Senior Management Programme In Business Analytics

IIM Calcutta has designed the Senior Management Programme in Business Analytics to equip senior managers with the ability to craft and implement an analytics strategy for their business.

The Senior Management Programme in Business Analytics (SMPBA) is an intensive, 9-month, multi-modular, programme with face-to-face sessions at IIM Calcutta and includes a global immersion session at the Cambridge Judge Business School Executive Education.

The learning journey includes in-class sessions, taught by faculty from IIM Calcutta and Cambridge Judge Business School.

Key Benefits

  • Participants who successfully complete the programme receive IIM Calcutta Executive Education alumni status.
  • Identify the applications of analytics in your organisation.
  • Supervise the implementation of analytics projects.
  • Direct analytics teams on the tools and techniques to adopt.
  • Consider the ethical and regulatory issues involved while harnessing the power of analytics.
  • Compare your organisation's approach to analytics versus the best analytics practices across industries.

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    We are closely monitoring the ongoing COVID-19 pandemic. As the situation continues to change rapidly, the health, safety and well-being of the entire community is of paramount importance to us. We are committed to providing you with the most current information available about the program. Our aim is to ensure the academic integrity and learning experience of the program that you are applying for.

    Participant Profiles

    • Minimum ten years work experience.
    • Must be currently employed.
    • A minimum of 50% in graduation/post-graduation.
    • Confident fluency in written and spoken English.

    Program Curriculum

    • The business value of data analytics

      • Analytics readiness of an organisation and building a data-driven decision making culture
      • Building organisational capability for making use of analytics
      • Appreciating the emerging nature of competition and the role of business analytics
    • Statistics for analytics

      • The art of summarising data and statistical learning in decision- making
      • Applied probability and decision-making under uncertainty
      • Regression techniques and the art of capturing relationships among variables of interest
      • Data sampling and the art of inferring about the population from samples
    • Data sources

      • RDBMS, unstructured data and other forms of data
      • Data extraction and cleaning
      • Dimensionality and outlier analysis
    • Descriptive analytics

      • Appreciation of analytical reasoning and empirical findings from data
      • Challenges in data visualisation and data interpretation
      • Interpretation of raw data
      • Interpretation of statistical summary of data
    • Experimentation

      • Identifying a business problem
      • Creating a hypothesis to solve the business problem
      • Defining parameters that validate the hypothesis
      • Testing the hypothesis through analysis
      • Interpreting the results of the analysis
    • Predictive analytics

      • Business forecasting principles and issues
      • Artificial Intelligence and Machine Learning in decision-making – the role of supervised learning
      • Role of supervised and unsupervised learning in decision-making
      • Time series analysis based decision-making
      • Combining human expertise with data-driven intelligence for decision-making
      • Artificial neural network and deep learning in decision-making
    • Prescriptive analytics

      • Learning through simulation and games
      • Individual and group decision making issues
      • Use of discrete optimisation concepts in decision-making
      • Insights from game-theoretic situations, network externalities and network effect on the economy,
      • Information cascade effects in decision-making
    • Global perspectives of business analytics

      • Business analytics case studies from Europe, North America, China, Japan, Asia
      • GDPR and emerging data privacy laws and concerns across the globe
      • Data security concerns and best practices across the globe
    Note: The list of topics is not exhaustive and is subject to change.

    • Prof. Peeyush Mehta - IIMC faculty

      Prof. Peeyush Mehta - IIMC faculty

      Programme Director & Professor

      Operations Management Group, IIM Calcutta

      Professor Peeyush Mehta has a Ph.D. from IIM Ahmedabad. He has been a faculty at IIM Calcutta, IIT Kanpur and has been a Research Fellow at the Singapore-MIT Alliance at Nanyang Technological University, Singapore. His research interests are in Supply Chain, Game Theory and Manufacturing Strategy.

    • Prof. Uttam Kumar Sarkar - IIMC faculty

      Prof. Uttam Kumar Sarkar - IIMC faculty

      Programme Director & Professor

      Management Information Systems Group, IIM Calcutta

      Professor Uttam Kumar Sarkar has a Ph.D. from IIT Kharagpur. He has been faculty at Jadavpur University, IIT Delhi, IIM Calcutta and at the University of Miami. His research interests include Machine Learning, Social Networks Analysis, Artificial Intelligence and Discrete Optimisation.

    • Dr. Nektarios Oraiopoulos - CJBSEE Faculty

      Dr. Nektarios Oraiopoulos - CJBSEE Faculty

      University Lecturer in Operations Management

      Director of the MPhil in Strategy, Marketing & Operations Programme

      Dr. Oraiopoulos earned his PhD from Georgia Institute of Technology. His research is focused on understanding how organisations make high-stakes decisions, such as whether to invest in a new project, when to terminate a project that is not performing well, what data they can leverage to become more innovative, and what organisational structures they should put in place to empower a sound decision-making process. He has worked with organisations across various industries and sectors, including AstraZeneca, British Telecom, HSBC, Johnson & Johnson, and the Abu Dhabi Police Force.

    • Dr. David Stillwell - CJBSEE Faculty

      Dr. David Stillwell - CJBSEE Faculty

      University Lecturer in Big Data Analytics & Quantitative Social Science

      Academic Director of the Psychometrics Centre

      David studies the links between big data and psychology; his research with 6 million social media users found that the computer can predict a user’s personality as accurately as their spouse can. Follow up research found that personalizing an advert to the recipient’s psychology is more effective than generic ads.

      David has also published research using various big data sources to show that spending money on products and services that match one’s personality leads to greater life satisfaction, that people tend to date others who have a similar personality, and that people who swear seem to be more honest. David is currently pursuing research with companies’ internal data for People Analytics.

    Dates & Fees

    Dates Length Location Tuition Fees

    System Requirements

    This programme includes live online classes. To attend a live online class you will need to have a PC/Laptop/Mac with
    • Speakers and microphone: built-in or a USB plug-in or wireless Bluetooth
    • Webcam: built-in or USB plug-in
    • Processor: with Dual Core 2Ghz or higher (i3/i5/i7 or AMD equivalent)
    • RAM: 4 GB or higher
    • OS: Either MacOS 10.7 or higher OR Windows 8 or higher
    • An internet connection: Minimum bandwidth of 3.0 Mbps (up/down)
    • Browser: IE 11+, Edge 12+, Firefox 27+, Chrome 30+
    • Zoom software client installed on your PC/Laptop/Mac
      We use the Zoom software application to conduct live online classes. Zoom works on a variety of PCs/Laptops/Mac systems and also on phones and tablets. You can join your live online class from a phone or tablet if it supports the Zoom client. We recommend that you attend classes from a PC/Laptop/Mac.