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PART II,DOMAIN A:ANALYZING INFORMATION

2A-16 2013 Association for Financial Professionals. All rights reserved.v1.0

Topic 2: Define Key Inputs and Input to OutputLogic

With an understanding of the desired outputs for the model, the FP&A

professional can then begin to define the inputs and input-to-outputlogic needed to produce the outputs. Inputs come in many forms. These

may include:

Value drivers (or business drivers) and related key performance

indicators (KPIs).

Historical data or seed data that can help establish trends.

Proxies and assumptions that take the place of missing data or

predict what conditions will be like during the analysis period. Note

that proxies and assumptions are discussed in later topics.

Specifying inputs and input-to-output logic often revolves around a

study of value drivers related to the end product. Value drivers are

discussed in Part I, Domain A, Chapter 3: Organization. After

introducing some types of inputs, the discussion therefore addresses

how value drivers and KPIs are used to help define both inputs and the

logical flow of inputs to outputs. Afterward, there is a discussion of how

to construct high-level flowcharts and flowcharts of more detailed

calculation processes for models.

Specify inputs

When deciding what inputs to specify in the model, the first question to

ask is, What critical factors do we need to know about the situation and

the future that will drive the outputs? This is a brainstorming process

of listing out all critical factors and then separating them into direct

inputs, contextual inputs, and derived inputs:

Direct inputs are those inputs or drivers entered directly in the

model and are used as inputs to calculations. Direct inputs can be

variables, constants, or semi-variables:

o Variables are data that can assume any one of a set of values as

needed or expected in the model. Variables can be based on

value drivers, the most up-to-date historical data, or assumptions.


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CHAPTER 1:SPECIFYING OUTPUTS AND GETTING INPUTS

2013 Association for Financial Professionals. All rights reserved. 2A-17v1.0

o Constants (givens) are values that are not expected to change in

the model and are used for stable relationships. Constants could

be assumptions, historical data, internal policies, or facts (e.g.,

five workdays per week).

o Semi-variables (step variables) are inputs that are used for

relationships that are stable over a given relative range, and then

step up or down to a new stable level once the range is exceeded.

Contextual inputs(contextual drivers or indirect inputs) are

those inputs or drivers that are not used in the model directly but

may help determine model logic or may be used in descriptive

summaries to provide support for scenarios or conclusions and

recommendations. Contextual inputs should be removed from the

list of direct inputs and put on the assumptions tab or elsewhere.

Derived inputs are the outputs of calculations in a model that are

used as inputs to different calculations in the model. Models are

more flexible the more they make use of derived inputs because

derived inputs and the calculations they are based upon leverage the

interrelationships between elements. Derived inputs are discussed

further in Chapter 3, Topic 3.

Additional discussion of variables, constants, and semi-variables

follows.

Variables

Variables will form the majority of direct inputs to a model, especially

when generating projections into the future. Variables are used as inputs

for assumptions, for example when historical data is not available. Even

when historical data is available, how the input will behave going into

the future could vary and so a variable direct input is usually necessary.

FP&A professionals could start with a long list of potential variables,which can then be reviewed to determine which are really constants or

semi-variables and also which are better as contextual or derived inputs.


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Constants (givens)

Constants, also called the givens in a model, are inputs that are

typically easy to collect because by definition they do not change

frequently, if at all. Constants are still modeled as direct inputs because

calculations should not contain hard-coded values and the values might

also differ the next time the model is used.

One example of constants are internal policies. Internal policies are

those strategic or operational values set by organizational policy.

Examples include minimum cash balances, working capital, weighted-

average cost of capital, depreciation schedules, capital expenditures,

dividend payout policy, operating and financial leverage, relevant

marketing or manufacturing decisions, managements attitude toward

taking risk (risk appetite), or managements preference for debt versus

equity.

Semi-variables (step variables)

Semi-variables or step variables require modeling the relevant range or

ranges for the model, perhaps as separate input fields. For example, if

one employee can produce between a relevant range of 0 and 100 parts

per week, if 150 parts are needed per week, an additional employee

would be needed and number of employees might be an input field.

Note that if the relevant range will not be exceeded within the model

(e.g., that range is considered reasonable), these inputs can be treated as

constants but some data validation might be needed so the range is not

inadvertently exceeded.

The determination of which inputs should be direct inputs, contextual

inputs, or derived inputs often starts with a study of value drivers and

their related key performance indicators (KPIs). In this way, the inputs

and the input-to-output logic are often developed simultaneously.

Specify value drivers and related KPIs

Value drivers, or business drivers, are factors that affect the

organizations ability to generate economic value. Activities meant to

influence value drivers are often measured using key performance


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indicators. A key performance indicator (KPI) is a metric that

indicates the level of performance required to achieve a defined

objective in a certain activity.

As discussed in Part I, Domain A, Chapter 3: Organization, a financial

value metric such as net profit margin is driven by financial value

drivers such as sales revenue, and each of these drivers are driven in

turn by a number of operational value drivers, one of which might be

direct sales volume. Direct sales volume is in turn driven by one or

more tactics such as new account development, which might be

measured by the KPI number of new accounts.

Purpose of identifying value drivers and KPIs

Identifying value drivers and KPIs is a high-level, top-down effort that

can help frame the big picture and clarify the purpose of the end product

prior to getting into the details of the model. Studying value drivers

helps the FP&A professional to understand the financial and economic

relationships between inputs and helps to construct the logical flows and

high-level model process flowchart logic.

Understanding the key value drivers for a particular end product and

how the business opportunity impacts the drivers will help the FP&A

professional and decision makers understand how a project will

maximize a business opportunity or improve business operations so that

recommendations will have relevance for decision makers. Another

benefit of studying value drivers is that it helps to identify potential

project or operational risks and opportunities. These risks and

opportunities can be listed in a risks and opportunities (R&O) analysis

for possible inclusion in scenarios, as is discussed in Chapter 3, Topic 2.

Value drivers can also be used to generate derived inputs using theknown relationships between the drivers and other information that is

unknown when making a projection. For example, when building a set

of pro forma financial statements, drivers of revenue will give you your

revenue for the model. Drivers of expenses will give you your expenses

for the model. Drivers of capital expenditures will give you your capital

expenditures, and so on.


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new company or one experiencing strong growth may have significant

negative free cash flow and this is a normal consequence of its life cycle

stage.

External drivers specific to a particular business question could include

impact on the environment or a local community, availability of suitable

land and infrastructure, useful life or maintenance costs for technology

and equipment, or local market costs for services such as construction.

Also, some macro-environment factors can be drilled down to relevant

specifics, such as the impact of a specific regulatory approval process

on a product release or the inflation rate of the raw materials used in a

product.

Selected external drivers and KPIs are therefore specific to the

organization and the end product. Take for example a chain of mall-

based retail clothing stores that markets to a niche market segment:

End product: Increase mall retail space foot traffic.

External drivers of foot traffic: Unemployment levels and

disposable income for niche demographic, mall foot traffic, ratio of

vacant to occupied spaces in mall, seasonality, rate of change in

clothing trends, etc.

KPIs: Number of persons entering store, ratio of walk-ins to sales.

Another example is for a hotel chain:

End product: Maximize hotel revenues.

External drivers of hotel revenue: Unemployment rates,

disposable income, travel budgets for organizations, gas prices,

regional events, regional situation (e.g., political or social strife), etc.

KPIs: Occupancy rate, price realization, etc.

Internal value drivers and related KPIsInternal value drivers and related key performance indicators (KPIs) are

drivers and metrics that the organization can influence or control. Many

internal value drivers and KPIs will be ones that the organization has

previously determined are vital to the organizations business model and

strategy. When these exist, FP&A professionals should select an


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appropriate subset that relates to the end product or business question.

When decision makers are already measuring and managing success

using these drivers and KPIs, it will be straightforward to show how the

planning or analysis results are pertinent to the audience and how they

impact the organizations strategic or tactical goals.

Newer organizations or organizations that have not engaged in formal

strategic planning may not have a set of clearly identified drivers and

KPIs, in which case the FP&A professional may need to consult with

internal experts to develop a set of drivers and metrics for the end

product.

Like external value drivers, internal value drivers and related KPIs will

be specific to the organization and end product. The prior example of a

mall retail clothing store is continued for internal drivers:

End product: Increase mall retail space foot traffic.

Internal drivers of foot traffic: Choice of malls for stores, store

location in mall, store layout, shelf layout, product mix, advertising,

number of salespersons, training of salespersons, etc.

KPIs: Number of persons entering store, walk-ins to sales ratio, etc.

Internal drivers for the hotel chain example follow:

End product: Maximize hotel revenues.

Internal drivers of hotel revenue: Location, customer experience,

frequent stay programs, coordination with convention space,

upselling initiatives, availability of ancillary services, etc.

KPIs: Occupancy rate, price realization, ancillary services paid,

customer complaints, satisfaction with complaint resolution, etc.

Differentiating between direct and contextual inputs

The process of selecting which inputs or value drivers will be direct (orderived) inputs and which will be contextual inputs only involves

deciding what is necessary and sufficient to produce the end product.

Necessary is a criterion that will help restrict key inputs to what is

feasible to model within scope and deadline constraints. Sufficientis a


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criterion that will help ensure the set of inputs as a whole can answer the

business question, including any scenarios that need to be developed.

Other selection criteria include driver volatility and prediction

usefulness. Volatility relates to the frequency and size of swings in

variations. Volatile drivers often still need to be explicitly included in

the model if they are critical to understanding the issue. They may

require more assumptions and you should understand that these

assumptions become quickly less reliable the farther into the future they

are projected. Prediction usefulness refers to how predictable a driver

has been in the past in forecasting correlated events. Drivers with poor

correlation might be excluded.

The variables selected may start out broadly in the first iterations, then

get narrowed or changed as the understanding of the end product and

available information evolves.

Document the logical flow of inputs to outputs

The logical flow of inputs to outputs uses logical arguments to show the

overall factors and drivers that come in to play in a complex model.

More detailed flowcharts show how the inputs lead to calculations and

the results of those calculations become inputs to other calculations, and

so on, until the final outputs are generated.

The purposes of producing a logical flow of inputs to outputs are to:

Ensure that all relevant considerations and major components of the

model are accounted for

Show cause and effect

Make the design and documentation transparent

Provide a method of checking for logic errors or model auditing

Enable presentations of high-level model logic to interested parties

For example, if it is a revenue projection model, the purpose of the

flowchart is to show where the money is coming in, how things tie

together, and what factors influence each revenue stream.


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Flowcharts can be created using an automated flowcharting tool such as

Microsoft Visio, but they can also be created manually in an Excel

worksheet tab or in a PowerPoint slideshow.

High-level logic flowchartsHigh-level logic flowcharts are a top-down method of showing all of the

major influences on a given model output. High-level logic flowcharts

are especially vital for complex models with many drivers and

influencing factors. These flowcharts are top-down because they start

from a major output and branch into more and more specific drivers. A

common way of presenting this information is a value driver tree (see

Part I, Domain A, Chapter 3 for an overview of value driver trees).

These high-level flowcharts do not indicate the specific calculations but

instead provide a way to check that all considerations and constraints

are accounted for. Exhibit II.A.1-7 shows an extract of an example of

the logic for free cash flow (FCF) resulting from a utility companys

economic assistance customers (EACs). Note that some of the specific

drivers or inputs on the right could be further broken down into

additional levels of detail. Note also that F( ) denotes function of in

the chart.


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Exhibit II.A.1-7: Illustrative FCF Driver Flowchart for Economic Assistance Customers

Economic AssistanceCustomer (EAC)

Impact on Free Cash

Flow (FCF)

Economic AssistanceCustomer (EAC)

Impact on Free Cash

Flow (FCF)

Change in excess

cost over billed rate

due to funding

timing

EAC Program Costs

Cost of lost

customers who pay

full rate

Collections from

customers who pay

full rate

Timing of payments

from customers who

pay full rate

EAC customer

collections

Timing of EAC

payments

EAC cost of

electricity

EAC collections

Timing of Assistance

Funding

Operating Expenses

CapEx

F(change in EAC

customers)

F(rates and

competitor rates)

Billed amount

Payment amount

Fixed costs

Rate

Usage

Billed amount

Income

Other billsF(payment terms

and ability to pay)

Billed amount

Payment amount

EAC Income

EAC Income

maximum obligation

Billed amount

Income

Other bills

Electricity rate

EAC usage

Number of EACs

EAC income level

EAC Income

maximum obligation

F(payment terms

and ability to pay)


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Detail-level process flows

For specific portions of a complex model or for a simple model, an

additional level of detail can be mapped out to help with design. At this

higher level of detail the inputs, calculations, and outputs (ICO) of a

model can be shown. This type of process flow should visually

differentiate between the inputs, derived inputs, calculations, and

outputs.

Detail-level model process flows may be constructed in many ways. A

simple model may require only simple mathematical arguments such as

plus, minus, multiply, and divide, or it could list financial functions to

perform such as Excel worksheet functions. Other detail-level model

flowcharts will use standard flowchart methodology (i.e., symbols such

as boxes for processes and diamonds for decision points with arrows

between processes). In this case, the mathematical operators and

calculations to perform might be specified within the flowchart boxes,

or they might be omitted to keep the chart simple, as is often needed

when a detail-level flowchart must still show many complex interactions

between elements.

Exhibit II.A.1-8 shows a process flow produced on a worksheet tab,

which ensures that it is easily accessible within the model. The chart

shows how an organization selling products for families with newborns

estimates their revenue based on the new customers gained and the

number of existing customers retained after accounting for churn (lost

customers). Note that the exhibit differentiates between direct inputs,

derived inputs and outputs, while the calculations are all shown using

operator symbols (plus, times, and equals).


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Exhibit II.A.1-8: Revenue Projections of a Simple Model

Transparency and continued relevance

Model logic and flow development throughout this iterative process

should be very open and transparent. Documenting as you go is the only

way to keep this process transparent. Clearly documenting the logical

flow using a basic flowchart is a best practice.

It is important to keep this flowchart up to date so that decision makers

can understand conceptually how the model works. When they

understand the models logic and assumptions, only then will they be in

a position to apply their expertise rather than blindly relying on a black

box (or rejecting the model outright). From the FP&A professionals

perspective, a useful flowchart will improve formal presentations and

make justifying the methods used to arrive at the results more obvious

and visual. Flowcharts will also be valuable for future model users and

auditors so they can trace the models process.

Formal review of inputs and logical flows

Large, complex projects may have a formal review step to validate the

inputs to be used and the logic of the model for quality assurance

purposes. Such reviews may occur at various development stages.


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Mining Company Case Study

The Inputs

The following direct inputs are planned for the Panama Mine Purchase Analysis Model. The first twofields sum to the initial year investment cost. The next field is the discount rate, or the cost of funds

used for present value calculations. The copper reserves and extraction per year fields are listed in

metric tons (MTs or 1,000 Kg) and together they dictate the expected life of the mine. The copper

base price field is the average historical price of copper in the initial year. The copper price growth

rate is a compounded growth rate to apply to the copper base price in the first year and to the prior

years calculated copper price for subsequent years.

The retirement obligation is the cost of closing the mine and any necessary environmental

remediation. The cash expenses field is an assumption that the expenses can be estimated as a

certain percentage of revenue. Depreciable assets, asset salvage value, and depreciation period

are to be used to estimate straight-line depreciation for the model as a simplifying assumption since

the real assets will be depreciated at different rates. The income tax rate is also a simplifying

assumption because it omits consideration of tax deductions, deferred taxes, and so on that would

be used to arrive at a more realistic effective tax rate. Note that all amounts listed in US$ millions

are entered in whole dollars but are formatted to display in millions. Finally, note that the values

entered in the input fields so far could be test data or early assumptions at this point.

(Continued on next page.)


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High-Level Flow

The following flowchart shows a value driver tree for calculating the net present value as of the

terminal year of the Panama mine. This flowchart shows that NPV requires knowing the terminal

year of the mine, which is variable based on the amount of copper reserves and the extraction per

year. Therefore, the model will need to calculate NPV for each year and then look up the NPV forthe terminal year. The NPV calculation is primarily determined using the present value of the after-

tax cash flows based on the discount rate, plus the initial cost. The retirement obligation is only

deducted in the final year. Note that F() denotes function of in the flowchart.

Detail-Level Flow

The detail-level flow on the next page shows inputs, the derived inputs, the outputs, and

calculations (math operators and Excel worksheet functions (e.g., PV, IRR)) the analyst plans on

using. Starting from the top, the copper base price is used as the Year 0 copper price. Thereafter,

the prior-year copper price times one plus the growth rate are used to create compounding growth

in average annual copper prices. The copper price per MT for the given year is multiplied by the

amount of MTs of copper extracted per year to find the base revenue per year. Then the cash

expenses assumption is used to calculate the cash expenses for the given year. The third item

required to calculate the income before tax per year is the depreciation per year, which is a functionof the depreciable assets, salvage value, and depreciation period. Income before tax per year is

multiplied by the tax rate to calculate the income taxes, which are subtracted from the income

before tax to find the income after tax. Depreciation is added back at this point to find the after-tax

cash flow per year, and this amount is used to calculate the IRR for each year of the mine.

(Continued on next page.)


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2A-30 2013 Association for Financial Professionals. All rights reserved.v1 0

On cell A30, the after-tax cash flow per year is added as cumulative sums, A PERCENTRANK.EXC

function in Excel is used to find the payback period. The discounted payback period is also

calculated starting with after-tax cash flow, but a present value (PV) function is used to calculate the

cumulative discountedcash flow for each year. Net present value is calculated using an NPV

function, which should equal the discounted cash flow per year less the first-year cash expensesand/or capital. NPV divided by the first-year cash expenses equals the profitability index ratio.

Starting in cell H7, the copper reserves divided by the extraction per year equals the estimated life

of mine. Since the final year of the project is variable, this model calculates the other outputs for

each potential terminal year. Therefore, a LOOKUP function will be used to match the terminal year

of the mine to a project year field within the calculations and then return that years outputs for IRR,

NPV, and profitability index. The payback period outputs are found using an array function to return

the minimum payback period that is greater than zero (see Part II, Domain C for more information).

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