Why Isn’t Traditional Business Intelligence Enough Today?

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Business intelligence is nothing new, but we gather, analyze, and use it is changing.

Businesses have adopted mainly business intelligence tools to answer specific and predictable questions and track key metrics like high-level views or sales goals to increase productivity. With the development of new technology and artificial intelligence tools, traditional BI reporting is losing its importance. Due to the unpredictable, fast-moving environment of business and strong competition. Business intelligence tools are not enough. Companies are adopting modern BI techniques and becoming more data-driven. The shift from traditional business intelligence to data-driven techniques across all spheres of business has enabled businesses to expand sales, come up with new innovations, boost production, reduce operating costs, and establish a valuable position in the market.

Business monitoring and real-time analytics will help businesses manage challenges in a better way and position them for growth. BI provides more retroactive analytics, i.e., using past events to improve the future. Today, organizations must adapt quickly to changing conditions. Businesses will be able to automate business monitoring and error detection. BI traditionally relies on constant IT involvement and a complex IT system. In the long run, this system is slow and ineffective, and it keeps business data in the hands of only a few skilled individuals. Businesses are not provided with full decision support.

 

When is the best time to move beyond traditional business intelligence?

  • When people working in the corporate do not have access to the same data and do not have a shared view of the business.
  • When corporate leaders are unable to innovate and ask new questions without consulting the analytics team.
  • Information that does not reflect a 360-degree view of the organization, relevant data sources, and other factors available to the business.

 

The data-driven strategy

Nowadays, companies are adopting data-driven decision making. They use data analytics techniques to grow their businesses. However, not all companies have been able to adapt to the changes. Many companies still use spreadsheets for analysis. Businesses are trying to keep up with the evolution and deal with big data analytics. Only 48.5% of companies successfully adopted data-driven innovations in a report, and only 41.2% compete on analytics. The traditional methods of BI have successfully served the business industry. Now it’s time to consider the big picture.

 

Continuous Intelligence

By using continuous Intelligence, business operations can be analyzed in real-time, using current and historical data to take appropriate actions for the welfare of the business. Using this approach is more flexible and fluid. During issues requiring further investigation, it helps to traverse huge data sources, identify important data points, and connect with business stakeholders. The system can be used on many levels, including supply chain management, customer service, fraud detection, and IoT-enabled manufacturing. CI can accelerate business value by transforming any process with the most current and relevant data, guiding and automating actions at the right time to accelerate business outcomes. Between CI and BI, one extracts data from a different source to determine the right amount to purchase at the right time, while the other simply reports on basic information.

 

Modern business intelligence

Modern BI offers mainstream tools that are flexible and self-service accessible, so businesses can build reports and analyses on the fly and exchange data to optimize results. DataOps and data democratization are used to offer a continuous stream of information consumable by businesses. In addition to supporting data from legacy systems and hybrid ERP systems, modern BI is also cloud-ready for multi-cloud and hybrid implementation scenarios. The full process is available without context or additional information. In addition to supporting cross-process and cross-application reporting, it is built on a powerful data model that provides real business context. It is easy to use and flexible, both today and in the future.

 

Cost-cutting and real-time analytics

Companies implement cost-cutting practices to reduce expenses and maximize profit. The method is primarily used during economic downturns or when a company is in financial distress. To manage uncertain business conditions effectively, companies use automated business monitoring and real-time analytics. In a changing environment, this is extremely important. Today, many companies use automated processes to solve problems faster with the help of machine learning algorithms that analyze data continuously and detect errors in real-time. Business intelligence alone takes too long to detect errors. The best method is to use vendor solutions that provide the fastest time to value and a much higher return on investment. Moreover, companies are shifting from traditional pull analytics to push analytics, which provides better insights so that proactive measures can be taken right away.

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