There was a time, not too long ago, when Finance and Accounting had complete control over most of the decision making data in any business. I caught the tail end of that generation. At my first job as Financial Analyst for a licensing division of the Walt Disney Company, the finance department had control over all data, including the G/L, contract systems, customer and vendor database, budget and forecast files, and even the IT function. We owned the keys to the kingdom.
Skip ahead 15 years and now Accounting is being cast aside as the provider of “historical” information by the “forward-looking” Analytics and Data Science departments. Across all industries, companies are looking for qualified data analysts to fill the data-driven “intelligence” void that Accountants can’t fill. Why is this happening and what can you do to stay relevant?
According to a 2016 report by Deloitte, despite being a quantitative function, the accounting world, including tax, has been slow in requiring analytics skills from its professionals. By having the profession focus on compliance and reporting, a massive gap in analytical capabilities has developed. Finance professionals are not far behind. A January 2016 report by the Institute of Management Accountants, revealed that most CFO’s believe that less than 50% of their team possesses SOME of the required skills in business analytics.
There is no question that, in the analytics age, accountants face the very real risk of being relegated to summarizing the clerical and mundane “hindsight” information while the analytics guys will handle the much sexier “insight” and “foresight” projects. That is unfortunate because accountants are uniquely positioned to be the best Data Scientists. You see, many companies are failing to deliver value from analytics because they have techie people, with no business background, trying to find profit in their raw data. They don’t have a good sense of how businesses make money so they don’t know where to look for important patterns. What companies really need is Finance and Accounting pros, with a solid understanding of how profit flows, to acquire the tech skills necessary to be able to extract the profitable insights that are hidden in transaction databases.
To that end, for Accountants who want to take advantage of the data science talent gap, here are the seven most important skills you will need to learn:
- Advanced Excel – In spite of all the analytics software being released on a daily basis, most Data Scientists still do a majority of their analysis in Excel. However, they use Excel to its highest potential, including the use of sophisticated data tables, statistical functions, report automation, and self-correcting models. Your objective should be to dominate the formulas and techniques that will allow you to manipulate large files of raw data.
- Data Mining/SQL Programming. While there are many programming languages that you can master for data analysis like Python and R, most Data Scientists rely almost exclusively on SQL to query transaction databases. That is because a lot of Data Science revolves around summarizing data and using analytics functions which are now built into most SQL databases. Your goal is to learn enough SQL to be able to query the raw transaction data of any database in your company.
- Advanced Revenue Analytics. The fastest way to add profit to the bottom line is through smarter pricing and sales channel optimization. Knowing how to find inefficiencies in a company’s pricing structure is an invaluable skill set, but you need to know how to get the right information and apply the right math. The most valuable analysts know how to find the right data set to explore any revenue question.
- Mathematical Optimization. The end game of Data Science is to find the set of decisions that are the most optimal to achieving long-term profitability, whether the solution has to do with increasing revenue or decreasing costs or both. As the domain experts on the P&L, accountant should be able to direct managers on how to tweak their tactics in order to create the most contribution. You must understand the algorithms of mathematical optimization and how to use them properly to provide creative solutions to unraveling the puzzle of achieving higher profit.
- Analytical Segmentation. The era of business-line, channel, or regional P&Ls is over. Companies are requiring Customer Segment P&Ls to understand where they should invest their limited resources. Highly targeted marketing, sales, and pricing strategies have been proven to deliver the most profit. Using data to reveal important trends at the customer level is the new “actualized” state for analytics-driven businesses.
- Visualization. Most people see the word “visualization” and think fancy graphs. To me it means the ability to reformat data insights for easy consumption depending on the audience. The way a CEO might need to see a set of data is not the way the Head of Marketing may need to see it. It’s no longer about having one pro-forma template. Being able to use SQL, Excel, and special functions and graphs to aggregate and present the same data from many different perspectives so that insights can be identified easily is fundamental to navigating today’s complex business cycles.
- Real-Time Models. The latency of accounting reporting is responsible for the reactive nature of managerial decision making. While it would be illogical to reveal the score of a game only after the final whistle, many companies still wait on month-end financials before proposing future tactics. Accounting information needs to become more real-time in order for it to compete with other business intelligence. By creating performance reports that use streaming data from all transaction systems, accounting can provide managers with a clear view of how their decision are affecting the final results.
The pressure is on for Finance and Accounting professionals to deliver more insights. The only way to stand above the crowd is to possess skills that are in high-demand, but in short supply. As a Financial Analyst turned Analytics Consultant, I understand exactly the skills that you need to be considered one of the elite analysts in the global talent market. Our groundbreaking course, Introduction to Data Science for Finance and Accounting Pros will equip you with a skill set that is highly coveted in today’s Big Data environment. Click below to learn more.
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Robert Hernandez, Revenue Discovery Expert Author Info: Robert Hernandez is an expert in the field of mathematical Optimization and Analytics. He has spent his entire career building data-driven forecasting and optimization models for companies in over 20 different industries, from tech to tourism. Robert possesses a very unique skill set including cross-disciplinary experience, advanced mathematical and analytics skills, data transformation, industry-specific knowledge and business-process improvement expertise. Read More+