Description
It also includes merits and demerits of simulation.
BUSINESS MODELLING & SIMULATION
• Business models are formal representations of a company’s operations and processes in quantifiable terms and help management in planning to: • 1. Analyze inter-relationships between investment and alternatives. • 2. Financial future of the project under various assumptions. • 3. Decide among various alternatives. • 4. Monitor performance vis-à-vis pre-determined targets.
Types of business models
• A. Optimization models- these seek to maximize an objective function and conceptually more elegant. • B. Simulation models – these seek to answer “what if” questions and are more popular and are in use.
Modeling – types and stages
• • • • • • • Types of modeling: 1. Optimization model 2. Simulation model Stages in modeling: 1.Model development 2. Improving the process of modeling 3. Conditions for successful use of models.
Optimization model
• If a company confronts with how much to invest and how much to borrow, the decision can be made with the objective of maximizing Net Present Value (NPV) of the firm as: Maximize NPV • = 0.35Y + [-X + (0.10/0.112)X] • = 0.35Y + [-X + 0.833X] • =0.35 Y + [-0.167 X]
Subject to the constraints
• X _ 80 (available level of investments are Rs.80 mn.) • Y _ 0.6X (new debt limited to 60% of investment) • X _ 20 + Y (firm has cash of 20 mn available) • X, Y > 0 (X, Y are non-negative)
Abbreviations used
• • • • • Y = level of borrowings X = level of investments 0.35 or 35% is the tax rate 0.10 or 10% is the return on investment 0.12 or 12% is the cost of equity capital
Further assumptions
• Here, V = Vo +tD, where • V= Total value of the firm • Vo = Market value of the firm’s existing assets (financed by equity & internals) • D = Debt outstanding • t = tax rate (presumed to be 35%) • This is a linear programming model with two decision variables. On solving, we get values of X and Y.
Simulation Model
• Business simulation model involves translating a company’s processes and also accounting into a set of equations, which can be run on a computer. The equations in the model can be classified into 3 broad types: • A. Economic or behavioral relationships • (such as projected revenues, COGS, fixed assets, current assets, spontaneous liabilities)
Simulation Models
• B. Accounting identities, such as projected EBIT, Interest, PAT, retained earnings, equity, debt, change in debt, external funds requirements, depreciation or amortization. • C. Management policy representation, such as dividend and external financing policies.
Simulation Models
• The model consists of (say 16) simultaneous equations, in (say 16) unknown variables which may be solved to get the values of both variables and unknown constants through simulation models.
Model development - steps
• • • • • • • 1. Feasibility study 2. Construction of Model logic 3. Programming and debugging 4. Model testing and validation 5. Documentation 6. Implementation 7. Updating and extension.
Simulation Model-shortcomings
• Model will be based on certain assumptions. The sequence can change and the process is iterative. • 1. It follows bottoms up approach, which produces undue emphasis on lower level inputs and neglect important concerns. • 2. Management policies are generally represented in a simplistic and inadequate manner. 3. Inefficient screening of plans.
Improving modeling
• 1. Follow top-down approach, which gives importance to key decision policies. • 2. Avoid cluttering the model with excessive details. A simple model with a sharp focus on key financials decisions has greater appeal to management. • 3. Use of optimizing model like Linear Programming Problem (LPP) develops key decisions as it output.
Improving Models
• 4. Explore through a series of computer runs (in simulation) the implications of various management policy requirements on the optimal set of decisions – financial or otherwise. • 5. Inject greater relevant theory in financial or accounting dominated models to reflect relevant issues.
Conditions for successful use
• 1. Operations of the business must be understood well. • 2. Ensure relevant data of good quality is available. • 3. The firm has a well developed budgetary and planning system. • 4. The modeling project must be enthusiastically supported by the top management.
Conditions of successful use
• 5. The potential users of the model must be involved in model development right from the beginning. • 6. The modeling project should focus on problems of serious concern. • 7. Modeling project should be kept as simple as possible in the initial stages. 8. There must be abundant allowance for judgmental inputs.
ALCAR Model
• Problem on determination of new strategy: • The income statement of Y Limited for year 0, which has just ended is as follows: • Sales Rs.1000 mn • Gross Margin @ 25 % Rs.250 mn • Selling,Genl.&Admn.exps.@10% -100 mn • Profit Before Tax (PBT) – Rs.150 mn • Tax Rs.60 mn, PAT – Rs.90 mn.
The problem of V Ltd.
• V Ltd. is debating whether it should maintain the status quo or adopt a new strategy? • For Answer – refer to Excel File.
Major phases in simulation
• 1. Define problem:
– Objectives of the system studied – Variables those may affect achievement of those objectives 2. Construct simulation model: Specification of variables and parameters Specification decision rules Specification of probability distributions Specification of incrementing procedure
Major phases in Simulation
• 3. Specify values of variables and parameters determination of starting conditions determination of run length 4. Run of the simulation 5. Evaluate results : determine statistical tests compare with other information 6. Validation & plan new experiment (if necessary)
Meaning of Simulation
May have different meanings depending in its application in business. It generally refers to using a computer to perform experiments on a model of a realy system.
Examples of Simulation
• • • • Video games Virtual reality animation Airplane flight simulation Job shops which are characterized by complex queuing problems • Certain types of inventory • Layout • Maintenance problems
Examples of Simulation
• • • • To determine production schedules To determine inventory levels Maintenance schedules To plan capacity, and to plan resource requirements and processes • In services, to analyze waiting lines, to schedule operations, hospital overcrowding
Usefulness of Simulation
• To aid in design of real system before it is operational. • To see how the system may react to changes in its operating rules. • To evaluate system’s response to changes in its structure. • Particularly appropriate to situations where the size or the complexity of the problem makes the use of optimizing technique difficult or, if not impossible.
Usefulness of Simulation
• Can also be used in conjunction with traditional statistical techniques • And also management science techniques • Useful in training managers and workers in how the real system operates • Useful in demonstrating the effects of changes in system variables, in real time control. • Useful in developing new ideas about how to run the business.
Simulation and computerization
• 1.Computer language selection or software selection • 2.Flowcharting • 3.Coding • 4.Data generation • 5.Output reports • 6.Validation
Simulation programs
• • • • • • • • General Purpose: SLAM II SIMSCRIPT II.5 SIMAN GPSS/H GPSS/PC PC-MODEL RESQ
Simulation Programs
• • • • Special Purpose: MAP/1 SIMFACTORY These allow for specifying number of work centers, their description, arrival rate, processing time, batch size, quantities of work-in-process, available resources – labor, sequences and so on.
•
Features in simulation software
• Interactive usability • User-friendly and easy to understand • Allow modules be built and connected and not patchwork • Allow users to write and incorporate their own routines • Building blocks that contain built in commands (statistical analysis or decision rules for where to go next)
Features of simulation software
• Macro capability to develop machining cells • Material flow capability (material handling by trucks, conveyors, cranes, elevators, hydraulic methods, etc.) • Output standard statistics, such as cycle times, utilizations, wait times.
Merits of simulation
• Better understanding of real system • Compression of time- years of experience can be compressed into minutes by computer. • Does not disturb ongoing system. • More general and can be used where mathematical models cannot be used. • Can be used as a game for training purpose.
Merits of simulation
• Facilitates more realistic replication of real system. • Can be used to analyze transient conditions, where mathematical models do not help. • Many standard simulation software packages are available commercially. • Simulation answers “what if” questions.
Demerits of simulation
• No guarantee that model will provide good or correct answer or solution • No way to prove that simulation’s model’s performance is perfect and completely reliable. • Complicated systems can be costly and take a very long time. • Less accurate than mathematical models
Demerits of simulation
• Still lacks a standardized approach. Models built by different individuals may differ widely and significantly. • Significant amount of computer time may be needed to run complex models. • Mathematical analysis, where appropriate to a specific problem, is usually faster, accurate and less expensive. It is provable also, whereas simulation model may not be provable.
Conclusion
• Anything that can be done mathematically can be done with simulation. However, simulation is not always the best choice. Simulation has nothing fixed. There are no boundaries or limits. Expanding computer power and memory have pushed out the limits of what can be simulated. Continuous development of software have made creating simulation models much easier.
Moral of the story
• Simulation is something very useful in life as well as business. You can take the help of computer software, if necessary or visualize the model yourself.
doc_472070085.ppt
It also includes merits and demerits of simulation.
BUSINESS MODELLING & SIMULATION
• Business models are formal representations of a company’s operations and processes in quantifiable terms and help management in planning to: • 1. Analyze inter-relationships between investment and alternatives. • 2. Financial future of the project under various assumptions. • 3. Decide among various alternatives. • 4. Monitor performance vis-à-vis pre-determined targets.
Types of business models
• A. Optimization models- these seek to maximize an objective function and conceptually more elegant. • B. Simulation models – these seek to answer “what if” questions and are more popular and are in use.
Modeling – types and stages
• • • • • • • Types of modeling: 1. Optimization model 2. Simulation model Stages in modeling: 1.Model development 2. Improving the process of modeling 3. Conditions for successful use of models.
Optimization model
• If a company confronts with how much to invest and how much to borrow, the decision can be made with the objective of maximizing Net Present Value (NPV) of the firm as: Maximize NPV • = 0.35Y + [-X + (0.10/0.112)X] • = 0.35Y + [-X + 0.833X] • =0.35 Y + [-0.167 X]
Subject to the constraints
• X _ 80 (available level of investments are Rs.80 mn.) • Y _ 0.6X (new debt limited to 60% of investment) • X _ 20 + Y (firm has cash of 20 mn available) • X, Y > 0 (X, Y are non-negative)
Abbreviations used
• • • • • Y = level of borrowings X = level of investments 0.35 or 35% is the tax rate 0.10 or 10% is the return on investment 0.12 or 12% is the cost of equity capital
Further assumptions
• Here, V = Vo +tD, where • V= Total value of the firm • Vo = Market value of the firm’s existing assets (financed by equity & internals) • D = Debt outstanding • t = tax rate (presumed to be 35%) • This is a linear programming model with two decision variables. On solving, we get values of X and Y.
Simulation Model
• Business simulation model involves translating a company’s processes and also accounting into a set of equations, which can be run on a computer. The equations in the model can be classified into 3 broad types: • A. Economic or behavioral relationships • (such as projected revenues, COGS, fixed assets, current assets, spontaneous liabilities)
Simulation Models
• B. Accounting identities, such as projected EBIT, Interest, PAT, retained earnings, equity, debt, change in debt, external funds requirements, depreciation or amortization. • C. Management policy representation, such as dividend and external financing policies.
Simulation Models
• The model consists of (say 16) simultaneous equations, in (say 16) unknown variables which may be solved to get the values of both variables and unknown constants through simulation models.
Model development - steps
• • • • • • • 1. Feasibility study 2. Construction of Model logic 3. Programming and debugging 4. Model testing and validation 5. Documentation 6. Implementation 7. Updating and extension.
Simulation Model-shortcomings
• Model will be based on certain assumptions. The sequence can change and the process is iterative. • 1. It follows bottoms up approach, which produces undue emphasis on lower level inputs and neglect important concerns. • 2. Management policies are generally represented in a simplistic and inadequate manner. 3. Inefficient screening of plans.
Improving modeling
• 1. Follow top-down approach, which gives importance to key decision policies. • 2. Avoid cluttering the model with excessive details. A simple model with a sharp focus on key financials decisions has greater appeal to management. • 3. Use of optimizing model like Linear Programming Problem (LPP) develops key decisions as it output.
Improving Models
• 4. Explore through a series of computer runs (in simulation) the implications of various management policy requirements on the optimal set of decisions – financial or otherwise. • 5. Inject greater relevant theory in financial or accounting dominated models to reflect relevant issues.
Conditions for successful use
• 1. Operations of the business must be understood well. • 2. Ensure relevant data of good quality is available. • 3. The firm has a well developed budgetary and planning system. • 4. The modeling project must be enthusiastically supported by the top management.
Conditions of successful use
• 5. The potential users of the model must be involved in model development right from the beginning. • 6. The modeling project should focus on problems of serious concern. • 7. Modeling project should be kept as simple as possible in the initial stages. 8. There must be abundant allowance for judgmental inputs.
ALCAR Model
• Problem on determination of new strategy: • The income statement of Y Limited for year 0, which has just ended is as follows: • Sales Rs.1000 mn • Gross Margin @ 25 % Rs.250 mn • Selling,Genl.&Admn.exps.@10% -100 mn • Profit Before Tax (PBT) – Rs.150 mn • Tax Rs.60 mn, PAT – Rs.90 mn.
The problem of V Ltd.
• V Ltd. is debating whether it should maintain the status quo or adopt a new strategy? • For Answer – refer to Excel File.
Major phases in simulation
• 1. Define problem:
– Objectives of the system studied – Variables those may affect achievement of those objectives 2. Construct simulation model: Specification of variables and parameters Specification decision rules Specification of probability distributions Specification of incrementing procedure
Major phases in Simulation
• 3. Specify values of variables and parameters determination of starting conditions determination of run length 4. Run of the simulation 5. Evaluate results : determine statistical tests compare with other information 6. Validation & plan new experiment (if necessary)
Meaning of Simulation
May have different meanings depending in its application in business. It generally refers to using a computer to perform experiments on a model of a realy system.
Examples of Simulation
• • • • Video games Virtual reality animation Airplane flight simulation Job shops which are characterized by complex queuing problems • Certain types of inventory • Layout • Maintenance problems
Examples of Simulation
• • • • To determine production schedules To determine inventory levels Maintenance schedules To plan capacity, and to plan resource requirements and processes • In services, to analyze waiting lines, to schedule operations, hospital overcrowding
Usefulness of Simulation
• To aid in design of real system before it is operational. • To see how the system may react to changes in its operating rules. • To evaluate system’s response to changes in its structure. • Particularly appropriate to situations where the size or the complexity of the problem makes the use of optimizing technique difficult or, if not impossible.
Usefulness of Simulation
• Can also be used in conjunction with traditional statistical techniques • And also management science techniques • Useful in training managers and workers in how the real system operates • Useful in demonstrating the effects of changes in system variables, in real time control. • Useful in developing new ideas about how to run the business.
Simulation and computerization
• 1.Computer language selection or software selection • 2.Flowcharting • 3.Coding • 4.Data generation • 5.Output reports • 6.Validation
Simulation programs
• • • • • • • • General Purpose: SLAM II SIMSCRIPT II.5 SIMAN GPSS/H GPSS/PC PC-MODEL RESQ
Simulation Programs
• • • • Special Purpose: MAP/1 SIMFACTORY These allow for specifying number of work centers, their description, arrival rate, processing time, batch size, quantities of work-in-process, available resources – labor, sequences and so on.
•
Features in simulation software
• Interactive usability • User-friendly and easy to understand • Allow modules be built and connected and not patchwork • Allow users to write and incorporate their own routines • Building blocks that contain built in commands (statistical analysis or decision rules for where to go next)
Features of simulation software
• Macro capability to develop machining cells • Material flow capability (material handling by trucks, conveyors, cranes, elevators, hydraulic methods, etc.) • Output standard statistics, such as cycle times, utilizations, wait times.
Merits of simulation
• Better understanding of real system • Compression of time- years of experience can be compressed into minutes by computer. • Does not disturb ongoing system. • More general and can be used where mathematical models cannot be used. • Can be used as a game for training purpose.
Merits of simulation
• Facilitates more realistic replication of real system. • Can be used to analyze transient conditions, where mathematical models do not help. • Many standard simulation software packages are available commercially. • Simulation answers “what if” questions.
Demerits of simulation
• No guarantee that model will provide good or correct answer or solution • No way to prove that simulation’s model’s performance is perfect and completely reliable. • Complicated systems can be costly and take a very long time. • Less accurate than mathematical models
Demerits of simulation
• Still lacks a standardized approach. Models built by different individuals may differ widely and significantly. • Significant amount of computer time may be needed to run complex models. • Mathematical analysis, where appropriate to a specific problem, is usually faster, accurate and less expensive. It is provable also, whereas simulation model may not be provable.
Conclusion
• Anything that can be done mathematically can be done with simulation. However, simulation is not always the best choice. Simulation has nothing fixed. There are no boundaries or limits. Expanding computer power and memory have pushed out the limits of what can be simulated. Continuous development of software have made creating simulation models much easier.
Moral of the story
• Simulation is something very useful in life as well as business. You can take the help of computer software, if necessary or visualize the model yourself.
doc_472070085.ppt