Business intelligence is nothing new, but the way we gather, analyse and make use of this intelligence is changing.
Companies have largely adopted business intelligence tools to answer specific and predictable questions and ensure tracking for key metrics like getting high-level views or sales goals to increase the productivity of the company. However, when it comes to new technology and artificial intelligence tools, traditional BI reporting is losing its significance. In the unpredictable fast-moving business environment and a strong competitive age, achieving a sustainable market is not an easy task. It requires more than the usual BI tools. Companies are becoming more data-driven and adopting modern BI techniques. This shift from traditional BI to data-driven techniques throughout every sphere of business has enabled growing sales, coming out with innovations, boosting production, reducing operating costs and making a valuable position in the industry.
Adopting business monitoring and real-time analytics will not only help manage challenges in a better way but also position the business for growth. Traditional BI provides more retrospective analytics i.e., using data to understand the past to improve future events. But now organizations must adapt quickly to changing conditions. This will help businesses to automate business monitoring and error detection. Traditional BI requires the constant involvement of IT staff and a complex IT system. This system is very slow and ineffective in long run and keeps the power of business data only in the skilled hands. It does not provide businesses with full decision support.
When is it the right time to move beyond traditional BI?
- When people working in the organization do not have access to the same data and do not have a universal view of the businesses.
- When business leaders are unable to innovate and ask new questions without consulting the analytics team to reinvent the wheel.
- Insights that do not reflect a 360-degree view of what is going on in the organization, relevant data sources and factors available in the business.
The data-driven strategy
Businesses are nowadays adopting data-driven decision making. They are using data analytics techniques for their business growth. Though not many organizations have successfully evolved with the change. Still, now companies use BI tools like a spreadsheet for analysis. Companies are trying to cope up with the evolution and struggling with big data analytics. According to a report, only 48.5% of companies could successfully adopt data-driven innovations and only 41.2% are competing on analytics. Though the traditional methods of BI successfully served the business industry now it’s time to look at the big picture.
The continuous Intelligence approach is using real-time analytics for business operations, taking reference from current and historical data to take proper actions for the business welfare. This approach is more flexible and fluid. It helps to look across huge data sources, identify important data points and make connections with business stakeholders during issues demanding further examination. It can be operated at many levels from the supply chain, customer service, fraud detection, and IoT enabled manufacturing. CI can accelerate business values by transforming any process with the most current and relevant data, to guide and automate actions at the right moment and accelerate business outcomes more accurately. The main difference between CI and BI is that one extract data from a different source to determine the right quantity to buy at the right time and the other is simply reporting on basics.
Modern business intelligence
Modern BI offers mainstream tools with flexibility and self-service access so that businesses can create reports and analyses on the fly and share data to get optimized business results. It follows the principle of DataOps and data democratization to offer a continuous stream consumable by business customers. Modern BI provides facilities like support data from legacy systems and hybrid ERP systems and is also cloud-ready to support multi-cloud and hybrid implementation scenarios. It provides the full process for real insights without context or additional information. It is built on real business context from a powerful data model and allows both cross-process and cross-application reporting. It is easy to use and flexible for now and in the future.
Cost-cutting and real-time analytics
Cost-cutting is implemented by companies to reduce their expenses and maximise profit. This method is mainly used during financial distress for a company or economic downturns. This is very crucial in this changing environment. Companies are nowadays using automated processes to solve issues faster with the help of machine learning algorithms to continuously analyse data and detect errors in real-time. BI alone takes too much in detecting errors. The best method is to use vendor solutions that offer the fastest time to value and much higher ROI. The companies are also shifting from pull analytics to push analytics which provides better insights so that proactive measures can be taken immediately. Companies are using automated business monitoring and real-time analytics to effectively manage uncertain business conditions.
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