Business Tools,  Finance,  Management

How Your Business Can Benefit from the Big Data of Finance

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There is a ton of big data out there and nearly every business is being affected by the gathering and analysis of this data. The impact varies from data gathered by the internet of things (IoT) to industry and enterprise data, social listening, and more. However, there is another data set out there, the big data of finance.

What is this data set made up of? The catchphrase “big data” refers to large sets of data that require extensive computing power to gather, store, and analyze. However, with the increasing volume of data created by consumers has come the power of cloud computing, meaning even small businesses can take advantage of this data without having to create a huge computing infrastructure of their own. Larger businesses have the advantage of their own information systems management teams, which means they can use proprietary software and analysis not available to smaller businesses.

Financial data includes customer spending and credit behavior, employee efficiency data, investment and market trends, and industry predictions that can be applied to individual businesses. Beyond these areas, there are applications in financial consulting and accounting that are revolutionizing the industry and allowing smaller firms to legitimately compete with the big four financial accounting firms.

How can your business take advantage of this data, even if you are not in the financial sector? Here are some tips about each type of data and how it can affect nearly any company.

Consumer Credit and Customer Behavior

For many years, one of the primary numbers lenders and companies were concerned with when it came to customers was their credit score. But today’s credit evaluation goes far beyond that, with companies like LendUp looking at things like social interaction online and whether a consumer has recently changed phone numbers. Those with more social connections and higher interaction tend to be better risks.

Other credit behaviors are also tracked in the set of financial big data and can be used so that lenders can go far beyond the credit score to make a reasonable determination. If your business offers in-house financing or branded credit cards, this data can be an invaluable tool.

More than just consumer financial behavior is revealed in big data, but other customer behavior as well: when they buy, when and how they borrow, and even how much they shop around before making a purchase. This customer behavior, both individual and taken as a consumer group, can reveal the reason for seasonal trends and even inspire marketers on how to reach more consumers during traditionally slow periods.

Employee Monitoring and Personnel Management

How efficient are your employees? When and where are lulls in performance and what can be done to correct or modify them? When are sales slower, and what does that have to do with employee behavior? All this can be monitored using the big data of finance and tracking sales patterns on a much smaller scale than we once did.

For instance, instead of tracking monthly, weekly, or even daily sales and employee activity, we can track it by the hour or in even smaller increments. You might see that sales dip Friday afternoon when employees are ready to go home, but rise at the end of the pay period when they are trying to maximize commissions or meet quotas set for them.

The point is that big data makes this tracking and analysis possible but also gives your company actionable data. This data helps you improve user experience by having the right staff on hand and the computing power to handle surges in online traffic. This improvement of user experience is often what gives companies an edge, especially in price competitive fields.

This can also help you determine the cause of lull times: perhaps it is consumer behavior, not employee behavior that better determines revenue during certain periods. The big data of finance helps you track both employee and consumer behavior and informs your personnel management strategy.

Investment Decision Making

One sure way to grow your company and increase revenue is informed investment in the right things at the right time. One of the biggest pieces of financial big data is historical and current market data that can be used to predict trends. This predictive analytics can provide some peace of mind when considering when and how to invest company profits.

On the flip side, big data does not just help predict market behaviors, but also investor behavior. This can help determine when investors are most open to stock purchases, and therefore how to time initial public offerings and other stock releases to achieve the ideal outcome.

Predictive analytics even allows companies to run various market scenarios through computer models, helping them make more sound financial decisions. This can include following pricing trends in raw materials and timing inventory purchases accordingly.

Income Projections and Debt Management

While some industries are seasonal, and income projections are fairly simple, the truth is that nearly any business goes through income and sales slumps and peaks throughout the year. Projecting income and, more importantly, cash flow, are essential to business planning. Big data can help with more than just enterprise data from your business, but industry data as well.

These income projections can help you when it comes to writing the best business plan to secure funding from a variety of sources. They can include venture capital or even small business loans.

The big data of finance is just one of the sets of information that can benefit your business in customer service, employee management, various investment decisions, and in calculating income and debt management. Used wisely, big data can be the key to taking your business to the next level.

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Brooke Faulkner is a writer, professional ponderer, and proud momma of two from the Pacific Northwest. When she's not at her desk, she's likely to be found zipping around on her old ATV. You can follow her on LinkedIn.

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