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Predictive Analysis: In & Out

By SiliconIndia   |   Thursday, 21 February 2013, 07:16 Hrs
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Bangalore: Predictive analysis is the thorough analysis of data accumulated; extracting information from that analysis and inferring the trends and patterns. In simpler words it helps an organization to help predict the future through thorough analysis of the past. Yan Krupnik on Supply demand-chain has pointed out that global business technology research group IDC (international data center) Manufacturing; the advanced business analytics market grew to a $31.7 billion market since 2010. Predictive analysis is indeed the present and future of any business.

In this era, every aspect of business is being registered and comes in the form of data. These data includes statistics, expenditures, investments, consumer behavior, point of sale data, prices of the goods, and foresights. But mere collection of this data is futile. This data should be utilized to make further decisions which turn out to be lucrative. The entire focus should be on making smarter decisions and help the organization on cost cutting through in depth analysis. This is when predictive analysis plays the key role. Extracting some real value from the available data and turn it into something fruitful.

This predictive analysis is worth comparing to the traditional business intelligence tools. Traditional business tools such as spreadsheets, reports, queries etc. sure these tools also have some importance but the basic difference lies in the methodology and the outcome. The traditional tools helps in the insight of what happened and what went for or against the campaign/product/agenda, whereas predictive analysis gives a foresight, reading the old behavior pattern. The latter does not only help but also somehow gives the courage to take risks and certain decisions by scrutiny of the existing data.

Predictive analysis is utilized in the field of retail, banking, marketing, social media, restaurants etc, but this particular phenomenon will only be useful if the software utilized to collect the data is industry specific. If the data collecting tools commemorate the data which is not industry specific, then the predictive analysis will obviously be faulty or will have loopholes. This rather than being useful might turn disastrous. One should be very careful while picking up the software vendors. They should provide software which is specific to the industry and as a buyer its one duty to make them understand the nature of one’s business and the precise requirements.

Yan Krupnik also says that the businesses using predictive analysis experienced inventory reduction of cost up to 40%. Predictive analysis also helps in assorting and optimizing the prices and reduces over production or acute production, giving estimation, thus helping in reducing the loss of manufacturing in excess, basically monitoring the previous demands. This improves customer service, gives an understanding of demands and proves extremely favorable in the marketing related business.


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