Topic 2: Define Key Inputs and Input-to-Output Logic

Mining Company Case Study: Introduction (continued) These outputs were selected for the model because NPV greater than zero is a key project acceptance hurdle and IRR is the discount rate at which an investment s NPV equals zero and is thus another way of understanding the project s minimum acceptance criteria, especially as it regards the cost of project funding. Similarly, the profitability index is attractive when it exceeds a ratio of 1.0. The payback period and discounted payback period show how long it takes to recoup the initial investment in terms of actual dollars and present value dollars respectively. Together, these measures are often used to evaluate capital budgeting projects because each provides a different piece of information for making accept or reject decisions. Since each method has its own strengths and weaknesses, using the outputs together can provide the best information in total. However, the mining company considers NPV to be the metric of most value because it shows by how much the project will increase shareholder wealth. Each of these metrics is discussed in more detail in Part II, Domain B. The final model output, the expected life of the mine, is a key output critical for understanding whether the mine will have sufficient resources to be a profitable long-term investment. It is calculated using the reserve estimates and the amount extracted per year. Other important outputs to be produced using a set of pro forma financial statements (not shown in this case study) for the entire organization include the following: For the financing question, a key output is the external financing required; interest expense will be an input to the profitability analysis so this will require an iterative model. (See Part II, Domain C, for an example unrelated to this case study.) Another output is the marginal (additional) profit to the organization generated by the mine for each of the first three years of the project. (See Part II, Domain B, for an example of financial statement projections unrelated to this case study.) Finally, while also not specifically addressed in this case study, often an output of a potential investment analysis is the comparison of a project against competing alternatives for organizational funds. The outputs of the financial model could be directly compared to other potential projects of similar risk or they could be risk-adjusted so as to compare apples to apples. Risk-adjusted comparisons are discussed in Part II, Domain B. Topic 2: Define Key Inputs and Input-to-Output Logic With an understanding of the desired outputs for the model, the FP&A professional can then begin to define the inputs and the input-to-output logic needed to produce the outputs. Inputs come in many forms. 2014 Association for Financial Professionals. All rights reserved. IIA-23

PART II, DOMAIN A: ANALYZING INFORMATION These may include: Value drivers (or business drivers) and related key performance indicators 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 here 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 all critical factors and then separating them into direct inputs, contextual inputs and derived inputs. Direct Inputs Direct inputs are those inputs or drivers entered directly in the model and used as inputs to calculations. Direct inputs can be variables, constants or semi-variables. Variables 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. Variables will form the majority of direct inputs to a model, especially when generating projections into the future. Variables are used as inputs IIA-24 2014 Association for Financial Professionals. All rights reserved.

for assumptions, for example, when historical data are not available. Even when historical data are 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 (all discussed below). Constants Constants, also called the givens in a model, 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). Constants 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, management s attitude toward taking risk (risk appetite), or management s preference for debt versus equity. Semi-Variables Semi-variables (or 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. Semi-variables require modeling the relevant range or ranges for the model, perhaps as separate input fields. For example, say that one 2014 Association for Financial Professionals. All rights reserved. IIA-25

PART II, DOMAIN A: ANALYZING INFORMATION 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. Contextual Inputs 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 Derived inputs are the outputs of calculations in a model that are used as inputs to different calculations in the model. The more models make use of derived inputs, the more flexible they are, 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. The determination of which inputs should be direct, contextual or derived often starts with a study of value drivers and their related key performance indicators. 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 organization s ability to generate economic value. Activities meant to influence value drivers are often measured using key performance 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. IIA-26 2014 Association for Financial Professionals. All rights reserved.

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 is 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 the known 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, drivers of capital expenditures will give you your capital expenditures, and so on. Value drivers that cannot be used as direct or derived inputs are often still valuable as contextual inputs. These drivers might be addressed as considerations or constraints within the overall logic of the model. 2014 Association for Financial Professionals. All rights reserved. IIA-27

PART II, DOMAIN A: ANALYZING INFORMATION External Value Drivers and Related KPIs External value drivers and their related KPIs are factors outside the control of the organization that are likely to have an influence on the end product. As defined and described in Part I, Domain A, Chapter 5, external drivers are sometimes considered in the following macroenvironment categories, which is sometimes called a PESTLE analysis: Political Economic Social Technological Legal Environmental Considering each of these areas in turn can ensure that no important external factors are ignored in the model. See Part I, Domain A, for specific examples of macroenvironment drivers in each of these categories. External drivers can also be specific to an organization, business unit or product decision: Market growth Overall market size Customer needs and expectations Loan covenants Competitor actions such as their offerings, marketplace positioning strategies and anticipated responses to the organization s actions Organization-specific external drivers can help provide subtle distinctions in how variable interrelationships should be interpreted. For example, understanding where a company or product is at in terms of its life cycle will influence how its free cash flow should be interpreted. A 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 IIA-28 2014 Association for Financial Professionals. All rights reserved.

equipment, or local market costs for services such as construction. Also, some macroenvironment 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 KPIs Internal value drivers and related 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 organization s business model and strategy. When these exist, FP&A professionals should select an 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 organization s 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 2014 Association for Financial Professionals. All rights reserved. IIA-29

PART II, DOMAIN A: ANALYZING INFORMATION KPIs, in which case the FP&A professional may need to consult with internal experts to develop them 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, ratio of walk-ins to sales, 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, up-selling 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 (or derived) inputs and which will be contextual inputs involves only 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. Sufficient is a criterion that will help ensure that 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 IIA-30 2014 Association for Financial Professionals. All rights reserved.

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 and then may be 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 into 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, for 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. 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 slide show. 2014 Association for Financial Professionals. All rights reserved. IIA-31

PART II, DOMAIN A: ANALYZING INFORMATION High-Level Logic Flowcharts High-level logic flowcharts are a top-down method of showing all of the major influences on a given model output. They 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.1-2 on the next page shows an extract of an example of the logic for free cash flow (FCF) resulting from a utility company s 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. 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. IIA-32 2014 Association for Financial Professionals. All rights reserved.

Exhibit II.A.1-2 Illustrative FCF Driver Flowchart for Economic Assistance Customers Exhibit II.A.1-3 on the next page 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 2014 Association for Financial Professionals. All rights reserved. IIA-33

PART II, DOMAIN A: ANALYZING INFORMATION (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). Exhibit II.A.1-3 Revenue Projections of 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 the flowchart up-to-date so that decision makers can understand conceptually how the model works. Only when they understand the model s logic and assumptions 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 professional s 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 model s process. IIA-34 2014 Association for Financial Professionals. All rights reserved.

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. The Inputs Mining Company Case Study The following direct inputs are planned for the Panama mine purchase analysis model. The first two fields 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, 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 year s 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 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. 2014 Association for Financial Professionals. All rights reserved. IIA-35

PART II, DOMAIN A: ANALYZING INFORMATION High-Level Flow Mining Company Case Study (continued) 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 for the 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 deducted only in the final year. Note that F() denotes function of in the flowchart. Detail-Level Flow The detail-level flow below shows the direct inputs, the derived inputs, the outputs and the 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 prioryear copper price times one plus the growth rate is 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 function of 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. IIA-36 2014 Association for Financial Professionals. All rights reserved.

Mining Company Case Study (continued) In cell A30, the after-tax cash flow per year is added as cumulative sums. An IF Statement and MAX 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 discounted cash 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 expenses and/or capital. NPV divided by the first-year cash expenses equals the profitability index ratio. Starting in cell H6, 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 year s 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.) 2014 Association for Financial Professionals. All rights reserved. IIA-37