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ICAEW recognises the FAST Standard

Posted by Kenny Whitelaw-Jones


Last week in London the Institute of Chartered Accountants in England and Wales (ICAEW) launched their Twenty principles for good spreadsheet practice. In this document the ICAEW recommend that organisations adopt a standard. As one of the member firms of the FAST Standard Organisation were delighted that the ICAEW also officially recognised the FAST Standard in their document. 

This short film, sponsored by the FAST Standard Organisation, gives you an overview of the event and an introduction to the ICAEW principles.

The ICAEW made this statement on their website, "Businesses of all shapes and sizes are very heavy users of spreadsheets, and in some cases key business decisions costing millions of pounds rest on spreadsheet modelling. Yet studies suggest that 90% of them contain mistakes.
It isn’t just the headline-grabbing high profile errors. Smaller businesses also lose money, not only through errors but also through sheer inefficiency caused by poorly designed spreadsheets that lack such basics as integrity checks and documentation. Use of these principles will help organisations reduce risk and improve efficiency of spreadsheet use, saving valuable time and money."

The 20 principles for good spreadsheet practice are below:
The spreadsheet’s business environment
1. Determine what role spreadsheets play in your business, and plan your spreadsheet standards and processes accordingly.
2. Adopt a standard for your organisation and stick to it.
3. Ensure that everyone involved in the creation or use of spreadsheets has an appropriate level of knowledge and competence.
4. Work collaboratively, share ownership, peer review.

Designing and building your spreadsheet
5. Before starting, satisfy yourself that a spreadsheet is the appropriate tool for the job.
6. Identify the audience. If a spreadsheet is intended to be understood and used by others, the design should facilitate this.
7. Include an ‘About’ or ‘Welcome’ sheet to document the spreadsheet.
8. Design for longevity.
9. Focus on the required outputs.
10. Separate and clearly identify inputs, workings and outputs.
11. Be consistent in structure.
12. Be consistent in the use of formulae.
13. Keep formulae short and simple.
14. Never embed in a formula anything that might change or need to be changed.
15. Perform a calculation once and then refer back to that calculation.
16. Avoid using advanced features where simpler features could achieve the same result.

Spreadsheet risks and controls
17. Have a system of backup and version control, which should be applied consistently within an organisation.
18. Rigorously test the workbook.
19. Build in checks, controls and alerts from the outset and during the course of spreadsheet design.
20. Protect parts of the workbook that are not supposed to be changed by users.

We are delighted that the FAST Standard has received this recognition and hope you enjoy our coverage of the event.

To find out more about the FAST standard visit 

To download our How to standardise modelling ebook, click the link below.

How to standardise modelling ebook
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Sign Convention - Positive vs. Negative

Posted by Kenny Whitelaw-Jones


This post first appeared on the financial modelling handbook website.

When should numbers in a financial model be positive, and when should they be negative?

This question is one that modellers often feel quite strongly about. Although the FAST Standard has a well established position on this, I want to open this up for discussion ahead of writing the handbook guide.

The whole idea of the financial modelling handbook collaborative, "publish as we go" model is that we can explore topics iteratively, and hopefully all gain from perspectives we hadn't considered previously.

The reality is that we can't escape sign switching. It's going to happen somewhere in our model. The question is therefore not "whether to sign switch" but rather "how to sign switch and where".

Before we get into what the FAST Standard says about sign convention, and why it takes the position it does, we'll look at the advantages and disadvantages of two approaches: inflow / outflow and positive as normal.

1. Inflow / outflow

In this approach all values which represent inflows to the business are positive numbers. All values that represent outflows from the business are negative numbers.

Advantage: Inherent readability of financial statements

Users expect to see financial statements presented according to the inflow / flow convention, with inflows represented as positive numbers, and outflows represented as negative numbers.


Advantage: Simpler logic in arithmetic expressions

When inflows are expressed as positive numbers, and outflows as negative numbers, arithmetic expressions can be more simple. i.e. a column of numbers can just be added up, without worrying which are being added and which subtracted from the total.

Weakness: Sign switching of inputs

Sometimes modelling assumptions are provided as positive numbers. They therefore have to either be sign switched on input, or sign switched within calculations. It’s often the case that values have to be sign switched numerous times to accommodate the requirements of functions and presentation. This increases the risk of error.

However, the flip side of this is that forecasts are often driven off "actuals" which are provided on inflow / outflow convention. More on this below.

Weakness: Mid calc sign switching often required

Let's take an example. When calculating say, the balance of non current assets, one will need to know the amount of capex and the amount of depreciation (ignoring asset disposals for the moment). Under inflow / outflow convention capex is a (cash) outflow, depreciation is a (non-cash) outflow. Yet capex increases the balance of non-current assets, whereas depreciation reduces that balance. There will need to be some kind of sign switching going on in the middle of this, very often buried within the calculation.

Weakness: Sea of negatives

On occasion in a model a value will become unintentionally negative when it should be positive, or positive when it should be negative.

Which is more like to be spotted . . .

This single positive among the negatives?


Or the single negative among the positives?


2. "Positive as normal"

In this convention all numbers are positive, and the "direction of flow" is indicated by the label. Inflow numbers will include labels like Revenue, Income, Receipts, Drawdown, Borrowings. Outflow line items will have labels like Expenses, Costs, Payments, Expenditure, Repayments, Distribution.

Advantage: How assumptions are often provided

Assumptions are often provided as positive numbers. Sign switching is not required on input or within calculations and in many cases logic can be simpler as a result. However this is not universally true, especially where forecasts pick up from a last set of actuals.

Advantage: Negatives stand out as unusual

See the side by side comparison above. I suspect that different people will have different views about which is easier to spot. Please leave a comment with your thoughts on this.

Weakness: Can't just "add up"

In the inflow / outflow convention we can usually just add up the numbers and let the sign convention take care of itself. In "positive as normal" whether a line is being added or subtracted has to be written into the formula.

Weakness: Not appropriate for financial statements

Most users will be used to seeing financial statements expressed using "inflow / outflow" convention and will expect to see the model's financial statement outputs presented in this way.

Note however that there are regional variations about how the balance sheet is presented. Sometimes both the asset and liability balances are presented as positive numbers. Sometimes only the asset values are expressed as positives, with the liability balances expressed as negatives.

3. What FAST recommends

FAST recommends a "mixed economy" of sign convention. "Positive as normal" in the calculation engine / working sheets of a model, and inflow / outflow on the presentation / financial statements. The reason for this can be hopefully seen from the diagram below: the advantages of each of the two conventions apply to specific parts of the model.


How sign switching is done in FAST models


Only line items that are going to flow into the financial statements are sign switched. The suffix "POS" is added to the positive version in order to maintain distinction between the line items, and thus maintain consistency and integrity about row labels being unique. The example above, "Fuel costs" are being exported to the financial statements, and are therefore give "export" line item formatting.

4. Issues with this approach

The mixed economy of "positive as normal" in the calculation sheets and "inflow / outflow" on the financial statements works really well, especially in "bottom up" models where all line items are built up from provided assumptions. This is typical of project finance and infra modelling.

It's less typical in Corporate Finance and FP&A where we're often starting from a set of actuals, expressed in inflow / outflow convention. FAST is not currently sufficiently clear on this.

In this regard are three possibilities:

1. Adopt FAST positive as normal in calculations and sign switch the actuals prior to input



  • avoids a lot of additional sign switch calcs.
  • The calculations are all positives which avoid mid calc sign switching and is simpler.


  • The actuals inputs don't match the actuals outputs - this gets horribly confusing when trying to ensure alignment of outputs.
  • The sign switching is done outside the model and is not transparent. When the actuals are updated this could cause confusion.

2. Adopt FAST positive as normal in calculations and explicitly sign switch the actuals before using them



  • The actuals inputs match the actuals outputs.
  • The calculations are all positives which avoid mid calc sign switching and is simpler.
  • The sign switching is explicit.



  • More sign switch calcs - switching "pre calc" as well as the normal "post calc"

3. Adopt inflow / outflow throughout the model



  • Avoids having to worry about what to do with the inflow / outflow actuals



  • We get into sign switching in the middle of calculations e.g. capex / depreciation issue.
  • Have to deal with all the other weaknesses of inflow / outflow

At F1F9 we've been following the second approach in our Corporate Finance and FP&A modelling.

  • How have you approached this problem in your models?
  • Have I missed anything on the "advantages" and "weaknesses" of each approach?
  • Do you have any recommendations for a better approach?


To join in this discussion, visit the financial modelling handbook website.


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Do financial modelling standards inhibit innovation?

Posted by Kenny Whitelaw-Jones

FAST Standard and innovation
This is one of several questions that is asked regularly about our adoption of the FAST standard.

We think that standards are more likely to promote innovation than inhibit it.

In his book, "The World is Flat", Thomas Friedman quotes Joel Cawley, Head of IBM''s strategic planning unit:

"Standards don't eliminate innovation, they just allow you to focus it. They allow you to focus on where the real value lies, which is usually everything you can add above and around the standard"

In software development the code is never an end in itself. The end point is the application created by the code and the problem it solves. Standardisation in coding facilitates innovation in application development: better software solves more problems.

Spreadsheet models are never an end in themselves. They are created to answer a business question. Knowing what question to ask - and knowing what to do with the answer - is where the real value lies. This is what our clients add above and around the standard.

As one of F1F9's Private Equity clients puts it:

"Every investment we make starts with a hypothesis. The financial model is the environment in which we conduct experiments to test that hypothesis. Our focus is on formulating the right hypothesis, and then understanding what the experiment tells us. FAST helps us by reducing the time it takes us to understand the spreadsheet itself, so that we have more time to think about and act on what it is telling us"

The greater the level of financial innovation, the greater the requirement for clarity and transparency in the modelling. 

Another F1F9 client put it like this:

"The application of standards allows a team based approach to modelling and reduces our risk. This gives people the confidence to try out new and innovative solutions to client problems, knowing that their analysis will be understood by their colleagues and by the client."

Software standards capture the distilled wisdom of thousands of developers who, through decades of trying things out, have come to understand what works and what fails to work.

As an independent standards body, the FAST Standard Organisation is now doing the same for financial modelling.

free financial modelling course 31 days to better financial modelling  
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Introducing the Financial Modelling Handbook

Posted by Kenny Whitelaw-Jones


There are lots of good books about Financial Modelling. As useful as many of them are, they all represent one person's view on how modelling should be done. With the Financial Modelling Handbook project, I am trying to change that by writing a book that draws on the wisdom and experience of the wider modelling community.

I was inspired to start the Handbook by books like Business Model Generation, David Roodman's open approach to writing his book Due Diligence, and more recently Unboss. These books were co-created by distributed groups of experts who share a passion for their topic.

Over the past few years I have taught lots of people to build models and each time I teach a class I learn just as much as the students. New insights are emerging all the time as people apply the principles of FAST to their area of modelling. It would be a wasted opportunity to write a book without tapping into all that great knowledge.

I realise there will be some who think that this is a cynical F1F9 marketing gimmick. It is not. It is an attempt to write a geniunely better modelling book.

I will not be making any money from this project and neither will F1F9. It is a non-profit venture. The whole guide will be available for free online. In due course a hard-copy version will be available to purchase. If sales of the hard-copy version generate any profits, these will be given away to charity.

We will continue to pubish small sections of the book regularly. These have been grouped together as financial modelling guides. These guides can be viewed and shared online, and freely downloaded in PDF format. They will be updated in response to the feedback we receive.

The book is based on the principles of the FAST Standard. It will teach some some essential model build skils, as well as looking at applications in particular domains. There will be lots of worked examples.

Find out how to get involved or review what's been published so far.

 This article was originally posted on the website of the Financial Modelling Handbook


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10 Presentation pitfalls to avoid

Posted by Kenny Whitelaw-Jones


This blog post is also featured as a guest blog on the website.

At some stage in every financial modelling career, there comes a time when you're required to present the results of your analysis. I've seen lots of modellers present, and these 10 mistakes keep coming up. Avoid these presentation pitfalls, and hopefully you'll find your career progressing faster!




The future of any business or project is a range of possible outcomes. The question is how likely is each outcome? When you present the results of your modelling as a range of possible outcomes it helps everybody to think through the risks, including the unknown unknowns.

I’m amazed at how many presentations talk about a single point base case estimate of some metric, often IRR.

Sometimes to 4 decimal places.

Just because your base case model is showing an IRR of 14.2345% - don't be tricked into thinking that this is what is actually going to happen.

The only thing you can say with any confidence about your base case is "this is what isn't going to happen".




Nobody is there to talk about the model. It's your job to translate what the model is telling you into business insights, and then communicate them effectively. Spending time walking somebody through your spreadsheet is rarely a good use of time. Unless they’ve asked for it specifically, and even then . . . !




You are smarter than your model. When you are running sensitivities or changing your model, make sure you have a hypothesis first about how the model is going to react. If the model doesn't react the way you expect, your first position should be that the model is wrong.

Here's an example from some presentations I saw this week. Analysts were required to run sensitivities at different levels of gearing. This requires making two changes in the model. 1. the gearing assumption, 2. the headroom in the term debt facility. If students change the leverage, without increasing the headroom, the model doesn't draw down the debt. The result was a chart of cover ratios at different leverage levels that looked like this:DSCR

The base case gearing was 65%. The model worked at lower levels of gearing as the model was able to draw down less debt, but not at higher levels due to the headroom constraint.

Quite a few students made this mistake; but instead of trusting their intuition that when you increase debt, cover ratios must decrease, they believed what the model told them, and set about trying to explain it. There were all sorts of wonderful reasons why increasing debt didn't mean lower coverage ratios.

Rather than rationalising reasons that your model doesn't act the way you expected it to, you should be looking for an explanation of what the model is telling you.




Interesting to model doesn't mean interesting to your audience, and it doesn't mean it's material to the business.

Just because something was "interesting to model" doesn't mean it should automatically go into your presentation. In fact it’s a relatively reliable indicator that it shouldn’t.




Every slide must have a "so what". If you don't know what the point of a slide or graph is, drop it from the deck. Ask this question of every piece of information you put in your deck.

Some analysts think that if you just present enough data then people will get it. If you’re that analyst you’re not going like this: when you make a presentation you're telling a story. While you want to show data, your audience is longing for insight. You want to chart every line in your model, your audience wants to understand what decisions they need to take.

While we're on the subject of charts:


6. BLUF.


Bottom Line Up Front. Lead with your conclusions. If the purpose of your presentation is to ask for an investment of $1.5 billion dollars in your infrastructure project, start with that.

Say "The purpose of my presentation is to ask for $1.5 billion to invest in Project X. I'm going to talk you through the rationale for the project and we're then going to look at the key risks, and how we are going to manage those risks".

In college you're told to end with your conclusions. In business you have to start with them. Don't talk for 20 minutes keeping people guessing about what it is that you actually want them to do.




The only acceptable answer to a question you don't know the answer to is "I don't know the answer to that question". No matter how slick you think you are, your audience can smell your BS a mile off. They will then apply a BS discount factor to everything that comes out of your mouth from that point onwards.

Conversely, if you don't know, and you're honest about it, it builds trust. Unless you don't know the answer to any of the questions they ask, in which you shouldn't be making the presentation in the first place.




Your audience want reassurance that you understand the risks of the business venture you are modelling. Blindly telling them that everything is going to be OK is not going to cut it. Your infectious enthusiasm for the sector is going to make your presentation more enjoyable, (see point 10), but it's not going to persuade anybody to part with $1.5 billion unless they know that you know where the risks lie and how you are going to manage them.




It's a slow painful death for your audience. If the presentation is worth doing, it's worth doing properly. Learn your material. Or don't turn up.




Don't phone in your performance.

Get out in front of your audience. Use a remote slide clicker - they cost a few dollars. Make eye contact with every single person in your audience, in turn, constantly. Vary your voice. When you're making a presentation, you control the energy in the room. If you're not putting energy into the room, you're taking it out. Choose.

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Avoid starring in a spreadsheet horror story – Our top 3 tips to improve your financial modelling

Posted by Kenny Whitelaw-Jones


It may seem a little odd that one of the key foundations of business over the last 25 years has been the humble spreadsheet. Yet it is hard to find a key financial decision that has not been based on calculations made in this ubiquitous software tool.

As our e-book shows, nightmares lurk amongst the innocent rows and columns of figures for those that don’t take care with how they process their figures. Research has shown that 88% of spreadsheets contain errors of some sort and approximately 50% of financial models in use operationally in large businesses have material defects.

Many different organisations have been hit by spreadsheet problems in a variety of ways. The root causes of many are surprisingly simple errors. MI5 admitted that they had bugged 134 of the wrong phones because of a spreadsheet formatting problem. Oxford University candidates experienced interview upheaval when administrators muddled up spreadsheet numbers for registration and examination marks.

Unsurprisingly, spreadsheet problems are seen most in the world of finance where the values involved can be terrifying and the financial calculations can become extremely complicated.

An eagle-eyed reader of a US Federal Reserve statement spotted a hitherto unnoticed error in a spreadsheet worth up to 4 billion dollars. Who knows the value of the financial impact of the spreadsheet error found in the published research papers of leading Harvard economists, Carmen Reinhart and Kenneth Rogoff? Their flawed research has been claimed as a basis of several countries’ current economic austerity programmes.

The problems highlighted are not only embarrassing for those involved, they can be costly both in terms of money wasted and in jobs that are lost. At least one CEO has had to resign as a result of errors being discovered in figures that they had previously announced.

The stories which have attracted uncomfortable publicity are only the tip of the iceberg. There must be many more unpublicised spreadsheet skeletons lurking in the cupboards of many an accounting department.

What 3 things should managers responsible for building and operating spreadsheets do?

1. Adopt a standard for creating spreadsheets that can be followed by people in your organisation.

The FAST standard is the only internationally recognised standard for building spreadsheets. It is managed by an independent standards organisation, which is backed by F1F9 as well as international accounting firms, Grant Thornton and Mazars.

FAST defines a Flexible, Appropriate, Structured and Transparent approach for creating understandable spreadsheets and reducing errors. It still gives users the freedom they need to tailor their calculations to particular business needs but it also  imposes simple disciplines that mean that their work is understandable. Most importantly its adoption means that errors can be spotted. 

2. Ensure that procedures are in place for managing spreadsheets and the IT environment where they are saved and shared.

Such procedures should include:

  • Simple version control and file numbering processes which identify clear responsibility for who is in charge of spreadsheet updates. Many errors are caused because the wrong version of a spreadsheet is updated or viewed.
  • Review of spreadsheet work ranging from sense-checks of model outputs to independent examination of the spreadsheet coding for more complicated applications.
  • Routines for regular communication between those making and managing commercial decisions and those who are building spreadsheets to ensure that correct assumptions are used.
  • Control and audit procedures to identify and track who can access and has updated spreadsheet files.

3. Pay attention to the human-side of spreadsheet control.

Make people aware of the risks of working with spreadsheets and provide training in how to build and manage them safely and efficiently. A culture of positive collaboration and improvement should be encouraged where good design and error elimination is promoted with clearly defined responsibilities.

Given that spreadsheets have been around for over 25 years, it seems surprising that businesses have not mastered ways to manage them yet. But the truth is that high profile errors keep appearing. Part of the problem seems to be a philosophical one. Because the nature of Excel use is everyday and accessible, many managers just don’t look on it as something that needs managed in the same controlled way as other computer systems. Some have already become enlightened. Others have not, to their cost.

Download the Dirty Dozen ebook
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Webinar: The changing face of capital providers in project finance and PPP

Posted by Kenny Whitelaw-Jones


This complimentary webinar will be presented by leading project finance advisor and Vair Training Head Instructor: Charles "Chip" Haskell. Chip will look at the basic math surrounding changing parameters of financial instruments for project finance available to infrastructure projects and public-private partnerships.

A significant driving force in project returns and unit pricing is the look, feel and shape of the debt component. The traditional long-term syndicated loan structure has all but disappeared as a financing instrument, perhaps never to return.

However, the need for long-term financing still remains and necessity is the mother of all invention. So where there is demand, supply will be created.

We'll also look at the financial math required to model differing and evolving debt instruments, while also discussing the valuation implications for debt, equity and potential purchasers of the product.

A recorded version of the webinar will be made available shortly after the event to all who register.

 Register for project finance webinar
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Why fixed price financial modelling contracts are bad news for everyone

Posted by Kenny Whitelaw-Jones

When we published the Introduction to Agile Financial Modelling ebook last month we noticed a common thread in the feedback we received from Financial Modelling professionals:
“We agree with what you’re saying about Agile modelling, but our clients want fixed price contracts for model build. How does an iterative, Agile approach work when it comes to pricing?”

Our new ebook is a response to that question. If you’ve ever had a client say to you, “We have all of these needs and wants that have yet to be defined in detail but please tell me precisely how long it will take and how much it will cost?” then this ebook may be an interesting read for you.

In the book we discuss:

Why clients start out wanting fixed price contracts

Why fixed price contracts are generally bad news for modelling projects

Some approaches we have found to be effective in dealing with the disconnect between and Agile approach to financial modelling and requests for fixed price contracts.

  • Why clients start out wanting fixed price contracts
  • Why fixed price contracts are generally bad news for modelling projects
  • Some approaches we have found to be effective in dealing with the disconnect between an Agile approach to modelling and requests for fixed price

As ever your comments and feedback would be much appreciated.

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Please stop using pie charts

Posted by Kenny Whitelaw-Jones

In the name of all that’s good in the world, please, please, please.

Our friend Stephen Few has been saying this for a while. It doesn’t seem like many of us are listening.

Pie charts are useful for one thing and one thing only: communicating that a series of numbers add up to 100%. That’s it.

Pie charts fail at everything else.

Generally we use pie charts to communicate a “part to whole” relationship. The problem is that they do a really bad job. That doesn’t seem to stop them from being ubiquitous; the fast food of the data visualisation world.  They are tempting for a quick calorie hit, but ultimately lacking in nutrition.

The difficulty with pie charts starts not with the charts themselves, but with the limitations of human perception. The reality is that human beings are not very good at comparing the size of different areas. We are much better at comparing the size of different lines.

Look at these circles, imaginatively labelled “A” and “B”.

stop using pie charts 1


How much bigger is circle B than circle A? It’s more than 4 times bigger, but is it as much as 10 times bigger? We can tell that it’s bigger, but we do a poor job of saying by how much with any real confidence.

Now look at these two lines that we’ve called “C” and “D” (we’re nothing if not creative):


stop using pie charts 2


How much longer is line D than line C?

Most people find it easy to tell that line D is around 3 times as long as line C, but it is hard to say with confidence how many times larger circle B is than circle A.

How does this phenomenon play out when it comes to the humble pie chart?

Take a look at the following chart, showing visitors to this website from 4 different sources:

stop using pie charts 3 resized 600

In this chart we can tell 3 things:

1. All parts add up to 100%

2. Organic Search accounted for the largest single share of traffic (somewhere just short of half of all visits)

3. Email marketing, Social media and Referrals were probably all about the same, but it’s hard to be sure and we certainly couldn’t tell with certainty which of those 3 is the largest, and which is the smallest.

So, in order to make this chart useful to readers, we have to give them additional guidance as to the relative size of the smaller parts, and tell them just how big the larger part is.

It’s hard to tell without labels, so we dutifully add the labels, and now the chart looks like this: 

stop using pie charts 4


But when we stop to look at it, we realize that we have, in effect, created a circular table.

And worse than that, it’s a colour coded circular table. We have to look back and forward between the 3 smaller components in order to match the piece of pie to the label in the legend, and then, in our heads, try to rank them using the numbers. It’s not the hardest thing you’ll ever have to do in life, but you can probably think of more fun ways to pass your time. (Like doing this for example). 

And that’s before we succumb to the temptation to add some “cool” 3D effects and perspective, thus making it truly impossible to make any meaningful visual comparison. Don’t even get me started on this mess:

stop using pie charts 5 resized 600

Stephen Few suggests, and I whole-heartedly agree with him, that a more useful presentation looks like this:


stop using pie charts 6 resized 600

I know, it’s not as “fancy” as that 3D exploding pie chart, but it actually communicates some useful information. 

1. The items are placed in order for us; no effort is required to rank the components

2. The bar for each category is placed next to the label for that category, we don’t have to track back and forward to make sense of the chart

3. The chart takes advantage of the fact that humans are good at comparing lines – we can now see clearly the differences between the 3 smaller components

4. The data values are also presented in line with the bars, again making visual tracking much easier – no colour coding is required to relate the categories to the values

6. The chart still communicates that the numbers add up to 100%

So, let’s hear your arguments in defence of the pie chart; Stephen’s been saying this stuff for years, and pie charts don’t seem to be going anywhere.

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Have your say on the future of FAST financial modelling

Posted by Kenny Whitelaw-Jones

Last week the FAST Standard Organisation announced the establishment of a International User Group for the FAST Standard

Lots of our course Alumni and online training clients have asked how they can get involved in the future development of the Standard. At the same time the FSO has been looking for a mechanism to engage meaningfully with professional modellers who can input on the future development of the Standard. The User Group brings both of these requirements together. 

According to Bert Verstaete, Co-ordinater of the User Group, the FSO is looking for individuals who:

1. Are active modelling professionals.

2. Have positive personal experience of FAST models, either in a build, user or reviewer capacity.

3. Can commit to remote participation in the group, and to making an active and positive contribution to the process.

If this is you, please apply to join the user group.




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