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Indian Institute of Management Bangalore

Business Analytics – the Science of Data Driven Decision Making

★★★★4.0 • 1 review


The theory of bounded rationality proposed by Nobel Laureate Herbert Simon is evermore significant today with increasing complexity of the business problems; limited ability of human mind to analyze the alternative solutions and the limited time available for decision making. Introduction of Enterprise Resource Planning (ERP) systems has ensured availability of data in many organizations; however, traditional ERP systems lacked data analysis capabilities that can assist the management in decision making. Business Analytics is a set of techniques and processes that can be used to analyse data to improve business performance through fact-based decision-making. Business Analytics is the subset of Business Intelligence, which creates capabilities for companies to compete in the market effectively. Business Analytics is likely to become one of the main functional areas in most companies. Analytics companies develop the ability to support their decisions through analytic reasoning using variety of statistical and mathematical techniques. Thomas Devonport in his book titled, "Competing on analytics: The new science of winning", claims that a significant proportion of highperformance companies have high analytical skills among their personnel.

In a recent article1 based on a survey of nearly 3000 executives, MIT Sloan Management Review reported that there is striking correlation between an organization's analytics sophistication and its competitive performance. The biggest obstacle to adopting analytics is the lack of knowhow about using it to improve business performance. Business Analytics uses statistical, operations research and management tools to drive business performance. Many companies offer similar kind of products and services to customers based on similar design and technology and find it difficult to differentiate their product/service from their competitors. However, companies such as Amazon, Google, HP, Netflix, Proctor and Gamble and Capital One uses analytics as competitive strategy. Business Analytics helps companies to find the most profitable customer and allows them to justify their marketing effort, especially when the competition is very high. There is a significant evidence from the corporate world that the ability to make better decisions improves with analytical skills


The course is designed to provide in-depth knowledge of handling data and Business Analytics tools that can be used for fact-based decision-making using real case studies. Primary objectives of the course are:

  • Understand the emergence of business analytics as a competitive strategy.
  • Analyse data using statistical and data mining techniques and understand relationships between the underlying business processes of an organization.
  • Learn data visualization and storytelling through data.
  • Learn decision-making tools/Operations Research techniques.
  • Use advanced analytical tools to analyse complex problems under uncertainty.
  • Use analytics in customer requirement analysis, general management, marketing, finance, operations and supply chain management.
  • Analyse and solve problems from different industries such as manufacturing, service, retail, software, banking and finance, sports, pharmaceutical, aerospace etc.
  • hands on experience with software such as Microsoft Excel, Evolver, LINDO, Qlikview, SAS Enterprise Miner, SPSS, R, @RISK and other proprietary software.

Who should attend

Anyone who is looking for “sexiest job” should attend this course. This short-duration programme will equip the participants with analytical tools and prepare them for corporate roles in analytics based consulting in marketing, operations, supply chain management, finance, insurance and general management in various industries. The course is suitable for those who are already working in analytics to enhance their knowledge as well as for those with analytical aptitude and would like to start new career in analytics.


U Dinesh Kumar’s research interest includes Business Analytics and Big Data, Artificial Intelligence, Machine Learning, Deep Learning Algorithms, Stochastic models (Reinforcement Learning Algorithms), Reliability, Optimization, Six Sigma and Performance Based Logistics. He has published several r...


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