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Big Data and Financial Reporting

May 2, 2018
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Financial reporting has been the life-blood and focus of companies since the beginning of time. A few things have changed though, like the size of the numbers, the technology used to look at them, and how we share that information throughout an organization. But looking at what financials can tell us has pretty much remained the same. And what is that? Financial data can tell us what happened, ex. how many units were purchased last quarter and at what profit, what the spend was for a department versus what was projected, etc. This is all important information, but it’s data that looks backward and only hints at the future, so projections are essentially guesswork based on patterns. For financial reporting to move out of the past and become the foundation for data-driven decisions of the future, the information needs to be viewed in the context of the world in which it exists. But spreadsheets and flat databases don’t have the complexity or capacity to help us understand data that way. What is needed is a new technology that can pull in data from multiple, seemingly disparate sources to provide greater insight into a company’s financial position and inform those forward-looking decisions. This is where Big Data shines.

What is Big Data?

It’s a buzzword that you’ve probably heard a lot of. But really, what is Big Data? It’s important to first understand the idea behind Big Data. It’s a straightforward concept - the more information you have about something, the easier it is to not only understand it but to predict what that something might do or become. For example, if you have lots of data about the performance of pizza parlors in a specific city, how profitable they are, how long they operate before closing up shop, and so forth, you can predict the success of a new pizza restaurant in that city. But if all you look at is a narrow set of information, like the success of a pizza restaurant in a certain city, your predictions will have limited accuracy. You might be able to predict how well a pizza parlor would do in that city, but be unable to predict how it would do in another city. You have no idea if other elements that affect the success of a pizza place exist in the new city. But with Big Data, you could. Big Data pulls information from multiple sources and layers them to provide a more complete picture of what is happening. These data sources come from traditional places, like organizational data and demographics, and less traditional sources, like social media. That data is then joined in an effort to identify trends and patterns that would otherwise be missed. If we go back to our pizza parlor example, traditionally you’d look at the success rates of restaurants in a city of similar size to predict how successful a new restaurant would be. Big Data, on the other hand, could pull in more information to create a more accurate predictive model. Instead of just using success rates for pizza restaurants, analysis of the data might include the number of local professional sports teams, other nearby businesses that help or hurt a restaurant’s sales, the frequency of people posting pictures of their food on Instagram from the area, and local average temperature. All of these elements may influence how our pizza parlor will fair, but would be opaque without the use of Big Data systems and the analysis of that information.

What Does This Mean for Financial Reporting?

As you can see from the previous example, there are many factors that can affect the financial performance of a company, and some of those factors may not be immediately obvious. Just looking at the financial data for a region may not tell you that sales dipped because of an unusual amount of snow that caused clients to stay home from work more frequently and therefore push off purchases for several months. But the analysis of a wide range of data can help you understand what happened and predict what you’ll see going forward. Because Big Data pulls in information from so many places, it would be nearly impossible to spot trends using spreadsheets and simple or traditional reporting techniques. However, when Big Data is combined with other analysis tools like business intelligence and financial dashboard reporting, trends become apparent quickly that would otherwise go unrecognized. Business leaders are able to see the interplay of otherwise disconnected data and the impact it has had on their financials while also creating a more accurate predictive model that can be used in decision making going forward. Competition is fierce in today’s corporate world, and every advantage is needed to stay ahead of the game. The more information you have, the better decisions you can make. Stepping beyond simple “what happened” financial reporting and reviewing performance in a broader scope can provide the insights that drive intelligent decisions and predictions. Big Data pulls in the myriad of data needed to have a complete picture, making financial analysis patterns apparent and actionable.

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