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Autor(en): 
  • William Shelton
  • Megan McKernan
  • Grant Johnson
  • Samantha Cohen
  • Philip S Anton
  • James Ryseff
  • Stephen B Joplin
  • David Kravitz
  • Alejandro Vigo Camargo
  • Early Predictive Indicators of Contractor Performance: A Data-Analytic Approach 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Juli 2022  
    Genre:  Wirtschaft / Recht 
    ISBN:  9781977409546 
    EAN-Code: 
    9781977409546 
    Verlag:  Rand Corporation 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 279 mm / B 216 mm / D 6 mm 
    Gewicht:  272 gr 
    Seiten:  108 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Getting early indication of potential contractor performance risks and contract execution issues is critical for proactive acquisition management. When contractors are in danger of not meeting contractual performance goals, Department of the Air Force (DAF) acquisition management may not be fully aware of the shortfall until, for example, a schedule deadline is missed, government testing indicates poor system's technical performance, or costs exceed expectations. Concerns continue to be raised about cost and schedule growth in acquisition and experts postulate about a lack of knowledge about the status of acquisition programs. In this report, the authors focus on metrics to identify emerging execution problems earlier than traditional acquisition oversight systems to enable more-proactive risk and performance management. They summarize their findings, which include a taxonomy of contractor relative risks, leading indicators of performance, relevant data sources, risk measures and equations, and a prototype that implements some of these findings using real data sources. This research should be of interest to acquisition professionals and leadership who are searching for ways to improve acquisition performance through early identification of potential relative contractor risks and execution problems to inform active program management and mitigation of risks. The prototype should be of interest to acquisition officials (from program managers to milestone decision authorities) to help them access more data in an easy-to-understand way so they can focus their limited time on areas that require increased management attention. This approach should be useful during any phase of the acquisition process.

      



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