Why All Businesses Need Data Analytics

How do you define data analytics? Do you know it as compiling numbers to help inform decisions? Or the idea of gathering results in order to make adjustments? If so, you are almost on the right track.

For most businesses, data analytics has become the central aspect of success. It is a common concept where leaders or professionals collect, evaluate, and interpret raw data. They use this information to uncover discrepancies, identify trends, and draw conclusions for a given organization. The main goal is to turn large datasets into actionable insights so that business functions can evolve and progress into the future.

Almost every industry uses some form of data analytics. In the marketing space, data analytics are used to track engagement and audience reach on digital campaigns. For the finance sector, data can be leveraged to study fraud and risk management. And in retail or e-commerce, employees rely heavily on data to understand consumer behavior and manage inventory levels.

While data is critical for every business, many companies still lack the proper understanding of how real data works. For instance, some might collect the numbers, but they ask all the wrong questions to make optimizations. Others might use data platforms to find the information, but they aren’t fully trained to utilize these kinds of applications.

At the same time, another key mistake businesses make is the integration aspect. They may know the data exists, but they resist to acknowledge what the expertise can actually do.

Wendy Lynch, CEO and Founder of Analytic Translator, adds her insight to this: “Every company above 500 employees would benefit from internal analytic expertise about their own business,” she says. “I believe running a company without an integrated data platform is corporate malpractice. It is the same as piloting a plane on a cloudy night without instruments. Perhaps you know the general direction you’re headed and where you hope to land, but you remain under-informed about the current status of the flight or what problems you might have.” 

Without question, data analytics can only help a business. As a recent study reports, nearly 91.9% of companies that invested in data analytics this year gained measurable value. In addition, the overall data market has totaled over $64.75 billion, where 80% of U.S. companies have adopted big data analytics into their operations. 

For businesses to stay ahead of data, it is important to learn not just how to collect and analyze, but to translate wisely. While the information is there, the question now becomes how it is used to drive smarter strategy and better outcomes. 

With over 35 years of experience in business analytics, here’s what Lynch might suggest would help businesses in the long run:

• Invest in people and tools – Data analytics only work if the proper team and resources are in place. Companies need skilled analysts or translators who can help clarify the complex data systems.
• Narrow the experience – Every analytical data point might not be necessary. Businesses should always sift through the exact results they need in order to focus on the organizational goals at large.
• Actively research. Good data comes with the right research to back it up. Before and after you compile your results, ensure to always research what you need, how competitors compare, and what you might do with the given information.
• Encourage the culture – When every employee understands a data-driven approach, it creates accountability and keeps the innovation alive. Having everyone on the same page is key to achieving true results.

Ultimately, data analytics is not simply just another tool for the business. At most, it is an essential practice that allows leaders to see the problems, spot the difference, and make well-informed decisions in the end.

In a world where business is always progressing, recognizing the impact of analytics is the greatest asset everyone needs. When used to its fullest potential, it becomes the best answer to operational survival.