be1

7/21/2019 be1

http://slidepdf.com/reader/full/be15695d22e1a28ab9b02996973 1/35

Version 6.1 - September 2012

Rio Tinto’s Project Evaluation Guidance (PEG)Volume 3 – Business Modelling Guidelines

The purpose of this volume is to outline a recommended approach for the designand construction of financial models used to evaluate investment opportunities.

7/21/2019 be1


Project Evaluation Guidance – v6.1 Sep 2012 Page 2 of 35

Introduction to the Project Evaluation Guidance

Document

The purpose of PEG

The purpose of PEG is to define Rio Tinto’s project evaluation methodology. It should be used when

valuing both new capital projects and existing businesses. While it aims to promote a consistent

approach to evaluating “normal” investments, the intent is to allow flexibility to address unique

situations.

The PEG documents

PEG 6 is based on PEG 5 and supporting documents (the Investment Committee Guidance Note

and the Business Modelling Guidance Note) and has attempted to bring them together into a more

focussed and accessible reference document.

The following diagram illustrates the structure of the PEG document. The two (light blue) sections

provide the over-arching guidance and “rules” that should be understood by all employees involved

in preparing, reviewing and making investment decisions. The dark blue sections are intended as

“practitioners’ guides” and, as such, provide a more detailed, step-by-step methodology of the

investment appraisal process:

Rio Tinto’s Investment Decision Making Process – Provides an overview of the steps that must

be followed when submitting an investment for approval and the decision-making bodies that will

need to be engaged.

The Principles and Protocols for Project Evaluation – Explains Rio Tinto’s high-level approach

that should be adopted when valuing an investment opportunity.

Developing an Investment Proposal – Outlines the content that should be addressed for different

types of investment proposals.

A Practitioners’ Guide to Project Evaluation – Augments the “Principles and Protocols” chapter involume 1. It is aimed at those who are directly involved in valuation and investment proposal

preparation. It includes practical guidance as well as finance theory.

7/21/2019 be1



Business Modelling Guidance – Outlines Rio Tinto’s financial modelling protocols including model

structure and model output.

Other documents complementing PEG

PEG 6 is complemented by a suite of other guidance documents that provide specific instruction

primarily on the technical components of project development. All can be found on the Prospectportal and are cross-referenced in PEG 6 where relevant.

Further detailed guidance includes:

Commercial Standards and Guidance Notes – include Marketing Evaluation Guidance Note and

other commercial, tax and accounting guidance.

Technical Standards and Guidance Notes – include Capital Cost and Operating Cost Estimation

Working Practice, Methodology for Estimating Capital Cost Escalation, Contingency and Other

Allowances, Closure Standards and Guidance, and other guidance and standards from T&I (e.g.

HSEC, PDI).

Other Standards and Guidance Notes – include Sustainable Development Decision Making

Criteria, Energy and Climate Strategy toolset, and other guidance and standards.

7/21/2019 be1



Contents page

Introduction to the Project Evaluation Guidance Document 2

Glossary 5

1. Overview 6

2. Rio Tinto’s Business Modelling Philosophy 7

2.1 Introduction 7

2.2 Purpose of the business model 8

2.3 Business model content and functionality 9

3. Guidance on Model Design 10

3.1 Software to be used 10

3.2

Model design and development 10

3.3 Model structure – General 10

3.4 Individual sheet structure and input protocols 11

3.5 Selecting the data to input 13

3.6 Calculation Areas 17

3.7 Model Outputs 19

4. Model Integrity, Testing and Checklists 21

5. Model Ownership and Security 22

5.1 Change control 22

Appendix 3.1: Typical Business Model Structures - Overview 23

Appendix 3.2: Example of a Model Preface (Front Sheet) 24

Appendix 3.3: Examples from a Simple Multi-Sheet Model 26

Appendix 3.4: Examples of a Vertical Sheet Model 34

7/21/2019 be1



Glossary

“BED” means the Business Evaluation Department

“BMG” means business modelling guidelines

“BUs” means business units

“CGU” means cash generating unit

“HSEC” means Health, Safety, Environment and Communities

“LME” means the London Metal Exchange

“M&A” means mergers and acquisitions

“NPV” means net present value

“PDI” means Project Development and Implementation

“PEG” means project evaluation guidance

“T&I” means Technology and Innovation

7/21/2019 be1



1. OverviewThe key principle is:

• Simplicity is encouraged. A good model will be easy to follow, easy to audit and will tell the right

story to the user.

The key messages from this chapter include the following:

• Models are key business tools that support both short and long-term planning in Rio Tinto. They

are essential for communicating to Business Unit and Headquarters’ management the value

chain through the business.

• The Business Modelling Guidelines chapter (BMG) focuses on high level models used to

prepare business valuations and to support major projects put before the Investment Committee.

The aim is to improve the integrity and allow easier validation of such models.

• Improved quality, consistency and transparency should permit the user to focus on the business

and the key value drivers, rather than how the model works.

• Each Business Unit, or project team, should have a core valuation model which shows the

central estimate of future cash flows as defined in PEG. A well thought out model should then

allow focussed development of particular areas so as to suit individual project evaluation needs.

• Excel remains the software of choice for high level models. Each model should have a “Preface”

sheet which describes the model structure and the protocols used, plus a summary of key

developments of the model. Planning the structure is critically important.

• Protocols are recommended for file and sheet naming, clearly identifying sources of data,

formatting and colour coding, transparency (avoiding hidden inputs or calculation) etc. A well

documented and annotated model should be an accessible model.

• Two levels of detail for input data and consequent calculation are discussed; a well structured

model has to draw a balance between complexity and functionality. Related models should be

identified and relationships mapped where appropriate.

• Care must be taken in projecting physical or cost parameters into future periods. Assumed

performance improvements should be clearly and separately shown, with sources identified.

• Extracts from a worked example using a typical structure are shown in the appendices and are

available in full as an Excel file. No single template is mandated; business needs should drive

the overall model design.

• Model integrity checks should assist the user in validating the model. A BMG self audit checklist

has been prepared and is available from BED.

• Models should have clearly defined ownership, be stored securely and have appropriately

controlled access.

The electronic version of the sample model is available on the BED portal.

7/21/2019 be1



2. Rio Tinto’s Business Modelling Philosophy

2.1 Introduction

Financial models are critical business tools that support both short and long-term planning in Rio

Tinto. Good models are essential for communicating to management the value chain through the

business and, inter alia, they aid operational decision making, capital investment and acquisition/

divestment studies. Their use for evaluating alternatives and providing timely and accurate output is

key to enabling value maximising decisions by management.

Business Evaluation (BED) and Technology and Innovation (T&I) are asked to review all major

investment proposals and must rely on being able to access and review the logic that supports the

business case. This requires an ability to run sensitivity analyses and understand the key value

drivers.

Decision makers need to understand the overall business and improved model quality, consistency

and transparency should permit users to focus on the business, rather than how the model works.

This chapter therefore covers the model design and practical implementation of PEG.

It is expected that models used to derive valuations for Rio Tinto businesses and projects would

have a core structure which seldom exceeds 5 Mb in size, excluding multiple alternative scenarios

which might be saved in the same file. These models, which are also used for many other purposes

are typically fed by inputs from other financial and physical models (e.g. from mine planning software

and short-term plans).

The diagram below indicates how models might typically be related in BUs; it is recommended that

even the subsidiary model users consider adopting many of the suggestions in this guidance note.

Reasons for producing this guideline include:

• Improving integrity and validation of models. A clear model will allow the reader to understand

the overall business and rapidly test the validity of the outputs.

• Encouraging quality and consistency of model design with uniform application of conventions

and correct implementation of PEG.

• Encouraging transparency of models to ease their use by others – easing transferability of

models as personnel changes occur, facilitating reviews by BED and T&I etc.

G u i d e l i n e s f o r m o d e l d e s i g n Specific Project

ModelsCompetitor

Models

Processing(short/medium term

outlook)

Mine ProductionPlanning

(life of asset)

Pricing(short/medium term

outlook)

BU Valuation Model

Other models (for example)

7/21/2019 be1



It is not suggested that each Business Unit (BU) should have the same model template; Rio Tinto

operations have differing business focuses and the substantial work carried out in creating the

existing suite of BU models should be built upon. However, it is important that there is a clear

understanding of the relationships between the various models that exist within the BU.

A supplementary activity that relates to this document has been the initiation of a process for

reviewing selected BU valuation models against the BMG, ensuring that models are sufficiently

transparent, determining that sound version control procedures are in place and the models have

ongoing integrity (see section 4).

This chapter is not intended to be a detailed manual on the use of Excel; various text books and

papers cover this ground and BED/ T&I can suggest additional reading on request.

2.2 Purpose of the business model

Underlying any valuation of a BU, there should be a business model which covers the life of the

asset concerned. This model may present the individual assets of a BU or the aggregate value of a

group of BU assets. If the assets are interconnected in an operational or business way, it is

recommended that the assets are modelled in the same file.

Currently, Rio Tinto HQ and the BU’s use these models, in differing degrees, for the following:

• As part of the annual planning process, Rio Tinto HQ collects valuations of all its businesses

using the Cash Generating Unit (CGU) template sent out by Controllers. These are used to

assess total Group value, to show sensitivities to major input parameters (see scenario

discussion in section 3.6.2) and to consider potential impairment issues. These annual

valuations, prepared by each BU and expressed in Net Present Value (NPV) terms, lay down a

PEG compliant “central estimate” valuation for the forthcoming plan year.

• For mines, it is used to support the reserves prepared for the plan – albeit with amended

assumptions to meet Rio Tinto guidance on both JORC and SEC reserve submissions.

• Optimisation studies including strategic option analysis and sensitivity analysis. This may be

concerned with quantum changes in business activity or simply assessing the value of operating

procedure changes, revenue or cost saving initiatives. A model should show the elements of the

business value chain and the potential to increase NPV.

• Project evaluation and justification (to the Investment Committee) of the (physical and) financial

benefits of proposed capital investments.

• Competitor studies including potential acquisitions or divestments and for benchmarking.

• Crosschecking with the outputs from the more complex (data based) financial systems used

(e.g. SAP and in-house financial models).

These different applications of models will usually require some customisation/ variation from the

central estimate case logic and structure. The nature of the input detail, the analysis logic and the

output formats required for any specific purpose may be different but any valuations so derived

should be reconcilable with the central estimate case.

Implicit in the above, is the compliance with PEG for the core part of the model. This requires the

derivation of a 100% equity-based cash flow statement. It is therefore preferable that additional

workings incorporating debt, minority interests, etc. should be shown separately.

It should also be noted that a high level model will be unlikely to have the same precision as a full setof accounting statements derived from the BU’s financial systems (typically for the first two years of a

plan period). The model should have a near identical cash flow statement but it is recognised that

7/21/2019 be1



profit and loss or balance sheet numbers (if included) may not have the same precision in relation to

debt, non linear items, special provisions, etc.

2.3 Business model content and functionality

However well constructed, any model is only as good as the inputs provided to it. BUs will have

short-term models which should provide the foundations of and be compatible with the early years of

the long-term business model. Theoretically, more detailed input allows greater functionality and

accuracy but this has to be balanced by the practicality of using the model, for both the owner and

other potential users, and by the relevance of data over the asset life (accuracy tends to reduce,

particularly after the initial plan years). As indicated above, this guidance focuses on higher level

models which aim to provide a succinct representation of the overall business.

The disadvantage of projecting forward from early year hard coded inputs in a high level model is

that their relevance may reduce sharply once the model is asked to run options away from the

central estimate case. It is therefore necessary to decide on the functionality required for the model

and ensure that the data inputs are capable of driving both the physical and financial calculations

that lead to meaningful outputs.

As a minimum, any model should have a representative material balance that can be followed

logically from ore in the resource to the saleable product. Where there are key constraints on

physical activity, the modellers should consider including a flag or test against the constraint.

Similarly the financial numbers should be logically laid out and provide a comprehensible trail from

input to output. In particular, inputs taken from financial software (e.g. SAP) should be taken back to

the most original, appropriate source and whilst aggregation of like costs may be required, numbers

based on intermediate calculations should generally be avoided as inputs to the model (e.g. show

“tonnes” and “grade” rather than “contained metal”).

7/21/2019 be1



3. Guidance on Model Design

3.1 Software to be used

Microsoft Excel is the current tool of choice for high level models. Each BU should have at least an

Excel representation of its business, in a form that corresponds to the annual valuation for the

current planning period.

3.2 Model design and development

Rio Tinto does not recommend a single “master template”, the broad design is left to the modelling

team. The process should start with the key stakeholders (potential users, output recipients, data

providers, etc.) contributing to defining a scope and then outlining the logic to be used, to ensure that

the desired results will be calculated. Clarity on the critical outputs expected and the key business

variables driving the result should be decided early on to avoid a model with excessive detail/ logic in

non-critical areas. Visually outlining the overall design on a whiteboard or similar can be very useful.

A documented scope with the estimated budget and timescale for the development should be

agreed.

While creating a new model or carrying out a major review of an existing model, it is recommended

that the stakeholders continue to meet to discuss the evolution of the model and to review the

outputs and flexing options that they are expecting. It is also important to consider how the data

inputs should be sourced and to be aware of potential difficulties in obtaining good data. Throughout

the development process, there should be a clear owner of the model who is constantly testing it and

correcting the inevitable errors that occur during the build process.

The BED portal shows a checklist for BMG compliance. Consider using this checklists to confirm

that the model is meeting its objectives as well as aligning with Group guidance.

In summary, a best practice model is:

• Transparent in design and easy to use, allowing more focus on productive use of the model for

analysis rather than struggling to produce simple results from a badly designed model.

• Focussed on the important business issues, so time is not wasted in unnecessary development

of redundant features and/ or detail.

• Easily maintainable.

3.3 Model structure – General

Two styles of model structure are typically used:

Format A: Models with multiple worksheets; these typically may show;

i) All inputs/ calculations/ outputs on separate sheets OR

ii) Sheets for each functional area (marketing, mining, process, etc.) showing clearly separated

and appropriate inputs and calculations plus a sheet aggregating the results into cash flow,

earnings and other summary outputs.

Format B: Models in which the entire business is represented in a single vertical sheet. This allows

multiple options to be considered and then placed side by side in the model file so that the

differences between cases can be directly compared. A separate sheet with common business

drivers can then be added so that all the cases can be flexed together and the relative

consequences assessed.

Appendix 3.1 shows some typical structures used for modelling.

7/21/2019 be1


7/21/2019 be1



• All models should be set up to show annual data in columns running from left to right. Sub

division of years (e.g. monthly or quarterly for initial periods) is used by some BU’s and, as a

minimum, it is recommended that such columns should be placed on a separate sheet or

consideration be given to placing them in a separate model that may mirror the model row

structure. If these part year periods form part of the calculation process, this should not detract

from the ability to run sensitivities/ flexes.

• The start date for the valuation should be clearly shown and each calendar year should be in the

same column on every sheet. This will assist model development and make auditing much

easier.

• Inputs should never be duplicated in the core modelling area; i.e. data should not be entered in

more than one location. If a range of cases/ inputs (e.g. for sensitivity analysis) is required, a

suitable multi-case table can be included; this is then read using one of the Excel functions at the

commencement of each calculation run. An example of this is shown on the AltInput sheet in the

sample model, with a simple drop down function selecting the case to be valued.

• All inputs should be clearly identified and colour coded. A dark blue font on a pale green

background (to show up when photocopied) is used in the example (Appendix 3.3). One

business modeller who suffers from colour blindness has requested care with colour coding as

he sometimes cannot differentiate the signal being given. Remember that sheets may

sometimes be printed in black and white – so suitable use of soft cell shading (fill) will at least

indicate cells which may be inputs.

• Colouring of data which is being read from other sheets in the same file is optional, but if used,

cells must be coloured differently to the raw input colour. An example is given in the sample

Preface sheet (Appendix 3.2).

• If, while developing or populating a model, the data in a cell or the logic of a calculation is

dubious, use a separate (temporary) strong colour to identify this cell as one which needs further

checking.

• All inputs should be shown separately from the related calculation and output rows. If structure

A i is used, all inputs will usually be on a single sheet. Some BU’s prefer to input data for a

functional area and then lead into the matching calculation directly below; this is acceptable if

there is clarity and co-positioning of the relevant inputs.

• There should be no hidden cells, rows or columns containing input data; use the Excel “Data/

Group” facility to allow rows or columns that are not being worked on to be temporarily hidden,

but do not use permanently hidden rows. Similarly, intermediate calculations may be grouped

and temporarily hidden to aid clarity (see section 3.5.1).

• No cells should have a mix of raw inputs and calculation such as “=K24*45” – again, no hiddeninput data. If the 45 in this example is constant across a row, enter it as a hard code (say cell

E24) and use “=K24*$E$24”; if the 45 varies with time, enter the parameter across a separate

row and multiply the result along the lines of “=K24*K25”.

• Ideally there should be no logic changes across the columns – other than in the historical data

columns (see section 3.5.9) or in any initial years where hard coded input is made. The design

should aim to have only one formula across any row. If a logic change is required in future

years, consideration should be given either to introducing a separate input row or to using the

Excel “IF” function. Conditional formatting, showing a strong colour, may be used to show a

switch in the logic as decided by an “IF” function.

• Reserve column A on each sheet for row notes to indicate:

7/21/2019 be1



○ Sources of input data and date. If data has come from an external source, ensure that a Rio

Tinto person has at least endorsed its validity – showing this in column A

○ Basis of calculation logic – if not obvious

○ Any other comments that might aid the reader understand how that row of the model

functions

• If the note becomes excessively long for the space available, either merge several cells down

column A to create a larger entry box or, only then, consider using the “insert comment” facility,

available by right clicking the cell.

• Identify each row with an appropriate descriptive title – typically use columns B and C. Where

possible, consider linking further uses of that title with a formula, rather than re-typing it.

• Provide a units column consistently through the worksheets, typically in column D, and use

consistent formats for units. This is preferable to including the unit in the title column of the row

e.g. Rather than “Tonnes mined kt“ show “Tonnes mined” and “kt” in separate columns.

•

Provide a column to the left of the annual (year) columns where totals or averages (e.g. grades)can be shown (see Appendix 3.3). This allows a quick sanity check which will be more visible

than if the totals are placed on the far right of the sheet.

• Use consistent number formatting and avoid large numbers of significant figures. Use “millions”

with perhaps no more than a couple of decimal figures rather than a large “thousands” number.

Where appropriate, use brackets rather than a minus sign to indicate negative numbers.

• A sheet will be easier to read if zero value cells use the dash (“-“) convention where a zero

number has been deliberately entered or an algorithm is present.

• It is not necessary to enter cost inputs as negatives but where values are being aggregated as in

a cash flow statement or a profit and loss statement, it is recommended that revenues are shown

in black and costs are shown in red with brackets. See examples in Appendix 3.3.

3.5 Selecting the data to input

As indicated in chapter 2, as far as possible, inputs should be in real terms reflecting currency of the

valuation date. If nominal input values are essential, consider a suitable cell colour code to indicate

this and show as Nominal$ in the unit column.

It is acceptable to have some intermediate subsidiary calculations in the input area – for example

where sub totals of product or ore tonnes might be a useful check of the validity of an input row.

Defining the source and level of detail for the inputs is intrinsic to a model’s value as a management

tool. As discussed in section 3.3 above, there is a balance required between complex/ detailed andhigh level summary inputs. It is important to understand what data is available from existing sources,

how meaningful it may be over multiple future years and how to extract the key drivers for use in the

model.

3.5.1 Use of the data/ group function

Whilst constructing, using or reading a model, the Data/ Group function is extremely useful as it

permits rows which are not being worked on to be temporarily hidden. A well structured input sheet

can be reduced to a few major headings and, if required, a few visible key input rows - when all the

grouped rows are hidden. This allows rapid appreciation of the high level logic followed and

navigation to the rows of interest.

The same function can be used to hide the row notes in column A, as described above, so that it

does not occupy screen space when not required.

7/21/2019 be1



A similar argument applies for calculation and output areas. Grouping is used in the sample model.

(Note – remember that hiding the data for graphs using grouping renders the graph blank in Excel –

one solution is to put data at bottom of sheets and away from the grouped rows).

3.5.2 Input currency

While the US$ is the dominant currency of many Rio Tinto models, other models assume inputs thatare in their local currency plus sometimes a mix of other currencies. This is essential where these

elements represent a significant part of revenue or costs. As a minimum, each model should show

some percentage of the input costs and/ or revenues as being related to the US dollar and include

logic that reflects this when the US$/ local currency rate is flexed. See Appendix 3.3 for an example

where a simplistic aggregate percentage is estimated for operating costs and another for capital

costs. Complex multi-currency projects will usually require a more sophisticated analysis.

3.5.3 Commercial input

The PEG eRoom provides guidance for the major commodities that Rio Tinto produces, where there

is either a fully transparent (LME) or partially transparent (benchmark) pricing basis. Product Groups

selling more specialised commodities such as industrial minerals will have their own pricing sources.

The model should show the base price where appropriate and, where there are adjustments to this

price due to premia or discounts, these should be shown separately to allow sensitivities to be

tested. Royalties, freight and other selling costs should be input to allow the revenue to be correctly

computed.

3.5.4 Operating cost input

Each business will have to determine an appropriate level of cost detail for its model. Chapter 2

outlines the direct operating and the general & administrative costs that should typically be

considered. This guideline cannot address the wide variety of input drivers that apply across Rio

Tinto, but it is suggested that two levels of detail be considered:

Level 1 is populated with fixed costs and variable unit costs (on occasions derived from an absolute

input value divided by the driver – e.g. absolute dollars/ absolute tonnes); this is a minimum

requirement and the major functional activities should be reflected in both physical and financial

terms. For example the mining function might be reflected by the following inputs:

Physical Drivers Financial Input

Ore mined (drill/blast/load tonnes) Variable cost ($/t)

Ore grade (%) Feeds into recovery/ revenue calculation

Waste mined (drill/blast/load tonnes) Variable cost ($/t)

Ore haul (tonnes) Variable cost ($/truck hour or $/EFH {Effective Flat Haul} km)

Waste haul (tonnes) Variable cost ($/truck hour or $/EFH km)

[None] Fixed operating costs ($)

Level 2 should be considered when a deeper analysis of the business is required and includes

productivity and input price data; for this guidance note, this level is set as “best practice”. The

inputs are broken down into more fundamental drivers and costs in order to allow an aggregate of a

particular cost type to be made and the impact on the business better assessed. A typical example

would be where the total energy demand from the operation is computed and the sensitivity to

different energy price inputs assessed.

7/21/2019 be1



The ore mined row in the table above, for Level 1, might then be broken down as follows:

Physical Drivers Financial Input

Ore drill/blast/load (tonnes) Variable cost ($/t)

Labour numbers/t Labour price ($/hour)

Energy litres or kWh/t Energy price ($/litre or kWh)

Ore mined (tonnes) Supplies/maintenance ($/t)

Similar breakdowns would then be selected for waste mined and for hauling variable and fixed

costs.

If a site aggregation of labour or energy is required, each functional area of the operation would

need to have inputs divided into similar categories.

If the model does not go into this detail, it may be necessary to use a more detailed, short-term

model to check that the important value drivers are reflected in the level 1 modelling. Section 8 of

volume 2 provides guidance on cost assessment.

3.5.5 Rollover of physical and cost parameters into future years

If input data appears only to be available for a limited number of years it will be necessary to project

these inputs forward.

The modeller should firstly check whether an engineered forecast can be provided; for example it

would be dangerous in all but the simplest of conceptual studies or sensitivity analyses to create a

valuation without taking inputs from a properly sequenced and costed mine plan. If the mine cost

inputs are Level 2 as described above, the validity of flexed cases will be more relevant than a Level

1 input model which may rapidly lose accuracy.

Where input assumptions have to be projected forward because no engineered data is available, the

validity of the projection will still be influenced by the level of detail at which the inputs are modelled.

But one should bear in mind that uncertainty increases and accuracy falls with years.

Using near term cost forecasts as the basis for forward projections may pose risks as they may not

be representative of long-term costs – this has been particularly true in recent years where input

costs (e.g. steel and energy) have risen far faster than inflation. It is reasonable to assume that

there is a correlation between input costs and a strong rise in commodity prices but as commodity

prices revert to a long-run level, so will (some) input costs return to long-run levels. The guidance on

this is covered in chapter 2, but the relationship between revenue prices and input costs must be

considered carefully before rolling out a long-term (flat) assumption. Where major expansions areinvolved, projection of both fixed and variable costs may need review.

3.5.6 Forecasting improvements

A key issue to watch when modelling improvements is that of quantum performance improvements

which may have been included in the model. These may come from:

• Capital investments: the model should split out sustaining capital (including necessary HSEC

expenditure) from development capital. The impact of the latter may be on physical, revenue or

cost performance; the model structure should allow the benefit of the improvement to be visible

in the inputs and it should show the aggregate (incremental) effect in the outputs. The sample

Excel model includes an example where the recovery at a concentrator is improved as a result ofcapital investment. A drop down selection option is available on the Input cell so that the result

“with and without” the investment can be shown.

7/21/2019 be1



• Management improvement initiatives: some models have single line entries for “unspecified” (un-

engineered or undefined) improvements. Whilst it is always better to include defined

improvements, it is recommended that the benefit of any “target” improvements should be

modelled in a way that shows how much they contribute to the overall valuation. Care should be

taken that these savings are not double counted with any PEG cost saving trends (e.g. falling oil

price).

3.5.7 Capital cost input (including closure)

Capital costs are most often inputs from subsidiary workings/ models (e.g. mine planning software).

As noted above, sustaining operational capital, including ongoing HSEC capital, should be shown

separately from development capital. It is recommended that the model should show which major

development projects are approved and which are not.

Closure capital must be shown separately and, where appropriate, consideration may have to be

given to showing both non-cash provisions for closure and actual cash expenditures.

If variations from a central estimate case are required, a decision will be needed on how to flex

capital; flexing capital proportionately to physical or commercial sensitivities may not be appropriateand there may be a need to utilise new hard coded entries from an engineered alternative case. In

some circumstances, simple switches might be included in the logic so that a particular capital

expenditure profile can be “in “or “out” - with a corresponding effect on physical or financial

performance. This equates to a Level 1 standard of model.

For major project submissions, as described for operating costs, a more sophisticated Level 2 model

will break down the capital inputs in more detail and may well have some simple algorithms which

allow a degree of automatic flexing as volumes or other drivers change.

As existing operating companies will have asset registers with a range of residual depreciation lives,

it is generally recommended that the forecast depreciation charges for existing assets are hardcoded inputs to the model. For ongoing sustaining and improving capital, suitably high level average

depreciation rate(s) can be used so as to allow changing capex inputs to impact depreciation –

possibly in two or three categories depending on the applicable local tax regulations (care must be

taken in cases where earnings depreciation is different to tax depreciation).

3.5.8 Working capital

Inputs for major working capital would normally cover inventory, debtors and creditors. Whereas

inventory should be calculated from the physical plans and should pick up any differences between

sales tonnes and production tonnes, debtors/ creditors are typically input as an average number of

days (of revenues/ costs) so that this part of working capital flexes with prices, costs and volumes.

Working capital must be calculated in nominal terms, per section 7.5.7 of volume 2, in order to showthe value impact of holding it. The model should reflect the liquidation of working capital at the end

of asset life.

3.5.9 Historical data

The inclusion of prior year data provides a useful opportunity to compare forecasts with actual

performance. Re-organisations or major investments may render comparison difficult but, even if

only a selection of high level numbers are incorporated, this can provide a good benchmark when

considering the forward looking assumptions.

It is strongly recommended that the model shows at least two years of ‘actuals’ for existing

operations. Applying the calculation logic of the model to these years will also allow a check on thelogic for much of the model. When moving the base year for the model forward (e.g. for each

planning cycle), the historical information should not be discarded.

7/21/2019 be1



3.5.10 Carbon costs

Section 7.5.7 of volume 2 requires that models include an estimate of carbon costs. In all cases the

inputs and calculations of this cost should be shown separately in the model.

3.5.11 Terminal values

Excel allows multiple years laterally across the working sheets and it is recommended that the model

is populated with data for the anticipated valuable operating life of the operation. Therefore, terminalvalues are not recommended.

3.5.12 Input links to other models

During construction of a model, many modellers will collect inputs from a series of external or

subsidiary (Excel) data sources and keep live links to these sources to assist with auditing the

developing design. These should provide input data only and the high level model should never

drive any calculations in the source models. When the links are broken, the high level model should

be capable of functioning in its own right.

Where the model is being used to run multiple options the alternative input methods include:

• Keeping live links with regularly used source files and creating the different options in this source

file – e.g. market tonnage and price mixes or varying mine plans;

• Using a discreet area in the model where alternative inputs can be copy/ pasted;

• Setting up an input area where several scenarios are hard coded (copy/ pasted from subsidiary

data sources) and then selected using either a switch logic, a look up function logic or a macro

(see also section 3.6.2) to run through the cases. The sample Excel model does this for

alternative mine plans and alternative price scenarios on the AltInput sheet - with drop down

selection of the requisite case being made in the yellow highlighted cells on the Input sheet.

The use of live links is generally considered the most risky approach because these can fall out of

synchronisation when models are e-mailed or worked on in isolation. This guideline favours hard

coding using copy/ paste, but BUs should make a conscious choice as to what suits their needs after

due consideration. If live links are retained, it is suggested that a specific cell colour protocol is

adapted - see example in Appendix 3.2.

It is recommended that each BU should maintain a summary map of the relationships between these

additional models. It is also suggested that if a model is being updated or further cases are being

run, the relationship between the then current version of the model and the annual central estimate

valuation should be shown on the Preface sheet.

3.6 Calculation Areas

The model should flow logically and, where practical, it is recommended that physical calculations bekept separate from financial calculations. Working in discrete blocks with an easy to follow sequence

and an obvious concluding row for each section is recommended.

The primary objective of the calculation algorithms is to reflect the business value chain and show

how it is affected by the key business drivers. Calculations should show:

• All significant physical movements including, if appropriate, any rehandling or movement to/ from

stockpiles/ stocks. Unless they are significant, physical and value calculations are not normally

necessary for all the immediate stocks in the mining process since many models will usually

assume steady state stocks with a higher level working capital calculation capturing any major

movements; e.g. for a major expansion;

7/21/2019 be1



• A material balance for the entire production process – from ore in-situ to saleable product. The

model should not take product tonnages as hard coded numbers from a subsidiary model, but

should show the recovery and other factors used to compute them;

• Sufficient calculation rows for a reviewer to understand the aggregation of physicals, revenues

and costs. Models should avoid cells with excessively long formulae which carry out complex

calculations that are hard to follow; such formulae should be broken down into steps that ensurethe logic is clear;

• Workings should generally be in real money terms. Exceptions to this include:

○ Computation of tax, including depreciation. Tax computation is often complex and the model

designer should take expert advice from the tax department;

○ Computation of working capital;

○ Earnings statements and balance sheets (if included) as derived from the real terms cash

flow calculation;

•

Whether calculations are in real or nominal terms, possibly using a cell colour coding, and alsowhether numbers are in mid-year, start of year or end of year terms. Similarly, the date of the

NPV calculation (start or mid-year) should be clearly identified;

• The element of revenues plus operating and capital costs that are determined by different

currencies – where significant;

• Whether the resulting valuation is a 100% valuation or Rio Tinto’s share – if not a 100% owned

entity.

Section 7 of volume 2 provides fuller guidance on some of these issues.

The simple working example shown in Appendix 3.3 assumes cash flows are spread evenly over the

full financial year considered. This may not be the case, particularly during project start ups. BED orT&I can provide advice on how to model this.

3.6.1 Calculation summary

On a long calculation sheet where certain key calculations have been concluded many rows from the

top of the sheet, interim summary rows can usefully be placed near the top of the sheet. This will

help a new reader to navigate to the relevant calculation area.

An equally effective approach is to use the Group facility in Excel to close down the calculation to a

very small number of rows with just the key outputs visible. The relevant rows can then be opened

up for the reader to examine as required.

3.6.2 Sensitivities and scenario analysis

There are numerous ways of calculating and showing the model sensitivities discussed in section 8

of volume 2. Changing the hard coded inputs is the simplest, but something more sophisticated is

required if multiple alternatives are to be considered.

Data tables are a simple to use Excel function allowing two input parameters to be flexed with the

resulting outcome in a format that is ideal for graphical representation. It is worth doing a brief

manual calculation check of one cell of an array output like this; just to ensure the logic has been

correctly applied.

Where one parameter is to be flexed by a constant multiplier, it is often practical to build in the

multiplier along the row concerned and drive this from a clearly identified input cell.

7/21/2019 be1



Section 8 of volume 2 provides upside and downside scenarios detailing a set of synchronised

assumptions on prices, cost and, in some cases, currency. This will require the running of scenario

analyses where multiple parameters are to be changed. This could be done using individual hard

copy/ pasted entries on multiple rows, but it is possible to automate a model so that either a switch or

an Excel lookup function can be incorporated. The sample Excel model does this with a drop down

switch on the Input page which selects from a “menu” of scenarios on the AltInput sheet. The

handling of currency exchange rates needs particular care, because the PEG scenario cost profiles

are derived from US$ data and therefore the local currency content of costs must be modelled when

changing exchange rates.

Simple macros can be used for scenario analysis but it is not the purpose of this document to

provide advice on macro writing. Using macros is a specialist skill and is generally discouraged,

especially for multi user business models.

The long single vertical sheet model described above allows multiple cases to be placed on adjoining

sheets with certain key drivers, to be tested for sensitivity, entered on a separate input sheet, which

drives all the cases simultaneously. The structure of such a model is shown in Appendix 3.4.

3.6.3 Range names

Many modellers use range names to facilitate spreadsheet navigation and selection of print ranges.

Range names can present problems during a model’s construction – if cutting and pasting or logic

changes are frequent – but they do aid understanding provided they are clearly defined. For

example: Price *exchange is far easier to comprehend than H7*H43 .

An excessive number of names can quickly cause confusion to a new reader, it is suggested that a

limited number of names are used and are defined on the Preface sheet.

3.7 Model Outputs

Model outputs will be individual to each business unit, with the format and results presented to suitmanagement requirements. Once the model has been developed and tested, running it is a different

activity. The new reader or user of the model should rapidly be able to appreciate the key features of

the business from a set of well chosen outputs.

It is recommended that outputs, such as earnings statements, be presented in a way that is initially

comparable with the format and definitions used for the business’ monthly reporting and plan

formats. Revenues should be on the same basis (ex works, delivered, etc.), costs should be shown

so that they can be aggregated to match the same departmental functions, etc. This should then aid

the review of the model against history and current year actuals.

Depending on the business or project being evaluated, deeper analysis of the results can then beadded as part of the model outputs. As a minimum all models should show:

• A real terms cash flow over the life of the asset. This should show 100% equity cash flows

before debt; with any financing impact shown separately. The output sheet in Appendix 3.3

includes columns to show, for each revenue and cost heading, the total cash over the asset life

and the discounted cash value of that row. This provides a high level view of the major

constituents of the net present value.

• A nominal terms earnings statement (P&L).

Modelling of balance sheets can be difficult; particularly those including financing/ debt, non-linear

provisions etc. The advantage is that they can provide a validation of the modelling outputs. BUsshould decide on whether to include a full or partial balance sheet.

7/21/2019 be1



Other outputs may include charts and tables showing the key features of the business including

identification of key drivers to support sensitivity analyses and a summary of the sources of

underlying value. Waterfall analysis is a particularly useful format for showing the value chain, as

shown in the example in Appendix 3.3. Care should be taken that graphs are not misleading, for

example with inappropriate scales, and that they deliver a meaningful message about the business.

When a new annual valuation is prepared; the output should be structured so that, by comparison

with the previous version, the major reasons for the value change are visible – at least at high level.

Where the model is being used for an investment proposal; the elements of the value being added

should equally be visible.

3.7.1 Output summary

In most cases the output area is extensive and delivers a substantial amount of information.

Consideration should therefore be given to a summary output area – optionally on a separate sheet.

This should present the key results only, including key sensitivities, and be suitable for printing or

pasting into a written report as a standalone summary. The summary might include the project

name, location, ownership, mined tonnes/ schedule, operating and capital costs, products, revenues,

valuation and, most importantly, the valuation date and case description.

If the model is used to run multiple scenarios, copy/ pasting this summary onto an archive sheet

(within the model or otherwise) can provide an important reference for future use. Supplementary

output sheets, with a specific set of data, may also be created for forwarding to an interested party,

who does not want or should not have the whole model.

3.7.2 The CGU template

The sample Excel model now includes an output section which mirrors the sheet named CGU2 in the

template sent out by Controllers as part of the annual planning process. This shows the raw 100%

equity basis cash flows over the life of the cash generating unit and allows selected sensitivities to be

hard copy/ pasted into this output section.

The key sensitivities to be reported in the template are taken from the PEG price guidance tables

and consist of one upside scenario and one downside scenario. The business model should be run

with the appropriate scenario inputs and the results copy/ pasted into the allocated areas of the

output sheet. Controllers review these two scenarios and will ask for further sensitivities to be run if

the carrying value of the asset is below or close to the downside scenario NPV. Additional areas in

this output section allow these further sensitivities to be recorded.

This data can then be copied directly into the full CGU template, which has been amended to match

the sample model output format.

An addition to the 2012 CGU template is a request for data on the reserves and resources

consumed in the annual plan valuation. This should be acquired from the appropriate Competent

Person and would not normally be available in the high level business model.

3.7.3 The PEG sensitivity template

The sample model also includes a modified version of the PEG Excel template which should be

included in an Investment Committee proposal. The example deals with an overall operating asset

rather than just a project; the sensitivities therefore need to be slightly different and should be

selected to suit BU requirements. The section in the sample model can be quickly modified if a

particular project is to be reported,

7/21/2019 be1



4. Model Integrity, Testing and ChecklistsFor a model to be useful it must be technically accurate as well as giving a suitable reflection of the

overall business. It is therefore essential that the complete model is tested, typically against the

following headings:

• Meets specification – giving the required outputs

• Formulae are appropriate – reflecting the business drivers

• Numeric accuracy – the quality of inputs and calculation

• Robustness – able to deal with all feasible scenarios or applications

Specific testing techniques will vary but a good starting point is the BMG checklist, which has been

prepared to allow assessment of models against this document.

It is recommended that, throughout the model, and particularly in the calculation area, suitable built

in integrity checks should be built which flag potential errors to the user – be they in the insertion of

new input data or in the execution of the calculation logic. These may include check rows which

carry out simple maths checks to ensure that row totals derived by adding across columns give the

same totals when added vertically or that total costs divided by a suitable physical driver show

sensible unit costs etc. Output graphs will often show a discrepancy in the logic, if for example there

is an unexpected step change on the graph or simply an out of range outcome.

Where physical constraints are being tested or where values should not leave a given range, the

modeller should consider using the data validation function and/ or conditional formatting to flag

when the constraint is breached.

One check of numeric accuracy may be to compare the model outputs with the outputs from other

planning tools at the BU (e.g. the initial years of the BU plan might be generated in SAP and, if

possible, some flexed cases should be compared over these years).

There are some excellent Excel auditing tools which can be used to review the content and structure

of models. These can show where inconsistent formulae have been introduced across rows, where

hard coded entries have been input, where complex formulae have been created, etc.

It is recommended that testing of new models, or reviews of ongoing models, should be carried out

by someone other than the model creator. This will allow an impartial assessment of the

transparency and usability of the model, as well as checking its underlying performance. All major

changes to the model should be shared with this independent reviewer. BED/ T&I can assist with

the auditing of models.

It is not enough to have a model which is mathematically precise as there may be flaws in the

underlying logic used. A user’s experience will therefore always be called upon and, if the model is

well structured and transparent, there is a far better chance of intuitively recognising faults in the

logic when reviewing the results, particularly if extreme case inputs are being considered.

The model owner will have collected multiple inputs from different departments in the BU. After

constructing/ updating the model, it is strongly recommended that he/ she shows the relevant model

outputs to the input providers so that they can review them and comment if surprised by what the

output shows.

7/21/2019 be1



5. Model Ownership and SecurityThere should be a defined owner of the model, whose identity is flagged on the Preface sheet. The

model should be stored securely on an appropriate network drive with controlled access as required.

In some BUs, the number of people familiar with the model is very small. Such models should be

made as accessible as possible, while good practice demands a reasonable degree of back-up for

the primary owner of the model. Some BUs have chosen to prepare a user manual for their models;

the need for this is considered on a case by case basis.

Where sections of a model are particularly confidential/ sensitive, a cut down version using summary

data might be created; for example detailed sales contracts might be summarised to provide average

price inputs if the model is being used by a technical group who do not need this detail for their

analyses.

The use of the cell locking function should be considered for all but selected input cells, particularly if

the model is being used by people outside of the model owner’s department.

As shown in Appendix 3.2, at the bottom of the Preface sheet, it is recommended that a suitableconfidentiality statement be inserted in every model. The words chosen for the sample model have

been approved by the Rio Tinto Legal Department.

5.1 Change control

The sample Preface sheet in Appendix 3.2 shows an area at the bottom where users of the model

can comment on the content, logic, etc. of the model. The purpose of this is to encourage

suggestions for improvement by asking users to send comments on the model back to the primary

owner of the model. It is then the owner’s decision on what changes to implement, to document

them and raise the version number accordingly.

Each BU should develop a formalised procedure for change control related to their primary businessvaluation models.

7/21/2019 be1



Appendix 3.1: Typical Business Model Structures - Overview

TYPICAL BUSINESS MODEL STRUCTURES

SHEET tem SHEET ItemPREFACE File name; contents; protocols;

change history; related modelsPREFACE File name; contents; protocols; change

history; related models

INPUTS - all financial & physical inputs Corporate guidance (exchange,discount etc)

PHYSICALS Input Reserves; mine plan; process etc

Commercial assumptions; prices;royalties; discounts; freight etc

Calculate Physicals; production and full materialbalance

Physicals (reserves, mine plan,processing etc)

COMMERCIAL (including financialinputs need to compute revenues - suchas exchange etc)

Input Prices; exchange; royalty; volumes(driven from physicals or as input from

Marketing); discounts; freight etc

Operating costs - variable & fixed(by area/process)

Calculate Revenues (by product and region asappropriate); unit prices etc

Capital costs - sustaining capital;major projects; closure

OPERATING COSTS Input Variable & fixed cost assumptions (byarea/process) - real (with nominal forearnings statement)

Other (tax, depreciation, debt if

appropriate etc)

Calculate Total operating costs

FIXED CAPITAL COSTS Input Sustaining capital; major projects;closure

CALCULATIONS Physicals; production and fullmaterial balance

Calculate Total capital costs

Revenues (by product and region

as appropriate); royalties

Depreciation

Total operating costs - real (withnominal for earnings statement)

FINANCIAL (tax, if complex, may be ona separate sheet)

Input Other - discount rate, tax, provisionsetc. Opening balances if appropriate

Fixed capital including closure Calculate Cash flow; NPV; earnings statements,

margins etc. Debt if required.

Depreciation/tax Sensitivities - as required

Working capital

Other - debt & funding if appropriate Check calculations

Sensitivities - as required

Check calculations

OUTPUTS - Summary reports & graphics Key physicals OUTPUTS - Summary reports & graphics Key physicals

Cash flow & NPV Cash flow & NPV

Earnings statement Earnings statement

Balance sheet - (optional) Balance sheet - (optional)

Key performance indicators & otheranalyses

Key performance indicators & otheranalyses

Charts Charts

SHEET Item

PREFACE As above

SUMMARY SHEET - major outputs Can look at multiple casessimultaneously. Compares options,shows graphs etc

COMMON DRIVERS (Major) inputs used to drive allvertical sheets simultaneously

VERTICAL SHEET 1 - Datum Case

showing entire business

Inputs as for multiple worksheetabove except for those driven fromCommon Drivers sheet

Calculations as above

Outputs as above - for datum case

then add alternative scenarios on new s heets

VERTICAL SHEET 2 - Scenario 1 New inputs for scenario, except forthose driven from Common Drivers

sheet


Outputs as above

VERTICAL SHEET 2 - Scenario 2 New inputs for scenario, except forthose driven from Common Driverssheet


Outputs as above

Multiple Worksheet - Format A ii

Vertical sheet model - Format B

these are identical so that outputsalways on same row

For scenario analysis, some modellerswill add an "alternative" input data

section. This may be at the bottom ofmain Input sheet or on a separate

identically formatted sheet allowing

either copy/paste of data to the mainInput area or including a logic to readthis with a switch or a macro (notencouraged by the BMG document)

Multiple Worksheet - Format A i

Note : As indicated in the BMG text, all models should maintain consistency in matchingcolumns and calendar years. i.e. 2007 is always column K for example.This will make it easier to move a multi sheet model into the vertical format if required for asubsequent analytical exercise (e.g. Strategic Production Planning).

7/21/2019 be1



Appendix 3.2: Example of a Model Preface (Front Sheet)Note : This is a sample Preface sheet. Where text is shown in red italics , these are explanatory comments and not part of normal Preface

CLICK 2 ON TOP LEFT CORNER TO OPEN UP TH E GROUPED ROWS IN EACH SHEET

Filename BMG sample model Axia 12 Rev 2 - 6 Jan 2012.xlsx Prepared in Excel 2007 but readable in earlier versions.

NPV 8 = US$ 494M = A$ 529M

MODEL NAME Axia Minerals LOM Business Model

PEG compliant? yesThis version shows

Operations covered All Axia operations in Australia including Mine A, Mine B, Process Plant and SG&A. Rio Tinto owns 80%.

CGU (s) included Axia Australia If more than one CGU included, expand and list all.

The model computes Cash Flow, Earnings and Net Present Value in Australian dollars as at 1 January 2012 over the remaining life of mine

The model is built on a 100% ownership basis. Rio Tinto share is only shown after the 100% cashflow/earnings calculation

For this sample high level valuation model, the life is deliberately short and the complexity low

This is a multi tab version of a model (Format Ai in the BMG section of PEG 6)

Contact

Creator(s) [email protected] London +44 7801 433202

Current Owner of model [email protected] London +44 20 7781 1979

Table of Contents

Sheet Item Comments Location - rows

Input General economic inputs PEG and Economics inputs 20 -47

(all financial & physical inputs) Commercial - Prices Product pricing - US$/unit

Commercial - Other Royalty, freight, terms

Physic als - Reserves Starting tonnes plus additions

Physic als - Mine plan Full Life of Mine physicalsPhysic als - Process parameters Recoveries etc

Operating costs - Mine Fixed & variable

Operating costs - Process Fixed & variable

Operating costs - SG&A Fixed & variable

Operating costs - Carbon tax Per PEG

Provisions and Closure Capital cost and provisions

Capital Sustaining and project capex

Other inputs Misc income, inventory, cash

Calc General financ ial - ex change/i nfl at ion Nom inal ex change rat e &

cumulative inflation

(All workings through to output) Physical production Saleable product

Revenues Converted to A$

Operating costs By process

Inventories Not used in this version

Capital costs & depreciation Simplified depreciation calc.

Working capital Creditors, debtors, inventory

Tax Simple flat rate example

Other income/expenses - net

Others - unit costs, margins, integrity checks Add as required

Tables for chart data Summaries to suit outputs

Output Key physicals Ore mined and product sales

(Summary reports & graphics) Cash flow & NPV (with value chain) Real terms cash flows

(with sensitivities as required) Earnings statement Nominal terms P&L

Balance sheet - (not included) Optional

Charts Key business graphs

KPIs Key performance indicators

CGU cash and sensitivities Rows set to feed CGU

template for Controllers

NPV sensitivities chart Example using BED template

Economic contribution chart Indicative example

AltInput (Alternative Data) Core and Alternative mine plans An optional sheet allowing

more than one mine plan

Central Estimate and Alternative price

scenarios

Allows selection of price &

cost scenarios per PEG 5

(a simple scematic poviding

an overview of the model is

outlined at the bottom of this

sheet)

Central Estimate case for 2012 plan, updated for new discount rate in December 2011. Itassumes no expansion of Mine B and mine closure in 2028.Update this for each significant version saved

Model description and

purpose

7/21/2019 be1



Preface continued with schematic summary below:

Protocols Used Examples

Colour coding Hard coded input - dark blue font on pale green, choice of colour to sui t John Smith (colour-bl ind) Must be coloured 1234

(to stand out in B&W)Must be coloured 1234

Input from another (linked) workbook - dark green font on pale green Must be coloured - none used t 1234

Data from another sheet in this workbook - automatic (black) on pale yellow not used this example 1234

All calculated cells - automatic (black) except NPVs in dark blue, no background colour 1234

1234

Column A Reserved for notes on sources of data, logic used etc (hideable with column group function)

Col umns B & C Descri pt or of each row; maj or head ings i n B and sub-head ings i n C

Column D Units where appropriate

Columns E & F Used to sum row data and show NPV, also to provide single value inputs or check cells

Columns G & H Two prior year's actual data - these are coloured with a turquoise background; hard coded inputs have a dark blue font

Column I Always year 2012.

This model does not include quarterly or monthly computations but they could be added in a subsidiary sheet if required.

There are no hidden inputs or calculations with hard coded inputs

Real terms All inputs and calculations are in real terms except on those rows where the uni ts cel l i s in ital ics and showingNominal.

Negative values Shown in brackets - with red font

Debt No debt or interest calculations are included in this model.

Nam es Names are l imi ted t o t he c el ls as li sted under " Formul as /Name Manager" on t he t ool bar

A brevi at ions Cons ider l is ti ng any abrevi at ions t ha t may not be obvi ous t o model users .

Others/links ……. There are no l inked fi les in this sample reference case; all inputs are hard coded.

History

Case - standard mode l Comme nts & Changes made NPV - A$M

01 Jul y 2009 Referenc e c as e - A xia 09 V er1 2009 pl an vers ion for updat e - di sc ount rat e 7% 385

02 October 2009 Plan 2010 - Axia 10 Ver1 2010 plan version for HQ 395

24 November 2009 After HQ review - Axia 10 Ver2 420

02 February 2010 2010 cont ract s - A xi a 10 Ver3 430

04 August 2010 Re-set fo r P lan 2011 - Ax ia 11 dra ft 450

30 S eptember 2010 P lan 2011 - Ax ia 11 Ver1 490

30 Apri l 2011 Updated aft er 1s t Qt r pl us re-est imat e of

benefit from concentrator upgrade project -

Axia 11 Ver 4

502

16 Oct ober 2011 P lan 2012 - Ax ia 12 Ver1 - 16Oct11 552

21 December 2011 Plan 2012 - Axia 12 Rev 1 - 21Dec11 529

(called working model for this example)

Related model versions Case - special studies

23 Oct ober 2010 E xpans ion s tudy - Ax ia 25Mt Exp V er1 450

Other related models

Source files - linked NONE

Source files - not linked

MineplanAB.xls

Processplan.xls

Comments & Sugge stions

2012 plan version for HQ. Reforecast tonnes and costs after 2Q result known. Better

prices for plan 2012. Strong A$ exchange rate.

(consider a diagrammatic map

of these other related models

if appropriate)

Marketplan.xls

Financecosts - SAP.xls

A dark blue font on a bright yellow background is used to show switch drivers and cells switched

to/from Central Estimate case using AltInput sheet data

2011 plan version for HQ. Reforecast tonnes and costs after 2Q result known. Better

prices for plan 2011

2012 plan version for HQ but updated to reflect revised PEG discount rate of 8%

CONFIDENTIAL

This document contains confidential information belonging to members of the Rio Tinto Group of companies. No further copies may be made nor may it be disclosed to any third parties

without the prior consent of the Current Owner of the Model as shown above. If consent is given, disclosures to third parties must only be made pursuant to an appropriate non-disclosure

agreement.

This area is reserved for users of the model to make com ments on the model - suggesti ons for improvement, errors found or queries on the logic. If this

applies, please mark up and colour highlight the applicable rows, summarise the issue below here and send back to the Current Owner of the model as

indicated above.

Comments here and in column A of relevant sheet (with colour highlight)

2010 plan after HQ review. Some costs reset. Delayed replacement of haul trucks.

Amended tax logic per London advice.Updated for PEG5 guidance incl. Scenario analysis. Added CGU format to Output

Inserted actual 2010 contracts now finalised. See Input rows for source.

Start year 2011. Actual for 2009 inserted.

Reforecast tonnes and costs after 1Q result known. Better prices

Recovery benefit increased to 8%

Inputs or calculations where there is doubt about the data or logic are coloured pink until the issue is resolved. Also used for some

non standard inputs

The following other BU models provide significant feed to this model, either directly linked or simply hard coded.

Quick evaluation of increase to 20Mt/y total ore rate.

BMG sample model - December 2011 - Final

AltInput (mine)

Datum

AltMin

Mine planningsoftware ….

Mine planswitch

Select mine plan used incalculation in Cell D44 inthe sheet called 'Input'

Input

General economic inputs

Site operations -Physicals

Calc

Physical production

Commercial inputs

Operating cost inputs

Provision & closure

Capital costs

Other

General financial

Revenue

Cash operating costs

Inventories

Fixed capital

Working capital

Tax

Other income

Output

Key physicals

Cash flow

P&L

Balance sheet - not incl.

Sensitivities

Key performanceindicators

Graphs & tables

AltInput (scenarios)

Similarly link these to the economic and commercialinputs

7/21/2019 be1



Appendix 3.3: Examples from a Simple Multi-Sheet ModelThe electronic version of this sample model is available on the BED portal, (zoom in on page for

greater clarity of this extract). The columns shown are columns A to N.

The extracts below are taken from the Input sheet and show the sources of data in column A; this

can be hidden using the “Data/ Group” facility in Excel so it is only visible when required. Each input

row should have a clearly identified source with appropriate authority. NPV result is shown top left of

every sheet so that the effect of changes are immediately visible. Scenario case is selected by drop

down in the cell.

The model has a full material balance and shows consumption of reserves per the engineered mine

plan. The mine plan physicals can be switched in this simplistic model, but appropriate changes to

capital and operating costs may also be needed.

Sources/Comments

Widen column A to read Filename BMG sample model Axia 12 Rev 2 - 6 Jan 2012.xlsx 2010 2011 2012 2013 2014 2015 2016Operating years driven from

Start Year 2011 or 2012 NPV 8 = US$ 494M = A$ 529M Operating Years Actual F'cast 1 2 3 4 5

Comments in column A Start Year 2012 Hard code inputs - blue font on green Alt inputs -

Valuation date 01-Jan

General Economic Inputs

Head Office Exchange/Price Assumptions Units

Local currency A$ Long termExchange Rate - Central estimate US$/A$ 0.93 0.80 0.99 0.95 0.94 0.93 0.93 0.93

Exchange Rate - for case chosen US$/A$ 0.93 0.80 0.99 0.95 0.94 0.93 0.93 0.93

US $ inflation rate % 0.00% 1.90% 2.20% 2.40% 2.60%

Australian $ inflation rate % 0.00% 2.80% 2.80% 2.80% 2.80%

RTHQ tax dept 6Jul11Tax Rate % 30.0% 30.0% 30.0% 30.0% 30.0% 30.0% 30.0%PEG 6 guideline, updated tp

8% in December 2011 Discount Rate per HQ % 8.0% Compound multiplier 0.962 0.891 0.825 0.764 0.707

Commercial Inputs SELECTED SCENARIO Central estimate Read from AltInput sheet

Prices Benchmark price - Product 1 US$/t flex 0.0% 255.0 280.0 494.0 494.0 494.0 468.0 448.5

Benchmark price - Product 2 US$/t flex 0.0% 400.0 430.0 455.0 455.0 455.0 429.0 409.5

Payable content - Product 1 % CIF 95.0% 95.0% 95.0% 95.0% 95.0% 95.0% 95.0%

Payable content - Product 2 % CIF 80.0% 80.0% 80.0% 80.0% 80.0% 80.0% 80.0%

Cost adjustment Scenario cost adjustment % total costs (apply after US$ adjustment - see Calc row 80) 0.0% 0.0% 0.0% 0.0% 0.0%

As per existing licences Other Royalties % CIF 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0%

Freight to po int o f sale - CIF Product 1 A$/t nb currency 20.0 20.0 20.0 20.0 20.0 20.0 20.0

Fre ight to po int o f sale - CIF Product 2 A$/t nb currency 26.0 28.0 30.0 30.0 30.0 30.0 30.0Creditor Terms days 40 40 40 40 40 40 40

Debtor Terms days 60 60 60 60 60 60 60

Choice of Start year but then

must change all Total

columns to sum from one year

different. Changing valuation

date requires change to NPV

formulae also

Apply to all costs except

carbon.

Sourced from Rio Tinto

Economics - plan guidelines

dated 1 August 2011 but then

updated in Oct 2011. Entered

on AltInput sheet. Need

second row to allow Scenario

cases to cost flex and

From Axia Transport, P

Smith, 4 July 2011.

Axia Finance, R Smith, 23

June 2011

Updated Oct 2011, M Smith. If

appropriate, customise these

rows to suit TC/RC, %

payable etc

Showing a couple of flex

factors to allow quick price

select drop down

Site Operations - PhysicalsCheck close Year start

Reserves Pit Aore in situ & stockpile Mt (0.0) 126.39 115.94 106.32 96.07 85.27 74.74

Grade - Metal 1 % 1.06% 1.05% 1.05% 1.05% 1.04% 1.03%

Contained metal 1 remaining Mt 0.0 1.33 1.22 1.12 1.01 0.89 0.77

Grade - Metal 2 % 0.78% 0.78% 0.78% 0.78% 0.78% 0.77%check rows + column F Contained metal 2 remaining Mt 0.0 0.99 0.90 0.83 0.75 0.66 0.58

Pit B ore in situ & stockpile Mt 0.0 126.21 120.36 113.43 107.21 102.30 96.59

Grade - Metal 1 % 0.65% 0.64% 0.63% 0.63% 0.62% 0.61%

Contained metal 1 remaining Mt 0.0 0.82 0.77 0.72 0.67 0.63 0.59

Grade - Metal 2 % 1.00% 0.99% 0.98% 0.98% 0.97% 0.96%check rows Contained metal 2 remaining Mt 0.0 1.26 1.19 1.12 1.05 0.99 0.93

Total

SELECTED MINE PLAN Core Read from AltInput sheet

Mine PlanPit A ore mined Mt 126.4 10.50 10.51 10.45 9.62 10.25 10.80 10.53 10.48

Grade - Metal 1 % 1.05% 1.07% 1.09% 1.08% 1.06% 1.08% 1.12% 1.12% 1.05%

Grade - Metal 2 % 0.78% 0.78% 0.79% 0.78% 0.77% 0.78% 0.81% 0.81% 0.76%

Waste Mt 567.5 39.00 38.00 41.79 46.50 36.98 39.19 37.67 27.38

Truck hours - ore mining khrs 62.7 4.50 5.00 5.22 4.81 5.12 5.40 5.27 5.24

Truck hours - waste mining khrs 212.8 13.75 14.25 15.67 17.44 13.87 14.70 14.13 10.27

Pit B ore mined Mt 126.2 3.85 4.85 5.85 6.93 6.22 4.91 5.71 5.33

Grade - Metal 1 % 0.64% 0.77% 0.82% 0.80% 0.77% 0.77% 0.77% 0.77% 0.76%

Grade - Metal 2 % 0.99% 1.12% 1.19% 1.16% 1.12% 1.12% 1.12% 1.12% 1.11%

Waste Mt 358.6 10.00 11.00 11.70 13.87 12.45 9.82 21.76 13.32

Truck hours khrs 63.1 2.50 2.63 2.92 3.47 3.11 2.45 2.86 2.66

Truck hours khrs 134.5 4.00 4.25 4.39 5.20 4.67 3.68 8.16 5.00

Total ore mined Mt 252.6 14.35 15.36 16.29 16.56 16.47 15.71 16.24 15.80

Total material mined Mt 1178.7 63.35 64.36 69.78 76.92 65.89 64.72 75.68 56.51

Switch allows an alternative

input data set to be pasted

and selected from the

supplementary sheet AltInput

Mine plan XXfrom G Smith,

26 June 11

Reserve estimate from L

Smith, Competent Person, 25

June 2011

Reserve estimate from L

Smith, Competent Person, 25

June 2011

select drop down

7/21/2019 be1



Variable cost inputs are selected to match major drivers. This shows Level 1 detail (see section

3.5.4).

Capital inputs can be broken down into considerably more detail; this just shows the summary rows.

Sustaining capital is best separated from significant development (project) capital.

The extracts below here are taken from the Calculation sheet. Good sequencing and clarity of logic

should make the calculations accessible to a new reader.

Column A can be used to explain any complex logic used.

Operating Cost Inputs - all in Australian $Mine Variable Costs Pit A Drill/Blast/Load A$/t material moved 0.60 0.65 0.65 0.65 0.63 0.63 0.63 0.63

Pit A Ore haul cost A$/hr - ore haul 200.0 200.0 180.0 170.0 170.0 170.0 170.00 170. 00

Pit A Waste haul cost A$/hr - waste haul 200.0 200.0 180.0 170.0 170.0 170.0 170.00 170. 00

Pit A Rehand ling s tockpi le A$/ t to/ from s tock This model has no stockpile activity - add rows if required

Pit B Drill/Blast/Load A$/t material moved 0.70 0.75 0.72 0.70 0.70 0.70 0.70 0.70

Pit B Ore haul cost A$/hr - ore haul 200.0 200.0 180.0 170.0 170.0 170.0 170.00 170. 00

Pit B W aste haul cost A$/hr - waste haul 200.0 200.0 180.0 170.0 170.0 170.0 170.00 170. 00Pit B Rehand ling s tockp ile A$/ t to/ from s tock This model has no stockpile activity - add rows if required

Mine Fixed Costs Mining department overhead etc A$M 15.00 15.00 15.00 14.50 14.00 13.50 13.50 13.50

From H Smith 4 July 2011

Process Variable Costs Input driven A$/t ore fed 4.00 4.00 4.00 4.00 3.80 3.50 3.50 3.50different finishing circuits Output driven - Metal 1 A$/t product 7.50 7.50 8.00 8.00 8.00 8.00 8.00 8.00different finishing circuits Output driven - Metal 2 A$/t product 14.00 15.00 15.00 15.00 15.00 15.00 15.00 15.00

Process Fixed Costs Process department overhead etc A$M 18.00 18.00 18.00 17.50 17.20 17.00 17.00 17.00

SG&A Other variable costs, overheads etc A$/t ore mined 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Other fixed costs, overheads etc A$M 14.00 14.00 13.00 12.50 12.50 12.50 12.50 12.50

Percentage US$ content All operating costs % 15% 15% 15% 15% 15% 15%

From Mine + P:rocess Plans Carbon tax inputs Tonnes of CO2 fr om oper at ions plan Mt 0.19 0.19 0.19 0.19 0.20 0.15 RT Economics guideline Anticipated unit charge US$/t CO2 19.00 19.00 19.00 27.00 27.00 27.00

Flex factor on operating costs flex 0.0%

Simple estimate - refine as

needed if percentage content

significantly changes through

From G Smith, 26 June 11 but

revised 10 Sept 2011

Not used here, but to allow

simple opcost sensitivity, this

Capital Cost InputsDepreciation method Plant and Equipment Straight yrs 5 20%

Property and Buildings Straight yrs 10 10%

Existing Asset Register check

Book value at start of year Plant and Equipment A$M 20 OK

Property and Buildings A$M 35 OK

Depreciation charge Exist ing P lant and Equ ipment A$M - nomina l 8.00 8.00 6.00 5.00 4.00 3.00 2.00 0.00

Existing Property and Build ings A$M - nominal 5.00 5.00 5.00 5.00 5.00 5.00 4.00 3.00

Closing balance these assets A$M 55.00 44.00 34.00 25.00 17.00 11.00 8.00

New Capital Expenditure - Summary Total $/unit driver

Plant & Equipment ustaining - mine (driver material mined) A$M 82.6 0.08 5.00 6.00 5.58 6.15 5.27 5.18 6.05 4.52

Sustaining - process (driver ore fed) A$M 39.8 0.18 2.60 2.90 2.93 2.98 2.96 2.83 2.92 2.84

Sustaining - G&A (driver ore fed) A$M 13.3 0.06 0.80 0.80 0.98 0.99 0.99 0.94 0.97 0.95

Sustaining - spare A$M 0.0

Carry over cash flow from these A$M 4.0 2.00 2.00

(assumes benefit alreadyincluded above)

Upgrade concentrator - both metals A$M 40.0 yes 40.00

Benef it - Recover ies inc reased by % 8.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%

A.N. Other project A$M 0.0

Benefit - as specified ….

Sub total Plant & Equipment A$M 179.6 8.40 9.70 11.49 12.13 9.22 8.95 9.95 48.31Axia Finance 23 June 2011 -

but existing charge for Plant &

Equipment awaiting internalreview Property and Buildings Sustaining A$M 15.0 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Projects - approved A$M 0.0From G Smith, 26 June 11 Projects - to be approved A$M 10.0

Sub total Property and Buildings A$M 25.0 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Note : Closure Capex entered separately

Total Capital pre adjustment A$M 204.6 9.40 10.70 12.49 13.13 10.22 9.95 10.95 49.31

Axia Finance 23 June 2011 -

but existing charge for Plant &

Equipment awaiting internal

review

From mine and process plan -

G Smith & H Smith as above.

two rates - allowed in year of

purchase

Any cash flows from projects

already approved should be

shown separately. The logic,

assume tax allowance depn.

same as P&L rate

Major Projects - P&E to be

approved

Major Projects - P&E

approvedIdentify new projects &

benefit. This example has a

switch cell in column F to

show effect as a sensitivity,

other benefit logic can be

select drop down

Physical Production Total

assumes no stockpiling Mine Summary Pit A ore production = feed to process Mt 126.4 10.50 10.51 10.45 9.62 10.25 10.80 10.53 10.48

Pit B ore production = feed to process Mt 126.2 3.85 4.85 5.85 6.93 6.22 4.91 5.71 5.33

Total waste Mt 926.1 49.00 49.00 53.48 60.36 49.43 49.01 59.44 40.70

Strip Ratio 58.8 3.42 3.19 3.28 3.65 3.00 3.12 3.66 2.58

This can be switched on or off

on Input sheet Process calculation Upgrade concentrator benefit % yes 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%

Metal 1

Contained Metal 1 recovered from Pit A ore kt 1,246.3 101.1 103.1 101.3 92.1 99.2 108.7 106.1 99.0

Contained Metal 1 recovered from Pit B ore kt 727.7 24.9 33.4 39.8 45.4 40.7 32.1 37.4 34.4

Total c ontained Metal 1 in Produc t 1 kt 1,974.0 126.0 136.5 141.0 137.4 139.9 140.8 143.5 133.4

Grade of Metal 1 in final Product 1 % 30.0% 30.0% 30.0% 30.0% 30.0% 30.0% 30.0% 30.0% 30.0%

Total Product 1 tonnes kt 6,580.1 420.0 455.0 470.1 458.1 466.5 469.3 478.2 444.7

Metal 2

Contained Metal 2 recovered from Pit A ore kt 903.9 71.9 73.3 72.0 65.5 70.6 77.3 75.4 70.4

Contained Metal 2 recovered from Pit B ore kt 1,066.6 34.5 46.3 54.4 62.1 55.8 44.0 51.2 47.1

Total c ontained Metal 2 in Produc t 2 kt 1,970.5 106.4 119.6 126.4 127.6 126.3 121.2 126.6 117.5

Grade of Metal 2 in final Product 2 % 40.0% 40.0% 40.0% 40.0% 40.0% 40.0% 40.0% 40.0% 40.0%

Total Product 2 tonnes kt 4,926.2 266.0 298.9 316.1 319.0 315.8 303.1 316.5 293.8

7/21/2019 be1



This example is an A$ model but has revenues in US$. If selling prices are multi currency, this

should be reflected in the modelling.

This shows Level 1 cost calculations. The assumed US dollar element of costs is applied to the total

costs except for those, such as carbon costs where 100% US is assumed. The effect of the scenario

cost adjustment is computed after the exchange adjustment.

Revenue Total @ NPV 8

Product 1 - sell ing price, payable CIF US$/t 425 242 266 469 469 469 445 426 408

Product 2 - sell ing price, payable CIF US$/t 325 320 344 364 364 364 343 328 312

Product 1 - Revenue CIF US$M 2,794 1,701 101.75 121.03 220.61 215.01 218.92 208.64 203.76 181.25

Product 2 - Revenue CIF US$M 1,601 948 85.10 102.83 115.07 116.11 114.94 104.03 103.69 91.67

Total US$M 4,395 2,649 186.85 223.86 335.68 331.11 333.86 312.67 307.45 272.92

US$M

Royalty US$M (132) (79) (5.61) (6.72) (10.07) (9.93) (10.02) (9.38) (9.22) (8.19)

Freight and Packaging US$M (260) (153) (12.25) (13.98) (17.86) (17.52) (17.49) (17.19) (17.73) (16.47)

Net Revenue US$M 4,003 2,416 168.99 203.17 307.75 303.66 306.35 286.10 280.50 248.27

Net Revenue A$M 4,297 2,591 211.24 205.22 325.50 324.64 329.41 307.63 301.62 266.95Model NPV requires A$

workings as well as US$

Cash Operating Costs Total @ NPV 8

Mine Costs Pit A Drill/Blast/Load A$M (439) (260) (29.70) (31.53) (33.95) (36.48) (29.75) (31.50) (30.37) (23.85)

Pit A Ore haul cost A$M (11) (7) (0.90) (1.00) (0.94) (0.82) (0.87) (0.92) (0.90) (0.89)

Pit A Waste haul cost A$M (36) (21) (2.75) (2.85) (2.82) (2.96) (2.36) (2.50) (2.40) (1.75)

Pit A Rehandling stockpile A$M 0 0

Pit B Drill/Blast/Load A$M (340) (183) (9.69) (11.89) (12.63) (14.56) (13.07) (10.31) (19.23) (13.06)

Pit B Ore haul cost A$M (11) (6) (0.50) (0.53) (0.53) (0.59) (0.53) (0.42) (0.49) (0.45)

Pit B Waste haul cost A$M (23) (12) (0.80) (0.85) (0.79) (0.88) (0.79) (0.63) (1.39) (0.85)

Pit B Rehandling stockpile A$M 0 0

Sub total - Variable Costs A$M (860) (490) (44.34) (48.64) (51.66) (56.29) (47.37) (46.26) (54.77) (40.84)

Fixed Costs A$M (219) (127) (15.00) (15.00) (15.00) (14.50) (14.00) (13.50) (13.50) (13.50)

Total Mining Costs A$M (1,079) (617) (59.34) (63.64) (66.66) (70.79) (61.37) (59.76) (68.27) (54.34)

Mine Unit Costs Cost per tonne of ore A$/t ore (4.27) (4.14) (4.14) (4.09) (4.28) (3.73) (3.80) (4.20) (3.44)

C os t per tonne of mater ial moved A$/ t r oc k (0.92) (0.94) (0.99) (0.96) (0.92) (0.93) (0.92) (0.90) (0.96)

Process Costs Input driven - variable A$M (905) (532) (57.39) (61.43) (65.18) (66.23) (62.58) (54.97) (56.86) (55.32)

Output driven - variable A$M (127) (74) (6.87) (7.90) (8.50) (8.45) (8.47) (8.30) (8.57) (7.97)

Fixed Costs A$M (274) (158) (18.00) (18.00) (18.00) (17.50) (17.20) (17.00) (17.00) (17.00)

Total Process Costs A$M (1,306) (764) (82.26) (87.33) (91.68) (92.18) (88.25) (80.28) (82.43) (80.28)

Process Unit Costs Cost per tonne of feed A$/t (5.18) (5.73) (5.69) (5.63) (5.57) (5.36) (5.11) (5.07) (5.08)

C os t per tonne of pr oduc t (s al eable) A$/ t (113.99) ( 119. 93) (115. 83) ( 116. 61) (118.61) ( 112.81) (103. 93) ( 103. 72) ( 108.70)

SG&A Variable Costs A$M (253) (146) (14.35) (15.36) (16.29) (16.56) (16.47) (15.71) (16.24) (15.80)

Fixed Costs A$M (201) (115) (14.00) (14.00) (13.00) (12.50) (12.50) (12.50) (12.50) (12.50)

Total SG&A A$M (453) (262) (28.35) (29.36) (29.29) (29.06) (28.97) (28.21) (28.74) (28.30)

Total Cash Operating Costs - excl. carbon cost A$M (2,838) (1,643 ) ( 169. 96) (180. 33) ( 187. 64) (192.02) ( 178.59) (168. 24) ( 179. 45) ( 162.93)

US$ related share of total costs - in real A$ A$M (426) (246) (28.15) (28.80) (26.79) (25.24) (26.92) (24.44)

at central estimate case exchange rates

(if flexing exchange) Impact on total operating costs A$M 0 0 0.00 0.00 0.00 0.00 0.00 0.00

Total Cash Operating Costsafter exchange flex- excl. carbon cost A$M (2,838 ) (1,643 ) ( 187. 64) (192.02) ( 178.59) (168. 24) ( 179. 45) ( 162.93)

Scenario cost adjustment A$M 0 0 0.00 0.00 0.00 0.00 0.00 0.00

Carbon TaxTotal charge

A$M (90) (49)(3.77) (3.81) (3.83) (5.44) (5.81) (4.35)

Net operating cash costs A$M (2, 928) ( 1,691) ( 169. 96) (180. 33) ( 191. 40) (195.83) ( 182.41) (173. 69) ( 185. 26) ( 167.28)

SCA is applied to total costs

excl. carbon

This row computes impact of

flexes to exchange rate from

the central estimate case -

before applying the scenario

factor to the new total opex

7/21/2019 be1



Simple examples of depreciation and tax calculations are shown below – these can be very much

more complicated for some BUs and appropriate detail to reflect the cash flow implications should be

included.

This simplified model does not include a margin analysis but this might typically be added after

derivation of revenues and costs.

Integrity checks can be added either through the calculation area or grouped together as allowed for

in the above extract. Select these to check maths or capacity or whatever is appropriate for the

business.

Also in the sample model, an area for customised chart data has been included below the main

calculations. These can be laid out and formatted to suit the chart style - with links to the source

calculation so the chart changes as the model is flexed.

LOM LOM

Fixed Capital - new expenditure & depreciation Total @ NPV 8

Fixed capital Sustaining capital A$M (151) (92) (9.40) (10.70) (10.49) (11.13) (10.22) (9.95) (10.95) (9.31)

Project capital A$M (54) (36) 0.00 0.00 (2.00) (2.00) 0.00 0.00 0.00 (40.00)

by category for depreciation Real terms cash - Plant & Equipment A$M (180) (113) (8.40) (9.70) (11.49) (12.13) (9.22) (8.95) (9.95) (48.31)

Real terms cash - Buildings A$M (25) (15) (1.00) (1.00) (1.00) (1.00) (1.00) (1.00) (1.00) (1.00)Total capital investment pre flex A$M (205) (128) (9.40) (10.70) (12.49) (13.13) (10.22) (9.95) (10.95) (49.31)

Read from Input, apply % to US$ related share of total costs - in real A$ A$M (92) (57) (5.62) (5.91) (4.60) (4.48) (4.93) (22.19)This computes the change in at central estimate case exchange rates

(if flexing exchange) Impact on total capital costs A$M 0 0 0.00 0.00 0.00 0.00 0.00 0.00

Scenario cost adjustment A$M 0 0 0.00 0.00 0.00 0.00 0.00 0.00

Net capital cash costs A$M (205) (128) (9.40) (10.70) (12.49) (13.13) (10.22) (9.95) (10.95) (49.31)

Nominal terms cash invested - for depreciatio A$M - nomi (244) (148) (12.49) (13.49) (10.80) (10.81) (12.23) (56.62)

sum check

Simplified Depreciation Capital Expenditure - Plant & Equip. nominal A$M - nomi (213) (130) (11.49) (12.47) (9.75) (9.72) (11.12) (55.47)

Capital Expenditure - Buildings. nominal A$M - nomi (30) (18) (1.00) (1.03) (1.06) (1.09) (1.12) (1.15)

Annual Depreciation Charge - Plant & Equip A$M - nominal (2.30) (2.49) (1.95) (1.94) (2.22) (11.09)

Annual Depreciation Charge - Buildings A$M - nominal (0.10) (0.10) (0.11) (0.11) (0.11) (0.11)

Year

1 A$M - nominal (2.40) (2.60) (2.06) (2.05) (2.33) (11.21)

2 A$M - nominal (2.40) (2.60) (2.06) (2.05) (2.33) (11.21)

3 A$M - nominal (2.40) (2.60) (2.06) (2.05) (2.33) (11.21)

4 A$M - nominal (2.40) (2.60) (2.06) (2.05) (2.33) (11.21)

5 A$M - nominal (2.40) (2.60) (2.06) (2.05) (2.33) (11.21)

6 A$M - nominal (0.10) (0.10) (0.11) (0.11) (0.11) (0.11)

7 A$M - nominal (0.10) (0.10) (0.11) (0.11) (0.11) (0.11)

8 A$M - nominal (0.10) (0.10) (0.11) (0.11) (0.11) (0.11)

9 A$M - nominal (0.10) (0.10) (0.11) (0.11) (0.11) (0.11)

10 A$M - nominal (0.10) (0.10) (0.11) (0.11) (0.11) (0.11)

Annual Charge A$M - nomi (244) (2.40) (4.99) (7.05) (9.10) (11.44) (20.35)

Write off post closure years A$M - nominal 0.00 0.00 0.00 0.00 0.00 0.00

Total depreciation -new capital only A$M - nomi (244) (2.40) (4.99) (7.05) (9.10) (11.44) (20.35)

Carried forward depreciation - old capital A$M - nomi (55) (13.00) (13.00) (11.00) (10.00) (9.00) (8.00) (6.00) (3.00)

Closure cash after scenario adjustment - net

of asset sales A$M (90) 0.00 0.00 0.00 0.00 0.00 0.00

simplified example, expand as

needed for business Working Capital - at end of each year

Working capital Creditors A$M 18.63 19.76 20.98 21.46 19.99 19.03 20.30 18.33

Debtors A$M (34.72) (33.73) (53.51) (53.37) (54.15) (50.57) (49.58) (43.88)

Other inventory/stores etc - end of year A$M 10.00 10.00 10.43 10.31 10.38 10.24 10.54 9.80

Total - real terms A$M (6.10) (3.97) (22.10) (21.60) (23.78) (21.29) (18.74) (15.75)

Nominal terms A$M - nominal (6.10) (3.97) (22.10) (22.20) (25.13) (23.13) (20.93) (18.09)

Change in working capital - nominal A$M - nomi 3.97 2.13 (18.13) (0.10) (2.93) 2.00 2.20 2.84back into real terms for NPV Change in working capital - real 0.00 2.13 (18.13) (0.10) (2.78) 1.84 1.97 2.47

Tax Total @ NPV 8

(Real terms - simple tax calc) Net Revenue A$M 4,297 2,591 211.2 205.2 325.5 324.6 329.4 307.6 301.6 267.0

Net Cash costs A$M (2,928 ) (1,691 ) (170.0) (180.3) (191.4) (195.8) (182.4) (173.7) (185.3) (167.3)

Operating Cash Flow A$M 1,369 900 41.29 24.89 134.10 128.81 147.00 133.95 116.36 99.67

Depreciation carried forward A$M (51) (41) (13.00) (13.00) (11.00) (9.73) (8.52) (7.36) (5.37) (2.61)

Depreciation - new purchases A$M (193) (103) (2.40) (4.86) (6.67) (8.38) (10.24) (17.72)

Closure provisions A$M (88) (52) 0.00 0.00 (5.80) (5.80) (5.80) (5.80) (5.80) (5.80)

Taxable Profit A$M 1,037 704 28.29 11.89 114.90 108.42 126.01 112.41 94.95 73.53

Tax Rate % 30.0% 30.0% 30.0% 30.0% 30.0% 30.0% 30.0% 30.0%

Tax on Operations A$M (311) (211) (8.49) (3.57) (34.47) (32.53) (37.80) (33.72) (28.48) (22.06)

Tax Payable A$M (311) (211) (8.49) (3.57) (34.47) (32.53) (37.80) (33.72) (28.48) (22.06)

Tax Loss carry forward A$M 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

This logic lays out each year

and is reasonably easy to

follow. BED also have a

complex formula which will do

the same in many less rows.Available on request

You may want to indicate that

the logic used has been

approved by a particular

manager or other BU function

Shows two categories of

capex - can increase to more

if needed

Logic reads year in column C

and applies annual charges

which are then summed at

bottom of table

derived in real terms;

converted to nominal for

calculation of annual change in

flexes with process tonnes;

would normally have fuller

inventory calc

logic to ensure no residual

depreciation remains

A simple flat rate calculation

excluding debt etc.

Customise for BU concernedwith advise from tax

department

7/21/2019 be1



The extracts below are taken from the Output sheet. The summary cash flow table, in real terms,

shows, in column F, the life of mine contribution to NPV from each revenue and cost row and it is

recommended that this should always be included. As noted in Chapter 2, NPV computations for

submissions should primarily be in US$; the sample model also shows the local currency NPV.

Separate tables showing summaries of key outputs can then be prepared to provide high level

information for users/ readers.

Earnings statements should be shown in nominal terms; this extract is in local currency.

Sources/Comments

Widen column A to read Filename BMG sample model Axia 12 Rev 1 - 21Dec11.xlsx 2010 2011 2012 2013 2014 2015 2016 2017Years driven from Input sheet

NPV 8 A$ 529M Operating Years Actual F'cast 1 2 3 4 5 6

Comments in column A Start Year 2012

Valuation date 01-Jan LOM

SELECTED SCENARIO Central estimate

Output - key physicals Total Grade

Ore mined - Pit A Mt 126 11 11 10 10 10 11 11 10Ore mined - Pit B Mt 126 4 5 6 7 6 5 6 5

Total ore mined Mt 253 14 15 16 17 16 16 16 16

Sales - Product 1 Gross kt 6,580 30% 420 455 470 458 466 469 478 445

Sales - Product 2 Gross kt 4,926 40% 266 299 316 319 316 303 317 294

Total sales Gross kt 11,506 686 754 786 777 782 772 795 739

Cash Flow & NPV (US$M - Real terms)Ungeared Cashflow LOM LOM

Revenues - US$M Total @ NPV 8

Product 1 US$M 2,794 1,701 101.7 121.0 220.6 215.0 218.9 208.6 203.8 181.3

Product 2 US$M 1,601 948 85.1 102.8 115.1 116.1 114.9 104.0 103.7 91.7

Sub total US$M 4,395 2,649 186.9 223.9 335.7 331.1 333.9 312.7 307.5 272.9

less Royalty US$M (132) (79) (5.6) (6.7) (10.1) (9.9) (10.0) (9.4) (9.2) (8.2)

Freight - if applicable US$M (260) (153) (12.3) (14.0) (17.9) (17.5) (17.5) (17.2) (17.7) (16.5)

Net Revenue US$M 4,003 2,416 169.0 203.2 307.8 303.7 306.4 286.1 280.5 248.3

Operating Costs - US$M

Mining US$M (1,005) (575) (47.5) (63.0) (63.0) (66.2) (57.1) (55.6) (63.5) (50.5)

Processing US$M (1,216) (712) (65.8) (86.5) (86.7) (86.2) (82.1) (74.7) (76.7) (74.7)

SG&A US$M (422) (244) (22.7) (29.1) (27.7) (27.2) (26.9) (26.2) (26.7) (26.3)

Exchange and Scenario cost adjustments US$M 0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Carbon tax US$M (84) (46) 0.0 0.0 (3.6) (3.6) (3.6) (5.1) (5.4) (4.1)

Net Cost US$M (2,727) (1,577) (136.0) (178.5) (181.0) (183.2) (169.6) (161.5) (172.3) (155.6)

OPERATING SURPLUS US$M 1,276 839 33.0 24.6 126.8 120.5 136.7 124.6 108.2 92.7

Sustaining capital US$M (140) (85) (7.5) (10.6) (9.9) (10.4) (9.5) (9.3) (10.2) (8.7)

Project capital US$M (50) (33) 0.0 0.0 (1.9) (1.9) 0.0 0.0 0.0 (37.2)

Exchange and Scenario cost adjustments US$M 0 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Ne t C losure cap ital incl ad jus tment US$M (84) (24) 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Net Capital US$M (274) (142) (7.5) (10.6) (11.8) (12.3) (9.5) (9.3) (10.2) (45.9)

Working capital change US$M (2) (11) 0.0 2.1 (17.1) (0.1) (2.6) 1.7 1.8 2.3

Tax payable US$M (290) (197) (6.8) (3.5) (32.6) (30.4) (35.2) (31.4) (26.5) (20.5)

NET CASH FLOW (before financing) US$M 709 489 18.7 12.6 65.2 77.7 89.5 85.7 73.4 28.6

cash in bank at start date Add any opening cash US$M 5 5 4.0 5.0 4.7

LOM RESULT US$M 714 494 22.7 17.6 70.0 77.7 89.5 85.7 73.4 28.6

IRR % n/a

CUMULATIVE CASH - LOM US$M 714 70.0 147.7 237.1 322.8 396.2 424.8

CUMULATIVE NPV - LOM US$M 494 67.3 136.5 210.4 275.8 327.7 346.4

exchange effect using an

average % US content from

central estimate case, then

t t t

IRR only applicable where a

project is being assessed -

set logic to read incrementalcash

exchange effect using an

average % US content fromcentral estimate case, then

t t t

Profit and Loss Statement (A$M - Nominal terms) LOM

Total

Revenues Product Sales Revenue A$M 5,751 233.6 226.1 355.0 363.9 379.4 365.2 369.2 336.9

Less royalty A$M (173) (7.0) (6.8) (10.7) (10.9) (11.4) (11.0) (11.1) (10.1)

Less freight A$M (343) (15.3) (14.1) (18.9) (19.3) (19.9) (20.1) (21.3) (20.3)

NET REVENUE A$M 5,236 211.2 205.2 325.5 333.7 348.1 334.2 336.8 306.5

Operating Costs Mining A$M (1,340) (59.3) (63.6) (66.7) (72.8) (64.9) (64.9) (76.2) (62.4)

Processing A$M (1,610) (82.3) (87.3) (91.7) (94.8) (93.3) (87.2) (92.1) (92.2)

SG&A A$M (561) (28.3) (29.4) (29.3) (29.9) (30.6) (30.6) (32.1) (32.5)

Exchange and Scenario cost adjustments A$M 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Carbon tax A$M (114) 0.0 0.0 (3.8) (3.9) (4.0) (5.9) (6.5) (5.0)

Inventory movements A$M 15 0.0 (0.4) 0.1 (0.1) 0.1 (0.3) 0.9

Provisions - closure A$M (108) 0.0 0.0 (5.8) (6.0) (6.1) (6.3) (6.5) (6.7)

Depreciation A$M (299) (13.0) (13.0) (13.4) (15.0) (16.0) (17.1) (17.4) (23.3)

Cost of Sales A$M (4,016) (183.0) (193.3) (211.0) (222.1) (215.0) (211.9) (231.1) (221.2)

Other income (expense) A$M 24 1.2 1.2 1.2 1.2 1.3 1.3 1.3 1.4

EBIT A$M 1,244 29.5 13.1 115.7 112.8 134.4 123.6 107.0 86.7(not applicable this model) Financial items (incl interest) A$M 0

Income Tax Expense A$M (361) (8.5) (3.6) (34.5) (33.4) (40.0) (36.6) (31.8) (25.3)

PROFIT AFTER TAX A$M 882 21.0 9.5 81.2 79.4 94.4 86.9 75.2 61.3

Produce P&L also in US$ if required.

7/21/2019 be1



Choice of output graphics is important in delivering insight to the user. A selection of examples is

shown below. The waterfall chart shows the value chain that adds up to the NPV of the business.

The chart below shows how little value is added in the later years.

These charts can also be adapted to show the impact of an individual project on the business –

plotting the outcome with and without the investment.

Other charts will typically show the KPIs of the business. Each of these should be customised to suit

the business and the information being sought from the model. Typical charts might be as below

with cost and margin analyses, capacity constraints etc being added to support the assessment of

the major drivers of value.

0

500

1,000

1,500

2,000

2,500

3,000

NPV Value ChainUS$ Millions

Central estimate NPV 8 US$494M

0

100

200

300

400

500

600

Cumulative Post Tax Cash Flow

US$ Millions

Central estimate NPV 8 US$494M

7/21/2019 be1



0

10

20

30

40

50

60

70

80

Material Mined per annum - Mt

Pit A ore mined Pit B ore mined Total Waste

0

20

40

60

80

100

120

140

160

180

200

Cash Operating CostsUS$ Millions

Mining Processing SG&A Exchange and Scenario cost adjustments Carbon tax

7/21/2019 be1



The sample model includes an additional output area which matches with the style of presentation

required by Controllers in the CGU template sent out as part of the planning process.

The sample model includes shows a template similar to that suggested in section 4 of volume 2 -

where an alternative sensitivity profile is shown in chart format.

Output to suit CGU entry USE ONLY WHEN CENTRAL ESTIMATE SELECTED ON INPUT SHEET

CGU2

CASHFLOW SCHEDULE & SENSITIVIT IES FOR AXIA AUSTRALIA

Country Australia

YEAR 2010 2011 2012 2013 2014 2015 2016 2017 2018Actu al F 'cast

COMMODITY PRICES AND EXCHANGE RATE USED IN CENTRAL ESTIMATE (REAL TERMS)Business Unit Product Prices - Real terms

Primary commodity Product 1 US$/t (paste into CGU) $494.00 $494.00 $494.00 $468.00 $448.50 $429.00 $429.00

Secondary commodity Product 2 US$/t (paste into CGU) $455.00 $455.00 $455.00 $429.00 $409.50 $390.00 $390.00

Tertiary commodity n/a (paste into CGU)

Invert exchange rate Exc hange R ate - Cent ra l est imate US$/A$ (do not paste into CGU) 0.95 0.94 0.93 0.93 0.93 0.93 0.93

TRUE E xc ha ng e R ate - fo r c as e c hos en US $/A$ (do not paste into CGU) 0.95 0.94 0.93 0.93 0.93 0.93 0.93

This case 2012 real terms cash flows, in A$ (m)

0.9NPV @

8.0%

Revenue A$M 2,591 325 325 329 308 302 267 302

Operating costs A$M (1,430) (162) (167) (153) (145) (157) (139) (154)check definition Controllers SG&A costs A$M (262) (29) (29) (29) (28) (29) (28) (29)

Tax A$M (211) (34) (33) (38) (34) (28) (22) (28)

Working capital changes A$M (11) (18) (0) (3) 2 2 2 (3)

Sustaining capex A$M (92) (10) (11) (10) (10) (11) (9) (11)

Other capex A$M (61) (2) (2) - - - (40) (10)

Other A$M 5 5 - - - - - -

Free cash flow excl financing A$M 529 74 83 96 92 79 31 68

This case 2012 real terms cash flows, in US$ (m)

NPV @8.0%Revenue US$M 2,416 308 304 306 286 281 248 281Operating costs US$M (1,333) (153) (156) (143) (135) (146) (129) (143)SG&A costs US$M (244) (28) (27) (27) (26) (27) (26) (27)Tax US$M (197) (33) (30) (35) (31) (26) (21) (26)

Working capital changes US$M (11) (17) (0) (3) 2 2 2 (3)Sustaining capex US$M (85) (10) (10) (10) (9) (10) (9) (10)Other capex US$M (57) (2) (2) - - - (37) (9)Other US$M 5 5 - - - - - -Free cash flow excl financing US$M 494 70 78 89 86 73 29 63

Central estimate NPV 8 A$529M Central estimate NPV 8 US$494M 2012 US$ (millions)

SENSITIVITY ANALYSIS (this is working output area for sensitivities, select central estimate on input sheet before saving core model)

(select scenario or flex % on Input sheet, then "copy"/"paste special"/ "value" the result from working output into appropriate box below)

Discount Central estimate Upside Scenario Downside Scenario

Discount rates +/- 2% from CE rate A$ (m) US$ (m) A$ (m) US$ (m) A$ (m) US$ (m)

10.0% 489 456 660 685 356 297

8.0% 529 494 717 743 386 322

6.0% 576 537 783 810 421 351

(the sensitivities below here are generally optional - see CGU guidance sheet on the template from Controllers)

Discount Product 1 plus 10% Product 1 minus 10% Product 2 plus 10% Product 2 minus 10%

rate A$ (m) US$ (m) A$ (m) US$ (m) A$ (m) US$ (m) A$ (m) US$ (m)

10.0% 623 581 394 367 572 534 445 415

From central estimate 8.0% 680 634 424 395 623 581 480 448

6.0% 746 695 458 427 683 637 521 485

DiscountOperating Cost plus 10% Operating Cost minus 10% Local L/T FX rate 0.837 Local L/T FX rate 1.023

rate A$ (m) US$ (m) A$ (m) US$ (m) A$ (m) US$ (m) A$ (m) US$ (m)

10.0% 349 325 668 623 632 544 407 405

From central estimate 8.0% 372 347 731 682 694 596 436 433

6.0% 398 371 805 751 766 657 467 466

This area corresponds with

the second of the CGU sheets

which RTHQ Contollers ask

Business Units to complete

as part of the annual planning

process

The numbers from 2010 can

be hard code copy/pasted into

CGU sheet 2

Annual cashflow numbers can

be hard code pasted into CGU

sheet 2. Do not paste the

NPV column as CGU

calculates it.

CGU reads exchange from

CGU sheet1 but sensitivity

below needs to know if

inverted.

Show NPVs for central

estimate and upside/downside

per plan guidelines (per PEG

5, these are "New Horizon"

and "The Unwinding" at time

of writing this).

Simple +/- price sensitivities

for two (if appropriate) major

products

Simple +/- sensitivities for

total operating cost and for

exchange (if appropriate).

Apply to long termf x if different Apply to long termf x if different

CGU 2 sheet will calculate the

US$ numbers - no need to

paste across

-100

-80

-60

-40

-20

0

20

40

60

80

100

120

2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029

2012 US$ (millions) Cash Flow Schedule & Sensitivities

7/21/2019 be1



Appendix 3.4: Examples of a Vertical Sheet ModelA typical Level 2 model set up in a vertical format might be structured as follows:

The extracts below are taken from an old Axia model but the principals shown remain relevant.

The overall structure might be as below.

The Preface Table of Contents might then be as follows

For a model with Level 2 inputs the generic inputs would be placed on the Common Inputs sheet as below:

Vertical Structure - Format B Standard model populated with alternative scenarios …..

Excel Sheets Preface - as

normal

Summary -

compares

different cases

Common inputs

(drivers) used in all

cases

Datum

case

Scenario 1 Scenario 2

etc ….

3

4

5

6

7

8

9

10

1112

131415

1617

181920

21222324

2526272829

303132

3334

353637

38394041

424344

4546

4748

49

5051

52

5354

55565758

5960

61

A B C D E F G H I J

Filename Axia 06 Vertical Style Ver 2 - 7Aug06.xls NPV 8 US$ 342M

MODEL NAME Axia Minerals LOM Business ModelPEG compliant? yes

This version shows

Operations covered All Axia operations in Australia including Mine A, Mine B, Process Plant and G&A. Rio Tinto owns 80%.

The model computes Net Present Value in Australian dollars as at 1 January 2006 and shows earnings over the remaining life of mine

The model is built on a 100% ownership basis. Rio Tinto share is only shown after the 100% cashflow/earnings calculation

For this sample high level valuation model, the life is deliberately short and the complexity low

This is a vertical tab version of a model (Format B in the BMG - see section 3.3) with level 2 cost inputs Contact

Creator(s) [email protected] Bristol +44 7801 433202Current Owner of model [email protected] London +44 207 7532287

Table of Contents

Sheet Item Comments Location - rowsSummary(summary reports & graphics) Summary physicals Comparative summaries

Summary financialsValue chain comparisons NPV breakdowns by caseGraphics

Common DriversGeneral economic inputs PEG and Economics inputsCommercial - R ef erenc e prices/Other Produc t pricing - US$/unit

Common operating parameters Major drivers to all scenarios

Datum Case Full model in vertical sheet (all flexing financial & physical inputs) Commercial - this case Product pricing - US$/unit

Physicals - Reserves Starting tonnes plus additions

Physicals - Mine plan Full Life of Mine physicalsPhysicals - Process parameters Recoveries etc

Operating costs - All functions Fixed & variableOperating costs - Carbon tax Per PEGProvisions and Closure Capital cost and provisionsCapital Sustaining and project capex

Other inputs Misc income, inventory, cash

(All calculations through to output) G eneral financial - exchange/inf lation Exch & cumulativ e inflation

Physical production Saleable productRevenues Converted to A$

Operating costs By process and natureInventories Not used in this versionCapital costs & depreciation Simplified depreciation calc.

Working capital Creditors, debtors, inventoryTax Simple flat rate example

Other income/expenses - netCash flow & NPV Real terms cash flowsEarnings statement Nominal terms P&L

Balance sheet - (not included) Optional

Charts for Datum case Key business graphsKPIs Key performance indicatorsOthers - unit costs, margins, integr ity checks Add as required

Tables for chart data Summaries to suit outputs

Scenario 1 Repeat of Datum sheet with different inputsSame structure as for datum

Add additional scenarios as required

Datum case for 2006 plan. It assumes no expansion of Mine B and mine closure in 2020.Update this for each significant version saved

Model description and

purpose

34

35

36

37

38

39

4041

42

B C

OPEX InputsKey Factor Inputs

Labor - total including oncostsOperators/Mechanics A$/manyear

Supervisors A$/manyear

Managers A$/manyear

Power A$/kWhDiesel US$/litre

ANFO A$/kg

7/21/2019 be1


The central estimate case inputs would then be taken from the mine and process plans relevant to

that case and might have the following headings. Each of these when multiplied by the generic

inputs allows calculation of the appropriate operating cost:

Mining costs

Process and overhead costs

The calculation rows then continue as per the multi sheet model and produce the required outputs

for the central estimate case and each scenario.

The addition of a summary sheet, in this example at the front, allows the multiple cases to be

compared. For more detail on how this is used, the reader is asked to contact the T&I team who are

responsible for the Strategic Production Planning (SPP) studies.

5657

58

59

60

61

62

63

64

65

66

67

68

69

70

71

72

73

74

75

76

77

78

79

80

81

82

84

85

86

87

88

B C D E

Operating Cost Inputs - all in Australian $Mine Variable Costs Pit A Drill/Blast/Load - Operators Number

Pit A Dr il l/Blast/Load - Diesel used li tre/t material moved

Pit A Drill/Blast/Load - Explosives used kg/t material moved

Pit A Drill/Blast/Load - Other supplies/maint. A$/t material moved

Pit A Ore haul cost Pit A Ore Haul - Operators Number

Pit A Ore Haul - Diesel consumption li tre/t ruck hour

Pit A Ore Haul - Other supplies/maint. A$/truck hour

Pit A Waste haul cost Pit A Waste Haul - Operators Number

Pit A Waste Haul - Diesel consumption litre/truck hour

Pit A Waste Haul - Other supplies/maint. A$/truck hour

Pit A Rehandling stockpile Pit A Rehandling S/P - Operators Number

Pit A Rehandling S/P - Diesel consumption litre/truck hour

Pit A Rehandling S/P - Other supplies/maint. A$/truck hour

Pit B Drill/Blast/Load Pit B Drill/Blast/Load - Operators Number

Pit B Drill/Blast/Load - Diesel consumption litre/t material moved

Pit B Drill/Blast/Load - Explosives used kg/t material moved

Pit B Drill/Blast/Load - Other supplies/maint. A$/t material moved

Pit B Ore haul cost Pit B Ore Haul - Operators NumberPit B Ore Haul - Diesel consumption li tre/t ruck hour

Pit B Ore Haul - Other supplies/maint. A$/truck hour

Pit B Waste haul cost Pit B Waste Haul - Operators Number

Pit B Waste Haul - Diesel used litre/truck hour

Pit B Waste Haul - Other supplies/maint. A$/truck hour

Pit B Rehandling stockpile Pit B Rehandling S/P - Operators Number

Pit B Rehandling S/P - Diesel consumption litre/truck hour

Pit B Rehandling S/P - Other supplies/maint. A$/truck hour

Mine Fixed Costs Operators NumberSupervisors NumberManagers NumberPower kWhOther overheads A$M

90

91

92

93

94

95

96

97

98

99

100

102

103

104

105

106

108

109

110

111

112

113

B C D E

Process Variable Costs Input circuits - Operators Number

Power kWh

Major consumable XX A$/t material fed

Other supplies A$/t material fed

Product A output ci rcuits - Operators Number

Power kWh

Other supplies A$/t material produced

Product B output ci rcuits - Operators Number

Power kWh

Other supplies A$/t material produced

Process Fixed Costs Operators Number

Supervisors Number

Managers Number

Power kWh

Other overheads A$M

G&A Other var iable costs, overheads etc A$/t production (or ore)

Other fixed costs, - operators Number

Other fixed costs, - supervisors Number

Other fixed costs, - managers Number

Other fixed costs, - power kWh

Other fixed costs, - overheads A$M

Date post:	05-Mar-2016
Category:	Documents
Upload:	vahombe
View:	216 times
Download:	0 times

be1

Documents