Nine things to think less about when building a FAST model



Andrew Berkley


10 Mar 2015




At F1F9, we talk a lot about financial modelling fluency.  Just as I speak in English (without thinking “now I must speak in English”), so I model using FAST (without thinking “now I must model in FAST”).  Modelling fluency means that I can model while watching the television.

And because I have invested the time and energy and concentration to achieve fluency, so that gives me less to think about while I model.

So what happens to all that spare thinking time?  Where does it go?  Answer: I spend more time thinking about what I have to model (the “conceptual model“) because I don’t have to think as hard about how I am to model it (the “spreadsheet engineering”).

Here are nine other things that you have to think less about if you are fluent in FAST financial modelling:


1. What makes a good label? It is easy to fall into the trap that modelling is somehow real life.  It isn’t.

In the event of a dispute, the parties will look to the contract first and then the model. The contract always wins.

A fluent FAST financial modeller will work with labels that are unique. A fluent FAST modeller makes sure that their labels are also aligned – if not identical to – the definitions in the contract. You can find detailed guidance on labels in the FAST Standard.


2. When are visual signals (cell background and font colours, font type, font size etc.) being over-used? Finance professionals do not have the best record when it comes to choosing what colours look good. Perhaps it is best that they stick to black and white.

Every colour in a FAST model is there for a reason – and if it is possible to communicate meaning through just one signal, then we will use just one signal. That’s why inputs have a light yellow background but keep black font – even though there is a convention that says inputs should have both light yellow background and blue font.

That’s why a fluent FAST modeller does not mark their calculations in bold. You can tell it is a calculation since the row beneath the calculation will be blank (white background).

One signal is sufficient. Anything more risks being clutter.


3. Is there a case for using Excel Names? I had an excellent discussion with an Excel user whose ambition is to remove all direct cell references from their Excel models. Their point being that when you type ” = F13″ you have no idea what is contained in F13 and, more important, what should be contained in F13. Location is of minimal importance; meaning is of huge importance.

Their solution: use Excel Names.

In a FAST model, a fluent FAST modeller will use direct cell references but will recognise their weaknesses. They do not give them meaning through using Excel Names. Instead, they use the concept of line items and calculation blocks that present – as clearly and consistently as possible – the meaning attached to a particular computation:

  • unique labels
  • links to ingredients used in the calculation set out immediately above (so that audit arrows are easy to trace)
  • units
  • single consistent formula copied across the columns
  • row totals for flows; and
  • headings, sub headings and sub sub headings.


4. How should I lay out my workings? The consequence of “extreme modularity” is that calculations are broken down into their constituent parts. Formulas become shorter (no longer than your thumb set out against the formula bar) and the technical complexity of the model is laid out down the vertical axis.

I would much rather review ten calculation blocks with short formulas than one calculation block with a long formula.  It is easier on the eye; it is easier to print out and explain to a stakeholder.


5. Is my primary concern presentation or transparency of calculation? The conventions associated with FAST are designed to make model calculations as easy to review and understand as possible. So it is important that they are applied to calculation worksheets.

There is nothing to stop a fluent FAST modeller stepping away from FAST and branding input sheets or output sheets or designing dashboards however they think best. That way the end user will still recognise the car interior as belonging to their car. This can be an important point in convincing senior stakeholders that a model rebuilt to the FAST Standard still belongs to them.


6. How should I design a model that accommodates different purposes? A model that needs to accommodate forecast data and actuals data needs careful design. Forecast data is calculation heavy; actuals data simply needs to be called up at the appropriate place. So I do not want to review forecast calculations that also include actuals data – unless the forecast is driven off the latest actuals.

A fluent FAST modeller will segregate according to purpose. When calculating ratios, ask for what purpose they are to be calculated. If for covenants as documented in a loan agreement, then the key question becomes “when?”. On what date is the ratio to be calculated? Answer: align dates with what the loan agreement says.

If ratios are to be calculated for analysis purposes then the modelling might be quite different. Here the answer to the question “when?” might be “whenever it is sensible and useful to do so”, e.g. whenever the denominator of the ratio is greater than zero.


7. How can I avoid time-consuming, non-productive modelling? A fluent FAST modeller is a great scavenger. They are always looking for things that they have modelled previously that they can recycle. They will make heavy use of “find and replace” (Ctrl + H) in order to spot and minimise spelling mistakes.

If a model contains a spelling mistake, what other mistakes has the modeller allowed to creep in undetected?

And a fluent FAST modeller will never indulge in keyboard repetition – the sort of “tap – BANG!; tap – BANG!; tap – BANG!” keyboard technique that is too often the sign of someone who needs to review their working practices.


8. How can I manage the risk of my model going circular? A FAST model is designed to be read from top to bottom and from left to right. Counterflows are links that refer to calculations on the same worksheet but below or to calculations on a different worksheet to the right. I think of it as looking ahead in your workings and knitting an answer back into the model. Counterflows increase the risk of circularity in a financial model.

A fluent FAST modeller will recognise that counterflows are necessary – especially when using corkscrews or calculating tax. But they will know when counterflows arise and will take steps to minimise them.


9. How much should I to build “cleverness” in my model? I do not expect my car engine to decide when to start. Instead, I expect the model to respond to my instruction.

When building a model, a fluent FAST modeller will assume that the model is incorrect and needs to be checked. They will check the audit trail (Alt M P) as they put calculation blocks together, review calculations by charting them (F11), and use row totals when modelling flows and flags.

They will remain in control of when numbers change. Hence, fluent FAST modellers work with calculation set to manual.

They will use the simplest functions they can find. Someone once picked me up when I commented that OFFSET was a poor function because it was too powerful. A fluent FAST modeller will build a model that uses brittle formulas – they break easily when garbage is fed into them. They show errors when the model is no longer working properly.


I described these as nine things to think less about when you are a fluent FAST modeller. However, thinking about them – in particular when you are not modelling – makes you a better modeller.

There’s plenty more we have to say on how best to build financial models, what they should look like and how they should work. If you haven’t already downloaded our free example model, you can do that below:

Read more & download  our example model

Andrew Berkley
With a background in business education and financial advisory work, Andrew leads financial modelling training at F1F9. He has been with F1F9 since 2013.