CONVERTING SIMULATION DATA TO COMPARATIVE INCOME STATEMENTS

Transcription

1 CONVERTING SIMULATION DATA TO COMPARATIVE INCOME STATEMENTS L. Leslie Gardner Mary E. Grant Laurie J. Rolston

2 If a manufacturing system was a money amplifier, an accountant would see it like this: 2

3 If a manufacturing system was a money amplifier, an engineer would see it like this: 3

4 Models Built by Models Built by Accountants Engineers algebraic relationships time and spatial relationships cost, revenues throughput and queue lengths carrying costs shop floor congestion fiscal periods system state changes opportunity costs late orders spreadsheet simulation 4

5 HOW CAN WE BRIDGE THIS GAP? WHAT CAN SIMULATION CONTRIBUTE TO FINANCIAL ANALYSIS? (FOCUS ON CAPITAL INVESTMENT) 5

6 Outline Justifying a Capital Investment Measures of Investment Value Simulation-based Information Limitations Role of Activity-based Costing Example The Model Conversion of Data Conclusions 6

7 7

8 Justifying a capital investment ROI = IRR = return on internal investment rate of return EMV = expected NPV = monetary net present value value 8

9 Comparative Income Statements Before After Revenue $1,000,000 $1,000,000 Cost of Goods 600, ,000 Marginal Income 400, ,000 Depreciation 10,000 20,000 Other Fixed Costs 300, , , ,000 Net Income 90,000 95,000 Taxes(.50) 45,000 47,500 Income after Tax 45,000 47,500 Add Back Depreciation 10,000 20,000 Cash Flow 55,000 67,500 9

10 Simulation-based Information for Capital Investment Analysis Throughput constrains revenue Processing time, setup time, number of setups, volume affect variable costs Thresholds of cost parameters affect fixed costs such as warehouse space Shop floor congestion affects carrying cost which is reflected as interest expense in cost of goods 10

11 Examples of Variable Manufacturing Costs Classification Variable costs Measured attribute Prime costs Direct materials Volume Direct labor Processing time Variable Indirect materials Volume overhead Lubricants Processing time Tooling Processing time Supplies Volume Utilities Processing time Setup Setup time, number of setups Indirect labor Volume 11

12 Limitations of Simulation-based Information Costs generated are relative costs Information limited by detail level and the scope of the model Benefits of Simulation-based Information Modeling flexibility can give wide range of detail levels Captures dynamic nature of manufacturing system 12

13 Concepts: Activity-based Costing and Simulation Activities consume resources Products consume specific activities Principles: Trace costs directly when possible Allocate costs based on occurrence of appropriate cost driver Application to simulation modeling: Identification of cost drivers guides modeling efforts and forms a basis for cost allocation in 13

14 conversion of simulation data to income statements 14

15 Define problem Identify Simulation Modeling with Costs performance measures cost drivers Construct model Perform experiments Convert output to income statements 15

16 An Example: Facility and Equipment 4 part types 2 products bottleneck at finishing investigate profitability of purchase of fifth finishing machine 16

17 Performance Measures Revenue Variable costs - Raw materials - Direct labor - Indirect materials - Lubricants - Tooling - Supplies - Utilities - Setup cost - Indirect labor Cost Drivers Processing time for each machine Number of setups for each machine Product volume 17

18 Construct Model Adequate level of detail Cost collection - Post process conversion - Accumulation Initial conditions Length of simulation window Validation and verification 18

19 Converting Simulation Data to Comparative Income Statements Calculate unit variable costs from current financial data and performance measures or from specifications Infer costs from unit variable costs, performance measures and cost drivers Construct comparative income statements (conversion done in an electronic spreadsheet) 19

20 Comparative Income Statement Basecase Fifth Machine Revenue $2,363,400 $2,363,400 Cost of Goods 1,398,304 1,262,027 Marginal Income 965,096 1,101,373 Depreciation 210, ,000 Other Fixed Costs 595, , , ,475 Net Income 159, ,898 Taxes(.50) 79, ,949 Income After Tax 79, ,949 Add Back 210, ,000 Depreciation Cash Flow 289, ,949 20

21 Conclusions Translation of engineering data into financial terms Common models for engineers and accountants Use same models in business schools and engineering schools 21