Predictive Analytics for Business Forecasting
Last date for registration: 12 Jan, 2024
End Date : 27 Jan, 2024
Early Bird Discount Date : 01 Jan, 2024
Residential Early Bird Fee(excluding GST) : Rs. 1,34,100
Non-Residential Fee(excluding GST) : Rs. 1,19,000
Non-residential Early Bird Fee(excluding GST) : Rs. 1,07,100
Programme Overview
The past few decades have witnessed the growing adaptability of analytical forecasting tools in the corporate sector. This may be attributed to 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, analysing, and predicting stock prices. The methodology, covering various time series analysis techniques, and regression methods, is presented with 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 forecasting projects that would be either decided/brought by the participants or given to them. Learning from these projects will be the key take-away from the programme. 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 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, 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 timeseries 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 coversant 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 for executives with 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 of 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 dataset to work on during the programme.
Programme Fee
INR 1,49,000/- Residential and INR 1,19,000/- 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 01-Jan-24 will be entitled to an early bird Discount of 10%.
Early Bird Fee (Residential) INR 1,34,100/-(+ Applicable GST)
Early Bird Fee (Non-Residential) INR 1,07,100/-(+ 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.
Testimonial
This was, by far, the best Executive Education Programmes, I have attended in 21+ years as an IT Professional. An informative and exciting journey into Statistics with Predictive Analytics for Business Forecasting. For that kind of cohesion to take place nearly instantly among all attendees and one great instructor, Shubhabrata Das, from different cultures and backgrounds, as being in India, in such a short amount of time is something truly remarkable and unforgettable. Over the course of several months, I have tried to employ the skills attained from the course to some practical use-cases, within my organisation or with my professional colleagues.
Skills and knowledge, I earned during the course helped me to be a part of discussion moving beyond exchange of knowledge to working together to develop and implement solutions or complete and take up more projects on timeseries. During the days of the course, it was truly an exchange of ideas rather than knowledge being dumped into the brain. The short-term results of the Executive Education Programme was a renewed feeling of self-confidence and dedication towards taking up Business Forecasting projects and address the challenges faced.
Programme Director
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.
How to Apply