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Data Analytics in Business

Written By: David Lieberman

Today Analytics is the heart of a Business. Companies are challenged with a high volume and broad array of data which requires active and effective analysis. Analysis can help them make enhanced and improved business decisions, and hence help the business to maintain profitability. “Companies need to compete on the basis of key business processes, and how they optimize these processes with analytics,” says Thomas Davenport, professor, and director of research, Babson College, USA. Business analytics means simply to resolve business issues by applying the appropriate analytical techniques on the available business data. However, a practical definition would be how a business arrives at an optimal or realistic decision based on existing data.

Data Analytics is the technology to leverage the business data in order to make keener decisions which can be helpful in solving operational and managerial problems in a well-organized and productive manner. Nowadays, sectors such as telecom, retail, healthcare, and finance are investing heavily in analytics to stay ahead of the competition. For example, the Telecom Industry uses Analytics for Proactive Network Monitoring, Capacity Planning, Revenue Assurance, Subscriber Profiling, Social Network Modeling and Analysis, Personalized Advertising and Churn Management.

The Retail Industry uses analytics and Business Intelligence for Assortment Optimization and Shelf Space Allocation, Customer-Driven Marketing, Fraud Detection and Prevention, Integrated Forecasting, Localization and Clustering, Marketing Mix Modeling, Pricing Optimization, Product Recommendation, Supply Chain Analytics etc.

Analytics benefits all below-listed aspects of an organizations value chain:

  • Production: Production analysis can be used to analyze the production process. Using production analysis, material wastage can be reduced, production process time will be reduced and production alignment can also be done according to demand.
  • Sales: Sales forecasting can be used to set the sales targets and aligning production.
  • Marketing: Marketing Analysis can be used to analyze and predict the success of any marketing campaigns and promotional campaigns, to evaluate the marketing mix etc.
  • Product: Product Analysis can be used to identify the most likely product attributes for customers and can also be used for market basket analysis.
  • Finance: Risk analysis can be used in banking and finance industries. Financial analysis can be used for budgeting, cost-cutting, investment guidelines etc.
  • Logistics and Supply chain: Supply chain analysis can be used to keep a track on inventory and it can also be used for purchase guidelines.
  • Ecommerce: Web Analytics can be helpful to online business through understanding and optimizing customer experience to maximize the conversion ratio.

Author Bio:

David Lieberman, works as the president of https://planetofhotels.com/en. As one of the founding members of Planetofhotels, he has helped the company from its initial concept into the leading hotel reservation services. Also, he is a technology investor and advisor, helping companies and entrepreneurs with their projects and sites.

One comment on “Data Analytics in Business”

  1. Subarna

    Great content as usual.Thank you so much.

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Andre Bourque (SocialMarketingFella) is Editor Emeritus of Technorati.

He covers emerging trends and news in social, mobile, cloud, and related technologies.

Based in San Francisco, he can be contacted via his social channels and at: andrefbourque@gmail.com

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