 18-3
18.2 Performance Measurement Guides Performance 18-8
Congruent Outcomes: Linking Business Strategy to Employees’ Objectives 18-8
The Performance Measurement Process 18-9
Traits of Financial Performance Measures 18-12
Traits of Nonfinancial Performance Measures 18-13
18.3 Using the Balanced Scorecard to Assess Company Performance 18-15
Balancing the Four Perspectives 18-16
Linking Business Strategy to the Balanced Scorecard 18-17
Data Analytics in Action: New Measures and Targets 18-18
Evaluating Success 18-20
Company Index I-1
Subject Index I-0
Key Formulas Review K-0
