Seeing the future: forecasts and decision making in different operational environments
The aim of the project is to determine the appropriate forecasting approach in a range of (representative) operating environments.
This project is in collaboration with Panalpina World Transport Ltd, Costain and Markes International. Inaccurate forecasting causes a wide range of problems across different industries. First (and most importantly), there is the issue of inventories. The US alone is sitting on approximately $2 trillion worth of goods held for sale (CSCMP, 2015), and in the UK there are 24 million square feet of space dedicated to new warehouses (JLL, 2017). Second, there is capacity. In the civil engineering sector, there are serious concerns as to whether supply chains have the capacity to deliver ambitious government investment and align with spending plans (ORR, 2016). Forecasting issues can be managed via statistical techniques, or via sensing/judgemental approaches, or a combination (Syntetos et al., 2016). However, across industries and operational environments, the appropriate combination of such approaches is not clear, and judgemental processes are poorly understood.
Conceptual research suggests that statistical forecasts should be more appropriate for make-to-stock structures, whereas consultative/judgemental approaches should be more suitable for engineer-to-order (Christopher and Towill, 2000). However, the proposition is untested, and requires in-depth study.
Project aims and methods
A co-operative enquiry case approach is proposed, whereby the PhD student is immersed at each participating organisation for short periods to bring together quantitative archival data and opinion based data through qualitative approaches. The student will be encouraged to shape and discuss methodological approaches with industrial partners and the supervision panel over the course of the research methods training phase (ie first year).
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