Why Every Major Business Decision Must Be Backed By Big Data

4 min read
Curated from jeffbullas.com →

One of America’s most famous media proprietors, actresses and philanthropists, often attributes her success to following her gut feelings. According to her website, “Learning to trust your instincts, using your intuitive sense of what’s best for you, is paramount for any lasting success.”

Overall, she claims that trusting her gut more than anyone else’s opinion is one of the largest contributors to her success.

Can you guess who this woman is? More importantly, do you think that her claim is fair?

This woman is none other than Oprah Winfrey, and according to experts, her belief might be a little short-sided.

A gut feeling is something you intuitively accept and believe. The thought seems so undeniably true that it often influences your decisions automatically. If you’ve ever made a decision for your business based on a feeling rather than an objective measure, you’ve made a gut decision.

In general, gut feelings are pretty good at guiding simple everyday decisions – like what to wear. That being said, industry experts suggest that using gut feelings to guide big decisions can be extremely dangerous.

In the long run, every important decision you make – whether it’s in your personal or professional life – should be backed by data and logic, not just emotions or gut feelings.

Below, you’ll learn why every major business decision must be backed by data. This article will also provide five tried-and-true steps that you can implement in your daily work to make more data-driven decisions.

According to VisualCue, a Big Data visualization tool, almost every company has valuable data at their fingertips – it’s just difficult to connect the dots in the data. For example, if your business has a website or a social media presence, it harnesses data that can help improve its operations.

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One of the main ways companies use data is to learn more about their customers. Thanks to Big Data, it’s easy for companies to get better insights into what their customers want, what they will use and how they will complete future purchases.

Data can also be used to improve a company’s internal operations. Simply put, if you want to improve the way your company ships its goods, you can look to Big Data for help.

The first step to making data-backed decisions is to identify your goals. You might be interested in using data to look for new leads. Alternatively, you might want to use data to improve your customer churn rates. No matter what you are using it for, there is sure to be an area of operation where data can help you run a more efficient business.

Take a few moments and outline three to five business objectives and build a strategy around them. Search the internet or reach out to a data visualization company that can help you understand what data you’ll need to analyze to inform your objectives.

After you understand what data you need, identify where it can be found. Data flows from all directions, so you’ll need to evaluate every source of data to understand which areas will bring the most benefit.

During this step, you might also consider adding in new data collection procedures. For example, if your company is trying to improve your customer experience, you might want to start using a customer relationship management tool that can help inform your insights.

The third step is to decide who will work on this project. If your project relies on simple analytics that can be easily managed in Excel, you can feel confident completing the project in-house. If your data requires more in-depth analytics or you need help connecting all of your data sources, you might want to work with a third-party software as a service provider.

To complete this project in-house, you’ll need to start by identifying key players that’ll move the project along. These individuals will most likely be department heads.

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Yves Mulkers

Yves Mulkers is the founder of 7wData and a widely followed voice in the data and AI community. He curates the 7wData and AI Beat newsletters, reaching hundreds of thousands of data and AI professionals, and writes on data strategy, analytics, AI, and the evolving data ecosystem.