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Predictability Index

Iman Fozveh

Predictability Index.

Rel. Alberto De Marco. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Gestionale (Engineering And Management), 2020

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This study proposes to evaluate cost and schedule performance based on the early and accurate prediction of final outcomes, as opposed to the prevalent and reactive evaluation of final cost and schedule deviations at completion. Getting to know early in the delivery process the actual outcomes of a project enables project and corporate managers to undertake informed and proactive actions in a timely manner. The ability to timely forecast accurate project outcomes is fundamental in an industry marked by endemic cost and schedule deviations. Indeed, owners and contractors alike make key strategic decisions about individual projects and capital investment programs alike based on forecasted values. As a departure from current cost and schedule assessments solely based on deviations at completion, this study introduces the Predictability Index, a novel performance metric that also considers the project team’s ability to timely predict outcomes at completion. This study conceptually explains and defines the index and, based on the statistical analysis of retrospective data from 135 completed projects representing $29 billion in total installed costs, identifies threshold values of predictability performance. Also, actual case studies are discussed in order to illustrate the tangible benefits associated with the assessment of predictability performance to the project delivery process. Complementary, lessons learned and observations collected from the adoption and assessment of predictability by industry organizations are also discussed. A significant cultural shift within an organization is necessary for project teams to focus on predictability performance.

Relators: Alberto De Marco
Academic year: 2020/21
Publication type: Electronic
Number of Pages: 52
Corso di laurea: Corso di laurea magistrale in Ingegneria Gestionale (Engineering And Management)
Classe di laurea: New organization > Master science > LM-31 - MANAGEMENT ENGINEERING
Aziende collaboratrici: UNSPECIFIED
URI: http://webthesis.biblio.polito.it/id/eprint/16494
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