• LinkedIn
  • Twitter
  • Facebook
  • Youtube
  • 0Shopping Cart
ISBSG
  • About Us
    • About
    • Board
    • Testimonials
  • Products and Services
    • Partnerships
    • Products
  • Submit Data
  • Resources
    • Resources
    • Conference Presentations
  • Research
  • Events
  • Contact Us
  • Sign In
  • Search
  • Menu Menu
14 December 2022/project control/ITConf21

Parametric Joint Confidence Level Analysis: A Practical Cost and Schedule Risk Management Approach

by Galorath

Joint Confidence Level (JCL) analysis has proven to be successful for NASA. Bottom-up resource-loaded schedules are the most common method for jointly analyzing cost and schedule risk. However, the use of high-level parametrics and machine learning has been successfully used by one of the authors. This approach has some advantages over the more detailed method.

In this presentation, we discuss the use of parametrics and machine learning methods. The parametric/machine learning approach involves the development of mathematical models for cost and schedule risk. Parametric methods for cost typically use linear and nonlinear regression analysis. These methods applied to schedule often do not provide the high R-squared values seen in cost models.

We discuss the application of machine learning models, such as regression trees, to develop higher-fidelity schedule models. We then introduce a bivariate model to combine the results of the cost and schedule risk analyses, along with correlation, to create a JCL using models for cost and schedule as inputs.

We provide a previous case study of the successful use of this approach for a completed spacecraft mission and apply the approach to a large data set of cost, schedule, and technical information for software projects.

Read/download the presentation

Watch the presentation 

About Galorath

Galorath has invested decades of research and development into helping organizations better plan and control project costs, quality, duration, and risk. Leveraging its sophisticated modeling technology and thousands of project-applicable data-sets, Galorath and its line of SEER solutions have proven time and time again to accurately replicate real-world project outcomes more quickly and with much higher accuracy than anything else available on the market.

Share this entry
  • Share on Facebook
  • Share on Twitter
  • Share on WhatsApp
  • Share on Pinterest
  • Share on LinkedIn
  • Share by Mail

Categories

  • agile
  • benchmarking
  • estimation
  • events
  • maintenance and support
  • outsourcing
  • productivity
  • project control
  • recommended
  • sizing
  • Uncategorised

TAGS

academic general ITConf13 ITConf14 ITConf15 ITConf16 ITConf17 ITConf18 ITConf19 ITConf20 ITConf21 ITConf22 news short papers Webinars

ISBSG Limited

Location

Level 1, 147 Cecil Street
South Melbourne
Victoria 3205
Australia

(ABN 16 081 497 636)

Email: staff@isbsg.org

Fill out my online form
Fill out my online form
© Copyright - ISBSG 2022
  • Privacy Policy
  • Disclaimer
  • Terms and Conditions
Benchmarking Projects benchmarking estimation Estimation Models
Scroll to top
en English
af Afrikaanssq Albanianam Amharicar Arabichy Armenianaz Azerbaijanieu Basquebe Belarusianbn Bengalibs Bosnianbg Bulgarianca Catalanceb Cebuanony Chichewazh-CN Chinese (Simplified)zh-TW Chinese (Traditional)co Corsicanhr Croatiancs Czechda Danishnl Dutchen Englisheo Esperantoet Estoniantl Filipinofi Finnishfr Frenchfy Frisiangl Galicianka Georgiande Germanel Greekgu Gujaratiht Haitian Creoleha Hausahaw Hawaiianiw Hebrewhi Hindihmn Hmonghu Hungarianis Icelandicig Igboid Indonesianga Irishit Italianja Japanesejw Javanesekn Kannadakk Kazakhkm Khmerko Koreanku Kurdish (Kurmanji)ky Kyrgyzlo Laola Latinlv Latvianlt Lithuanianlb Luxembourgishmk Macedonianmg Malagasyms Malayml Malayalammt Maltesemi Maorimr Marathimn Mongolianmy Myanmar (Burmese)ne Nepalino Norwegianps Pashtofa Persianpl Polishpt Portuguesepa Punjabiro Romanianru Russiansm Samoangd Scottish Gaelicsr Serbianst Sesothosn Shonasd Sindhisi Sinhalask Slovaksl Slovenianso Somalies Spanishsu Sudanesesw Swahilisv Swedishtg Tajikta Tamilte Teluguth Thaitr Turkishuk Ukrainianur Urduuz Uzbekvi Vietnamesecy Welshxh Xhosayi Yiddishyo Yorubazu Zulu