Projects per year
In the absence of an abundance of data, resource planners use unstructured estimations as a source of decision making information. Challenges associated with such an approach are: a lack of transparency; slow and lagging response to information demands; poor consistency and agreement; cost intensive collection and ambiguous accuracy (Hird 2012). By developing a technique based on the efficient and structured collection of expert estimations, Hird (2012) overcomes such challenges. In applications to date, a small amount of legacy project data has been available to validate such methods thereby encouraging confidence in model results. This research explores the instance where no data is available for validation of the model. We propose the use of the Delphi method in combination with the technique proposed by Hird (2012). Through case studies, the technique is employed in a UK-based automotive firm. The objectives are: to identify suitable parameters and to evaluate the suitability of Delphi in this context. Initial findings suggest that Delphi is a legitimate means of validating quantitative models and developing confidence in model use. The process of applying Delphi engenders a sense of model ownership and encourages evaluation of current planning practices. Unstructured resource estimation in the absence of data for forecasting model development and validation is a widespread and long standing issue. Our findings also address the issue of expert knowledge retention.
|Publication status||Published - 12 Jul 2015|
|Event||27th European Conference on Operational Research (EURO XXVII) - University of Strathclyde, Glasgow, United Kingdom|
Duration: 12 Jul 2015 → 15 Jul 2015
|Conference||27th European Conference on Operational Research (EURO XXVII)|
|Period||12/07/15 → 15/07/15|