Why do some careers skyrocket, while others flat line?

Why do some careers skyrocket, while others flat line?

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13 Apr 2017

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Guest blog post from Steven O’Neill

As someone working in the area of talent acquisition for finance professionals, I often ask myself why is it that some candidates’ careers skyrocket while others seem to flat line.

It’s a question of which there are many possible answers. A person’s interest in work, suitability, luck, contacts and aptitude, all spring to mind as potential valid reasons. That said from where I sit, one thing in common with those who perform well, is their ability to see the big picture.

But what does that phrase really mean? And is it something we can all strive for in our professional lives?

In the context of those working in finance, seeing the big picture is being able to identify the key levers of a business and understand how to optimise them for the benefit of the organisation.

People who invest time in understanding this are the ones who tend to be good at what they do. And as a result are also the ones who can articulate in a meaningful way what they’re trying to achieve, how they intend to do it and why theirs is the preferred route to take.

Central to building this skill is the ability to model business scenarios in order to give some view of potential future outcomes. Whether it’s producing a full suite of projected financial statements or a simpler standalone return on investment analysis, solid financial modelling skills are of vital importance.

As accountants, we are often fooled into thinking that possessing such skills is a birthright that goes with the profession. However this is simply not the case, and like everything worthwhile in life, it takes time and practice.

So from a recruitment perspective here are three key reasons I believe investing in your financial modelling capability is worthwhile and can help you to stand out from the crowd:

The emperor has no clothes. I find accountants tend to overestimate their ability to use Excel. In fact, many try to highlight their use of pivot tables and Lookup functions as proof of having advanced skills. However, you need to realise that there is a very significant difference between someone who understands some of the well-used functionality of spreadsheets versus someone who is able to construct a robust financial model that can be used to underpin key decision making.

Simplicity is in fact complex. Being able to string together fifteen nested IF statements is not a badge of honour. It just means you have failed to produce a model that can be easily followed by others (and yourself, as over time even you will forget what you were trying to do!). The most impressive people I’ve come across are those who can explain complex situations in a simple matter of fact way.
And what’s more, they have a knack of keeping it simple even as complexity grows. Being able to build out models in a modular format will enable you to do this. The good news is that it is something that can be learnt.

The world has moved on. When I started out there wasn’t a whole lot of financial modelling going on. I think looking back there were several reasons for this; Computing wasn’t what it is today, so in many ways, you were more restricted in what could be done. But also in a world just embarking on the internet revolution, there was probably less complexity/risk out there (whether this was real or perceived we can debate some other time!).

But there’s no doubting the world has moved on. We now have computing packages that can be used for quite elaborate modelling and visualisation of data. But equally, the world has become even faster paced and trying to predict the future is becoming more challenging. In this context developing your I.T. skill set is essential.

While there are many online tutorials on modelling out there, the F1F9 courses are really well constructed and are all encompassing. Having completed two F1F9 courses I can say it delights me to know that such learning materials exist, as it is in all our interests to be able to build and share models to support better decision making.

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Do you have a better solution than this? I’m curious to know. If you do, or if you have any thoughts on my blog, join the discussion below.If you’d like to receive more information on data visualisation, please sign up to the topic-specific mailing list.
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