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A wily banker in the mid-1800s made it a point to gain knowledge of political instabilities in Europe and thereby predicted the market. During his time, Sir Henry Furnese became successful and infamous for his corrupt practices. However, his deals were recorded by Richard Millar Devens as “a train of business intelligence”. You would ask why? The idea and the concept of using <keyword id="6355729" type="ORGANIZATION" weightage="20" keywordseo="data">data</keyword> to gain an advantage over competition, is still in vogue and gaining ground. It has travelled from using data on computers, to floppy disks (where data could travel), to the internet and the cloud. Currently, the BI as it is now called, uses AI and ML to make the reams of data and make it available to decision makers who no longer need to depend on instinct alone. Today, small and large businesses use BI across a variety of uses - be it to predict what and when an e-commerce customer will buy next, to where elephants are roaming in a national park to ‘visualize’ the health status of a patient and much more. The importance of BI, as businesses are digitizing their operations. BI has evolved from hardware to a network to application to <keyword id="6359249" type="UNKNOWN" weightage="20" keywordseo="Analytics">analytics</keyword> and finally intelligent systems, that are assisted by AI. Currently, we are between the application and analytics stage, In spite of the endless promise, a number of BI adoptions have not produced the desired results. This reflects more about the way most traditional businesses work, rather than the <keyword id="6355118" type="UNKNOWN" weightage="20" keywordseo="technology">technology</keyword> itself, since most departments within a company refuse to share data, that creates silos, which breaks the philosophy of BI to - democratize data. The IT departments become proprietary owners of data. To break these walls, the technology too evolved from technical BI to self-service BI wherein sales teams, product development teams, marketing teams access BI for their daily decision making. The objective of self-service BI is to provide rights to data usage along with responsibilities. However, in reality, organizations need to train their staff adequately for this to be successful. When this is achieved, it would be easier to collect data from sources all across the organization as well. The ultimate goal is to enable end-user BI wherein every user can access BI without having to go through an engineering team. “The trends in BI that point to end user BI are Auto Narratives where insights/outcomes are delivered in natural language; BI Bots where users can ask and receive insights from specialized bots; mobile analytics – which can provide insights all day, all year; Collaborative BI where users collaborate on BI platforms to gain insights; and Data governance which ensure data data quality for unstructured data,” informed Abhishek Rungta, Founder and CEO of <keyword id="2938697" type="COMPANY" weightage="20" keywordseo="IndusNet-Technologies">Indusnet Technologies</keyword>. The business of intelligence The magic word that has made BI even more intelligent is AI. The confluence of both technologies is where computer intelligence meets business decision making. It is very important for companies to move and use data. “In most cases, 70% of data is never used by companies. There are riches in niches, and data can help you explore those niches or hidden gems within the company in different contexts.” Added Abhishek Rungta The key to achieving this at an organizational level is to automate the entire process of data gathering to prepare models and insights and the operational part. This is achieved by augmented intelligence where the functionality is added to the platform, to create what is now being called a ‘data story’. The ‘data story’ needs to make immediate sense. <keyword id="2220047" type="COMPANY" weightage="20" keywordseo="Indus-Net-Technologies">Indus Net Technologies</keyword> is focusing on predictive analytics, which uses data mining, modeling, and machine learning to determine the probability of future outcomes. With these <a href="https://www.indusnet.co.in/how-analytics-is-helping-insurance-companies-in-detecting-claim-frauds/?utm_source=prnewswire.com&amp;utm_medium=paid&amp;utm_campaign=press-release">predictive analytics</a>, healthcare companies are able to deliver personalised healthcare, with focus on individual patients and a greater understanding of trends for larger cohorts.The applications here extend to the financial world too, with banks having greater outlook in designing market specific products, where business performance is predicted to a high degree of accuracy, while delivering a keener understanding of risks involved and preventing fraud. <keyword id="6372399" type="PERSON" weightage="20" keywordseo="mckinsey">McKinsey</keyword>, in their Insurance 2030 report predicts that by <a href="https://www.mckinsey.com/industries/financial-services/our-insights/rewriting-the-rules-digital-and-ai-powered-underwriting-in-life-insurance">In 2030, underwriting as we know it today ceases to exist</a> with a majority of underwriting being automated owing to intelligence. AI and BI can come together to build a truly intelligent business where all its processes are guided data and its management. Apart from capturing data, analyzing it and help create decision making models and empowering employees with data, it can go many steps further. For one, the systems can be taught to ‘learn’ decision making via machine learning and lead to assisted intelligence that can shift the direction of a business and how it successful it can be. DISCLAIMER: This is a sponsored article in partnership with Indus Net Technologies.

Business Intelligence: How far and deep can it go to change the way organisations work?

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Business Intelligence: How far and deep can it go to change the way organisations work?

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