Why Every Finance Team Needs a Data Scientist

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To hear about the future of the finance function and the need for bringing a data scientist into the finance environment, Finance Monthly speaks with Angela Mazza Teufer, Senior Vice President of ERPM at Oracle.

We are living in the age of data, one in which both traditional quantifiable information and unstructured data is being hoarded in huge amounts. It takes a specific set of skills to draw useful business insight out of this data, and that is why data scientists have become so crucial to the modern business.

The introduction of GDPR regulation earlier this year has forced companies to become more data literate, and has in some cases seen them appoint Chief Data Officers (CDOs) or build teams responsible for overseeing data governance.  This represents an important step towards a future where all businesses are able to make the most of their data, but it takes more than data management to turn data into value. This is where data scientists become crucial, and particularly in select business functions.

As a function that has always dealt in data and whose remit has expanded significantly in recent years, the finance team has a great deal to gain by bringing advanced data expertise into the fold.  Finance teams have traditionally been made up of people with a specific set of practical skills, including management accounting, auditing and forecasting.  While these remain important, businesses increasingly expect their finance department to play a more active role in driving organisational strategy, which requires a more diverse set of abilities. Data science is the most important of these.

What data science brings to the table

One of the biggest challenges faced by businesses is how to make sense of the enormous volume of data they collect, from customers, internally, and increasingly from third parties. Finance teams could easily spend all of their time just gathering and analysing data on business assets and performance, but the challenge today is to distil this information into something meaningful, especially as even financial reports are increasingly filled with ‘intangible’ assets that are not so clearly defined as revenue and profit, such as customer reach.

Having a data scientist embedded into the finance function will provide the specialist understanding and valuable resource to combine information in all forms, identify patterns that might otherwise have gone unnoticed, and most importantly draw out actions for the CFO or finance director to take to the board.

This also frees up other members of the team to focus on their areas of expertise rather than expecting them to pick up a whole new set of skills and take on a role they never signed up for. No matter the department, trying to ‘upskill’ an employee in data science underplays the importance of the role and makes light of the years of training and experience that specialist data scientists undertake.

Often, some of the most valuable information companies collect today starts life as an unstructured, chaotic set of data points. It ranges from concrete demographic data on their customers to news events and sometimes even weather patterns. The task of combining all of these streams of information and making sense of them requires the full-time attention of a dedicated specialist. It is certainly not something that core finance employees can accommodate on top of their existing responsibilities, nor can it be effectively undertaken without the appropriate training.

In short, it is much more effective to bring a data scientist into the finance environment and educate them on its specific needs, data types and ways of working, than it would be to pile complex data science responsibilities onto existing team members.

The future of the finance function

The changes to the role of the CFO and the growing demand on the finance function to be more forward looking and predictive have been well documented, but many organisations still find themselves in a period of transition. They understand what’s expected from them but are still setting up their teams and processes to deliver on this expanded brief.

It is enough of a challenge to forecast accurately in periods of uncertainty, without having to collect, analyse and process data from beyond the balance sheet as well, but it can be overcome with expert support.  By bringing the right mix of skills into the finance team, companies can develop the skills they need quickly and start reaping the benefits today.

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