Analytics means extensive use of data, statistical analysis, explanatory and predictive modeling, and fact-based management to derive decisions and actions.
Why analytics? Currently, companies competing in the same industry offer similar kind of products and use comparable technology. High performance business processes are thus the only places where companies can differentiate. Many of the previous bases of differentiation are no longer available. The advantage of unique geographical location no longer matters greatly given the global competition and protective regulations are no longer that strong a deterrent. Proprietary technologies can be copied in no time and breakthrough innovation in products and services is becoming more and more difficult with the passage of time. What is left as the only basis of competition is improving business processes that work, with maximum efficiency and effectiveness and making the right business decisions in shortest time possible. Analytics help the organizations greatly in the pursuit of efficiency and effectiveness of their processes.
What are the business processes where analytics can help? Analytics can support almost any business process. To name a few, customer-based processes like customer segmentation, customer acquisition, customer retention, dynamic pricing, supplier-facing processes like capacity planning and demand-supply matching, financial processes like selecting portfolio of products, credit card scoring and future value analysis, and finally, human resource processes like recruiting and nurturing talents, and selecting and managing vendors.
In its current form, the subject of analytics is cross-disciplinary with inputs coming from the subjects of statistics, computing and management. This programme will provide participants with an overview of the concepts and advanced techniques that are currently being used in business as well as a glimpse of some techniques that have high potential for use in the near future. The sessions will be application oriented with enough hands-on sessions to make the participants get a feel of the techniques.
The following topics will be covered (but will not be limited to) in the programme:
• Clustering Techniques • Data Visualization
• Interactive Graphical Data Analysis • Bayesian Data Analysis
• Analytics for Strategy Formulation • Streaming Data Analysis
• Analytics for Strategy Formulation • Classification Techniques
• Forecasting • Text Mining
• Regression Modeling • Text Mining
The teaching methodology for this programme will be an appropriate mixture of classroom teaching, hands-on experiments, case discussion, identification of best practices, in-class participation, group reading and presentations, guest lectures and panel discussion.
This programme is intended for enabling practitioners, managers and decision-makers to use advanced analytics for better decision-making and to gain in- d depth understanding of these concepts using hands-on technique(s) and by relating to business cases. The programme may also be of interest to participants from various analytics organizations to understand better the underlying concepts of these advanced techniques. An aptitude for quantitative modeling and some prior experience in use of analytics is desirable.