ymca821-.pdf-published paper-5.pdf++

International Journal of Engineering Technology, Management and Applied Sciences

www.ijetmas.com November 2016, Volume 4, Issue 11, ISSN 2349-4476

102 Prof. Sreedhara Ramesh Chandra , Dr. Krishna Banana

Dr. KB and Prof SRC’s Integrated Model of Sensitivity to

Scenario Analysis with Breakeven Analysis for Operational

and Investment Risk Analysis

Prof. Sreedhara Ramesh Chandra Dr. Krishna Banana

Associate Professor & HOD, ML Eng. College, Assistant Professor,

Singarayakonda, Andhra Pradesh, India Department of Commerce &

Research Scholar, Acharya Nagarjuna University Guntur, Business Administration, Ongole

Campus, Ongole, Acharya Nagarjuna University Guntur,

Andhra Pradesh, India. Ongole Campus, Ongole. Andhra Pradesh, India.

ABSTRACT

It is evident that among the decisions on financial aspects of any business, the most important and critical is the long

term investment decision. It involves lock up of large amount of funds for long period future coupled with the risk of

uncertainty of returns affected by economic and business scenarios of the environment. The decisions with in-depth

assessment of the economic & business scenarios of the environment help to take the impotent decisions like long term

investments. The difficulty in forecasting number of scenarios and unable to establish relation between the values of

variables in between the scenarios is a concern for the need of further improvements of the methods in use of the

investment analysis. The price, costs and volume are the determinants of the investment decisions. The economic

environment is of a dynamic instinct. The economic scenarios are ever changing. The determinants of the decision are

subject to the changes affected by the changes in scenario. Therefore the analysis which analyses in tune with the

scenarios gives more accurate result. The existing methods and techniques though considering the scenario effects on

determinants, there are issues needed to be addressed for perfection in analysis and more accuracy in the decision. In

the light of the two method viz. the sensitivity and the scenario analysis the crystal ball and simulation software model

able to give greater consideration to the scenario impacts on determinants in analysis. It is felt that still there are some

issues needed to be addressed for perfection in application of the crystal ball and software simulations. This is one of

such attempt in eliminating the limitations of the crystal ball. This is the model designed to perfection with the

integration of both scenario and sensitivity analysis through Breakeven analysis able to measure the impacts of all at

once physically without the software. This model enables to consider multiple scenarios with multivariable sensitivity

with a deterministic relation between scenario values for analysis is the limitation of the crystal ball. This is made

possible with the effect of sensitivity to scenarios through extent of change from one to another at once with simple

concepts and calculations of proportions. Further this enable to provide a direct link between the operational risks and

investment risks. This model is equally useful for both operating risk measurement and control apart from the investment

risk analysis.

1. INTRODUCTION:

There are several analytical models are in use for analyzing and measuring the risk in investment decisions

under uncertainty conditions of environment. Among them the important are sensitivity, scenario, break-even

analysis, hillier Model of probability application with non correlated and correlated cash flows approaches,

simulation, risk adjusted discount rate, certainty equivalents, Decision tree analysis etc. the data used in

almost all these methods are starts from the predication/forecast of annual cash flows. It is evident that the

function in Cash Flows depends on three important factor determinants viz. the price, costs and volume.

Commonly the impact of scenario effects on cash flows is measured through determinants in scenario

analysis. A function in the determinants depends on internal and external environmental factors that show the

influence on determinants. The predicted functions in Cash Flows more particularly the cash inflows need to




be determined through measuring the forecasted scenario impact on the determinants i.e. price, costs and

volume.

Commonly the impact effects of changes in scenario on cash flows are measured through predicted changes in

determinants either by experience or expertise is called scenario analysis. The extent of responsiveness of cash

flows to a determinant is considered as the sensitivity analysis. In reality the concept of study of impact

means the extent of responsiveness from the existing or standard or desired or ideal figures and may not be the

resultant with distinct value of variables that are in consideration under the present scenario analysis. They

represent to a discrete scenario and it is hard to establish relation with distinct scenarios by discrete value

determination of variables is a major limitation of the scenario. Further the scenario concept is the core for

crystal ball and simulation analysis wherein there is no greater change beyond the consideration of many

number of scenario values to the determinants to derive the different scenario cash flows through a software.

In the context of modern trends in fast changing technologies and integration of world economies the

economic environments become more dynamic. As result the risk of the uncertainty increased further,

evidently it enhanced the need for effective assessment of risk in investment decisions. In light of the situation

several modern methods/models were developed. Amongst all the latest technique the crystal ball and

simulation apart from the sensitivity analysis, scenario analysis methods consider the scenario effects in

analysis with the chief determinants of cash flows. It is needed to overcoming the limitation of considering

only few determinants and ensuring all the considerable variables in analysis and increased accuracy in

measuring the risk factor in investment. This is an innovative model distinctly designed using the simple basic

relationships among the variables and their relationships in proportions ensuring an integrative effect of the

variables that gives totality to the process in deriving the most realistic factors to the fore in risk analysis.

The proposed model developed with the integration of sensitivity; scenario and breakeven concepts in such a

way that it can provide a better and more accurate values in terms of proportions with inter relation between

the different scenario values and with a perfect sensitivity effect i.e. clear measurement of effect or the

sensitivity through measuring the extent of effect from the predetermined. It further solves the major problem

of relational and non related cash flow error effects in analysis with the aspect of measurement of the effects

with reference to a unified constant variable (sales revenue).

The problem of measuring the values of determinants under different scenarios is made simple with the

application of corresponding multiplication constants for each of the chief and the sub determinants of cash

flows to any and every predicted scenario either under general or excel work sheet calculation. With the help

of an excel work sheet we can visibly measure the effects without much technical knowhow. It mostly

resembles a semi crystal ball simulation effects with physical visible calculations using more deterministic

values of variables through proportions.

Among the models available the sensitivity, scenario and breakeven analysis originated at the level of

determinants apart from the crystal ball simulation. These models, gave due consideration to measure the

extent of impact of the environment through the changes in one of the determents at each instance in

sensitivity and values of all the variable independently in each instance under scenario on the cash flows.

These three analytical models have similarities in consideration of data and each one has their way of

projection, they suffered from certain limitations. With the integration of the three ensure the overcoming of

the limitations and bringing the totality to the analysis.

The proposed model covers both micro level information, macro level information in an indexed manner (pre

determined on current price, costs and the volume figures on one hand and the exact measurement of effects

on results through sensitivity to changes observed/predated time to time and made possible to measure the

impact on results w.r.t. to changed scenario of any kind.

2. Key words:

Variable cost Ratio, BEP ratio, P/V Ratio, sensitivity constants, relational parametric constant sales revenue.

Percentage of profit on parametric constant sales revenue, Percentage of cash flows on the parametric sales, %




of PVCIF on parametric sales, % of NPV on parametric sales. Change in sales as a Percentage of the new or

scenario sales.

3. Research gap:

1. The limitation of no scope for consideration of all the determinants of cash flows is need to be avoid and

able to give all the determinants together in analysis in measuring the risk in investment proposals.

2. Unfulfilled need for the direct integration between operational risk and investment risk measurements

together to understand and disclose the relation between them for effective investment decisions.

3. Laxity of sensitivity constants for simplification in measurement efforts and results.

4. Giving scope for all the possible determinants of cash flows in risk analysis.

5. The limitation of crystal ball simulation i.e. it suffered with the limitations from the way of consideration

of the values of determinant variables viz. price, volume, costs etc in independent monetary or numerical

figures. Multiple complex calculations. No Possibility to conduct the same physically/manually with

minimum values such as proportions of variables. Presently there is no scope for ensuring the process of

analysis as a guide for operational risk control of the project after the commencement.

4. Objectives:

1. Ensuring greater accuracy in determining the values of determinants with more precession and much

simplicity for risk measurement through introduction of proportions or percentages.

2. Ensuring more effective way in Implication of risk aspect of the economic environment on all the

determinants of cash flows through the application of extent of response deviations and measurement of

effect with a relational constant value.

3. ensuring calculation of sensitivity of results /profits with respect to all the factor determinants of profits

to parametric relational constant value (constant sales revenue) Designing a perfect model for both

operational risk and investment risk assessment in consideration of all the determinants of any kind of

financial of risk.

4. Unique and Simplified way of calculation of NPV, PI and IRR directly with proportions of cash flows

instead of monitory figures of cash Flows.

5. Ensuring simplicity in measuring the measurement of risk under with integrative model of sensitivity and

scenario analysis under breakeven ensuring the effects of crystal ball and simulation physically in a

visible manner through micro soft excel work sheet without redundancy and With a multiplication

constant factor of sensitivity or elasticity factor for each of the determinant variables viz. costs, price,

volume.

6. Ensuring the sensuousness of the cash flows/profits in proportion to a common constant referral value, the

revenue. Minimizes/eliminates error in interpretation of results.

5. Research methodology:

Innovative research on conceptual enlargement for methodical expansions in advanced applications of break

even analysis for operational and investment risk analysis is used.

6. Limitations of the study:

1. Here in only the hypothetical examples used to explain and no live examples used in experimental

analysis of situations.

2. Practicability of the hypothetical conditions of the scenarios.

3. Not having enough research publications and empirical research literature in this area is also limitation.

7. Literature review:

Working in isolation the existing scenario analysis, sensitivity analysis, breakeven analysis has very limited

scope for measuring the risk through the predicted changes in the entire variable under multiple scenarios.




As the concept of the paper is to formulate the calculations innovatively, the common existing formulae were

collected from the review of literature.

1. The concepts used in BEA:

2. Sales(S): sales or selling price.

3. Variable costs (V): unit cost / proportional variable total cost.

4. Fixed costs (F): total fixed cost irrespective of level of output.

5. Contribution margin: it is the amount calculated with the following: C = S-V

6. P/V Ratio (Profit Volume ratio) it is the ratio of between the contribution and sales.

7. P/V Ratio: C/S*100

8. All formulas of BEA ring aground the following equation: S-V = C =F+P 9. S-V = C = F+P S S S 5.1.

Existing Other Formulas in Breakeven Analysis for Profit Planning Calculation of:

Breakeven Point (BEP) I units: F/Cpu In sales value/revenue: F/ p/v Ratio.

Determination of sales required to get a profit of Rs. P

Required sales {in units}: F+ desired P Cpu

Required sales {in revenue}: F+ desired P/ PV Ratio A

mount of profit (P) when sales are S units:

P= (S x Cpu) -F Amount of profit (P) when target sales are ‘S’ rupees:

P = (S x P/V Ratio) –F Calculation of safety margin sales SM/MS/SMS:

SMS= TS-BEP (in units or value) SMS in units: P / Cpu SMS in value: P / (P/V Ratio)

The newly invented formulae with the existing concepts are % of P = P/V Ratio (1-BEP Ratio) or P/V Ratio-

(P/V Ratio*BEP Ratio) Generally accessible from any text book of cost and management accounting and

drawn from the references

The scenario analysis:

1. It depends on the assumption that there are well delineated scenarios which may not be true in many

cases. Further the economy does not necessarily lie in three discrete states viz. recession, stability, and boom.

It can in fact be somewhere on the continuum between the extremes. When a continuum is converted in to

three discrete states some information is lost.

2. The independent scenario analysis needs to determine the values of variables in consideration of

concerned state of the scenario independently. As result it become inflexible and does not provide for

correlative implication with other scenarios under consideration.

__________________________________________________________________

Prasanna chandra projects planning, analysis,selection,

financing, implementation, and review, CFM-TMH professional

series in finance 7th editionpage No.11.7 & 8

3. In case of sensitivity analysis the major limitation is that it can be able to measure the changes with

respect to changes in only one variable at once is not useful for correct inference.

________________________________________________________________


financing,implementation, and review, CFM-TMH professional

series in finance 7th editionpage No.11.5to11.7

4. The financial break-even i.e. the present value breakeven is also a measure of risk in investment

decisions.




_________________________________________________________



series in finance 7th editionpage No.11.5to11.11

5. The conversion of a deterministic micro soft excel spread sheet model into dynamic simulation model

involves three steps.

a. Identification of the inputs to the model i.e. selling price quantity etc. that are subject to the

uncertainty and define the distribution for each of them. In crystal ball these uncertain inputs are called

assumptions.

b. Select a value of each of each of the assumptions in the model, calculate the value of each of the

output variables called crystal ball and store the result.

c. Repeat this process for number iterations. The resultant values may be summarized using descriptive

statistics.

_________________________________________________



series in finance 7th edition page No.11.5to11.19

Additional formulas used apart from the common BEA Formulas

1. Calculation of component wise multiplication constant factor of each component of Variable cost

sensitivity as @ re. 1 = component wise proportion of each variable factor to variable cost ratio. VC

ratio*proportion of VC component value (% of change in VC on VC.

2. Determination of sensitivity constant for measuring the effect of change in FC through FC cost ratio. FC

constant = Proportion of each component of Fixed cost in total fixed cost* BEP Ratio* PV Ratio. at Re.1.

3. Determination of sensitivity constant for measuring the effect of change in volume: BEP proportion * PV

Ratio proportion at Re.1.

4. The sales revenue is the only variable which has direct link between the costs, price, volume on one end

and the profits on the other. Further the sales revenue is the most important and a common standard of

measurement of performance and efficiency. It is a common phenomenon of target performance. In view

of this the sales revenue is identified as the common constant value to which the worth of every

determinant variable and their extent of effect on performance are measured. The pre determined value of

sales as constant factor enabled to derive the multiplication constants for each variable and the sub

variables.

5. With the help of the determination of multiplication constant/elasticity of the determinant factor it is made

possible to bring totality for the analysis.

8. Innovation Hypothesis:

a. Every business follows the principle of determination of target volume and value of sales at a given price

for the period of analysis under pre determined context/scenario as constant. Further the changes in

volume are possible to measure as a percentage on the volume/revenue after the. And price changes as a

percentage on prefixed price to arrive the results after the effects of the changes

b. It possible to determine the variable (either in total or at per unit) and fixed costs in total for the

corresponding target volume in any and every business on any prefixed context i.e. ideal/existing

facts/standers/budgets. Further it is possible to determine the extent of likely changes in the costs to other

context situations as percentage on costs.

c. The measurement of extent of effect of change in price/cost/ volume is made possible to bring the

prefixed / predicted results to the actual through measuring and adjusting with the extent of effect i.e.




sensitivity, affected by change situations /scenario without altering the prefixed parameters and without

redundancy indicate the uniqueness of the model.

d. This is the analytical model assess the effectiveness of investment proposal with a clear picturesque of the

way how results are effected by scenarios and the moments of results from scenario to scenario.

e. It is possible that the breakeven analysis need not keep the assumptions as prerequisites for conducting

analysis. More importantly it solves the problem of FC as constant and does not change.

f. It is possible that the measurement of actual results through a smooth passage from initial prefixed vale to

the actual value by measuring the extent of response (sensitivity).

9. ANALYSIS:

The sensitivity to scenario analysis is conceptualized and developed with the following disclosed common

facts of relation between the price, costs and revenues. Apart from the concepts, formulas commonly used in

BEA and the innovative formulas developed and published in May /June in the international journals the

IJBM & IRJBM.

1. The amount of change in VC is measured and considered as a percentage of VC (∆VC/VC*100) and

evidently the rate or % change in VC is the same as the rate / % change in VC ratio. Therefore the amount

of change in VC as rate of change in VC is synonymous to rate of change in VC Ratio. In view of this the

sensitivity constants are determined as:

2. The constants of sensitivity = VC Ratio/100 or VC/SP or variable cost proportion it is either to VC or in

its components.

3. Further in similar way the constants or sensitivity of FC is calculated as the product of PV Ratio and BEP

proportion (BEP/Total sales), because the BEP ratio moves in proportion to FC on one hand and show a

similar response to Volume on the other.

4. Therefore the Volume sensitivity constant is calculated as product of contribution proportion(c/s) and BEP

proportion (BEP/Sales). The scenario value of change in respect of volume is calculated on the volume

after the change and not the predetermined volume.

5. When there exists a change in both volume and fixed cost in-tandem the sub effect part sensitivity is

calculated as (BEP proportion * contribution proportion) *(the product of % change in FC and % change

in Volume).

6. The sensitivity constant of a change in SP is always being 1 and the percentage change in price intact is

the extent of response. Because change *1 is the same as the % change.

With the use of the above simple concepts of multiplication constants as the sensitivity constants / elasticity,

the scenario effect on results are calculated by multiplication with the scenario impact on the determinant

arrived as a % on the predetermined value of the respective determinant called sensitivity to the variable for

each of the identified determinants independently. The net effect is calculated by adding or deducting of

sensitivity of all. The net results after the scenario effects are arrived by adding/deducting the net effect of

sensitivity to the predetermined Rate of profit. Simultaneously as may number of different results is possible

to determine for the each of the number of scenarios that one predicts. Further it is possible to view visibly the

state inter relation among them. This is because the extent of effect of sensitivity or scenario effects is

measured in proportion/percentage to constant reference value of sales revenue. The way how the integrated

innovative model is developed can be elaborated with the following hypothetical example.

This is made possible to apply as many determinants/sub determinants that one wish to can be used and

effects are visibly verified. Though there is no limit for visualizing the number of scenarios, here for the

purpose three limits are used apart from the ideal/slandered/targeted.

The following figures are arrived keeping in view the existing/prevailing/ideal/slandered conditions

environment as:

Project cost Rs. 75000/- scrap value Rs. 5000 & life 5 years tax rate 40%

The following values are arrived through standard costing/budgeting under ideal conditions




Table: 9. 1

Change predicted under different scenarios

Particulars

standard/budgeted/target

under Ideal

Scenario effects in % /change in %

normal pessimistic optimistic

level or % of capacity 100% 80% 60% 100%

Output and sales 12500 10000 7500 12500

cost PU total cost 2 3 4

cost of direct materials consumed 2 25000 3 10 -5

cost of dire labour 1 12500 2 7 -3

direct other exp 0.2 2500 1 2 0

prime cost 3.2 40000

add variable factory OH 0.8 10000 6 19 -8

add fixed factory OH 0.6 7500 10 20 5

factory/manufacturing cost 4.6 57500

add office and admn variable OH 0.5 6250 2 5 -2

add office and admn fixed OH 0.6 7500 10 20 0

cost of production 5.7 71250

add selling & dist variable OH 0.75 9375 0 -2 -5

add selling & dist fixed OH 0.32 4000 10 20 5

project depreciation 1.2 15000 0 5 0

total cost 7.97 99625

profit 4.03 50375

sales 12 150000 0 -5 3

Table: 9. 2

Determination of profits under the breakeven analysis and determination of CV sensitivity constants

ideal conditions

level of output and sales in units(12500) 150000 12 element wise

VC sensitivity

constants (v/sp) total cost VCPU

cost of direct materials consumed 25000 2 .167

cost of dire labour 12500 1 .0833

direct other exp 2500 0.2 .167

prime cost 40000 3.2

variable element of factory OH 10000 0.8 .0667

variable element of office & admn OH 6250 0.5 .0417

variable element of selling & dist OH 9375 0.75 .0625

total VC/Vcpu/ & VC ratio 65625 5.25 (43.75%) .4375

contribution /Cpu/ & pv Ratio 84375 6.75 (56.52%) .5625

sales 150000 12 1.00

proportion of each

element of FC in total

FC

fixed element of factory OH 7500 0.221

element office & admn fixed OH 7500 0.221




element selling & dist fixed OH 4000 0.118

project depreciation 15000 0.441

total Fixed cost 34000 34000 1.0

total cost (F+V) (65625+34000) 99625

profit 50375

sales 150000

% profit on sales 33.58 33.58

BEP in units F/c 5037

BEP in revenue F/PV ratio 60444.44

% of bep in target sales bep/TS*100 40.2962963 40.296

Table: 9. 3

Determination of effects or sensuousness of profits to VC sensitivity affected by scenarios

variable cost

particulars

determination of sensitivity constants

sensitivity analysis together with scenarios under the Break

even Analysis

sensitivity

constants

changes predicted

under scenarios in

i.e.∆VC as % in VC

sensitivity of results to the

scenario

extent of

sensitivity/responsiveness of

profits to scenarios VC

ideal/prese

nt

nor

mal

pessi

misti

c

optimi

stic normal

pessi

mistic

optimisti

c normal

pessimi

stic

optimist

ic

1=(

VCPU/SP) 2 3 4 5=1*2

6=(1*

3) 7=(1*4)

7= sum

of 4

8= sum

of 5

9= sum

of 6

cost of direct

materials consumed 0.167 3 10 -5 0.500 1.667 -0.833

cost of dire labour 0.083 2 7 -3 0.167 0.583 -0.250

direct other exp 0.017 1 2 0 0.017 0.033 0.000

prime cost 0.267 0.683 2.283 -1.083 0.6833 2.2833 -1.0833

add variable factory

OH 0.067 2 5 -2 0.133 0.333 -0.133

add office and admn

variable OH 0.042 0 -2 -5 0.000 -0.083 -0.208

add selling & dist

variable OH 0.063 3 8 0 0.188 0.500 0.000

total Variable OH 0.4375 0.3208 0.750 -0.3417 0.3208 0.7500 -0.342

responsiveness of total

variable cost 1.0042 3.0333 -1.4250

aggregate weighted average change in VC to scenarios = (SP*

responsiveness to scenario /100)

0.1205 0.364 -0.171




Table: 9. 4

Calculation of Sensitivity constants for the determinants i.e. fixed cost and volume

particulars

(FOH/TFOH)

(BEP

proportion

*FOH) PV ratio/100

sensitivit

y constant

1 2 3 4=(2*3)

Volume of sales 0.40296 0.5625 0.227

Factory fixed OH other

than depreciation. 7500 0.22 0.0889 0.5625 0.050

Admn Fixed OH 7500 0.22 0.0889 0.5625 0.050

Selling Fixed OH 4000 0.12 0.0474 0.5625 0.027

Project Depreciation 15000 0.44 0.1778 0.5625 0.100

total fixed cost 34000 1.00 0.40296 0.5625 0.227

Volume and fixed cost sub

effect

0.40296 0.5625 0.227

Selling price (the extent of % change in price) or it is always

Table: 9. 5

Determination of effects or sensuousness of profits to FC, volume and price sensitivity affected by scenarios

particulars

sensitivity

constant

predicted scenario changes in

FC as % on ideal values of FC

and ( for volume change % on

scenario volume)

extent of

sensitivity/responsiveness of

profits to scenarios FC, sales,

price

4 5 6 7 8=4*5 9=4*6 10=4*7

Volume of sales 0.227 -25.00 -66.67 0.00 -5.67 -15.111 0.000

Factory fixed OH other than

depreciation.

0.050

10.00 20.00 5.00 0.50 1.00 0.25

Admn. Fixed OH 0.050 10.00 20.00 0.00 0.50 1.00 0.00

Selling Fixed OH 0.027 10.00 20.00 5.00 0.27 0.53 0.13

Project Depreciation 0.100 0.00 5.00 0.00 0.00 0.50 0.00

total fixed cost 0.227

1.27 3.03 0.38

volume and fixed cost sub

effect(when both changed in-

tandem :

(aggregate % change in Fixed

cost:(the total of 8/4, 9/4.10/4)

4= total

sensitivity*%vol*%FC

8=(.227*5.59*-25)---

0.227 5.59 13.38 1.69 -0.32 -2.02 0.00

Selling price sensitivity % change in SP 0 -5 3

Table:9. 6




Effects of the aggregate scenario sensitivity or sensuousness of profits and cash flows

determinant

factor

extent of sensitivity to scenarios

normal=80% pessimistic=60% optimistic=100%

extent

effect

effect

on profit

extent

effect

effect

on profit

extent

effect

effect

on profit

Initial profit as % on planned sales 33.58 33.58 33.58

less: total sensuousness of profits

to sensitivity of VC to scenario

variable cost 1.0042 1.0042 3.0333 3.0333 -1.4250 -1.4250

Profits after scenario VC effect

32.579167 30.55 35.008333

Less: total sensuousness of profits

to sensitivity of FC to scenario

Fixed cost 1.58 1.58 5.06 5.06 0.38 0.38

Profits after scenario FC effect 30.996 25.494 34.625

add scenario volume effect -5.67 -5.67 -15.11 -15.11 0.00 0.00

after volume effect 25.329 10.383 34.625

add scenario price effect 0 0 -5 -5 3 3

% of profit after the scenario

sensitivity effects 25.329 5.383 37.625

% of profit on the ideal revenues: (

P after the scenario*Nvol/old vol) PBIT 20.26 3.23 37.63

after tax rate 40% PAIT 12.158 1.938 22.575

add depreciation (=14/15*100) 9.33 9.33 9.33

(14000/150000*100)

cash inflows from the project 21.49 11.27 31.91

Table: 9. 7

Calculation of NPV of the project under predicted different scenario situations

expected cost of capital is 8% normal=80% pessimistic=60% optimistic=100%

PV annuity for 5 years @ 8% = 3.993 3.993 3.993

PVIF 85.809 45.003 127.401

PV of scrap (5000/150000*100*.6806) 2.27 2.27 2.27

PV of cash flows as a % on sales 88.08 47.27 129.67

initial investment as % on sales :

75000/150000*100 50 50 50

NPV as a percentage of predetermined sales (%of

PVIF-%PVOF) 38.08 -2.73 79.67

IRR 33.25 5.95 57.65

PI 88.08/50=1.72 47.27/50=0.90 129.67/50=2.55

10. Evaluation:

With the help of the determination of the sensitivity constants detailed in the table 9.2 for the VC and Table

9.4 for the FC and Volume and it made very much simple in determining the sensuousness of the




profits/results to each and every determinant as given table 9.3 and table 9.5. And the aggregate effect as

detailed in the Table 9.6. With the help of measuring the results after the sensitivity impacts and converting

the resultant rate as % on the predetermined sales revenue by multiplying the result with the ratio of actual

scenario volume and prefixed volume the PBIT is determined. The next process is as usual in determining the

NPV/IRR/PI. The difference is only that instead of physical value of cash inflows it is determined with the

CIF as a % on predetermined sales which is the key constant for measuring all the effects including the NPV

is the real concept of establishing and ensuring perfect integration of the total process of the model. It

becomes the error free relativity among the scenarios determinants and the process. Therefore it is perfect

rational analytical tool in studying the extent of difference in between the scenario values. If necessary,

calculating the standard deviation would be the sufficient to measure the deviation/variance coefficient to

arrive at the investment decision. Further it serves as a integrated controlling tool of operation after the

commencement of the project.

This model ensures the entire process of analysis in proportions with perfect inter relation among the

determinants and between the scenarios from the beginning to the end. The method of proportional value

analysis enabled the perfect integration of scenario effects from the beginning with assessment of changes as a

% in costs, price and volume through the process with the impact of sensitivity till the end with perfect

integration on breakeven concept based measurements of effects of determinants on results. Therefore the

integration sensitivity scenario enabled through breakeven analysis enable to overcome the limitations and

multiplicity of value considerations. Further it ensures all the variables what so ever one consider as important

made involved in the analysis for investment analysis.

This is the integrated model further perfectly fitted to the assessment of operational risk analysis enabling the

study of day to day change in costs, prices and projected volume on day to day basis for strategy formulations,

strategic operational decisions including pricing.

11. Conclusion:

This is the tool represents a perfect blend of integrated system of absorption technique in data collection and

representation of costs, direct costing and breakeven techniques in relating and processing and deriving the

results. Whereas in adopting the standers for comparison and interpretation of measured results, the use of

budgeting /sundered costs techniques. Therefore this is a perfect model of operational risk measurement apart

from the investment risk analysis.

12. References:

i. S.P Jain & K.L Narang, Cost accounting principles and practice, 22nd Revised Edition (2011), Kalyani

Publishers.

ii. M.N Arora, A Textbook of Cost and Management Accounting, 10/e , Vikas Publishing.

iii.Prasanna chandra projects planning, analysis,selection, financing,implementation, and review, CFM-TMH

professional series in finance 7th edition

iv. Management and cost accounting sixth edition, cengage learning india edition, by colin drury.

v. Chandra Sreedhara Ramesh & Banana Krishna (June, 2016) Innovative Formulations and Enhanced Scope

of Break Even Analysis. IRJBM ,Volume – IX (Issue – 6).

vi. Chandra Sreedhara Ramesh & Banana Krishna (May, 2016) Innovative Formulations and Enhanced

Additional Applications of Break Even Analysis. IRJBM, Volume – IX (Issue – 5).

vii. SRCSPS Karivena Effects in Application of Breakeven Analysis for Strategic Pricing Advanced

Applications in Breakeven Applications, IJMB June 2016, Vol 4, Issue 6.

viii. Prof. SRC & Dr. KB Innovations in Measuring the Impact and Action Recourse for Changes in Costs

Prices Product Mix and Volume on Profits, Developed as an Effective Mathematical Tool for Reporting

and Decision Making by Interlinking the Economic Analysis and Financial Analysis through Breakeven

Analysis




iX. Risk Management System Implementation: Improving the Role of Internal Control Unit (SPI)

September, 2016. theijbm, 2-MB1609-009’

Declaration:

I solemnly declare that the above is a sheer intuitive thought of my own and nothing is copied in the parts of

the above innovative formulations and analysis, except the generalizations cited and the references cited. If

you found the same anywhere in the past, it is purely due to non accessibility to such work, kindly give the

details of that work(s), if possible/necessary and they duly regarded. Your cooperation in this regard is

earnestly solicited.

Your comments and suggestions are earnestly solicited.

Thanking you sir,

With regards

S. Ramesh Chandra

ymca821-.pdf-published paper-5.pdf++

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