Advanced Analytics for Management

Start Date:Jan 13, 2020 End Date:Jan 18, 2020
Last Date for Application:December 30, 2019 Last Date for Early Bird:December 23, 2019
Programme Fee: 140000 INR

Plus, GST

Early Bird Fee:130200 INR

Plus, GST

Pay Now

Analytics involves extensive use of data, statistical analysis, predictive modeling, and fact-based organisational culture to drive 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, processes or services is becoming more difficult with the passage of time. What is left as the only basis of competition is constant improvement of business processes 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 state, 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 give a glimpse of some techniques that have high potential for use in the near future. The sessions will be application oriented with case studies and 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
  • Classification Techniques
  • Forecasting
  • Text Mining
  • Regression Modeling
  • Data Visualization
  • Bayesian Data Analysis
  • Analytics for Strategy Formulation
  • Selected Advanced Topics

This programme is intended for enabling practitioners, managers and decision-makers to use advanced analytics for better decision-making and to gain in-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.

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.

Faculty Chair

Arnab Laha

Programme Faculty



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