Long-Term Economic Forecasting with Structured Analogies and Interaction Groups

In this study, we employ judgmental forecasting techniques, Structured Analogies and Interaction groups for long-term forecasting. The aim of the paper is not to evaluate forecasting accuracy per se but to highlight the potential of such techniques in this so complex and challenging task. The case study is about Saudi Arabia and its aim to adopt a diversification strategy to reduce its dependency on the oil sector, where oil revenue consists 90% of its budget currently. The study has four phases: Unaided Judgment, Structured Analogies, and Interaction Groups with Structured Analogies - all three using disguised data – before finally working on the undisguised case study under review over a significant amount of time. Adopting judgmental methods are attributed to three main reasons: in an attempt to derive long-term economic forecasts about Saudi Arabia’s ability to diversify its investments, to discover the impact of different factors on financial and economic outlooks, and to explore the main reasons for deviating the accuracy of financial and economic forecasts

Forecasting and planning for special events in the pulp and paper supply chains

Due to global warming, flood is an increasing threat to companies operating in the pulp and paper industry. The impact of this threat needs to be managed. We deploy a qualitative investigation into how paper manufacturers can forecast and mitigate the impact of special events, most notably floods, across their supply chains. A grounded theory approach using semi-structured interviews held with supply chain consultants in three stages allowed for topic categories emerging during previous interviews to be explored. Analysis of these interviews uncovered tactics unique to the pulp and paper industry. The findings are three-fold. First, paper manufacturers should focus on basic forecasting methods which they are capable of, such as subscribing to flood warnings, rather than poorly executing advance machine learning forecasts. Second, planning is of equal importance to forecasting: integrated business planning should guide the process. Third, business execution should involve a proactive approach to decision-making which trusts data and has people that nurture and drive the process

Forecasting and planning for special events in the pulp and paper supply chains

Due to global warming, flood is an increasing threat to companies operating in the pulp and paper industry. The impact of this threat needs to be managed. We deploy a qualitative investigation into how paper manufacturers can forecast and mitigate the impact of special events, most notably floods, across their supply chains. A grounded theory approach using semi-structured interviews held with supply chain consultants in three stages allowed for topic categories emerging during previous interviews to be explored. Analysis of these interviews uncovered tactics unique to the pulp and paper industry. The findings are three-fold. First, paper manufacturers should focus on basic forecasting methods which they are capable of, such as subscribing to flood warnings, rather than poorly executing advance machine learning forecasts. Second, planning is of equal importance to forecasting: integrated business planning should guide the process. Third, business execution should involve a proactive approach to decision-making which trusts data and has people that nurture and drive the process