Self Paced Courses Operations and Decision Sciences

Analytics for Business Problem Solving

This course intends to expose learners to (managing) the art of building relevant business insights from the analysis of large numeric databases using numerous statistical and search tools.

Prof Arindam BanerjeeProf Tathagata Bandyopadhyay

Description

This course intends to expose learners to (managing) the art of building relevant business insights from the analysis of a large numeric databases using numerous statistical and search tools.

The emphasis of the programme will be more on discussing relevant issues of managing analytic functions and developing appreciation for data analytics/research among practitioners. While knowledge of specific statistical (and search) tools will be disseminated as part of the overall objective of the programme, it will not be enough to build expert knowledge of the same.

Why Should You Attend?

Learners will benefit from this course if they encounter some or any of the following situation(s) at work:

(i) If you are concerned about how to use customer and competitor information to effectively drive your marketing initiatives and would like to develop a suitable internal process within your organisation to do so

(ii) If you are interested in issues such as: a) identifying customer segments from data, b) measuring the effectiveness of your marketing initiatives, c) Marketing Mix Planning d) appreciating demand projections, e) optimising the communications budget, f) estimating/ forecasting impacts of alternative marketing plans, etc. through a process of collection and analysis of relevant data

(iii) If you are interested in redesigning your ongoing research to make it more useful for business decision-making

(iv) If you want to develop/refresh your understanding of basic statistical conceptss, some relevant data analytic tools and their applications

(v) If you are interested in the latest issues in analytics practice – big data and its future

Course Content

Course Introduction

Lecture 1: The Role of Analytics in Business Decision Making Part 1

Lecture 2: The Role of Analytics in Business Decision Making Part 2

Lecture 3: Catching Up On Basic Statistics: The Bare Necessities

Lecture 4: More Statistics to Make you an 'Expert'

Lecture 5: How to Connect Business Problems to Analytics?

Lecture 6: Try your Hands at Connecting Business Problems to Analytics

Lecture 7: Managing Pilots: When No Data is Available

Lecture 8: How to Evaluate Analytics (Prediction) Models and their Impact on Business? : Part 1

Lecture 9: How to Evaluate Analytics (Prediction) Models and their Impact on Business? : Part 2

Lecture 10: Catch Up: Basic Concepts of Regression: Part 1

Lecture 11: Catch Up: Basic Concepts of Regression: Part 2

Lecture 12: Catch Up: Basic Concepts of Regression: Part 3

Lecture 13: Applying Regression to a Business Problem: Explaining vs Predicting: Part 1

Lecture 14: Applying Regression to a Business Problem: Explaining vs Predicting: Part 2

Lecture 15: Catch Up: Forecasting and Basics of Time Series Data: Part 1

Lecture 16: Catch Up: Forecasting and Basics of Time Series Data: Part 2

Lecture 17: Qualitative Dependent Variable: Logistic Regression

Lecture 18: Machine Learning Review: Support Vector Machines

Lecture 19: Survival Analysis: Time Based Prediction of an Abrupt Event

Lecture 20: Packaging Insights into Story Telling: Tips in Logical Business Communication

Lecture 21: Unsupervised Search: Exploratory Analysis and its Applications: Part 1

Lecture 22: Unsupervised Search: Exploratory Analysis and its Applications: Part 2

Lecture 23: Social Media Data and Research : Introductions: Part 1

Lecture 24: Social Media Data and Research : Introductions: Part 2

Course Summary

Recommended Reading

This course is open to decision-makers, researchers, analytics professionals and students. It is relevant to domains such as FMCG, Consumer Durables, Consumer Financial Services, Insurance, Banking, Retailing etc.

Prof Arindam Banerjee

Arindam Banerjee joined the faculty at IIM Ahmedabad after working in industry for over seven years. He has worked on business problems in retail financial services, FMCG and consumer durable sectors. He specialises in developing business models based on the statistical analysis of large syndicated databases

For the past 20+ years at IIMA, he has taught courses in Quantitative Marketing and Research Methodology to post graduate and doctoral students. Besides, he has worked extensively with various Indian and global business organisations in building and strengthening internal processes to support “fact-based decision-making.” He has also imparted training in various in-house corporate management development initiatives. Recently, he has also worked as a mentor to a Marketing & Sales Analytics team of a global Management Consulting firm

He has published papers in several academic journals in management such as the Journal of Segmentation in Marketing, International Journal of Retail and Distribution Management, International Journal of Management and Decision Making, Asian Journal of Marketing, Asia-Pacific Journal of Marketing and Logistics, Strategic Outsourcing: An International Journal, Vikalpa and Decision.Prior to joining IIMA, he was a senior consultant at Mitchell Madison Group, a global management consultancy firm specialising in the financial services sector and was based at their Chicago office. Previously, he was at AC Nielsen(Chicago) where he headed a marketing analytics team that provided marketing support to Philip Morris Inc. In the year 2006-07, he took leave from IIMA for setting up a global risk analytics team at HSBC for the bank’s US-based consumer and mortgage lending business. He is currently a Professor in the Marketing Area at IIMA

Prof Tathagata Bandyopadhyay

Tathagata Bandyopadhyay joined IIM Ahmedabad as a faculty member in the Production and Quantitative Methods Area in 2005. Prior to joining IIMA, he taught at the Department of Statistics, University of Calcutta, India for around two decades.

At IIMA, he has been teaching quantitative techniques in the post graduate programme; research methodology, advanced probability for management and applied multivariate analysis in the doctoral programme. He has also taught in executive development programmes for companies like Indian Oil Corporation, Life Insurance Corporation of India, Monsanto, Larsen & Toubro, Cummins, City Bank, Coca Cola, Aviva etc. He has also coordinated management development programmes on analytics and global General Management Programmes for IIMA.

His research interests are varied but mainly in the realm of statistics and its applications to different fields. He has published papers in various national and international journals like Journal of the American Statistical Association, Biometrika, Annals of Applied Statistics, Statistical Science, Annals of the Institute of Statistical Mathematics, Journal of Statistical Planning and Inference, Statistics in Medicine and Biometrical Journal. He has visited and taught in various universities in the US, Canada, the UK, Sweden, and Singapore. He is now the Editor of the Calcutta Statistical Association Bulletin, the co-editor of Sankhya, Journal of the Indian Society of Agricultural Statistics and Vikalpa.

A learning path with Online@IIMA is adaptable, individualized and multifaceted. It is designed to foster an ecosystem where the learner will be capable of connecting micro modules to the core specialization - weaving the entire experience into a thorough learning opportunity towards a productive output or building sustainable solutions.

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  • Skill Level Intermediate
  • Language English
  • Certificate No
  • FeesFree
  • Start Date 19 Jun 2024
  • Duration 24 Lectures

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