Capital bias reducing human error in capital decision making

Capital bias
Reducing human error in capital decision-making
A report by the
Center for Integrated Research
Deloitte’s Capital Efficiency practice helps organizations make
better and faster decisions by
assisting them in improving the quality of their capital
allocation decisions to enhance robustness,
efficiency, and return on investment.
Capital bias
The balancing act | 2
Choreographing the optimism bias, expert bias,
and narrow framing | 3
Mitigating biases in planning: The US Navy | 7
Prioritization: Leveling the playing field | 9
Stripping away your own organization’s biases | 11
Endnotes | 12
CONTENTS

1
A look at the S&P 500 suggests just how dif-ficult it can be to
consistently drive positive results. Take one measure, return on
in-
vested capital (ROIC). In a Deloitte study, neither
the amount of capital expenditures (as a percentage
of revenue) nor the growth in capital expenditure
demonstrated any kind of meaningful correlation
with ROIC.1 Regardless of industry, individual com-
panies can often have a difficult time maintaining
high and steady returns on their investments year
over year.
Given such uncertainty in capital allocation re-
sults, it may not be surprising that more than 60
percent of finance executives say they are not con-
fident in their organization’s ability to optimally al-
locate capital.2 After all, many companies are bal-
ancing competing priorities, diverse stakeholder
interests, and a complex variety of proposals that
can make capital allocation decisions even more dif-
ficult to execute in practice.
Why is this? On paper it seems practical enough
for everyone throughout the organization to be on
the same page. In an ideal world, a company estab-
lishes the goals and priorities; then, from senior
managers to frontline employees, everyone is ex-
pected to act in a manner that supports these man-
dates.

However, behavioral science, and possibly your
own experience, suggest it’s likely not always that
simple. Individuals at any level of an organization
may be overly optimistic about certain courses of
action, rely too much on specific pieces of informa-
tion (and people), or simply interpret the objective
through too narrow a lens (that may even run coun-
ter to other views on how to achieve these goals).
Within the behavioral science field, these are
referred to as cognitive biases and they exist in
many endeavors, not just capital planning. These
same biases can explain why we are too optimistic
about our retirement portfolios, can rely solely on
the opinions of experts in matters of health, and
narrowly frame our car buying decisions based on
a single attribute, such as fuel efficiency—ignoring
safety features, price, and aesthetic design. In the
language of the behavioral sciences, these translate
into the optimism bias, expert bias, and narrow
framing, respectively.
Though these biases, and many others, are ex-
tensively covered within the academic literature
and other fields, they are typically not as salient in
matters of capital planning.3 Despite this often lack
of coverage, the evidence from our research sug-
gests they may be no less prevalent.
In this article, we dissect which attributes can
help us identify these biases. We close with cases
from the US Navy and a large telecommunica-
tions provider that highlight how they can manifest
throughout the capital planning processes.

The balancing act
Whether launching a new product, investing in equipment, or
weighing the
merits of an acquisition, corporate executives typically rely on
their capital
planning process to help shape these high-stakes decisions.
Shareholders,
creditors, and employees alike expect management to take this
obligation
seriously, and get it right consistently. Firms that excel in
capital planning can
be amply rewarded, but this is often easier said than done.
Capital bias
2
BIASES can arise throughout many areas of daily life. From
how we choose a retirement plan to picking out jams at the
grocery store,
we often make unconscious, suboptimal decisions.4
Capital planning decisions may be no different.
From the original Nobel Prize-winning work of
psychologists Amos Tversky and Daniel Kahneman
to more recent findings, more than 80 different
cognitive biases have been identified over the last
40 years.5 Of these, three common biases seem to
stand out as likely to wreak havoc on capital deci-
sion-making: the optimism bias, expert bias, and
narrow framing.6 Here’s an in-depth look at how

they typically work, and how organizations can
avoid succumbing to their influence.
The optimism bias: Fueled
by overconfidence and
uncertainty avoidance
Optimism, while not categorically bad, is often
closely tied to overconfidence. Known to minimize
uncertainty, overconfidence can lead to perilous
outcomes. In his book, Thinking, Fast and Slow,
Daniel Kahneman recounts a multiyear study in-
volving autopsy results. Physicians surveyed said
they were “completely certain” with their diagnosis
while the patient was alive, but autopsies contra-
dicted those diagnoses 40 percent of the time.7
Another long-term study asked chief financial of-
ficers (CFOs) to predict the performance of a stock
market index fund, along with their own company’s
prospects. When asked to give an 80 percent confi-
dence internal (that is, provide a range of possible
outcomes they are 80 percent certain results will
fall within), only 33 percent of the results actually
fell within their estimates—and most miscalculated
in an overly optimistic manner.8 Interestingly, the
same CFOs who misjudged the market, misjudged
the return on investment (ROI) of their own proj-
ects by a similar magnitude.9 Kahneman explains
that people defer to overconfident and optimistic
predictions due to our distaste for uncertainty. If
the CFOs provided a broader, vaguer estimate, they
may fear perceptions that they weren’t up to the

task. This, in turn, could lead to decision paralysis
(that is, the inability or unwillingness to make a de-
cision due to such broad estimates) or could make
them appear inept or unqualified to do the job.
Choreographing the
optimism bias, expert bias,
and narrow framing
Most people accept
that overconfidence
and optimism exist.
It is far more difficult,
however, to identify
these behaviors while
they are happening.
3
Most people accept that overconfidence and
optimism exist. It is far more difficult, however, to
identify these behaviors while they are happening.
Here are two methods to consider using to deter-
mine if excessive optimism is setting in within your
organization:
Take a survey of past performance. Like
the CFO study, compare past projections to real-
ity. If the estimates systematically proved more op-
timistic than reality, there may be evidence of ex-
cessive optimism. But make sure you avoid letting
hindsight dictate this analysis too much. In the case

of individual performance, for example, if a man-
ager did exceedingly well in the past, leaders should
not assume he or she will achieve the same level of
performance in the future. (We will cover this more
in our discussion on expert bias).
Focus on data, not just narratives, to
make decisions. When we have little information
to go on, it can be easier to manufacture a coherent,
overly positive story to fill in the blanks. But those
decisions rarely end up to be solid ones. In profes-
sional sports, many have cited “intangibles” as the
reason they picked a player to be on their team—
only to regret the decision shortly down the road
when the data suggests these intangible character-
istics aren’t leading to tangible victories. When data
is scarce or ambiguous, it can be easier for the mind
to form a more confident narrative based upon an-
ecdotal evidence. But stories shouldn’t be enough to
go on when making big decisions, such as multimil-
lion-dollar capital decisions.
The expert bias: What
happens when we rely
upon the “expert”?
Often, we are guiltiest of believing and act-
ing upon overly optimistic views when they derive
from “experts.” This could be your company’s lead
software engineer, the vice president of sales who
knows “what the customer really wants,” or even
the CEO. When we simply accept an expert’s opin-
ion or even our own, vs. seeking out additional in-
formation from a variety of sources, we fall victim
to the expert bias.

How bad can it get? In many cases, the experts
can prove to be no better at making predictions
than random chance would be. In his book, Ex-
pert Political Judgment, Philip Tetlock analyzed
more than 20 years of political pundits’ predictions
on a variety of policy and economic outcomes.10
When tracked (but not necessarily held account-
able), these experts performed about as well as they
would had they randomly guessed. Even more dis-
turbing, with greater fame usually comes greater
inaccuracy—a stark illustration of how people value
confidence over uncertainty.
One could argue that there is a big difference
between heeding the advice of a TV personality and
an analyst who is augmenting their predictions with
data. For the most part, we would likely agree, but
following even the best expert can also be danger-
ous.11 Just because someone was the most accurate
in the past does not mean we should only rely on his
or her opinions going forward.
Illustrating this point, one study asked MBA
students to predict six economic indicators by ei-
ther relying solely on the most accurate economist
based on past performance or an average of three to
six well-respected economists’ forecasts.12 While 80
percent of the students chose to rely on the single
How bad can it get? In
many cases, the experts
can prove to be no better
at making predictions
than random chance
would be.

Capital bias
4
top performer, the average estimates routinely per-
formed better. This showed that when making de-
cisions, relying on a number of informed opinions
can be better than chasing a top expert’s past per-
formance.
These studies, along with the conversation on
optimism suggest two things: First, a display of
confidence does not necessarily translate into better
results. Instead, it may signal a degree of ignorance
(or arrogance). Second, a good group of people
making a decision usually outweighs relying on the
“best” person to make the decision.
Narrow framing: Narrow
perspectives lead to
wide miscalculations
Another common, potentially perilous behav-
ior people often exhibit when making decisions is
engaging in narrow framing. Here, people isolate
problems, regardless of how broadly defined, into
smaller, individual decisions. So rather than aggre-
gating decisions into a portfolio of interdependent
choices, they tackle them individually. At face value,
this may sound intuitive. In practice, though, it can
lead to the mismanagement of risk and an isolated
view of problems.

Consider this hypothetical question from Tver-
sky and Kahneman:13
Which would you prefer?
(A) A guaranteed $240 reward or
(B) A 25 percent chance to win a $1,000
reward with a 75 percent chance to win $0.
In this case, more than 80 percent of respon-
dents chose the sure $240. Though, simple utility
maximization would suggest that option B has a
higher expected value of $250 (25 percent x $1,000
= $250).
They offer another hypothetical question involv-
ing losses:
Which would you prefer?
(C) A sure loss of $750 or
(D) A 75 percent chance to lose $1,000
with a 25 percent chance to lose nothing.
When a clear loss is at stake, 87 percent pre-
ferred option D, even though both options offered
the same expected value of losing $750. Reframing
the problem as a loss led to more risk-seeking be-
havior than the first example. So why explore these
dry hypotheticals? It shows that in some cases, peo-
ple are risk-averse (“Give me the sure $240”) and in
others, they are risk-seeking. (“I would rather have
a 25 percent chance to lose nothing than definitely
lose $750.”)

If these risks are not weighed and measured as a
total portfolio, our views and preferences may vary
as well. In another essay, Daniel Kahneman and
Dan Lovallo describe the dangers of narrow framing
in a corporate scenario.14 Picture a company with
two groups submitting capital planning proposals:
one group is in a bad position and has to choose be-
tween a guaranteed loss or the high likelihood of an
even larger loss. Now consider a different group in
the same company. This group has done well his-
torically and can stay the course and make the same
amount of money or take a marginal risk to make
even more. If looked at in isolation, the company
5
will most likely be risk-seeking for the first group
and risk-averse for the second. Instead, this organi-
zation would be better off aggregating both groups’
options and analyzing the problem set as a portfolio
of risk—rather than one of isolation.
With this in mind, it is clear that many different
factors can influence our frame of view in isolation.
Like the chasing the expert discussion, it’s feasible
a high performer who submits a capital project pro-
posal with excessive risk factors could be given too
much leeway because of his or her status.
Alternatively, hindsight can lead decision mak-
ers to view a new project too skeptically—even if it

originated from a sound strategy. A study of NBA
game strategies suggests that little information can
be gleaned from narrow wins or losses in individual
basketball games. Despite this information, after
a close loss, NBA coaches are much more likely to
overhaul their entire strategy.15 So it’s important
to note that, when examining choices in isolation,
people can be influenced by any number of external
factors that may or may not be relevant.
Kahneman and Lovallo assert that the best way
to mitigate narrow framing is twofold: First, orga-
nizations should utilize a process that groups to-
gether problems that, on the surface, may appear to
be different. Second, this process must also include
an evaluation element and use quality metrics that
properly align with the organization’s goals.16
Now that we have a better sense of how biases
work, we can explore how to mitigate them in capital
decision-making. The following two real-life exam-
ples will explore how it could work during two key
process steps: planning and prioritization. For the
planning stage, we illustrate how the US Navy con-
ducted their top-down planning and target-setting
to avoid narrow framing when field managers de-
veloped capital requests. The second case features
a large telecommunications provider that improved
its prioritization process by pooling expert opinion
and mitigating the effects of excessive optimism.
Capital bias
6

IN 2008, only 1 percent of the Navy’s energy con-sumption
came from renewable resources such as solar, wind, and
biofuels.17 To address this, the
Department of the Navy (DON) set aggressive en-
ergy goals that included having “50 percent of DON
energy consumption come from alternative sources”
by 2020.18
Switching to alternative sources of energy would
increase the Navy’s energy security and indepen-
dence. More alternative energy would offer the
DON the means to protect and produce enough en-
ergy to sustain daily operations, along with the abil-
ity to operate autonomously if a supply disruption
were to occur.
There’s typically no question to the merits of the
Navy decreasing its energy reliance on others. But
consider those tasked with making the capital re-
quests during the planning stage. In 2009, the Navy
Installations Command organized its capital plan-
ning process to align its maintenance spending with
the new energy goals.
Typically, capital requests sent to the Navy In-
stallations Command were framed through the
scope of need and cost. For instance, if someone
wanted to request a new roof for a building, they
would have to consider the cost and provide justifi -
cation for the need to replace it. In addition, the In-
stallations Command was weighing anywhere from
400 to 600 capital requests a year (approximately
$1 billion in annual funding requests).

Now, what if someone requests not only to re-
place the roof but also to install solar panels? How
does this request compare to another asking to re-
place a dying furnace with a new, more expensive,
energy-efficient one?
Given the many variables and the broad set of
maintenance requests, how could the Navy estab-
lish an appropriate framework to minimize bias?
In the past, they used a very common scoring
method: They would organize the request into tiers.
A “top” tier demonstrated high value in pursuing
a project while a “bottom” tier showed little value.
By not linking to specific, observable metrics, this
tier system lacked specificity and kindled an envi-
ronment for biases and inefficiency to grow. Field
managers had to develop business cases using their
own metrics or expertise, while project managers
would make requests based on a local view and not
on the bigger picture requirements of the organiza-
tion. The Navy realized it needed a new method to
achieve better results.
What does “better” look like?
The Navy decided it needed a better universal
success metric than a tiered system—a reliable way
to compare the furnace with the solar roof requests.
To combat narrow framing, according to Kahneman
and Lovallo, an organization needs a way to group
together requests that appear superficially different.
The new frame of reference needed to incorpo-
rate costs and energy efficiency. Under the current
program, it was like asking someone if they pre-

ferred a safe car or a fuel-efficient one. Intuitively,
we know people are rarely holistically in one catego-
ry or the other, so why should capital requests lean
completely on one feature as well?
To make the decision process more fluid, the
DON agreed that reducing carbon pounds con-
Mitigating biases in planning:
The US Navy
7
sumed adequately represented the energy goals
metric. Further, all requests had a dollar value as-
signed. By developing a more complete framing
metric combining these two parameters, all propos-
als could be translated into carbon pounds reduced
per dollar. This decreased the reliance on the best
narrative or some moving target of achievable out-
comes.
Secondly, the Navy used this metric to create an
expected “break-even” point for each maintenance
project.19 Utilizing these new metrics, project man-
agers were better able to develop energy proposals
and leaders had an easier frame to compare a di-
verse portfolio of requests.
To measure the efficacy of the new proposal pro-
cess, the Navy first ran through the prior year’s proj-
ects to see how they would have looked under the

new planning process. Had they used the new meth-
odology, the finance team would have seen that the
accepted projects would return an average of only
84 percent of the costs of the projects and reduce
four carbon pounds for every dollar spent.
Once everyone was able to reframe the propos-
als to align with the Navy’s goals, performance sub-
stantially increased. After the first year, 32 pounds
of carbon were reduced for every dollar spent while
returning savings of 224 percent to cost. By year
two, these numbers increased to 97 pounds of car-
bon reductions per dollar, a savings of 316 percent
(see figure 1).
Through better optimization of their portfolio
and improved alignment of proposals from man-
agers, the DON seems to overcome narrow fram-
ing and experienced growth in both financial and
strategic goals. According to the DON, defining and
implementing a metrics-based value framework re-
sulted in more aligned project proposals, improved
decision-making in capital planning, and a signifi-
cantly more impactful energy management strategy.
The new frame of reference needed to incorporate costs
and energy efficiency. Under the current program, it
was like asking someone if they preferred a safe car or a
fuel-efficient one.
Deloitte Insights | deloitte.com/insights
Figure 1. Carbon pounds saved per dollar
The Navy’s use of a universal metric for energy

goals increased its performance significantly
Before
implementation
Year 1
0
20
40
60
80
100
120
Year 2
Source: Deloitte Consulting LLP.
Capital bias
8
IN 2014, one telecommunications company’s mul-tibillion-
dollar capital budget took a page straight out of Michael
Lewis’s bestseller, Moneyball: The
Art of Winning an Unfair Game. At this company,
the prioritization process that determined which
project proposals were approved or denied started

as an “unfair game.” The expert bias was allowed to
run rampant. Because this firm’s success largely de-
pended upon the technology that fueled its service
offering, senior management empowered its engi-
neers to drive the capital spending process.
Those involved with the prioritization process
observed that the engineers, through “gold-plated”
business cases, routinely received their wish lists of
projects, while other departments learned to accept
this preferential treatment.
Identifying the expert
and optimism biases
Many elements led to the manifestation of the
expert bias and excessive optimism at this company.
Fueled by historical successes, the technology divi-
sion built up a reputation as a “winning bet.” This
led to an increase in reliance on engineers that be-
fore long, turned the capital spending process into
a technology-dominated exercise. Simultaneously,
proposals from other departments, such as mar-
keting and finance, were increasingly crowded out.
Meanwhile, as the overreliance on experts increased,
the need for data-backed validation decreased.
But then, the telecommunications market quick-
ly changed. Excessive optimism and the overreli-
ance on experts blinded the organization to chang-
ing industry trends such as the commoditization
of wireless networks. Now, new market pressures
transformed into shareholder pressures. Suddenly,
the organization was expected to cut its capital bud-
get by 20 percent compared to plan.

Leveling the playing field
of the “unfair game”
In Moneyball, Lewis chronicled how the Oak-
land A’s were able to circumvent baseball scouts’
anecdotal recommendations (that is, their expert
bias). Instead they relied on unbiased data mod-
els to achieve one of the best records in all of base-
ball—despite having one of the lowest payrolls in
the league. The CFO of the telecommunications
company sought similar outcomes within his capi-
tal budgeting process; he had to find a way to cut 20
percent while avoiding shareholder value destruc-
tion. Like the Oakland A’s, he knew they needed to
manage these biases by better managing their data
insights capabilities.
Similar to the case with the Navy, the commu-
nications company used an inclusive approach to
developing the decision criteria. Specifically, they
implemented a risk-adjusted benefit-to-cost met-
ric to quantify all investment proposals. Instead of
simply relying on the opinions of experts, this new
system attempted to capture their insights and con-
vert them from opinion into unbiased, data-driven
recommendations. For instance, while estimating
traditional project costs was familiar to managers,
it was more challenging to measure and compare
the value of diverse investments such as network
projects and maintenance projects. To estimate the
value of network expenditures, they considered the
Prioritization:
Leveling the playing field

9
population density of the area and the lifetime capi-
tal spend and operating costs to determine an aver-
age unit value for each local region. To evaluate the
impact of criticality for maintenance projects, they
estimated the potential lost revenue, percentage of
subscribers affected, and the likely timing of disrup-
tions.
But making more data-driven decisions is not
always enough. It is often important to communi-
cate these insights in a manner that is easy for deci-
sion makers to interpret.20 For this reason, the data
was aggregated into a portfolio optimization tool,
and a data visualization dashboard was overlaid on
top of this portfolio engine. In an easily compre-
hended graphic, management could now easily see
how each project ranked, which facilitated a more
transparent conversation among a broader range
of decision makers, thereby minimizing the expert
bias, and the reliance on heuristics (referred to as
“mental rules of thumb”).
With an agreed-upon framework and effective
portfolio tools, decision makers had more construc-
tive and efficient conversations to arrive at their
ultimate funding decisions. Consequently, manage-
ment was able to reach consensus faster and reduce
their budget by the board-targeted 20 percent.

In addition, shortly after launching the prioriti-
zation process, newly freed up capital was deployed
to finance a strategic acquisition.
Capital bias
10
NO matter the organization, biases will likely influence the
capital decision-making pro-cess if left unchecked. It seems
natural to
avoid uncertainty in favor of excessive optimism
(especially if we are the ones making the prediction).
Even if we are not making the decision, we frequent-
ly put too much weight on our experts’ shoulders.
And with high-dollar, high-risk decisions, we fre-
quently try to make the decision easier on ourselves
by narrowly framing the problem through a less
holistic lens.
Thankfully, there are a number of ways you can
use behavioral science techniques to prevent these
cognitive biases from negatively impacting high-
stakes decisions. (See figure 2 for a review). When
assessing your own capital decision-making process,
consider asking yourself:
• How are we submitting proposals? To
avoid narrow framing and the expert bias, con-
sider seeking capital spending proposals from a
diverse set of employees and departments. By
broadening your portfolio of submissions, you
can decrease the likelihood of only seeing the

world through a single lens.
• How are we assessing proposals? Consider
replacing catchy narratives with coherent, con-
sistent metrics. Doing so could level the playing
field across (hopefully) a broad set of proposals
and reduce much of the noise throughout the
decision-making process.
A financial decision is typically fueled less by the
underlying capital and more by the people tasked
with driving the decision. With this in mind, before
you choose where to spend your capital, you should
determine how you want to make those decisions.
Stripping away your own
organization’s biases
Figure 2. A summary of capital decision biases
Capital decision bias What it typically looks like How to
possibly address it
Optimism bias
• Overconfidence in estimates
• Narrow range of prediction
• Opting for narratives over
data points
• Track predictions against reality
• Remove anecdotal “proof points”
from the decision-making process

Expert bias
• Relying on a single decision maker
• “Chasing” a person’s or group’s
past performance
• Pool recommendations from a
diverse set of qualified individuals
• Do not chase past performance
Narrow framing • Focusing on a single attribute to
make the decision
• Determine a portfolio of
relevant metrics
• Make capital decisions in aggregate
rather than on a case-by-case basis
Source: Deloitte Consulting LLP. Deloitte Insights |
deloitte.com/insights
11
1. Deloitte conducted an analysis of the S&P companies over a
20-year period and found no meaningful correlation
between capex as a percentage of revenue and ROIC. Nor was
there a meaningful correlation between growth
in capex as a percentage of revenue and ROIC.
2. Over 60 percent of finance executives surveyed “are not

confident” in their organization’s ability to make optimal
capital allocation decisions: Deloitte webcast, “Capital
expenditure planning: A structured, portfolio approach,”
May 23, 2013, 1,280 respondents; Deloitte webcast, “Energy
management: How an effective strategy can im-
prove your budget and drive value,” July 27, 2011.
3. Kenneth A. Kriz, “Cognitive biases in capital budgeting,”
Wichita State University, accessed May 2, 2017.
4. Ruth Schmidt, Frozen: Using behavioral design to overcome
decision-making paralysis, Deloitte University Press,
October 7, 2016.
5. Timothy Murphy and Mark Cotteleer, Behavioral strategy to
combat choice overload: A framework for managers,
Deloitte University Press, December 10, 2015.
6. We …
1
CFO Insights
Pricing for profitability:
What’s in your pocket?
CFOs have long been confident in their ability to affect the
cost side of the margin equation. But with multiple layers
of overhead wrung out of the system and product costs
rising unabated, unlocking the price side has taken on a
certain sense of urgency.
Effectively implementing a pricing strategy, however, is
more than simply viewing products on a cost-plus basis.

It is also more than tracking pricing performance at the
aggregate level. Instead, the promise of pricing is in the
details: an effective strategy should rely on understanding
economic profitability at the customer, product, and
segment level—the so-called pocket margin—and using
that information to inform overall decision-making.
To get to that level of detail, though, may require
overcoming cultural, data, and compensation barriers to
determine pocket costs. The effort is worth it, however:
research has shown that pricing has up to four times
more impact on profitability than other improvements.1
In this issue of CFO Insights, we’ll look at the power of
understanding pricing at the customer level and discuss
ways to install pricing disciplines that deliver consistent,
positive results.
What are pocket margins?
Clearly, finance chiefs recognize the power of pricing. In
the Q2 2012 CFO SignalsTM survey, three-fourths of CFOs
reported that their finance organizations were at least
moderately involved in tracking and reporting pricing
performance and profitability.2 In addition, more than
half reported substantial involvement in aligning pricing
strategies with corporate strategies, managing exceptions
to general policies, and setting pricing based on data and
analytics.3
It’s also clear that finance chiefs are not afraid to wield
the pricing baton. That same survey found that 65% of
CFOs reported having raised prices, and 42% said more
increases were coming. 4 Still, how they raised prices was
not totally apparent, and when it came to profitability
analyses, customer-level profitability was comparatively
less utilized and influential than, say, geography-level
profitability analysis.5

But it is the customer-level economic profitability that can
offer an untapped reservoir of information—and potential
for improved margins. For example, which customer
segments are being given unwarranted volume discounts;
which are unaffected by slight price increases; and where
are delivery promises being made that materially increase
transaction cost, but are not charged for? To get at that
level of information, however, may require moving past
the aggregate view of pricing (gross margin, net margin)
that finance typically demands to the “pocket” view that
takes into account everything from payment terms to
freight costs in order to identify the true profitability of a
transaction (that is, gross margin less detailed allocations
of fixed costs and SG&A). And from that information,
CFOs can extrapolate how profitable individual products,
customers, and channels are and inform decisions that
include, but are not limited to:
2
• What price premiums should be associated with
products that significantly impact working capital?
• On a regional level, how should we assess and adjust
our product portfolio based on geographic dynamics?
• Instead of subsegmenting the market with multiple
products, are there loss leaders that can be cut from
our portfolio?
• Is discounting being used by our sales force uniformly

across the board, or in a strategic way with our best
customers?
• Are there ways to use the pocket cost information to
effectively increase prices without losing customers?
• Are we waiving our fee policies on low gross margin
transactions and simply breaking even?
Identifying and leveraging pocket information
While the analytic tools exist to identify costs at a pocket
level, the data is often widespread and incomplete, and
frequently siloed. Sales executives typically worry about
revenue and the commissions associated with it; supply-
chain professionals care about containing fuel and other
factors; manufacturing wants the lowest unit costs;
marketing focuses on which discount campaign to offer
next; and all are concerned with optimizing their particular
piece of a product’s life cycle.
But to fully assess pocket costs, finance should identify the
components that add or subtract value from the business
on a marginal basis. Those include factors that are not
part of cost of goods sold (COGS), such as expedited
shipping, fixed-asset or fixed-cost productivity, the cost
of capital included in payment terms, and the various
discounts and promotions offered. And one effective tool
to identify those factors is the price waterfall (see Figure
1). Working backwards from the list price, CFOs can use
the tool to identify margin leakages and create visibility
from a reference list price down to the pocket margin,
including discounts, rebates, and other cost elements.
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Negotiable items Invoiced items Revenue reducers Chargeable
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Source: Deloitte Consulting LLP
3
Moreover, the visual representation makes comparison
with competitors very easy—and offers convincing proof
of where price erodes in the multiple steps between
making and delivering a product.
Such an exercise also allows finance to match revenue
and costs for individual transactions. While a product
that earns 40% margin may look like the a winner in the
product portfolio, if it turns out to be highly engineered
and highly specialized, and requires extra sales support,
it may not be. Instead, it may be the product that earns
20% margin and only has to be packed and shipped that
you should be expanding. Knowing what your costs are
going forward may allow you to make the decisions that

fit into the overall product strategy and build economic
models that:
a. Affect strategy. By making sure everyone involved in
the pricing equation has a proper understanding of the
economics of the business, CFOs can influence not just
pricing policies, but overall business strategy.
b. Educate stakeholders. Having pocket-margin
information can allow a CFO to educate his or her
peers, CEO, and the board about pricing policies that
work. If, for example, the data shows that the sales
and marketing are pushing pricing strategies that sell
products that don’t contribute to the overall value of
the business, those policies can be adjusted.
c. Institute controls. One outcome of pocket costing is
often the exposure of “unwarranted discounting” —
awarding discounts to customers whose volumes do
not justify such action. One solution is to put limits on
who can discount to what level and assign a finance
person to authorize discounts that exceed that level.
d. Create a single version of the truth. Pocket costing
exposes which products or customers are contributing
value and which are not. That single version of the
truth also allows individual functions to make decisions
about resource deployment, such as where distribution
centers should be located, how much product should
be kept in inventory, and how goods should be
delivered.
Five questions for your pricing manager
For CFOs, acquiring and leveraging pocket-pricing
information should start with a series of questions for their

designated pricing managers. Specifically:
1. Who are our most profitable customers according
to the sales force? According to finance? Evaluating
profitability may be a very different process depending
on who is doing the evaluating. While the sales force
may be enamored with a particular customer based
on sheer volume, you may be barely breaking even on
that customer after selling and servicing costs are taken
into consideration. Armed with customer-profitability
information, however, a CFO can figure out where
unwarranted discounts are being given or where special
handling may be inflating costs. It also gives CFOs the
profitability data to reassess which customers can be
offered discounts and which can’t.
Figure 2. Pricing has 3-4 times the effect on profitability than
other improvements
1% improvement
Price
Variable cost
Unit volume
Fixed cost
Source: Compustat, Deloitte Analysis
Note: Impact estimate is based on the average Fortune 1000
company
12.3%
6.7%

3.6%
2.6%
Impact on operating profit
4
2. What are our transaction patterns, and what do
they tell us? Transactions over time speak volumes.
Take a customer with average gross margins of, say,
40% that has a large portion of annual transactions
under $100. If it costs $20 on average just to deliver the
goods, and sales is offering free delivery on these small
orders, it becomes very difficult to conclude that the
revenue stream is profitable. Gaining visibility into such
margin erosion can allow a CFO to challenge strategic
decisions, such as offering daily deliveries, or at least
explore the option of going back to the customer to
renegotiate terms so both parties win.
3. How do we allocate pocket costs in determining
price? Often in making pricing decisions, it is not
readily apparent how to allocate pocket costs. What we
typically observe is a smooth distribution of those costs.
So while at an aggregate level everything may appear
profitable, in reality most companies have winners and
losers—they just don’t know which is which. CFOs
should develop a better policy for allocations in order to
make better pricing choices.
4. Do we have the analytical talent to accurately
decipher pocket margins? These days, it is essential to

have finance staff, particularly in finance, planning, and
analysis (FP&A), who can analyze pricing-trends data by
geography, customer profile, product line, and other
dimensions. As in other areas of finance, however, such
specialized analytical knowledge is in short supply, and
CFOs need to figure out how to build that capability
either by developing talent in-house or hiring from
outside. In this case, CFOs should also be open to
developing someone from sales or marketing who
is knowledgeable about individual customer pricing
information. The point is that accounting knowledge
is insufficient in this case—you need someone who
has some operational knowledge to attain a better
allocation of costs.
Endnotes
1 Compustat, Deloitte Consulting LLP, 2009.
2 CFO Signals, Deloitte U.S. CFO Program, see 2Q2012.
5. Do our compensation practices help or hinder
our pricing strategy? Since sales and marketing
professionals are often compensated differently, it can
lead to pricing decisions that do not create value. For
example, if sales executives are paid commissions on
revenue or gross profit, they often don’t care if the
company charges for hazmat or has a large safety
inventory. None of that shows up in gross profit, but
it does affect overall financial performance. For CFOs,
aligning the compensation plan with pricing and
profitability objectives takes a true understanding of the
economics of the business, so the rewards offered are
aligned and are commensurate with the goals of the
business.

Out-of-pocket benefits
To adequately price in today’s competitive marketplace,
finance should build economic models that maximize
sale-by-sale profit. Central to creating those models is
a granular understanding of customer analytics on a
product-by-product basis.
The companywide deployment of such information can
help clear the way for informed decisions about everything
from channels and products to sales and advertising.
In addition, once a company has an understanding of
the impact on individual products and customers, that
information can offer a window into other areas of
operations, such as the proper levels of safety stock and
the cost-effective delivery methods.
Finally, gaining a handle on pocket margins can give
CFOs another tool for growth and allows them to further
drive the alignment of pricing approaches with corporate
strategies. Pricing, after all, can expand earnings faster
than cost cutting.
What’s in your pocket?
5
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Vos Contacts
Valérie Flament
Associée Conseil – Transformation de la Fonction Finance
[email protected]
Tel. : +33 1 40 88 24 64
Katia Ruet
Directeur Conseil – Transformation de la Fonction Finance
[email protected]
Tel. : +33 1 40 88 43 43

A propos du Deloitte CFO Program
Déployé en France et au sein du réseau international
de Deloitte, ce programme rassemble les
compétences, connaissances et savoir-faire nécessaires
pour accompagner les directeurs financiers dans leur
rôle, notamment leur contribution aux orientations
stratégiques et leur agilité dans un environnement
changeant.
Pour plus d’information sur le Deloitte CFO Program,
rendez-vous à l’adresse :
www.deloitte.com/us/thecfoprogram.
McKinsey Quarterly
The power of pricing
February 2003 | ArticleBy Michael V. Marn, Eric V. Roegner,
and Craig C. Zawada
Transaction pricing is the key to surviving the current
downturn—and to
flourishing when conditions improve.
https://www.mckinsey.com/business-functions/marketing-and-
sales/our-insights/the-power-of-pricing#
At few moments since the end of World War II has downward
pressure on prices been so great.
Some of it stems from cyclical factors—such as sluggish
economic growth in the Western

economies and Japan—that have reined in consumer spending.
There are newer sources as well:
the vastly increased purchasing power of retailers, such as Wal-
Mart, which can therefore
pressure suppliers; the Internet, which adds to the transparency
of markets by making it easier to
compare prices; and the role of China and other burgeoning
industrial powers whose low labor
costs have driven down prices for manufactured goods. The one-
two punch of cyclical and newer
factors has eroded corporate pricing power and forced frustrated
managers to look in every
direction for ways to hold the line.
In such an environment, managers might think it mad to talk
about raising prices. Yet nothing
could be further from the truth. We are not talking about raising
prices across the board; quite
often, the most effective path is to get prices right for one
customer, one transaction at a time,
and to capture more of the price that you already, in theory,
charge. In this sense, there is room
for price increases or at least price stability even in today's
difficult markets.

Such an approach to pricing—transaction pricing, one of the
three levels of price management
(see sidebar "Pricing at three levels")—was first described ten
years ago.1 The idea was to figure
out the real price you charged customers after accounting for a
host of discounts, allowances,
rebates, and other deductions. Only then could you determine
how much money, if any, you
were making and whether you were charging the right price for
each customer and transaction.
A simple but powerful tool—the pocket price waterfall, which
shows how much revenue companies
really keep from each of their transactions—helps them
diagnose and capture opportunities in
transaction pricing. In this article, we revisit that tool to see
how it has held up through dramatic
changes in the way businesses work and in the broader
economy. Our experience serving hundreds of
companies on pricing issues shows that the pocket price
waterfall still effectively helps identify
transaction-pricing opportunities. Nevertheless, in view of
evolving business practice, we have greatly
expanded the tool's application. The increase in the number of
companies selling customized products

and solutions or bundling service packages with each sale, for
instance, means that assessing the
profitability of transactions has become much more complex.
The pocket price waterfall has evolved
over time to take account of this transition.
Today, it is more critical than ever for managers to focus on
transaction pricing; they can no longer rely
on the double-digit annual sales growth and rich margins of the
1990s to overshadow pricing shortfalls.
Moreover, at many companies, little cost-cutting juice can
easily be extracted from operations. Pricing is
https://www.mckinsey.com/quarterly/overview
sales/our-insights/the-power-of-pricing
therefore one of the few untapped levers to boost earnings, and
companies that start now will be in a
good position to profit fully from the next upturn.
Advancing one percentage point at a time
Pricing right is the fastest and most effective way for managers
to increase profits. Consider the average
income statement of an S&P 1500 company: a price rise of 1
percent, if volumes remained stable, would

generate an 8 percent increase in operating profits (Exhibit 1) —
an impact nearly 50 percent greater
than that of a 1 percent fall in variable costs such as materials
and direct labor and more than three
times greater than the impact of a 1 percent increase in volume.
Unfortunately, the sword of pricing cuts both ways. A decrease
of 1 percent in average prices has the
opposite effect, bringing down operating profits by that same 8
percent if other factors remain steady.
Managers may hope that higher volumes will compensate for
revenues lost from lower prices and
thereby raise profits, but this rarely happens; to continue our
examination of typical S&P 1500
economics, volumes would have to rise by 18.7 percent just to
offset the profit impact of a 5 percent
price cut. Such demand sensitivity to price cuts is extremely
rare. A strategy based on cutting prices to
increase volumes and, as a result, to raise profits is generally
doomed to failure in almost every market
and industry.
Following the pocket price waterfall

Many companies can find an additional 1 percent or more in
prices by carefully looking at what part of
the list price of a product or service is actually pocketed from
each transaction. Right pricing is a more
subtle game than setting list prices or even tracking invoice
prices. Significant amounts of money can
leak away from list or base prices as customers receive
discounts, incentives, promotions, and other
giveaways to seal contracts and maintain volumes (see sidebar
"A hole in your pocket").
The experience of a global lighting supplier shows how the
pocket price—what remains after all
discounts and other incentives have been tallied—is usually
much lower than the list or invoice price.
This company made incandescent lightbulbs and fluorescent
lights sold to distributors that then resold
them for use in offices, factories, stores, and other commercial
buildings. Every lightbulb had a standard
list price, but a series of discounts that were itemized on each
invoice pushed average invoice prices
32.8 percent lower than the standard list prices. These on-
invoice deductions included the standard
discounts given to most distributors as well as special discounts
for selected ones, discounts for large-

volume customers, and discounts offered during promotions.
Managers who oversee pricing often focus on invoice prices,
which are readily available, but the real
pricing story goes much further. Revenue leaks beyond invoice
prices aren't detailed on invoices. The
many off-invoice leakages at the lighting company included
cash discounts for prompt payment, the cost
of carrying accounts receivable, cooperative advertising
allowances, rebates based on a distributor's
total annual volume, off-invoice promotional programs, and
freight expenses. In the end, the company's
average pocket price—including 16.3 percentage points in
revenue reductions that didn't appear on
invoices—was about half of the standard list price (Exhibit 2a).
Over the past decade, companies have
tried to entice buyers with a growing number of discounts,
including discounts for on-line orders as well
as the increasingly popular performance penalties that require
companies to provide a discount if they
fail to meet specific performance commitments such as on-time
delivery and order fill rates.
By consciously and assiduously managing all elements of the

pocket price waterfall, companies can
often find and capture an additional 1 percent or more in their
realized prices. Indeed, an adjustment of
any discount or element along the waterfall—either on- or off-
invoice—is capable of improving prices
on a transaction-by-transaction basis.
Embracing a wide band
The pocket price waterfall is often first created as an average of
all transactions. But the amount and
type of the discounts offered may differ from customer to
customer and even order to order, so pocket
prices can vary a good deal. We call the distribution of sales
volumes over this range of variation the
pocket price band.
At the lighting company, some bulbs were sold at a pocket price
of less than 30 percent of the standard
list price, others at 90 percent or more—three times higher than
those of the lowest-priced transactions
(Exhibit 2b). This range may seem spectacular, but it is not very
unusual. In our work, we have seen
pocket price bands in which the highest pocket price was five or
six times greater than the lowest.
It would be a mistake, though, to assume that wide pocket price

bands are necessarily bad. A wide band
shows that neither all customers nor all competitive situations
are the same—that for a whole host of
reasons, some customers generate much higher pocket prices
than do others. When a band is wide,
small changes in its shape can readily move the average price a
percentage point or more higher. If a
manager can increase sales slightly at the high end of the band
while improving or even dropping
transactions at the low end, such an increase comes within
reach. But when the price band is narrow,
the manager has less room to maneuver; changing its shape
becomes more difficult; and any move has
less impact on average prices.
Although the lighting company was surprised by the width of its
pocket price band, it had a quick
explanation: the range resulted from a conscious effort to
reward high-volume customers with deeper
discounts, which in theory were justified not only by the desire
to court such customers but also by a
lower cost to serve them. A closer examination showed that this
explanation was actually wide of the

mark (Exhibit 3): many large customers received relatively
modest discounts, resulting in high pocket
prices, while a lot of small buyers got much greater discounts
and lower pocket prices than their size
would warrant. A few smaller customers received large
discounts in special circumstances —unusually
competitive or depressed markets, for instance—but most just
had long-standing ties to the company
and knew which employees to call for extra discounts,
additional time to pay, or more promotional
money. These experienced customers were working the pocket
price waterfall to their advantage.
The lighting company attacked the problem from three
directions. First, it instructed its sales force to
bring into line—or drop—the smaller distributors getting
unacceptably high discounts. Within 12
months, 85 percent of these accounts were being priced and
serviced in a more appropriate way, and
new accounts had replaced most of the remainder. Second, the
company launched an intensive
program to stimulate sales at larger accounts for which higher
pocket prices had been realized. Finally, it

controlled transaction prices by initiating stricter rules on
discounting and by installing IT systems that
could track pocket prices more effectively. In the first year
thereafter, the average pocket price rose by
3.6 percent and operating profits by 51 percent.
In addition to these immediate fixes, the lighting company took
longer-term measures to change the
relationship between pocket prices and the characteristics of its
accounts. New and explicit pocket price
targets were based on the size, type, and segment of each
account, and whenever a customer's prices
were renegotiated or a new customer was signed, that target
guided the negotiations.
Pocket margins become more relevant
For companies that not only sell standard products and services
but also experience little variation in the
cost of selling and delivering them to different customers,
pocket prices are an adequate measure of
price performance. Today, however, as companies seek to
differentiate themselves amid growing
competition, many are offering customized products, bundling
product and service packages with each
sale, offering unique solutions packages, or providing unique

forms of logistical and technical support.
Pocket prices don't capture these different product costs or the
cost to serve specific customers. For
such companies, another level of analysis—the pocket margin—
is needed to reflect the varying costs
associated with each order. The pocket margin for a transaction
is calculated by subtracting from the
pocket price any direct product costs and costs incurred
specifically to serve an individual account.
One North American company, which manufactures tempered
glass for heavy trucks and for farm and
construction machinery, sharply increased its profits by
understanding and actively managing its pocket
margins. Each piece of the company's glass was custom-
designed for a specific customer, so costs varied
transaction by transaction. Other costs differed from customer
to customer as well. The company's
glass, for example, was frequently shipped in special containers
that were designed to be compatible
with the customers' assembly machines. The costs of retooling
and other customer-specific services
varied widely from case to case but averaged no less than 17
percent of the target base price (Exhibit
4a).

As with pocket prices, a fuller picture emerges when a company
examines each account and creates a
pocket margin band. The glass company's pocket margins
ranged from more than 60 percent of base
prices to a loss of more than 15 percent of base prices (Exhibit
4b). When fixed costs were allocated, the
company found that it required a pocket margin of at least 12
percent just to break even at the current
operating level. More than a quarter of the company's sales fell
below this threshold.
Traditionally, the pricing policies of the glass company had
focused on invoice prices and standard
product costs; it paid little attention to off-invoice discounts or
extra costs to serve specific customers.
The pocket margin band helped it identify which individual
customers were more profitable and which
should be approached more aggressively even at the risk of
losing their business. The company also
uncovered narrowly defined customer segments (for example,
medium-volume buyers of flat or single-
bend door glass) that were concentrated at the high end of the
margin band. In addition, it evaluated its

policies for some of the more standard waterfall elements to
ensure that it had clear objectives,
accountability, and controls for each of them—for instance, it
decided to base volume bonuses on
stretch performance targets and to charge for last-minute
technical support. By focusing on and
increasing sales in profitable subsegments, pruning less
attractive accounts, and making selective policy
changes across the waterfall elements, the company pushed up
its average pocket margin by 4 percent
and its operating profits by 60 percent within a year.
Taming transactions
The game of transaction pricing is won or lost in hundreds,
sometimes thousands, of individual decisions
each day. Standard and discretionary discounts allow percentage
points of revenue to drop from the
table one transaction at a time. Companies are often poorly
equipped to track these losses, especially
for off-invoice items; after all, the volumes and complexity of
transactions can be overwhelming, and
many items, such as cooperative advertising or freight
allowances, are accounted for after the fact or on

a company-wide basis. Even if managers wanted to track
transaction pricing, it has often been
impossible to get the data for specific customers or transactions.
But some recent technical advances
have helped remove this obstacle; enterprise-management-
information systems and off-the-shelf
custom-pricing software have made it easier to keep tabs on
transaction pricing. Managers can no
longer hide behind the excuse that gathering the data is too
difficult.
Current price pressures should go a long way toward removing
two other obstacles: will and skill. In the
booming economy of the 1990s, robust demand and cost-cutting
programs, which drove up corporate
earnings, made too many managers pay too little attention to
pricing. But now that a global economic
downturn has slowed growth and the easiest cost cutting has
already occurred, the shortfall in pricing
capabilities has been exposed. A large number of compani es
still don't understand the untapped
opportunity that superior transaction pricing represents. For
many companies, getting it right may be
one of the keys to surviving the current downturn and to
flourishing when the upturn arrives. It has

never been more crucial—or more possible—to learn and apply
the skills needed to execute superior
transaction-price management.
About the author(s)
Mike Marn and Eric Roegner are principals in McKinsey's
Cleveland office, and Craig Zawada is a
principal in the Pittsburgh office.
sales/our-insights/the-power-of-pricing#
sales/our-insights/the-power-of-pricing
Capital Expenditure Decisions
Copyright © 2020 McGraw-Hill Education. All rights reserved.
No reproduction or distribution without the prior written
consent of McGraw-Hill Education.
16-1
Chapter 16

Chapter 16: Capital Expenditure Decisions
Learning Objective 16-1 – Use the net-present-value method
and the internal-rate-of-return method to evaluate an investment
proposal.
16-2
Learning Objective 16-1. Use the net-present-value method and
the internal-rate-of-return method to evaluate an investment
proposal.
Discounted-Cash-Flow Analysis
16-3
Decisions involving cash inflows and outflows beyond the
current year are called capital-budgeting decisions.
Discounted-cash-flow analysis accounts for the time value of

money in such decisions.
Managers in all organizations periodically face major decisions
that involve cash flows over several years. Decisions involving
the acquisition of machinery, vehicles, buildings, or land are
examples of such decisions. Other examples include decisions
involving significant changes in a production process or adding
a major new line of products or services to the organization’s
activities.
Decisions involving cash inflows and outflows beyond the
current year are called capital-budgeting decisions.
Discounted-cash-flow analysis accounts for the time value of
money. It is a mistake to add cash flows occurring at different
points in time. The proper approach is to use discounted-cash-
flow analysis, which takes into account the timing of the cash
flows. There are two widely used methods of discounted-cash-
flow analysis: the net-present-value method and the internal-
rate-of-return method.
(LO 16-1)
Net-Present-Value Method
1. Prepare a table showing cash flows for each year,
2. Calculate the present value of each cash flow using a
discount rate,
3. Compute net present value,

4. If the net present value (NPV) is zero or positive, accept the
investment proposal. Otherwise, reject it.
16-4
These four steps constitute a net-present-value analysis of an
investment proposal:
1. Prepare a table showing the cash flows during each year of
the proposed investment.
2. Compute the present value of each cash flow, using a
discount rate that reflects the cost of acquiring investment
capital. This discount rate is often called the hurdle rate or
minimum desired rate of return.
3. Compute the net present value, which is the sum of the
present values of the cash flows.
4. If the net present value (NPV) is equal to or greater than
zero, accept the investment proposal. Otherwise, reject it. (LO
16-1)
Net-Present-Value Method (2/5)
Mattson Co. has been offered a five year contract to provide
component parts for a large manufacturer.
16-5

Here a table has been prepared by Mattson’s accountant
showing the cash flows during each year of a proposed
investment to provide component parts to another manufacturer.
The proposal requires special equipment that would need to be
purchased if the proposal is accepted, associated cash revenue
and expense items are also included. (LO 16-1)
At the end of five years, the working capital will be released
and may be used elsewhere by Mattson.
Mattson uses a discount rate of 10%.
Should the contract be accepted?
16-6
Other information available is that the working capital required
to accept the proposal will be returned at the end of the
contract, and Mattson requires a minimum of a ten percent
hurdle rate.
We need to decide whether we should accept or reject the
proposal. (LO 16-1)

Annual net cash inflows from operations
16-7
First, we calculate the net annual cash inflows to Mattson.
Mattson would have net cash inflows of $80,000 per year for the
next five years if the proposal is accepted. (LO 16-1)
Mattson should accept the contract because the present value of
the cash inflows exceeds the present value of the cash outflows
by $85,955. The project has a positive net present value.
16-8
Two costs that would be incurred immediately if the proposal is
accepted are the investment in equipment and the immediate
need for working capital. The present value of those
expenditures are the same, because we would purchase the
equipment today and need the working capital today.
The annual net cash inflows would be received over a five-year

period, so we must bring that value back to the present, in order
to compare apples to apples. The present value of the net cash
inflows is $303,280.
We will also need to reline the equipment in three years at a
cost of $30,000. The present value of this amount is $22,530.
In addition, when the contract is completed, we will sell the
equipment. The present value of the salvage value is $3,105.
We then add together all of the present values. A positive net
present value means that the value of accepting the proposal
exceeds the negatives, and that the return on this investment is
at least as high as the hurdle rate. Considering the net present
value method only, this proposal should be accepted by
Mattson. (LO 16-1)
Internal-Rate-of-Return Method
The internal rate of return is the true economic return earned by
the asset over its life.
The internal rate of return is computed by finding the discount
rate that will cause the net present value of a project to be zero.
16-9
An alternative discounted-cash-flow method for analyzing
investment proposals is the internal-rate-of-return method.
An asset’s internal rate of return, or time-adjusted rate of return
is the true economic return earned by the asset over its life.
Another way of stating the definition is that an asset’s internal

rate of return, IRR, is the discount rate that would be required
in a net-present-value analysis in order for the asset’s net
present value to be exactly zero. (LO 16-1)
Internal-Rate-of-Return Method (2/5)
Black Co. can purchase a new machine at a cost of $104,320
that will save $20,000 per year in cash operating costs.
The machine has a 10-year life.
16-10
A new machine will cost $104,320 and will save Black
Company $20,000 per year in cash operating costs.
This machine will last ten years. (LO 16-1)
Future cash flows are the same every year in this example, so
we can calculate the internal rate of return as follows:
Investment required
Net annual cash flows
= Present value factor
$104,320
$20,000
= 5.216
16-11

The IRR is calculated by taking the amount of the investment
and dividing it by the net annual cash inflows.
This gives us a present value factor to enter into the tables with.
(LO 16-1)
$104,320
$20,000
= 5.216
The present value factor (5.216) is located on Table IV in
Appendix A. Scan the 10-period row and locate the value 5.216.
Look at the top of the column and you find a rate of 14%, which
is the internal rate of return.
16-12
We look in a present value table across the ten-year line until
we find the number that is closest to our calculated factor.
We find our 5.216 factor under the 14% column.
This is the internal rate of return. (LO 16-1)
Here’s the proof . . .
16-13

To prove that 14% is the rate of return, we work backwards and
calculate the net present value to be zero.
The decision rule in the internal-rate-of-return method is to
accept an investment proposal if its internal rate of return is
greater than the organization’s cost of capital, or hurdle rate.
(LO 16-1)
Learning Objective 16-2 – Compare the net-present-value and
internal-rate-of-return methods, and state the assumptions
underlying each method.
16-14
Learning Objective 16-2. Compare the net-present-value and
internal-rate-of-return methods, and state the assumptions
underlying each method.
Comparing the NPV and IRR Methods
Net Present Value

The cost of capital is used as the actual discount rate.
Any project with a negative net present value is rejected.
Internal Rate of Return
The cost of capital is compared to the internal rate of return on
a project.
To be acceptable, a project’s rate of return must be greater than
the cost of capital.
16-15
Calculation of the net present value is relatively simple.
The cost of capital is used as the actual discount rate and any
negative value is rejected because it does not return the hurdle
rate.
The internal rate of return, once calculated is compared to the
hurdle rate.
If the return is greater than the cost of capital, the project is
acceptable. (LO 16-2)
Comparing the NPV and IRR Methods (2/2)
The net-present-value method has the following advantages over
the internal-rate-of-return method:
Easier to use.
Easier to adjust for risk.
16-16

The net-present-value method exhibits two potential advantages
over the internal-rate-of-return method. First, if the investment
analysis is carried out by hand, it is easier to compute a
project’s NPV than its IRR. For example, if the cash flows are
uneven across time, trial and error must be used to find the IRR.
This advantage of the NPV approach is not as important,
however, when a computer is used.
A second potential advantage of the NPV method is that the
analyst can adjust for risk considerations. For some investment
proposals, the further into the future that a cash flow occurs, the
less certain the analyst can be about the amount of the cash
flow. Thus, the later a projected cash flow occurs, the riskier it
may be. It is possible to adjust a net-present-value analysis for
such risk factors by using a higher discount rate for later cash
flows than earlier cash flows. It is not possible to include such a
risk adjustment in the internal-rate-of-return method, because
the analysis solves for only a single discount rate, the project’s
IRR. (LO 16-2)
Assumptions Underlying
Discounted-Cash-Flow Analysis
All cash flows are treated as though they occur at year end.
Cash flows are treated as if they are known
with certainty.
Cash inflows are immediately reinvested at the required rate of
return.
Assumes a perfect capital market.
16-17

Some assumptions are made in discounted cash flow analyses.
In the present-value calculations used in the NPV and IRR
methods, all cash flows are treated as though they occur at year-
end. Most annual operating-cost savings actually would occur
uniformly throughout each year. The additional computational
complexity that would be required to reflect the exact timing of
all cash flows would complicate an investment analysis
considerably. The error introduced by the year-end cash-flow
assumption generally is not large enough to cause any concern.
Discounted-cash-flow analyses treat the cash flows associated
with an investment project as though they were known with
certainty. Although methods of capital budgeting under
uncertainty have been developed, they are not used widely in
practice. Most decision makers do not feel that the additional
benefits in improved decisions are worth the additional
complexity involved. As mentioned above, however, risk
adjustments can be made in an NPV analysis to partially
account for uncertainty about the cash flows.
Both the NPV and IRR methods assume that each cash inflow is
immediately reinvested in another project that earns a return for
the organization. In the NPV method, each cash inflow is
assumed to be reinvested at the same rate used to compute the
project’s NPV, the organization’s hurdle rate. In the IRR
method, each cash inflow is assumed to be reinvested at the
same rate as the project’s internal rate of return.
A discounted-cash-flow analysis assumes a perfect capital
market. This implies that money can be borrowed or lent at an
interest rate equal to the hurdle rate used in the analysis. (LO

16-2)
Choosing the Hurdle Rate
The discount rate generally is associated with the company’s
cost of capital.
The cost of capital involves a blending of the costs of all
sources of investment funds, both debt and equity.
16-18
The choice of a hurdle rate is a complex problem in finance.
The hurdle rate is determined by management based on the
investment opportunity rate.
This is the rate of return the organization can earn on its best
alternative investments of equivalent risk.
In general, the greater a project’s risk is, the higher the hurdle
rate should be. (LO 16-2)
Learning Objective 16-3 – Use both the total-cost approach and
the incremental-cost approach to evaluate an investment
proposal.
16-19

Learning Objective 16-3. Use both the total-cost approach and
the incremental-cost approach to evaluate an investment
proposal.
Comparing Two Investment Projects
To compare competing investment projects, we can use the
following net present value approaches:
Total-Cost Approach
Incremental-Cost Approach
16-20
The total-cost approach uses all of the relevant costs of each
proposal and are included in the analysis.
The incremental-cost approach is where just the difference in
the cost of each relevant item under the two alternative systems
is included in the analysis. (LO 16-3)
Total-Cost Approach

Each system would last five years.
12 percent hurdle rate for the analysis.
MAINFRAME PC _
Salvage value old system $ 25,000 $ 25,000
Cost of new system (400,000) (300,000)
Cost of new software ( 40,000) ( 75,000)
Update new system ( 40,000) ( 60,000)
Salvage value new system 50,000 30,000
===============================================
=
Operating costs over 5-year life:
Personnel (300,000) (220,000)
Maintenance ( 25,000) ( 10,000)
Other costs ( 10,000) ( 5,000)
Datalink services ( 20,000) ( 20,000)
Revenue from time-share 20,000 -
16-21
The computing system used by the city of Mountainview is
outdated. The city council has voted to purchase a new
computing system to be funded through municipal bonds. The
mayor has asked the city’s controller to make a recommendation
as to which of two computing systems should be purchased.
The two systems are equivalent in their ability to meet the
city’s needs and in their ease of use. The mainframe system
consists of one large mainframe computer with remote terminals
and printers located throughout the city offices. The personal
computer system consists of a much smaller mainframe
computer, a few remote terminals, and a dozen personal

computers, which will be networked to the small mainframe.
Mountainview’s accountant has prepared the above schedule of
net costs.
Before we begin the steps of the net-present-value method, let’s
examine the cash flow data in the slide to determine if any of
the data can be ignored as irrelevant. Notice that salvage values
and datalink services do not differ between the two alternative s.
Regardless of which new computing system is purchased,
certain components of the old system can be sold now for
$25,000. Moreover, the datalink service will cost $20,000
annually, regardless of which system is acquired. If the only
purpose of the NPV analysis is to determine which computer
system is the least-cost alternative, then salvage values and
datalink services can be ignored as irrelevant, since they will
affect both alternatives’ NPVs equally. (LO 16-3)
Total-Cost Approach (2/3)
MAINFRAME ($) Time 0 Time 1 Time 2
Time 3 Time 4 Time 5
Acquisition cost computer (400,000)
Acquisition cost software ( 40,000)
System update ( 40,000)
Salvage value 50,000
Operating costs (335,000) (335,000) (335,000)
(335,000) (335,000)
Time sharing revenue 20,000 20,000
20,000 20,000 20,000
Total cash flow 440,000 (315,000) (315,000)
(355,000) (315,000) (265,000)

× Discount factor × 1.000 × .893 × .797 ×
.712 × .636 × .567
Present value (440,000) (281,295) (251,055)
(252,760) (200,340) (150,255)
SUM OF PRESENT VALUES = $(1,575,705)
PERSONAL COMPUTER ($)
Acquisition cost software ( 75,000)
System update ( 60,000)
Operating costs (235,000) (235,000) (235,000)
(235,000) (235,000)
Time sharing revenue -0- -0-
-0- -0- -0- _
Total cash flow 375,000 (235,000) (235,000)
(295,000) (235,000) (205,000)
× Discount factor × 1.000 × .893 × .797 ×
.712 × .636 × .567
Present value (375,000) (209,855) (187,295)
(210,040) (149,460) (116,235)
SUM OF PRESENT VALUES = $(1,247,885)
16-22
The slide shown here displays a net-present-value analysis of
the two alternative computing systems.
The exhibit uses the total-cost approach, in which all of the
relevant costs of each computing system are included in the
analysis.
Then the net present value of the cost of the mainframe system

is compared with that of the personal computer system. (LO 16-
3)
Total-Cost Approach (3/3)
Net cost of purchasing Mainframe system
$(1,575,705)
Net cost of purchasing Personal Computer system $(1,247,885)
Net Present Value of costs $(
327,820)
Mountainview should purchase the personal computer system
for a cost savings of $327,820.
16-23
Since the NPV of the costs is lower with the personal computer
system, that will be the controller’s recommendation to the
Mountainview City Council.
A decision such as Mountainview’s computing-system choice,
in which the objective is to select the alternative with the
lowest cost, is called a least-cost decision.
Rather than maximizing the NPV of cash inflows minus cash
outflows, the objective is to minimize the NPV of the costs to
be incurred. (LO 16-3)
Incremental-Cost Approach
INCREMENTAL ($)
Time 0 Time 1 Time 2 Time 3
Time 4 Time 5
Acquisition cost software 35,000

System update 20,000
Operating costs (100,000) (100,000) (100,000)
(100,000) (100,000)
Time sharing revenue 20,000 20,000
20,000 20,000 20,000
Total cash flow ( 65,000) ( 80,000) ( 80,000) (
80,000) ( 80,000) ( 60,000)
× Discount factor × 1.000 × .893 × .797 ×
.712 × .636 × .567
Present value ( 65,000) ( 71,440) ( 63,760)
( 42,720) ( 50,880) ( 34,020)
SUM OF PRESENT VALUES = $(327,820)
16-24
The slide shown here displays the incremental net-present-value
analysis of the city’s two alternative computing systems.
The result of this analysis is that the NPV of the costs of the
mainframe system exceeds that of the personal computer system
by $327,820. (LO 16-3)
Total-Incremental Cost Comparison
Total Cost:
Net cost of purchasing Mainframe system
$(1,575,705)
Net cost of purchasing Personal Computer system $(1,247,885)
Net Present Value of costs $
(327,820)

Incremental Cost:
Net Present Value of costs $ (327,820)
Different methods, Same results!!
16-25
The total-cost and incremental-cost approaches will always
yield equivalent conclusions.
Choosing between them is a matter of personal preference. (LO
16-3)
Managerial Accountant’s Role
Managerial accountants are often asked to predict cash flows
related to operating cost savings, additional working capital
requirements, and incremental costs and revenues.
When cash flow projections are very uncertain, the accountant
may . . .
increase the hurdle rate,
use sensitivity analysis.
16-26
To use discounted-cash-flow analysis in deciding about
investment projects, managers need accurate cash-flow

projections. This is where the managerial accountant plays an
important role. The accountant often is asked to predict cash
flows related to operating-cost savings, additional working-
capital requirements, or incremental costs and revenues. Such
predictions are difficult in a world of uncertainty. The
managerial accountant often draws upon historical accounting
data to help in making cost predictions. Knowledge of market
conditions, economic trends, and the likely reactions of
competitors can also be important in projecting cash flows. (LO
16-3)
Postaudit of Investment Projects
A postaudit is a follow-up after the project has been approved to
see whether or not expected results are actually realized.
16-27
The discounted-cash-flow approach to evaluating investment
proposals requires cash flow projections. The desirability of a
proposal depends heavily on those projections. If they are
highly inaccurate, they may lead the organization to accept
undesirable projects or to reject projects that should be pursued.
Because of the importance of the capital-budgeting process,
most organizations systematically follow up on projects to see
how they turn out. This procedure is called a postaudit or
reappraisal.
In a postaudit, the managerial accountant gathers information
about the actual cash flows generated by a project. Then the
project’s actual net present value or internal rate of return is
computed. Finally, the projections made for the project are

compared with the actual results. If the project has not lived up
to expectations, an investigation may be warranted to determine
what went awry.
Sometimes a postaudit will reveal shortcomings in the cash-flow
projection process. In such cases, action may be taken to
improve future cash-flow predictions. Two types of errors can
occur in discounted-cash-flow analyses; undesirable projects
may be accepted and desirable projects may be rejected. The
postaudit is a tool for following up on accepted projects.
Thus, a postaudit helps to detect only the first kind of error, not
the second. As in any performance-evaluation process, a
postaudit should not be used punitively.
The focus of a postaudit should provide information to the
capital-budgeting staff, the project manager, and the
management team. (LO 16-3)
Learning Objective 16-4 – Determine the after-tax cash flows in
an investment analysis.
16-28
Learning Objective 16-4. Determine the after-tax cash flows in
an investment analysis.

Income Taxes and Capital Budgeting
Cash flows from an investment proposal affect the company’s
profit and its income tax liability.
Income = Revenue − Expenses + Gains − Losses
16-29
26
18
When a business makes a profit, it usually must pay income
taxes, just as individuals do.
Since many of the cash flows associated with an investment
proposal affect the company’s profit, they also affect the firm’s
income-tax liability.
Any aspect of an investment project that affects any of the items
in this equation generally will affect the company’s income-tax
payments.
These income-tax payments are cash flows, and they must be
considered in any discounted-cash-flow analysis.
In some cases, tax considerations are so crucial in a capital-
investment decision that they dominate all other aspects of the
analysis. (LO 16-4)

After-Tax Cash Flows
Suppose High Country’s management is considering the
purchase of an additional delivery truck.
High Country will consider the after-tax cash flows from the
incremental sales revenue and expenses in order to assist in
their decision making.
16-30
The first step in a discounted-cash-flow analysis for a profit-
seeking enterprise is to determine the after-tax cash flows
associated with the investment projects under consideration. An
after-tax cash flow is the cash flow expected after all tax
implications have been taken into account. Each financial aspect
of a project must be examined carefully to determine its
potential tax impact.
High Country Department Stores, Inc., operates two department
stores in the city of Mountainview. The firm has a large
downtown store and a smaller branch store in the suburbs. The
company is quite profitable, and management is considering
several capital projects that will enhance the firm’s future profit
potential.
Some expenses, depreciation being one of them, require no cash
flows, yet they reduce the amount of taxable net income. (LO
16-4)

After-Tax Cash Flows (2/3)
Incremental sales revenue, net of cost of goods sold (cash
inflow)$ 50,000 Incremental income tax (cash outflow),
$50,000 × 30% (15,000)After-tax cash flow (net inflow after
taxes)$ 35,000
A quick method for computing the after-tax cash inflow from
incremental sales is:
16-31
The sales manager estimates that a new truck will allow the
company to increase annual sales …
Chapter 14
14-1
Decision Making: Relevant Costs and Benefits

1
1
Chapter 14: Decision Making: Relevant Costs and Benefits
Learning Objective 14-1 – Describe seven steps in the decision-
making process and the managerial accountant’s role in that
process.
14-2
Learning Objective 14-1. Describe seven steps in the decision-
making process and the managerial accountant’s role in that
process.
The Managerial Accountant’s Role

in Decision Making
Designs and implements
accounting information
system
Cross-functional
management teams
who make
production, marketing,
and finance decisions
Make substantive
economic decisions
affecting operations
Managerial
Accountant
14-3
2
2
The accountant is increasingly a part of the upper-management
decision-making team.
Management accountants are called to deliver relevant

information to the team from the accounting information
system.
These teams then make decisions regarding production,
marketing, and financing affecting their organization.
The management accountant is considered a business advisor in
many organizations. (LO 14-1)
The Decision-Making Process (1 of 4)
1. Clarify the Decision Problem
2. Specify the Criterion
3. Identify the Alternatives
4. Develop a Decision Model
5. Collect the Data
6. Select an alternative
Quantitative
Analysis
7. Evaluate decision
14-4
3
3
Seven steps generally characterize a typical decision-making

process.
Defining the problem, determining the objectives of the
decision, identifying alternative courses of action, determining
what information is relevant, collecting information to support
the decision, then selecting the appropriate alternative. (LO 14-
1)
Learning Objective 14-2 – Explain the relationship between
quantitative and qualitative analyses in decision making.
14-5
Learning Objective 14-2. Explain the relationship between
quantitative and qualitative analyses in decision making.
5. Collect the Data
Primarily the
responsibility of the

managerial
accountant.
Information should be:
1. Relevant
2. Accurate
3. Timely
14-6
4
4
Accounting data is typically kept in quantitative measures, and,
is important in the decision–making process.
Managers must use their skills, their judgment and their ethics
to make difficult decisions.
While involved in all stages of the decision-making process, the
managerial accountant’s primary role is to provide quantitative
data and analysis that are relevant, accurate, and timely to the
decision being made. (LO 14-2)

5. Collect the Data
Relevant
Pertinent to a
decision problem.
Accurate
Information must
be precise.
Timely
Available in time
for a decision
14-7
4
4
A managerial accountant might ask, “What sort of information
should the accountant gather?”
Information that is useful to a decision has some common
characteristics. The information should be relevant, timely, and
accurate. Relevant information means that only the information

required to make the decision is presented. Information must
also be accurate in order to be useful. The accuracy of the
information is sometimes sacrificed in order to be timely.
Information that is delivered after a decision has been made is
of little use. If accountants had unlimited time, the information
could be extremely accurate. Accuracy suffers as the time
period shortens.
The management accountant’s job is to determine what
information is relevant and provide accurate and timely data
keeping a proper balance of accuracy and timeliness. (LO 14-2)
5. Collect the Data
Qualitative
Considerations
14-8
7

7
Qualitative characteristics are the factors in a decision problem
that cannot be expressed effectively in numerical terms.
Sometimes, a decision can be made that goes against the
quantitative analysis, because the effect on the company, their
employees, or their customers would be negative. (LO 14-2)
Learning Objective 14-3 – List and explain two criteria that
must be satisfied by relevant information.
14-9
Learning Objective 14-3. List and explain two criteria that must
be satisfied by relevant information.
Relevant Information
Information is relevant to a decision
problem when . . .

Capital bias reducing human error in capital decision making

Capital bias reducing human error in capital decision making

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