S01240

Predictive Analytics for Business Forecasting

Venue/Deadlines Program Dates Program Fees
Venue : IIMB Campus
Early Bird Discount Date : 16 Dec, 2024
Last date for registration: 27 Dec, 2024

Start Date : 06 Jan, 2025
End Date : 11 Jan, 2025
Residential Fee(excluding GST) :  Rs. 1,55,000
Residential Early Bird Fee(excluding GST) :  Rs. 1,39,500
Non-Residential Fee(excluding GST) :  Rs. 1,25,000
Non-residential Early Bird Fee(excluding GST) :   Rs. 1,12,500

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Important Deadlines

Venue : IIMB Campus
Early Bird Discount Date : 16  Dec, 2024
Last date for registration: 27 Dec, 2024
 

Contact Us

Ms. Vinitha Vandana
Landline No.:+91-80-26993475
Mobile No. +91-8951974078
Email: vinitha.vandana@iimb.ac.in

Mode
In-Person
Starting In
Jan-Mar
Level
Mid- Senior/Career
Duration
Short Duration
International Travel
No
Alumni Status
No

Programme Overview
Harnessing the power of predictive analytics, the corporate world has witnessed a surge in the adoption of analytical forecasting tools in the recent decades. This may be attributed to an increase in the complexity, competitiveness, and the rate of change in the business environment. The objective of this programme is to present a comprehensive view of the various tools and techniques used in forecasting for managerial decision-making, including the problem of demand estimation, market size determination, sales projections, analysis, and predicting stock prices. The methodology, covering various time series analysis techniques, and regression methods, is presented with an appropriate mix of case analysis and numerical demonstration with the aid of software package (R) to enable the participants to meet their own forecasting needs.

Participants would be divided into small groups to work on predictive analytics and forecasting projects that would be either decided/brought by the participants or given to them. Learning from these projects will be the key takeaway from the programme. A better part of a programme day is reserved for participants to work on this project. In addition, the participants are expected to work during the evenings of the programme days.

R, a free open-source software, is used throughout the course. Prior experience in working with R will be beneficial. On joining the program, introductory guidelines will be sent to the participants about a week before the programme to help them familiarize themselves with R. In addition, help would be available during the programme days to learn the necessary coding with R.

Programme Contents:
• Basic statistical concepts: standard error, confidence interval estimation, and significance values in testing.
• Simple and Multiple regression
• Logit Probit Models
• Time Series Decomposition Models
• Smoothing Models
• Box Jenkins (ARIMA)
• ARIMA with regression errors and ARIMAX
• Models for time series with multiple-level seasonality.
• Bass Model for new product forecasting
• Combining Forecast and Forecast Evaluation
• Forecasting projects/case studies from Industry
• Project work and presentations

Key benefits/takeaways

On completion of this course, the participants will be conversant in various forecasting models and implementing them using R. In particular, the participants should be able to:

  • Understand and implement various time series (Decomposition, smoothing, Box Jenkins) and regression models to present objective forecasts of sales, demands, stock prices, etc.
  • Produce and interpret forecasts of qualitative response based on probit and logit models.
  • Forecast growth of a new product using Bass-type models.
  • Critically compare and combine various methods used for forecasting.

Who Should Attend
The programme is targeted at executives with an analytic mindset intending to use various models in forecasting. While the programme would start with a basic review of statistical techniques, it will be useful if the participants have some introduction to elementary statistics at 10+2 or undergraduate level and previous exposure to forecasting problems in their work. Even if they do not have hands-on experience in solving such problems at any level. Participants are encouraged to bring data that are specific to a forecasting problem of individual interest; otherwise, they will be given alternative datasets to work on during the programme.

Programme Directors

Prof. Shubhabrata Das has been a faculty with IIMB since 1999. He has held visiting faculty positions at various institutes/ universities of international repute, including ESSEC Business School, Indian Statistical Institute Calcutta, University of Nebraska etc.

His major research domain is in Statistical methods, Actuarial Mathematics and Operations Research. Specific topics of interests include Multivariate Statistics, Statistical analysis of fuzzy data, Sports Analytics, Business Forecasting, Measurement and Scaling and Discrete optimization problems. He has published several papers in the refereed journals of international repute. Prof. Das is a co-author of a book titled ‘Facing the Future: Indian Pension Systems’. He is also the co-author of the chapter on canonical correlations in the Encyclopaedia of Biostatistics. Besides these, he has published several technical reports and delivered seminars at various international conferences all over the world.

Prof. Das engages in training and other consultancy services in the domain of Business Statistics, Business analytics, Advanced Market Research, Business Forecasting and Insurance with various prominent companies in the country. He has provided consulting service to different reputed companies. Recently he undertook a major forecasting project on Forecasting energy load for a MNC.

At IIMB, besides teaching the core courses on Statistics for the Post-graduate programs, doctoral programme and various executive education programs, he offers elective courses on Business Forecasting, Insurance analytics, Sports Analytics.

Prof. Das has been Research Chair Professor at IIMB. He was also a part of the IIMB faculty team that received IBM Faculty award. He also received best paper award in the 7th APRIA for work on Joint life Insurance Policy with differential benefit and premium. He is one of twenty
faculty members spread across four continents and twelve academic institutions of international repute that is recipient of a big four-year (2013-16) grant facilitating collaborating research on Risk analysis, Ruin and Extremes, awarded by the European Commission.

Soudeep received his Bachelors and Masters degree in Statistics from Indian Statistical Institute,  Kolkata. Then, he completed his Ph.D. in Statistics from the University of Chicago. His primary field of work is related to forecasting, time series data, spatiotemporal modeling, inference for random processes. He is also interested in sports analytics, especially problems related to soccer. Outside work, Soudeep takes keen interest in photography and blogging.

Participant Benefits

Participant Benefits
As a participant of this Short Duration Programme, you will be able to enjoy some exclusive benefits other than the outcomes such as skills and knowledge enhancement and building specific competencies that can help shape your career growth.

Some of the exclusive benefits of attending this programme are listed below –

  • Receive Executive Education eNewsletters
  • Invitation to share articles to the EEP blog (subject to a shortlisting process)
  • Participate in EEP webinars on various topics
  • Invitation to curated events and programs by the EEP office

Programme Charges

Programme Fee
INR 1,55,000/- Residential and INR 1,25,000/- Non -Residential (+ Applicable GST) per person for participants from India and its equivalent in US Dollars for participants from other countries.

Early Bird Discount
Nominations received with payments on or before 16-Dec-24 will be entitled to an early bird Discount of 10%.
Early Bird Fee (Residential) INR 1,39,500/-(+ Applicable GST)
Early Bird Fee (Non-Residential) INR 1,12,500/-(+ Applicable GST)

Group Discount
Group Discount of 5% percentage can be availed for a group of 3 or more participants when nominations received from the same organization.

Please Note
All enrolments are subject to review and approval by the programme director. Joining Instructions will be sent to the selected candidates 10 days prior the start of the programme.

  • The programme fee should be received by the Executive Education Office before the programme commencement date.
  • In case of cancellations, the fee will be refunded only if a request is received at least 15 days prior to the start of the programme.
  • If a nomination is not accepted,the fee will be refunded to the person/ organisation concerned.
  • A certificate of participation will be awarded to the participants by IIMB

How To Apply for the Programme

Certificate Sample

Note: Certificate image is for reference to potential participants only and may change at the discretion of Executive Education Programmes Office

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