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-