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How Data-Driven Decisions Benefit Business Intelligence

In the last decade, businesses have become adept at analyzing data and using business intelligence (BI) technologies to answer precise but predictable queries. This provides a means of tracking vital metrics like sales targets and allowing high-level views of order statuses across the company. However, BI reporting has become too rigid and slow to be useful to companies operating in today’s uncertain, fast-moving competitive environment. The key to long-term competitive advantage goes beyond traditional measures. This article at Analytics Insight speaks about the importance of business intelligence to remain competitive in a data-driven world.

Data-Driven Decisions Are More Viable Than Traditional BI

In today’s accelerating market, data drives organizations in countless ways. With artificial intelligence (AI) and machine learning (ML), data analytics has renewed its lease on life by becoming a must-have capability for businesses. The new technology and information make business intelligence one of the most critical components of an organization’s progress and growth. Thanks to digitalization and big data, today’s enterprises have access to all the data they need. As a result, you are now able to make data-driven decisions that deliver better results and support the growth and evolution of your business.

Insights from actionable data enable you to make better-informed decisions. Compared to conclusions based on intuition and beliefs, data-driven decisions have a much higher likelihood of success.

Data-driven decisions are more viable and render opportunities to excel and expand in the changing risk landscape. Data is now one of the most prized assets for any business. To optimize the use of data, you must adopt and encourage a data-driven culture within your organization.

Data Decisions to Support Business Intelligence

  • Do not make decisions based on beliefs, bias, and intuitions because they are limited to personal experience.
  • Define your objective and metrics clearly to analyze data efficiently.
  • Ensure the data collected is used to make relevant decisions.
  • Know the right questions to get the right insights from data.

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