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The 9th demcoratising forecasting workshop will take place in Al-Hussein Technical University on 8-9 and 11th January 2020 in Amman, Jordan. Democratising forecasting is an intiaitive lead by Bahman Rostami-Tabar ans sponsored by the International Institute of Forecasters. The aim is to share knownoledge on forecasting and influence relevant practices prioritising the need of population and the society. What participants will learn in the workshop? Assuming basic knowledge of statistics, participants will learn:

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My life objective is to help the World becoming a better place by offering skills and developing free resources for the population that may not have the means to afford a quality education in forecasting and modelling. That was the force behind Democratising Forecasting project that I initiated in January 2018. Democratising forecasting project The initiative sponsored by the International Institute of Forecasters provides cutting-edge training in the use of forecasting with R software in developing countries.

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The 8th demcoratising forecasting workshop will take place in Caucasus University on 16-18 December 2019. Democratising forecasting is an intiaitive lead by Bahman Rostami-Tabar ans sponsored by the International Institute of Forecasters. The aim is to share knownoledge on forecasting and influence relevant practices prioritising the need of population and the society. What participants will learn in the workshop? Assuming basic knowledge of statistics, participants will learn: The importance of forecasting and its relation to decision making in organizations; How to prepare, manipulate and visualize data using R; The theory behind forecasting models; How to produce forecasts and evaluate their accuracy across a range of statistical forecasting models using real-world data; How to use R functions and their packages to use generate forecasts; How to visualize, export and report results for interpretation and insights using RMarkdown.

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The 5th demcoratising forecasting workshop will take place in Institute of Human Virology in April 2019. Democratising forecasting is an intiaitive lead by Bahman Rostami-Tabar. The aim is to share knownoledge on forecasting and influence relevant practices prioritising the need of population and the society. Register here Registeration is closed on Friday 29 March 2019 at 02:30 (UK time). Prerequisites Basic knowledge in statistics; No knowledge of forecasting is assumed.

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The 6th demcoratising forecasting workshop will take place in Makerere University Business School in April 2019. Democratising forecasting is an intiaitive lead by Bahman Rostami-Tabar. The aim is to share knownoledge on forecasting and influence relevant practices prioritising the need of population and the society. Register here Registeration is closed on Friday 5th April 2019 at 02:30 (UK time). Prerequisites Basic knowledge in statistics; No knowledge of forecasting is assumed.

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Forecasting for Social Good

One of the key objectives of my research is to use Operational Research techniques to improve decision making in organizations with social missions, thereby positively contributing to advancing knowledge in the field of forecasting practice for social good.

Forecasting for Social Good incorporates the need of society rather than emphasising a pure financial performance with two main elements: i) decisions are not directly driven by profit and ii) gives priority to those who are generally external to the organisation. Topic may include but not limited to:

  • Health
  • Humanitarian and disaster relief
  • Education
  • Goverments
  • Social services

Forecasting for Social Good Initiative aims to explore and expose how (where) forecasting can have positive societal impact. The objective is threefold: i) expose the importance of forecasting for social good, ii) capture the otherwise dispersed current state of knowledge, and set the agenda to drive developments iii) create and establish research collaboration and partnership at the national and international level.

To that end, I have organised the first international workshop dedicated to the use of forecasting for social good in Cardiff University on Thursday and Friday 12-13 July 2018. This workshop was an important step to bring more attention to this extremely important topic. It brings together researchers and practitioners across 10 countries to discuss research agenda in this area, whilst helping me broaden my network and introduce important research collaborations with academics as well as build solid partnerships with organizations.

Please see below for more information about the conference:

  1. 24th IIF workshop on Forecasting for Social Good

  2. Short video about the conference on Forecasting for Social Good

We are organising the second international workshop on Forecasting for Social Good on 11-12 June 2020 in France.

Democratising forecasting

This is an ongoing initiative, sponsored by the International Institute of Forecasters will provide cutting-edge training in the use of forecasting with R in some of the world’s least developed countries to transfer knowledge in forecasting and help decision makers use it as an effective tool to support decision-making process. R is an open source programming language and software widely used for data analysis, manipulation, visualisation and modelling.

“These workshops aim to provide up-to-date training on the principles of forecasting and create an international network to conduct research on forecasting with social impact for less developed countries.”

The workshops will be provided by Dr Bahman Rostami-Tabar whose research focuses on forecasting for social good, supply chain forecasting and the interface between forecasting and decision-making. For more information please see IIF Website

To organise a workshop in your country, contact rostami-tabarb@cardiff.ac.uk.

Projects

Selected Publications

Grouped time series demand forecasting in supply chains

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Demand forecasting by temporal aggregation: Using optimal or multiple aggregation levels?

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Demand forecasting by temporal aggregation

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Recent Publications

Grouped time series demand forecasting in supply chains

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Demand forecasting by temporal aggregation: Using optimal or multiple aggregation levels?

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A novel ranking procedure for forecasting approaches using Data Envelopment Analysis

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Non-stationary demand forecasting by cross-sectional aggregation

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A note on the forecast performance of temporal aggregation

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Demand forecasting by temporal aggregation

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Recent & Upcoming Talks

Forecasting using R in Senegal
Jun 23, 2018 9:00 AM

Teaching

Subject I am teaching in 2018-2019 at Cardiff University :

BST832: Forecasting

The Forecasting module aims to provide students with an in-depth understanding of demand forecasting, and essential planning activity within the field of operations and supply chain management. It is taught by combining theoretical and applied approaches appropriate to an MSc audience and draws upon the latest forecasting techniques. It develops, applies and consolidates learning through solving problems related to real demand patterns. Specifically, it aims to:

  • Provide a systematic and comprehensive understanding of the use of forecasting methodologies in Operations Management and Logistics settings
  • Provide a comprehensive understanding of real industrial case studies using analytical modelling and simulation.
  • Provide a systematic capability to make decisions on the suitability of forecasting methods for the Operations Management and Forecasting problem in hand.
  • Develop the ability to originally apply innovative forecasting methodologies to operational problem solving.

BST835: Risk Management in supply Chains

This module will equip students with:

  • A comprehensive understanding of the major theoretical underpinnings of risk management strategies in a business and supply chain context.
  • An ability to critically evaluate the major debates within the topics.
  • Critical awareness of strategies, methods, tools and techniques that can be used to identify, analyse and respond to various risks.
  • Analytical skills in risk management by evaluating real manufacturing and service, public and private sector case studies.

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