Whether you know it as a cost-benefit analysis or a benefit-cost analysis, performing one is critical to any
project. When you perform a cost-benefit analysis, you make a comparative assessment of all the benefits
you anticipate from your project and all the costs to introduce the project, perform it, and support the
changes resulting from it.
Advantages of Cost-Benefit Analysis
The main advantage of a cost-benefit analysis is you're putting numerical values on all the costs and
benefits of a project, even the intangible ones. So, it's a systematic way to figure out the pros and cons of
a project, task or investment. It's also extremely versatile, with businesses performing cost-benefit
analyses to:
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Figure out whether a project is sound and justifiable by analyzing whether its
benefits outweigh the costs.
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Make decisions transparently and on an equal footing, so that every team
member can replicate the analysis across the various projects they're assessing.
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Take a broad spectrum of costs and benefits, many of which are intangible, and
convert them to the same "currency" so you can make an apples-to-apples comparison.
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Get a baseline for comparing projects so you can see which is the best path
forward.
The cost-benefit analysis is suitable for all sorts of projects, from evaluating new product development to
weighing investment opportunities, assessing change initiatives and deciding whether to hire new staff.
Disadvantages of Cost-Benefit Analysis
Despite these advantages, there are some limitations of the cost-benefit analysis. These mostly relate to
the accuracy of the data you put into the analysis and the problems associated with human agendas, such
as fudging the numbers to get the exact result you want.
It's Hard To Get Accurate Data
As with any type of analysis, the quality of what you get out depends on the quality of what you put in.
The more accurate your numbers, the more accurate your results.
The problem here is that a lot of your benefits will be hard to quantify. Attempts to measure items that are
generally unmeasurable – things like staff motivation or customer loyalty – will always be
approximations, and you have no way of knowing whether your estimate is anywhere close to the true
value. Most companies put safeguards in place to stop their estimations from being a wild stab in the
dark. But even then, you can get inaccuracies. What do you think happens to the analysis if:
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You rely too heavily on data collected from past projects, but the market has
moved since the data was collected and the old project had a different size, scope and objective to
the current one?
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You rely on subjective evaluations to quantify an intangible?
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You're attached to a particular project so you use only data that backs up what
you want to find?
As you can see, it's pretty easy to game the system, which will throw the whole analysis out of whack.
You Operate in an Imperfect Market
Cost-benefit analysis works really well for short-term projects where the market is not going to shift much
between the time you run the analysis and the time you put your project into action (like getting your
running shoes on store shelves). For projects with a longer-term horizon, you're going to struggle in the
face of ever-changing market conditions.
What happens, for instance, if mortgage and credit card interest rates go up so consumers have less cash
in their pockets at the end of the month? What about inflation? What if you preferred supplier goes bust
halfway through production and you have to switch to a more expensive supplier at short notice? What if
teens suddenly ditch blingy running shoes in favor of iridescent sandals?
Projects that go on for a long time can be problematic for the cost-benefit analysis because there are too
many outside factors that impact the accuracy of the analysis.
The Costs Turn Into a Budget
Another criticism of cost-benefit analysis is it turns a list of potential costs into a budget for the project.
When you put together the analysis and present it to senior leaders, there's a risk that decision-makers will
treat the expected costs as actual rather than an estimation. This can throw the budget off, cause the
misallocation of funds and defeat attempts to control costs further down the line.
Present Value Errors
To make a decision with a cost-benefit analysis, you have to compare the net present value (NPV) of the
project's costs with the net present value of its benefits. This means you have to calculate the value of all
future cash flows over the lifetime of the project (for instance all projected running shoe sales over the
next 10 years) and reduce them by the value of those benefits if they were incurred today.
The issue here is that, to calculate the NPV, you have to choose an appropriate discount rate for the
project, and that normally correlates with the usual returns for the business. For instance, if the running
shoe company normally gets returns of 10 percent per year on the sale of its running shoes, that's the
discounting factor you'd plug into the NPV calculation.
However, no one can accurately calculate the NPV, because t_here's no guarantee that the discount rate
you've used is realistic_. Who knows if "Bling Warrior" will make the same profits as the rest of your
product range? And a miscalculation of just one percent per year could push an otherwise profitable
project into the red. This makes it essential to run a sensitivity analysis of various scenarios, testing the
robustness of the cost-benefit analysis against changes in some of the key numbers to see if the project
still works from a financial point of view.
The terms risk and uncertainty refer to perceptions about the occurrence of ‘alternative’ future events, in
which current assumptions might not hold. However, the terms are not interchangeable. Risk exists when
the potential event or outcome can be reasonably identified and estimated with a certain degree of
confidence (e.g. annual rainfall, wind intensity, movements in relative prices). Uncertainty exists when
the potential event or outcome cannot be reasonably identified, or the probability of an event occurring is
unknown (e.g. tax changes, regulatory changes, technological change). Therefore, risk is the measurable
variability of a parameter whose distribution of values can be defined, while uncertainty is variability
whose distribution of values cannot be defined (Hillson and Murray-Webster, 2004). Both risk and
uncertainty impact on the variables defining an intervention, resulting in different outcome values for the
cash- or resource-flow statements of an intervention compared to estimates based on the deterministic
single value estimates. From the decision-maker’s standpoint, assumptions regarding future risk fall into
two broad categories, according to which variability can be ascribed either to an a priori probability or to
a statistical probability. In contrast, decision-maker assumptions regarding future uncertainty can be
ascribed either to subjective probability, in which the data to define a statistical probability are not
available, or to socialization, in which the future is inherently unknowable and may bear little or no
relation to the past or the present