CONVERTING SIMULATION DATA
TO COMPARATIVE INCOME STATEMENTS
L. Leslie Gardner
Mary E. Grant
Laurie J. Rolston
If a manufacturing system was a money amplifier, an
accountant would see it like this:
2
If a manufacturing system was a money amplifier, an
engineer would see it like this:
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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
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HOW CAN WE BRIDGE THIS GAP?
WHAT CAN SIMULATION CONTRIBUTE TO
FINANCIAL ANALYSIS?
(FOCUS ON CAPITAL INVESTMENT)
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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
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Justifying a capital investment
ROI =
return on
investment
EMV =
expected
monetary
value
IRR =
internal
rate of
return
NPV =
net present
value
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Comparative Income Statements
Revenue
Cost of Goods
Marginal Income
Depreciation
10,000
Other Fixed Costs
300,000
Net Income
Taxes(.50)
Income after Tax
Add Back Depreciation
Cash Flow
Before
$1,000,000
600,000
400,000
20,000
310,000 300,000
90,000
45,000
45,000
10,000
55,000
After
$1,000,000
585,000
415,000
320,000
95,000
47,500
47,500
20,000
67,500
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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
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Examples of Variable Manufacturing Costs
Classification
Prime costs
Variable
overhead
Variable costs
Measured
attribute
Direct materials Volume
Direct labor
Processing time
Indirect materials Volume
Lubricants
Processing time
Tooling
Processing time
Supplies
Volume
Utilities
Processing time
Setup
Setup time,
number of setups
Indirect labor
Volume
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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
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Activity-based Costing and Simulation
Concepts:
•
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
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conversion of simulation data to income
statements
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Simulation Modeling with Costs
Define problem
Identify
•
performance measures
•
cost drivers
Construct model
Perform experiments
Convert output to income statements
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An Example: Facility and Equipment
4 part types
2 products
bottleneck at
finishing
investigate
profitability of
purchase of
fifth finishing
machine
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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
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Construct Model
•
•
•
•
•
Adequate level of detail
Cost collection
- Post process conversion
- Accumulation
Initial conditions
Length of simulation window
Validation and verification
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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)
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Comparative Income Statement
Revenue
Cost of Goods
Marginal Income
Depreciation
210,000
Other Fixed
595,475
Costs
Net Income
Taxes(.50)
Income After Tax
Add Back
Depreciation
Cash Flow
Basecase
$2,363,400
1,398,304
965,096
Fifth Machine
$2,363,400
1,262,027
1,101,373
220,000
805,475 595,475
815,475
159,621
79,811
79,810
210,000
285,898
142,949
142,949
220,000
289,810
362,949
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Conclusions
•
Translation of engineering data into financial terms
•
Common models for engineers and accountants
•
Use same models in business schools and
engineering schools
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