Overview

The goal of this programme is to provide a thorough understanding of the tools and techniques utilised in forecasting for managerial decision-making. This includes addressing challenges such as demand estimation, market size determination, and sales projections. The methodology will cover a range of time series analysis techniques and regression methods, presented through a combination of case studies and numerical demonstrations. Participants will also have the opportunity to utilise software packages, such as R, to enhance their forecasting capabilities.

Objectives

  • Understanding forecasting fundamentals: Participants will gain an understanding of the basic principles, methods and types of business forecasting.
  • Data analysis and interpretation: Participants will learn to analyse historical data, identify patterns and make data-driven using statistical tools.
  • Forecasting techniques: Explore various quantitative and qualitative forecasting methods, including time series analysis, regression analysis and market research.

Who can attend

The programme is designed for executives with an analytical mindset who are looking to utilise various models for forecasting. The programme will begin with a basic overview of statistical techniques. It is recommended that participants have some familiarity with elementary statistics at the 10+2 or undergraduate level, as well as previous exposure to forecasting problems in their professional work. While hands-on experience in solving such problems is not required, it is beneficial.

Key Topics

Introduction to Business Forecasting

  • Qualitative Techniques & Quantitative Techniques
  • Time series Forecasting – Components, Decomposition, Smoothening Methods, ARIMA Methods
  • Causal Techniques – Linear Regression, Multiple Regression
  • Basic Statistical concepts
  • Time series forecasting
  • Naïve Models, Moving average, Exponential Smoothening, ARIMA, ARIMA.

Programme Director

Aditi Divatia

Associate Professor, Information Management and Analytics
Aditi Divatia holds a Ph.D. from the Birla Institute of Technology and Science (BITS Pilani), in the area of Business Analytics. She is a faculty in Information Management and holds a keen research interest in business intelligence and analytics. Prior to joining academics in 2004, she was professionally engaged for over 10 years with prominent IT companies, wherein she offered project-based consulting services. She reflects her extended zeal for teaching by conducting management development ...

Time Schedule

Date No. of Hours Duration Time
November 9 – 10, 2024
November 16 – 17, 2024
November 23 – 24, 2024
November 30 – December 1, 2024
20 Across
4 weekends
Sat – 06:00 pm – 08:30 pm
Sun – 10:30 am – 01:00 pm

Programme Fees

INR 38,000 per participant plus applicable taxes.
(10% Early Bird, Alumni and Group Discounts available)

Certificate of Participation

A Certificate of successful participation by S. P. Jain Institute of Management and Research (SPJIMR) will be issued to each delegate at the completion of the programme.

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