Senior Management Programme in Business Analytics (SMPBA)
The myths, promises, and realities surrounding business analytics need to be confronted and addressed by the senior management teams of organizations in today’s volatile business landscape. As the conventional differentiators of competitive advantage start vanishing fast, use of data driven intelligence has started emerging as the game changer. Understanding the emerging nature of competition, planning a roadmap for enhancing competitive capability, and visualizing the future of analytics-oriented competition have become a necessity for senior management in organizations.
Data-smart firms are developing new models of decision-making that exploit overwhelming amounts of data to make smart products and services for consumers. The potential to create value by data aggregation and analysis is huge, and firms leveraging analytics are at a vantage point in their competitive landscape. Newer sets of capabilities are required to bring the value of the data gathered from all the frontline processes.
The Senior Management Programme in Business Analytics (SMPBA) is an intensive, 9-month, multi-modular, programme. This programme is targeted towards senior managers who appreciate how analytics could unleash value for the firm and its consumers.
- To pave ways for improving organizational readiness in using data analytics as a powerful mechanism for business model innovation
- To recognize and inculcate necessary capabilities comprising analytical tools and techniques with behavioral skills toward competitive advantage
This programme is targeted towards senior management – the segment not being adequately served by the existing bouquet of LDPs in the analytics / data science space.
The Programme combines strategic aspects of Business Analytics with relevant technology oriented operational aspects for actionable appreciation of analytics by senior management.
It would help spread data driven decision making capabilities of participants.
The duration of the programme is 09 months. This is a multi-modular programme with 15 days at IIM- Calcutta Campus spread over 3 Campus visits which is compulsory for all participants, along with a few hours of Live Online Session (Direct to Desktop). The programme will be delivered through the D2D platform once a Week (Sunday- 9:00 am – 12:00 pm) (applicable for only live online classes)
The campus module will be conducted subject to the evolving COVID- 19 pandemic situation and will depend on Government and Institute policies related to the same.
Programme Fee - Rs. 6,00,000/- + (applicable taxes)
The pedagogy will be highly interactive including Campus Immersion at IIM Calcutta and D2D modules. This is a blended programme which includes classroom lectures, D2D modules, real-life case studies, group discussions, simulations.
|The business value of data analytics||Analytics readiness of an organization and building a data-driven decision-making culture,
Building organizational team for making use of Data Science and Analytics,
Appreciating the emerging nature of competition and the role of business analytics
|Statistics for Data Science||The art of summarizing data and statistical learning in decision making
Applied probability and decision making under uncertainty
Data sampling and the art of inferring about the population from samples
Regression techniques and the art of capturing relationships among variables of interest
|Descriptive Analytics||Appreciation of analytical reasoning and empirical findings from data
Challenges in Data visualization and data interpretation
|Experimentation||Data capture and preprocessing issues
Interpretation of raw data
Interpretation of statistical summary of data
|Data sources||Issues in filtering Raw Data for finding extract worth Modeling
Outlier analysis, Dimensionality reduction in Data Cleaning
|Predictive Analytics||Business forecasting principles and issues
Artificial Intelligence and Machine Learning in Decision Making – role of supervised learning
Role of 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 optimization concepts in decision making
Insights from game theoretic situations, Network externalities and network effect on economy, Information cascade effects in decision making
- Graduate with minimum 10 years of work experience and currently employed
- Minimum 50% in Graduation/Post Graduation
- Screening & selection will be done by IIMC