Cost Volume Profit analysis (CVP) is one of the most hallowed, and
yet one of the simplest, analytical tools in management accounting. In a
general sense, it provides a sweeping financial overview of the planning
process (Horngren et al., 1994). That overview allows managers to
examine the possible impacts of a wide range of strategic decisions.
Those decisions can include such crucial areas as pricing policies,
product mixes, market expansions or contractions, outsourcing contracts,
idle plant usage, discretionary expense planning, and a variety of other
important considerations in the planning process. Given the broad range
of contexts in which CVP can be used, the basic simplicity of CVP is
quite remarkable. Armed with just three inputs of data - sales price,
variable cost per unit, and fixed costs - a managerial analyst can
evaluate the effects of decisions that potentially alter the basic
nature of a firm.
However, the simplicity of an analytical tool such as CVP can cut
both ways. It can be both its greatest virtue and its major shortcoming.
The real world is complicated, no less so in the world of managerial
affairs; and a typical analytical model will remove many of those
complications in order to preserve a sharp focus. That sharpening is
usually achieved in two basic ways: simplifying assumptions are made
about the basic nature of the model and restrictions are imposed on the
scope of the model. Those simplifications and restrictions impinge on
the reality and relevance of analytical models, so attempts to improve
them will involve releasing some of their underlying assumptions or
broadening their scope. In this article, we propose a variation of the
CVP analytical model by broadening its scope to include cost of capital
and the related impact of asset structure and risk level on strategic
decisions, while at the same time preserving most of its admirable
Our variation of the conventional CVP model provides more useful
information to management because it focuses on more than operating
expenses and sales revenues. Financial managers have long recognized the
importance of including cost of capital and business risk variables in
capital budgeting decisions (Brigham, 1995). Our model not only
incorporates these admittedly important variables but recognizes the
fixed and variable nature of capital costs.
Criticisms of CVP Analysis
Most criticisms of CVP relate to its basic underlying assumptions.
Economists (Machlup, 1952; Vickers, 1960) have been particularly
critical of those assumptions. Their criticisms take many forms, but
they all arise from CVP's departures from the standard supply and
demand models in price theory economics. Perhaps the most basic
difference between CVP analysis and price theory models is that CVP
ignores the curvilinear nature of total revenue and total cost
schedules. In effect, it assumes that changes in volume have no effect
on elasticity of demand or on the efficiency of production factors.
Managerial accountants recognize these economic critiques, but they
believe nonetheless that CVP analysis is a very useful initial analysis
of strategic decisions (Horngren et al., 1994).
Additional criticisms of the underlying nature of CVP analysis arise
from its similarities to standard economic models, rather than its
differences. Similar to standard economic price theory models, basic CVP
analysis usually assumes, among other things, the following:
single-stage, single-product manufacturing processes; simple production
functions with one causal variable; cost categories limited to only
variable or fixed; and data and production functions susceptible to
certainty predictions. Further, CVP analysis is typically restricted to
one time period in each case. The shortcomings of CVP seem daunting, but
CVP is pliable enough to overcome them all, if necessary and desirable.
Nonlinear and stochastic CVP models involving multistage, multi-product,
multivariate, or multi-period frameworks are all possible, although a
single model embracing all of those extensions would seem a radical
departure from the whole point of CVP analysis, its basic simplicity.(1)
In general, the durability and popularity of CVP analysis undoubtedly
reflects the willingness of its users to "live with" the
shortcomings revealed by criticisms of its basic nature.
In this article, we are also content to "live with" the
basic CVP model. Our concerns lie elsewhere, namely, the somewhat
restricted focus of CVP on only sales revenue and operating expenses.
That limitation can leave some very important aspects of strategic
decisions overlooked. Schneider (1992; 1994), for example, suggests that
the scope of CVP analysis ought to be widened to include the impact of
managerial compensation schemes on target profit levels. In a similar
vein, we propose that the scope of CVP analysis be broadened to overcome
three limitations of the model in regard to asset structure and risk.
Those three limitations are as follows: CVP does not measure the impact
of the decision on wealth; it does not incorporate the effect of asset
structure changes required by the decision; and it does not acknowledge
the risk created by the decision (Magee, 1975; Cheung and Heaney, 1990;
Chan and Yuan, 1990). Some fairly simple extensions of the scope of the
basic model can do much to alleviate the shortcomings caused by those
In the following discussion, each of these three basic limitations of
the CVP model will be examined further and some simple extensions of the
model will be suggested. Strategic thinking, by definition, considers a
broad mix of variables, so even this expanded version of the CVP model
may still be subject to the basic criticism that it is too simple, in
part, because projects do not exist in isolation. The widespread
historic use of the basic version of the CVP model suggests that a
simple, parsimonious analysis is indeed an effective first step in
thinking about strategic decisions. The expanded version of the CVP
model presented here will be developed in that spirit.
Wealth Impacts of CVP Decisions
The first limitation of the basic CVP model that should be addressed
is the absence of any measurement of a decision's impact on wealth.
The current CVP model focuses on the total level of net profits
generated by a decision, which may or may not increase the wealth of the
firm. The ultimate effect of a particular decision upon wealth depends
on the investment in assets necessary to implement that decision. CVP
analysis could be recast completely in present value measures (e.g., see
Reinhardt, 1973). While it would probably be ideal to capture wealth
effects through present value analyses, the main advantage of CVP
analysis, its relative simplicity, would be lessened by the added
complexities of present value techniques. A simpler way to incorporate
wealth effects in the CVP model would be to include the firm's cost
of capital in the analysis.
The key here would be target income, which figures so prominently in
CVP analyses. As a simple expansion of the CVP model, target income is
defined as the minimum net income acceptable for a particular decision.
This minimum income level is formulated as follows: 
[NI.sup.T] = [k.sub.o] x [Delta]TA (1.0)
[NI.sup.T] = target net income; [k.sub.o] = cost of capital;
[Delta]TA = total assets required for a decision.
This definition of target income requires the explicit recognition of
two more variables in CVP analysis, namely, the cost of capital and the
total assets required to implement a decision.(3) The cost of capital
would be the minimum rate of return acceptable from the decision and the
total assets required for the decision would be any additional,
incremental assets that would have to be acquired in order to implement
the decision. Admittedly, these additional variables would seem to
encroach upon the simplicity of the current version of the CVP model.
However, the notion of target income itself implies that some estimates
of the cost of capital and the required investment are lurking somewhere
in a CVP analysis of this type. Otherwise, the target income itself begs
the question of how it was derived.
Given the above definition of target income, a CVP analysis could
then proceed in the usual fashion suggested. For example, a unit cost
approach to CVP analysis could be formulated as follows:
pQ = vQ + FC + ([k.sub.o] x [Delta]TA) (2.0)
p = selling price per unit; v = variable cost per unit; Q = total
quantity of units produced or sold; FC = total fixed costs.
The general thrust of the above CVP analysis would be to determine if
a particular pricing policy and cost structure strategy might yield at
least a minimum target income level that would meet the firm's cost
of capital. An achievement of at least that minimum income level, or
more, should preserve or enhance the existing wealth of the firm. As
Drucker states in a critique of cost accounting:
"Until a business returns a profit that is greater than its cost
of capital, it operates at a loss. Never mind that it pays taxes as if
it had a genuine profit. The enterprise still returns less to the
economy than it devours in resources. It does not cover its full cost
unless the reported profit exceeds the cost of capital. Until then, it
does not create wealth; it destroys it" (1995:59).
Introduction of Assets into CVP Analysis
The above introduction of assets into the analysis suggests that a
simple framework for analyzing required assets should be incorporated
into CVP analysis as well. The notion of variable and fixed assets,
somewhat akin to the notion of variable and fixed costs, would be a
useful addition to CVP analyses. This notion of variable and fixed
assets is a popular tool in financial forecasting in the field of
financial management (e.g., see Brigham, 1995). It arises from the
simple idea that some proportional relationships may exist between sales
or production volume and certain assets. If such proportional
relationships can be determined, then an expanded version of the CVP
model would allow for a much richer analysis of target income
The usual approach to asset requirements in financial forecasting is
to assume that fixed ratios exist between sales volume and the various
current assets of a firm, but the remaining assets are fixed within some
relevant volume range. Those ratios are often determined through an
analysis of average turnover ratios in a firm's industry or through
a study of a firm's own history of turnover ratio levels. The
dichotomy of variable and fixed assets can be modified to allow for some
assets to have both a variable and fixed component. But, the overall
idea is that assets can be analyzed within a variable versus fixed
framework just like costs.
In that regard, equation (2.0) above is modified in the following
fashion to allow for a variable and fixed analysis of assets as well as
pQ = vQ + FC + [([k.sub.o] x pQ/[R.sub.n]) + ([k.sub.o] x FA)] (3.0)
[R.sub.n] = normal ratio of sales to current asset;
FA = fixed assets allocated to decision.
In equation (3.0), target income is separated into returns on
variable and fixed assets, ([k.sub.o] x pQ/[R.sub.n]) and ([k.sub.o] x
FA), respectively. This separation recognizes that the behavior of these
two types of assets would normally require different analyses. The
operating variable and fixed cost analysis, however, remain unchanged
from the basic CVP model. A few additional comments are in order here in
regard to equation (3.0) above. First, the expression
"pQ./[R.sub.n]" is the estimate of current assets, given the
sales volume involved in the CVP analysis. This constant ratio
assumption implies that current assets increase and decrease in the
exact same percentage changes as sales volume. In some circumstances,
this assumption may be too limiting. Second, the fixed assets allocated
to the decision may require some entirely different incremental
analysis. A particular pricing policy and cost structure strategy may
require an increase in the total fixed assets of a firm, but that new
increment of fixed assets would presumably not change within some
relevant volume range of the proposed strategy.
An interesting variation of equation (3.0) would be to recast it in a
contribution margin approach, as follows:
pQ-vQ-([k.sub.o] pQ/[R.sub.n]) = FC+ ([k.sup.o] FA) (3.1)
Contribution margin is normally defined as the income remaining after
variable expenses are deducted from sales revenue. In effect, this
modified version of equation (3.0) would redefine contribution margin as
the net difference between sales and the sum of variable costs plus the
minimum required return on the variable assets required for the
decision. This version of contribution margin would explicitly recognize
that a variable opportunity cost is present in strategic decisions, as
well as variable operating costs. While this version of CVP analysis is
merely an algebraic manipulation, a separate consideration of variable
and fixed resources could allow for new insights within particular
decisions. For example, it would allow for a modified version of the
break even version of CVP analysis in which the return on fixed assets
([k.sub.o] x FA) would be set to zero. This modified version of break
even would imply that the return on fixed capital could possibly be
foregone in some circumstances but that return on circulating capital
would have to continue for a firm to remain viable.
Risk Considerations in CVP Analysis
The introduction of asset structure into CVP analysis heightens
another shortcoming of the traditional CVP model: its lack of attention
to operating risk. Intuitively, both cost structure and asset structure
would be direct determinants of a firm's operating risk. In
general, firms with relatively higher ratios of fixed costs to total
costs and fixed assets to total assets would be expected to have higher
operating risks. That is, changes in their sales and production volume
would have a proportionately greater impact on net income than firms
with relatively lower fixed costs and fixed assets. The expanded version
of CVP analysis in equation (3.0) includes both of those variables;
therefore, a further expansion that included operating risk would seem
worthwhile. In other words, every time a CVP analysis presumes a
different cost and asset structure, a new operating risk level will
The logical variable for dealing with this particular shortcoming of
CVP analysis is to adjust the cost of capital, [k.sub.o], to include the
impact of changes in operating risk caused by cost and asset structure
shifts. The field of financial management provides some useful ideas on
how to expand the CVP model in light of this shortcoming.
Basically, the cost of capital, [k.sub.o], for a particular strategic
decision would be a direct function of the operating risk of the venture
that would unfold from that decision. However, defining and measuring
that function is an extremely difficult proposition. Two approaches in
the field of financial management seem pertinent here, although neither
approach is completely satisfactory. The first approach involves
measuring a surrogate variable of operating risk, and the second
approach involves an analysis of fixed costs that provides a surrogate
Beta risk measure for the Capital Asset Pricing Model (CAPM) computation
of cost of capital.
In the first approach, a surrogate operating risk measure, the degree
of operating leverage, is obtained from the basic data employed in the
traditional CVP model (e.g., see Garrison and Noreen, 1994; Hilton,
1994; Zimmerman, 1995; Morse et al., 1996). This risk measure shows the
percentage change that can be expected in net income given some change
in sales volume. Contribution margin is a key variable in this analysis.
It is the income stream that is available to meet fixed expenses and
target profit levels. The degree of operating leverage recognizes that
contribution margin is an income stream that changes at the same rate as
sales volume, while net income will change at a different rate because
of the presence of constant fixed costs. Relating those two income
measures in ratio form provides an index of the relative sensitivity of
net income to changes in sales.
In basic terms, the degree of operating leverage can be defined as
DOL = CM/NI (4.0)
DOL = degree of operating leverage; CM = contribution margin; NI =
Drawing upon the usual version of the CVP model, the above leverage
relationship can be formulated as follows:
DOL = pQ - vQ / pQ - vQ - FC (4.1)
Note that no new information is required in the equation (4.1)
version of operating risk. The numbers employed in a typical CVP
analysis would be sufficient to develop this risk measure. While many
combinations of product prices and costs are possible, fixed costs are
the crucial variable driving the degree of operating leverage. The
higher are the fixed costs, the higher is the operating leverage. Other
things being equal, the higher a firm's degree of operating
leverage, the higher is its overall business operating risk. Over time,
a firm with a higher degree of operating leverage can expect a higher
variability of its net income stream. In the end result, a higher degree
of operating leverage will lead to a higher cost of capital, which in
turn means that target income levels in CVP analyses will be relatively
higher and more difficult to attain.
It is difficult to stretch this surrogate measure of operating risk
beyond the simple hypotheses offered above. That is, the degree of
operating leverage measure itself does not tie into the cost of capital
figure in a direct analytical manner. Some rough estimates of the
quantitative relationship between operating leverage and cost of capital
might be obtained from analyses of a group of firms in the same industry
or from a time series analysis of a single firm. In most settings, the
degree of operating leverage measure would probably serve best as a
variable that prompts decision makers to think about the consequences of
their strategic decisions on the cost of capital.
In the second approach to incorporating operating risk's effect
on the cost of capital, an accounting version of the Capital Asset
Pricing Model is employed. In CAPM, the cost of capital of a particular
project would be a function of the systematic risk involved in the
project's assets. This systematic risk would be the sensitivity of
the returns on those assets to broad movements in the economy, usually
measured as the returns on all securities in the capital markets. It is
formulated as follows:
[k.sub.a] = [k.sub.RF] + [B.sub.a] ([k.sub.M] - [k.sub.RF]) (5.0)
[k.sub.a] = cost of capital of project assets;
[k.sub.RF] = return on risk free assets;
[k.sub.M] = return on a market portfolio of risky assets;
[B.sub.a] = Beta systematic risk measure of project assets.
In equation (5.0) above, the only variable affected by a firm's
strategic decisions is the Beta systematic risk measure. This Beta
measure relates the returns on investment of a firm's assets to the
average returns on investment of all other firms in the economy, which
would be approximated by some index measure of the returns on a market
portfolio of risky assets. As the firm changes the cost structures
associated with its assets, it also changes the pattern of its cost and
income flows relative to all other firms in the economy. As a result,
the sensitivity of its asset returns to broad movements in the economy
would also change. If a firm's strategic decisions increase
[B.sub.a], its cost of capital on the assets associated with those
decisions, [k.sub.a], would also increase. Consequently, it would be
very useful if accounting data could be used to estimate the systematic
risk involved in strategic decisions.
Some ideas from the field of financial management, integrated with
some empirical work in accounting, are helpful in regard to linking cost
of capital with CVP analyses. The Beta systematic risk measure is the
key variable here. Beta risk measures are usually derived from stock
market returns, with variable [k.sub.M] representing the return on a
market portfolio of securities. Similar Beta risk measures have been
developed in accounting and financial management in which a firm's
accounting earnings over some time period are related to the average
earnings patterns of all firms taken together (White et al., 1994). For
example, these earnings variables could be expressed as returns on
assets (NI/TA) for variables [k.sub.a] and [k.sub.M] in equation (5.0)
above. The systematic risk measures obtained in this approach are
referred to as accounting betas. An examination of the underlying
origins of accounting betas yields some interesting insights about how
CVP analysis could be expanded to incorporate systematic risk measures.
An accounting beta can be thought of as a combination of the
individual betas of the various components of net earnings. The present
value of the assets necessary for the strategic decision being analyzed
can be considered the present values of the net earnings components, as
follows (Brealey and Myers, 1991):
[Beta.sub.A] = f([Beta.sub.pQ] - [Beta.sub.vQ] - [Beta.sub.FC]) (6.0)
PV([Delta]TA) = [PV(pQ)-PV(vQ)-PV(FC)] (6.1)
[Beta.sub.A] = Accounting beta;
PV = Present value.
The two sets of variables above in equations (6.0) and (6.1) can be
integrated in light of some simplifying assumptions that are often
employed in CVP analysis. If the variable costs (vQ) are perfectly
proportional to sales revenue (pQ) and if the fixed costs (FC) are
constant within the relevant volume range of a strategic decision, then
the systematic risks of variable costs ([Beta.sub.vQ]) and sales revenue
([Beta.sub.pQ]) are equal, and the systematic risk of the fixed costs
([Beta.sub.FC]) is zero. Substituting [Beta.sub.pQ] for [Beta.sub.vQ]
and setting [Beta.sub.FC] to zero, equations (6.0) and (6.1) can be
integrated by weighting each variable by the present value of sales
revenue, PV(pQ), as follows:
BA [multiplied by] PV([Delta]TA) / PV (pQ) = [[Beta.sub.pQ]
[multiplied by] PV(pQ)] / PV(pQ) - [[Beta.sub.PQ] [multiplied by]
PV(vQ)] / PV (pQ) - [[Beta.sub.FC] [multiplied by] (FC)] / PV (pQ) (7.0)
Since the difference between the present value of revenue, PV(pQ),
and variable costs, PV(vQ), equals the present value of freed costs,
PV(FC), and the systematic risk of the fixed costs, [Beta.sub.FC], is
set at zero, equation (7.0) reduces to the following relationship:
[B.sub.A] = [B.sub.pQ] [multiplied by] [1.0 + PV(FC)]/PV([Delta]TA)
Equation (7.1) demonstrates that the accounting beta for a particular
strategic decision is determined by the sensitivity of the
project's revenue stream to revenue patterns in the general economy
and by the project's asset structure. An incorporation of those two
variables in CVP analysis would allow for a full consideration of the
ultimate wealth impacts of the decision being analyzed. The inclusion of
accounting betas in CVP analyses would add two more variables that would
have to be estimated, both of which would detract from the basic
simplicity of the traditional CVP model. However, rough estimates of a
project's revenue beta and asset structure would certainly be
feasible and desirable in most cases.
The relative difficulty of estimating each of those additional
variables does vary somewhat. The revenue beta would be an estimate of
how the cyclical patterns of a project's revenue stream would
compare to the aggregate revenue streams in the general economy. This
characteristic of a project's market should be considered in making
strategic decisions. Most firms should have a good feel for their
particular markets from past experience and from information about
The relationship of the value of freed costs to the total assets to
be invested in a project is a bit more difficult to derive. A
firm's customary ratio of fixed assets to total assets would seem a
useful first approximation. But, a problem exists in that financial
accounting systems do not necessarily recognize all of the fixed assets
involved in a strategic decision. Certain fixed assets, such as research
and development programs or marketing campaigns, are expensed
immediately without any consideration for their long-term implications.
Thus, the fixed costs relationship in equation (7.1) might be
underestimated in many cases when regular accounting data are used.
As stated at the outset, present value analyses might detract too
much from the basic simplicity of CVP analysis. However, a present value
approach may be the only recourse for estimating the systematic risk
created by the fixed assets investment in a particular project. That
approach would not be unduly difficult because the necessary data should
be obtainable. After all, most of the fixed costs themselves have
already been estimated in a traditional CVP analysis, and information
about the discount rate is implicit in the target income level set in
such an analysis.
There may be some ambiguity involved in choosing what discount rate
ought to be used in estimating the present value of fixed costs. The
simplest approach would be to assume that the risk of those costs is
zero since they are not expected to vary at all in relation to general
cyclical movements in the economy. Given that assumption, the
appropriate discount rate for determining the present value of the fixed
costs, PV(FC), would be simply the risk-free rate of return, [k.sub.RF],
as per the CAPM estimate in equation (5.0).
The CAPM viewpoint may seem too simple in this context because these
pseudo-assets, the present value of fixed costs, do not necessarily lend
themselves to the portfolio diversification effects assumed in CAPM
analyses. That is, these assets may embody some unsystematic risks,
unique to the firm, which the firm cannot diversify away. Consequently,
a discount rate higher than the risk-free rate would be appropriate,
which could complicate the analysis necessary for this expanded version
of the CVP model.
The use of the risk-free rate, [k.sub.RF], for assessing the risk
impact of fixed assets in a strategic decision would be a conservative
approach. That discount rate would produce the highest present value of
fixed costs in equation (7.1), which in turn would produce the highest
estimate of a project's accounting beta, Betas. That higher beta
estimate would in turn lead to the highest estimate of the
project's cost of capital, [k.sub.a]. Since CVP analysis is not
purported to be anything other than a rough first estimate of a
strategic decision's impact upon a firm, a conservative estimate of
an asset structure's systematic risk level may well be an
appropriate approach. But, in any event, the important point is that the
impact of asset structure should enter into the strategic thinking in
An Illustration: Sports Equipment Manufacturing
To illustrate our above proposals, we have drawn upon a standard CVP
case expanded with industry asset data (Robert Morris Associates, 1993)
to broaden its scope in line with our suggestions. In this case, Hampton
Inc. is a small business that manufactures basketballs. The company has
a standard ball that sells for $25. At present, the standard ball is
manufactured in a plant that relies heavily on direct labor workers.
Thus, variable costs are high, totaling $15 per ball. During the current
year, the company sold 30,000 standard balls, with the following
Sales (30,000 bails) $750,000 Less variable expenses 450,000
Contribution Margin 300,000 Less fixed expenses 210,000
Net income $ 90,000
Using conventional CVP analysis, the company's breakeven point
(q) for current period operations was 21,000 balls, calculated as
0 = pq - vq - FC 0 = $25q - $15q - $210,000 q = 21,000 balls
The company's degree of operating leverage (DOL) for current
operations was 3.33, calculated as follows:
DOL = (pq - vq) / (pq - vq - FC) DOL = ($750,000 - $450,000) /
($750,000 - $450,000 - $210,000) DOL = 3.33
The company is discussing converting to a new, automated production
system to manufacture the standard basketball. The new system would cut
variable costs per ball by 40%; however, it would cause annual fixed
costs to double. Hampton's average current assets during the year
were $385,000. The ratio of sales to current assets was $750,000 /
$385,000 or 1.948. The company's fixed assets were $65,000. The
proposed production conversion would increase fixed assets to $100,000.
Assets are financed entirely with equity. Market analysis indicates
that the current risk-free rate of return is 5% and the market return on
stocks is 15%. The company's systematic beta risk ratio is
estimated to be 1.50. With the assumptions provided, the company's
cost of capital is estimated to be 20%.
[k.sub.a] = [k.sub.RF] + B ([k.sub.a] - [k.sub.RF]) [k.sub.a] = .05 +
1.5 (.15-.05) [k.sub.a] = .20
Breakeven sales and the degree of operating leverage under the
proposed production system are estimated using conventional methods, as
0 = $25q - $9q - $420,000 q = 26,250 balls
DOL = ($750,000 - $270,000) / ($750,000 - $270,000 - $420,000) DOL =
Using our expanded version of CVP analysis which incorporates the
company's cost of capital, the breakeven point increases to 30,000
$0 = $25q - $15q - $210,000 - .20 ($25q / 1.948) - .20($65,000)
q = 30,000 units
While the company sold 30,000 units last year for a reported net
income of $90,000, the net income earned was equal to the company's
cost of capital. Under the proposed production system, breakeven sales
is estimated at 32,755 units.
$0 = $25q - $9q - $420,000 - .20 ($25q / 1.948) - .20 ($100,000) q =
As previously demonstrated, the automated production system would
increase the company's degree of operating leverage. Increased
operating leverage tends to increase variability of cash flows and level
of firm risk (Zimmerman, 1995). The ratio of fixed assets to total
assets would also increase in this proposal. Hence, Hampton's cost
of capital could be expected to increase as a result of the proposed
production system. Assuming that the increase in DOL increases cost of
capital to 25%, the breakeven point would increase as follows:
$0 = $25q - $9q - $420,000 - .25($25q / 1.948) - .25 ($100,000)
q = 34,787 units
In this example, the breakeven points are much higher with our
expanded model. The firm will have to increase its volume over current
period sales in order to earn the cost of capital in the new production
system, a point which the traditional analysis did not reveal. The only
variable which remained constant in our analysis was the current asset
turnover, S/CA. However, this assumption is probably unrealistic. An
automated plant could allow for a higher working capital turnover ratio,
but the opposite could be true in certain circumstances. But, once
again, note that the traditional analysis ignores this consideration
CVP analysis is one of the most powerful techniques available in the
arsenal of managerial accounting analytical tools. It is a relatively
simple planning tool which allows managers to examine the possible
impacts of a broad range of decisions. However, the scope of
conventional CVP analysis can be broadened with an extended version of
its basic model designed to mitigate certain shortcomings. In
particular, CVP analysis does not consider the impact of strategic
decisions on the wealth of firms, nor does it consider the effect of
those decisions on firms' asset structures and risk levels. Those
considerations are important because virtually all CVP analyses deal
with decisions that alter the asset and cost structures of firms, which
means that the risk levels and costs of capital of those firms will also
change because of those decisions.
These missing elements in CVP analysis can be filled in with a small
number of additional variables. The wealth effects can be included by
analyzing the cost of capital of the assets necessary to carry out a
decision. The risk level imposed by a decision can be incorporated by
considering the degree of operating risk or the systematic risk level as
reflected by an accounting beta risk variable. The cost of capital
itself can be estimated through an analysis of the revenue patterns and
the asset structures involved in a decision. In general, through the use
of information that would usually be available in a CVP analysis, the
full impact of a strategic decision can be assessed.
1 Similar to Schneider (1992; 1994) our model can be viewed as a
variation rather than an extension of the basic CVP model. Schweitzer et
al. (1992) provide an excellent discussion of extensions of the basic
CVP model, including multi-period and multi-product analyses.
2 Income taxes are assumed away in the ensuing discussion. Manes
(1966) remains the best treatment of tax effects in CVP analysis, among
3 An implicit assumption here, and in the remainder of this
discussion, is that assets invested in a project will be continuously
renewed. That is, a perpetual asset, rather than a finite life asset,
will be assumed. A similar, but slightly more "complicated"
analysis can be developed for finite life assets by depreciating the
assets on an annuity basis at the appropriate cost of capital (e.g., see
Brealey and Myers, 1991: 219-223).
Brealey, Richard A., and Stewart C. Myers. 1991. Principles of
Corporate Finance. 4th ed. New York: McGraw-Hill.
Brigham, Eugene F. 1995. Fundamentals of Financial Management. 7th
ed. Orlando, FL: Dryden Press.
Chan, Y.L., and Y. Yuan. 1990. "Dealing With Fuzziness in
Cost-Volume-Profit Analysis." Accounting and Business Research 20
Cheung, J.K., and J. Heaney. 1990. "A Contingent-Claim
Integration of Cost-Volume-Profit Analysis with Capital Budgeting."
Contemporary Accounting Research 6 (Spring): 738-760.
Drucker, Peter F. 1995. "The Information Executives Truly
Need." Harvard Business Review 73 (January-February): 54-62.
Garrison, Ray H., and Eric W. Noreen. 1994. Managerial Accounting.
7th ed. Burr Ridge, IL: Richard D. Irwin.
Hilton, Ronald. 1994. Managerial Accounting. 2nd ed. New York:
Horngren, Charles T., George Foster, and Srikant M. Datar. 1994. Cost
Accounting: A Managerial Emphasis. 8th ed. Englewood Cliffs, NJ:
Machlup, Fritz. 1952. The Economics of Sellers' Competition.
Baltimore, MD: John Hopkins Press.
Magee, Robert P. 1975. "Cost-Volume-Profit Analysis, Uncertainty
and Capital Market Equilibrium." Journal of Accounting Research 13
Manes, Rene. 1966. "A New Dimension to Breakeven Analysis."
Journal of Accounting Research 4 (Spring): 87-100.
Morse, Wayne, James R. Davis, and Al L. Hartgraves. 1996. Management
Accounting: A Strategic Approach. Cincinnati: South-Western College
Reinhardt, U.E. 1973. "Break-Even Analysis for Lockheed's
TriStar: An Application of Financial Theory." Journal of Finance 28
Robert Morris Associates. 1993. RMA Annual Statement Studies.
Philadelphia: Robert Morris Associates.
Schneider, Arnold. 1992. "Cost-Volume-Profit Models Containing
Earnings-based Bonus Expenses." Accounting Enquiries 2 (August):
-----. 1994. "How To Include Earnings-based Bonuses In
Cost-Volume-Profit Analysis." Journal of Managerial Issues 2
Schweitzer, Marcell, Ernst Trossmann, and Gerald H. Lawson. 1992.
Break-even Analyses: Basic Model, Variants, Extensions. New York: John
Wiley & Sons.
Vickers, Douglas. 1960. "On the Economics of Break-Even."
Accounting Review 35 (July): 405-412.
White, Gerald I., Ashwinpaul C. Sondhi, and Dov Fried. 1994. The
Analysis and Use of Financial Statements. New York: John Wiley &
Zimmerman, Jerold L. 1995. Accounting For Decision Making and
Control. Chicago: Richard D. Irwin.