Spreadsheets for financial modeling, the FAST standard and F1F9

I had very recently visited the offices of a financial modeling company in Delhi. It is a British financial modeling company with their primary modeling team based out of Delhi, India. In this post I would be summarizing some of my findings during my visit. It should grant a perspective of the state of the art on use of spreadsheets for financial modeling purposes.

  • What’s the FAST standard?

The FAST acronym stands for Flexible, Appropriate, Structured and Transparent. It is essentially a standard for financial modelling.

  • Wait, what is it again?

Okay, just like in Java language we have several hoards of rules, guidelines and conventions to follow when we are coding, the FAST standard defines rules and conventions to follow while doing financial modeling. Financial modeling has been traditionally done with and in spreadsheets and thus the FAST standard basically set guidelines and best practices while working with spreadsheets with the purpose of various types of financial modeling. Furthermore as traditionally the most popular and widely used spreadsheet in modern times has been MS Excel, the FAST standard, although universal in intent, has become inevitably correlated with the Excel technology; as in it tries to work around the weaknesses and exploit the strengths of the Excel environment. Nevertheless the guidelines themselves are not Excel specific and it does not for example has Excel keyboard shortcuts or macro based shortcuts as part of it. However the recommendation to use shortcuts instead of mouse is certainly a part of it. So how well or whether FAST standard can be implemented on other environments than excel is an exploratory question.

  • Where can one find it?

The FAST standard is an open standard and is maintained by an universal group at http://www.fast-standard.org/

  • What is F1F9? (Apart from being a weird word, more of a cryptic code rather!)

F1F9 is a financial modeling company originating in UK with a considerable global presence across various regions of the world. Its their office that I had visited.

  • What with the weird name?

F1 and F9 are two keyboard shortcuts in MS Excel: Help & Calculate…. that is the company’s business, to help people calculate. Thus the naming F1F9. (Cheeky eh?)

  • F1F9 and FAST??

The FAST standard was conceived by John Richter and Morten Siersted around a decade back when they were both working in F1F9. It was later released as an open universal standard and has been ever since contributed to by many modelers from across the world. F1F9 has forever pioneered the cause of FAST and still believes in and follows it for its own modeling activities.

So there I was in the Delhi office of F1F9. Much of our work in the Spreadsheet Lab revolves around the fundamental research question of how to apply software engineering methodologies and good practices to the domain of spreadsheet programming to improve it and to resolve known and unknown issues; where the “programmers” are not really programmers but are all types of managers and business executives.

The idea was to learn how F1F9 is using spreadsheet programming to do their work of financial modeling; to identify areas where software engineering methods can be implemented; to perceive issues they might be facing with spreadsheets which they have accepted as part of life but which perhaps we at Spreadsheet Lab can solve.

So it was the FAST standard that I learned as the very first thing with a practical example of how it was being utilized to do a real life financial modeling.


Very soon I observed some obvious similarities between how financial modeling is being done in F1F9 and several widely used coding conventions and software engineering best practices. I compare the similarities based on two types, type one being similarities largely due to the FAST standard which is but analogous to best practices and conventions in coding; type two being similarities in the whole spreadsheet engineering processes and conventional software engineering processes and thus not being limited just to the domain of coding.

Note that these are only the similarities I have already identified based only on my current knowledge level of financial modeling, FAST standard and F1F9’s modeling style and therefore this list can surely grow in the future as I get to know more about these things.

What similarities can be identified with software engineering context:

Similarities due to the FAST standard: The FAST standard has several best practices and guidelines recommended in it to follow while doing financial modeling. It is similar to various standards and coding conventions that we follow in the software engineering world to come up with more mature and robust software. Certain parallels that are readily identifiable are the following: (Currently based only on the aspects of the FAST standard I have already learned)

  • Variable Naming Conventions:

In most programming paradigm or language we have well-defined variable naming conventions. Following these conventions are not required by the language itself or the compiler; the programs can function correctly even if they are not followed. However these conventions are religiously followed in order to make code more readable. To make programmers easily understand purpose of a piece of code; so that even someone who has not written the code can understand it. Its purpose is to provide some sort of meta data to the programmer. Something similar has been recommended in the FAST standard. It is not really naming convention but it serves the same purpose; it expresses information about all the variables and data that is used in the spreadsheet.

How it is done?

Unlike naming conventions and using upper case, lower case, camel case and so on in FAST it is done using different types of cell highlight colors, and relative position (columns in Excel) of variables, constants, series, calculations etc. in the spreadsheet, and maintaining this positions uniformly across the spreadsheets. Just by looking at which column the particular data is located or the cell highlight color a modeler can understand the nature and purpose of that data.

  • Addition of Comments

Like commenting is one of the most essential best practices for coding of programs, the same is also in use under the FAST standard. Cell comments are used to demarcate rows or areas of the spreadsheet which is in some way having some ambiguities or is unusual.

  • Use of CONSTANT declaration

In programming logic it is often considered good practice to not use constants directly inside operation expressions as hard coded values. Instead it is recommended to use certain variables for this purpose and fixing their values by declaring them as constants. In various programming languages this is done in various ways.

Similarly the FAST standard recommends not using embedded hardcoded values inside formulas; rather it is suggested to input constant values in certain cells and use those cell references after proper anchoring inside of formulas used across the spreadsheets. Like most programming language naming conventions identify such constant entities from their UPPER CASE names here it is identified from their cell highlight color and column location.

  • Driver and stub modules

In coding practice and in software engineering we have the culture of using driver and stub modules which are practically dummy modules that have been not coded yet, having some hardcoded values or values that are yet to be calculated in the software or program itself. These modules then work in conjunction with the modules of the program that have been actually completed in order to test or demonstrate the overall functionality of the program. Subsequently they are also coded and completed at a later stage. Similar thing is done in financial modeling in the FAST standard.


Use of placeholders are serving the same purpose like drivers or stubs. Placeholders are those values which are not originally supplied and are temporarily taken as assumptions. Based on the assumptions the rest of the model is completed and placeholders can then eventually be replaced with real values obtained at a later stage. Using placeholders enable the modelers to continue with modeling work and not wait for some values that have been not yet supplied.

  • Coding line length limit

In coding, many standards, guidelines and editors recommend or enforce something called the coding line length cap. This limits the coders from writing a line of code which more than 100 or 120 characters long because after this length readability of the code is seriously messed up. Similar thing is recommended in the FAST standard namely the “Thumb Rule” for the cell formulas. This rule states that any formula should not be so complicated or long that it is more than the length of your thumb. When requirement is there for a longer formula surely in some way the task can be divided and done by two or more shorter formulas.

  • Call by Reference and Call by Value

In programming we clearly distinguish between call by reference and call by value in context of method calls. Methods are smaller modules of a single program where some tasks or calculations are done. When methods are invoked, data is passed to them by the main program through inputs. These inputs can be variable references or pointers which means when the method will work with them the original variables  may become modified. The inputs can also be temporary variables with values copied from the original main program variable, in which case the methods can return new value after processing but cannot directly modify the original main program variables. Both has its own merits but normally it is considered safer to do call by value i.e. using copied values than original variables themselves.

Similarly in financial modeling, under the FAST standard, it is encouraged to use range names and not direct cell references when working with them in VBA code inside Macros. Direct cell reference can become altered when rows or columns are added to the sheet; range names however stick to the data in the cell and shifts along with the cell if pushed by new rows or columns. Therefore using range names inside Macros ensure that they always get the correct data passed to them or the code need not be repeatedly changed whenever rows or columns are added.

  • Use of checker tools:

Like in software engineering various types of checker tools and inbuilt checks in editors are used to ensure that best practices and conventions are maintained in coding, similarly automated checks for FAST standard compliance of the models is being done using various types of software checker tools.

Similarities due to model development cycle or process:

  • Configuration Control:

In software engineering build maintenance and configuration control play a very important part. Although there these operations are large and elaborate, here in F1F9 an elementary form of it is observed in the way version is controlled and back up is archived of the Excel workbooks containing the models in a manual fashion.


My first point of entry into the world of research work in spreadsheet use/engineering was the work of Felienne Hermans of the Software Engineering Research Group at TU Delft. From my primary explorations of her work I arrived at the understanding of how vulnerable the spreadsheet programming paradigm is to horrendous levels of mistakes, errors and goof ups.  Not even sure whether it can be called “programming” at all, because its mere use of spreadsheets governed by no rules or structures and moreover the “users” don’t know sh#% about programming. Yet the volume of this usage is humongous and so is the horror stories related to spreadsheet errors. Companies have lost billions of dollars, academics have lost reputation and credibility, CEO s have lost their jobs just due to spreadsheet errors. The Dirty Dozen book by F1F9 has quite a few examples of cases like this. This brings out how important it is to do something about it; to make some changes and bring some improvements so that the heavy dependence of the industry on spreadsheets can be sustained sans the inevitable hazardous risks related to spreadsheets use. The question that arises immediately is what is the reason behind such a risk?


Why are there so many problems?

The formalized answer to this question is perhaps beyond the scope of this article but in a simple way from what I understood, it all has to do with not following rules or good practices. From what I observe is that companies are functioning in three areas when it comes to working with spreadsheets.


By “rules” in the above diagram I mean rules, best practices, techniques and process flows. In other words we have to understand between spreadsheet use and spreadsheet engineering. Spreadsheets can be used in the way artisans make pottery or handicraft or a genius artist paints a masterpiece (though  meaning of which people find difficult to understand). On the other hand spreadsheets can be used in the way automobile is mass manufactured in the assembly line and rolled out on the streets. Anybody who knows to drive a Toyota will also be able to drive a Merc, BMW, Jeep, Renault, Ford or whatever make it is of the car. It is important to distinguish between engineering and handicraft or artistry. If I try to extend the Venn diagram to the analogy of cars it would be something like this…


A weird car design!
Figure A

I hope I have been able to send the point across by now. I hope now it is a bit easier to understand as Why there will be so many accidents in the road? Or Why the spreadsheet use today is vulnerable to erroneous effects? Majority of companies using spreadsheets today are operating in the reddish shaded part of the Venn diagrams in regards to how they use spreadsheets. Only a minority is operating in the bluish shaded portion; F1F9 and any other organization following the FAST standard being inside that area.

So what is the solution?

Again the formalized answer to such a question may be one or more PhD theses themselves and hence out of scope of this article. However to approach in a simple way now I will move away from the automobile industry analogy to the domain of medical industry. What is disease and health? A disease is when a malfunction has already victimized a human body and must be treated or cured. On the other hand health is the human body’s inherent capability to resist against potential diseases n’est-ce pas? The healthier a person is the less prone he or she is to various types of diseases. Increasing or maintaining health is therefore a sort of prevention from possibilities of disease.

The issue of spreadsheets can be approached in the manner analogical to above. Spreadsheet masses that are already existing in the world need to be cured of problems, got rid of issues, re-worked, re-engineered, or simply used with additional augmentations like visualizations, analyzers or such tools just like wheel chairs, artificial legs, prosthetics and so on! And on the other hand efforts must be applied in order to create healthier spreadsheets (luckily, unlike human beings where we have no control over the genetic prototype as of yet, here we have control of their design); to ensure that spreadsheets are created following set of logical, reproducible, feasible set of rules, carefully planned processes and under the guidance of a set of best practices.

So what’s happening in F1F9?

From my stint of study in the F1F9 office at Delhi I have reached a conclusion. A conclusion that summarizes in brief whatever is going on there based on what all I learnt. What is happening is just that F1F9 is consistently and meticulously producing healthy babies. Oops sorry, what I meant is healthy spreadsheets! They have chosen the path of prevention and they strive to avoid running into situations where they might need curesThey are not mere spreadsheets users but they are spreadsheet engineers. Their principal niche is financial modeling but this primary activity they are doing with spreadsheets and they are using spreadsheets in a really commendable manner. And how they are doing this? By following the FAST standard template of course. The FAST standard in the domain of financial modeling based on spreadsheets use is almost equivalent a secret genetic template in the hands of God to create healthier human beings! (This is merely my personal opinion at present point of time and may sound a bit exaggerated but yet the exaggeration has good substance behind it, this I can guarantee). If you carefully consider the best practices laid down by the FAST standard that is rigidly followed at F1F9 and compare it to the myriad of problems highlighted in Felienne Hermans research work, you are bound to feel (and eventually logically conclude) that such problems are very unlikely to occur in spreadsheets created in F1F9 or anywhere else where FAST standard is being followed! The cases studied under the research were mostly replete with everything that the FAST standard categorically asks to avoid and devoid of everything the FAST standard tries to religiously enforce. So in one word F1F9 had definitely taken one step forward in the process of spreadsheets evolution and the FAST standard is a golden key leading towards a bright future for the domain.

3 thoughts on “Spreadsheets for financial modeling, the FAST standard and F1F9”

  1. Hi Sohon,

    Great post, thank you!

    The majority of items you have outlined can be broadly categorised as ‘Financial modelling best practice’, an area of financial modelling performed by numerous companies, including F1F9, Corality, Numeritas and ModelCom to name a few. It would be very interesting to get your views as a researcher to compare the benefits of the different ‘dialects’ of best practice financial modelling.

    A large component of the areas you have covered are included in the majority of professional financial modelling consulting companies, which was highlighted in joint talk by myself and Morten Sierstedt (F1F9) in a talk to EuSpRIG in 2011.


    I would greatly value your thoughts on how you compare FAST to our methodology SMART and other related methodologies.

    A number of SMART financial modelling examples can be found here:



    ps. It would be great to catch up at EuSpRIG in Delft to discuss this further!

    1. Hello Rickard,

      Thanks a lot for your enthusiasm. I am practically a novice in the world of spreadsheet engineering and my introduction to this area in F1F9 was like one of the first stepping stones. It makes me glad to know that particularly in the domain of financial modelling, it is not only F1F9 who is implementing the best practices but many other organizations.
      I am eager to know more about the SMART methodology you mention about. Once I go through it, I will definitely share my opinion as well as how it compares with the FAST standard.
      And most importantly, of course, looking forward to meet you in person in Delft. So see you in July!

  2. This was a very good writeup. However I noticed some clear contradictions and the author’s comments:

    Never use Excel Names:
    Except for external links
    Except for references for macros
    Except were non-local precedent references are warranted

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