Evolution of the financial analyst

 Ernesto Hontoria

Versión en castellano: Evolución del analista financiero

Maybe I should not write about this because it reveals that I'm getting old, but I can't resist the temptation to tell what I think is a trend in the evolution of the financial analyst’ role. In my current position, I often educate young analysts in data search and interpretation, young people who often ask me how to progress in their careers.

Let's start by saying that in the years that I have been working in finance, I have witnessed how the position of the financial analyst has evolved following the technological changes experienced in the work environment. This evolution implies a change in the attributes that the financial analyst must meet to be able to skillfully carry out their tasks, and which, of course, weigh heavily when looking for jobs.

Allow me to make clear two points: The first one is that Excel is still a mandatory reference for financial analyst. The second is that it is no longer a differentiating factor. If 10 years ago companies were looking for analysts with solid financial knowledge and with moderate experience using spreadsheet, today's job demand assumes that financial analysts must have clear concepts and be able to handle Excel well. It is not conceived today a financial analyst who does not master Excel. They are asked at least to have skills in managing pivot tables, vlookups, hlookups, and in many job applications they are also asked to know how to program macros, something that – in my experience - few analysts master.

Until a couple of years ago my main concern when recruiting a financial analyst was their level of mastery of Excel, even more than his knowledge of financials’ concepts, which I presumed all they had. Recently my perspective has changed, not because Excel is no longer indispensable in the work environment, but because most analysts have become quite skilled with this tool and it is no longer a differentiating factor when recruiting them. Every day there are more graduates of business schools with good knowledge of the tool, and the factor that differentiates them is the use of new data visualization tools, or the ability to understand the management of more complex databases, and to understand statistics.

The situation has changed drastically in the last 15 to 20 years. If before it was difficult to get statistical data to make comparisons, nowadays companies have more data than the human mind can assimilate. A good financial analyst must be able to interpret them. It is no longer enough to say that sales rose 3 or 4 percent in the month of April. The analyst must be able to quickly interpret the mountain of numbers that are available to him in the company's databases, to determine which products, or combination of them, produced the growth in sales in April, what profile the consumers have, what profitability was obtained from the different items.

In fact, the challenge goes much further. In many companies the aim is to achieve real-time analysis, analyze sales (and consumers) at the same moment that the transactions are taking place, understand trends and predict the future.

The amount of data that companies generated and collected exceeds by far the ability of Excel to handle it. Several years ago, my father-in-law sent me an article that predicted the unavoidable death of Excel as the predilected tool of financial analyst, due to the obvious limitations of the tool to manage the exponential growth of available data. The prediction of the article has not come true and far from it, the popularity of Excel has continued growing, as well as its ability to handle data has continued to increase, although not as fast as the available data has done. On several occasions I have taken Excel models to the very limit that the tool allows, and I have had to appeal to the use of other applications.

Picture taken from Internet

Fortunately, new tools have emerged that expand the portfolio of products available to financial analysts, tools designed for massive data management (Big Data). It is the knowledge of these new tools that is becoming the differentiating factor when recruiting financial analysts. After all, the challenge for many companies is how to convert the mountain of data at their disposal into useful information that allows them to make the right decisions.

Today's challenge is to discover patterns, understand trends, and act before a competitor does. It is not an easy task. Large amounts of data require a minimum of statistical knowledge, their processing requires better technology, faster processors, better data visualization tools and handling techniques, and most importantly, analysts prepared to understand what they are doing, to correctly process the data, and verify it. Analyst should prevent their bosses to commit blunders when trying to interpret big amount of data. The situation has changed and with it the profile of the position.

Related post: The Role of the Financial Analyst