Ernesto Hontoria
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.
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Picture taken from Internet
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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
