BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//International Cost Estimating and Analysis Association - ECPv6.2.2//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://www.iceaaonline.com
X-WR-CALDESC:Events for International Cost Estimating and Analysis Association
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20200308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20201101T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200805T120000
DTEND;TZID=America/New_York:20200805T130000
DTSTAMP:20260502T164355
CREATED:20200612T183040Z
LAST-MODIFIED:20200626T191540Z
UID:14144-1596628800-1596632400@www.iceaaonline.com
SUMMARY:Lessons Learned Implementing EVM on Government-led Delivery Efforts
DESCRIPTION:Lessons Learned Implementing EVM on Government-led Delivery Efforts\nJoshua Teitelbaum\nWebinar Presentation: Wednesday August 5\, 2020 at 12:00pm EDT \nImplementing Earned Value Management on projects where a Government entity serves as the Lead Systems Integrator presents unique challenges and opportunities when compared to typical EVM applications on industry vendor contracts. This paper will cover lessons learned and best practices for implementing EVM on Government-led integration projects based on field experience from a team that has helped the Government with several such efforts. This will include a description of the methods and tools the team used to baseline projects\, gather data from performers\, and report status to stakeholders. \n 
URL:https://www.iceaaonline.com/calendar/lessons-learned-implementing-evm-on-government-led-delivery-efforts/
ATTACH;FMTTYPE=image/png:https://www.iceaaonline.com/wp-content/uploads/2020/06/CCEA-logo-060320.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200812T120000
DTEND;TZID=America/New_York:20200812T130000
DTSTAMP:20260502T164355
CREATED:20200612T125823Z
LAST-MODIFIED:20200731T145358Z
UID:14125-1597233600-1597237200@www.iceaaonline.com
SUMMARY:The costverse for the FlexFile: Enabling Powerful Analysis in R
DESCRIPTION:The costverse for the FlexFile: Enabling Powerful Analysis in R\nBenjamin Berkman\nJustin Cooper\nWebinar Presentation: Wednesday August 12\, 2020 at 12:00pm EST \n \nThe Cost and Hour Report (“FlexFile”) is a new Contractor Cost Data Reporting (CCDR) format that promises to change the world of Department of Defense (DoD) cost analysis by delivering significantly more granular cost and hour data than its predecessor\, the DD 1921 series of reports. The volume of the FlexFile requires a more thoughtful approach to importing\, wrangling\, transforming\, and ultimately communicating data than Microsoft Excel (Excel) may offer. This paper introduces three R packages that help the analyst exploit the FlexFile to its fullest extent.
URL:https://www.iceaaonline.com/calendar/the-flexfile-cookbook-powerful-analysis-via-r/
ATTACH;FMTTYPE=image/png:https://www.iceaaonline.com/wp-content/uploads/2020/06/CCEA-logo-060320.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200813T100000
DTEND;TZID=America/New_York:20200813T110000
DTSTAMP:20260502T164355
CREATED:20200602T191407Z
LAST-MODIFIED:20200626T155042Z
UID:14022-1597312800-1597316400@www.iceaaonline.com
SUMMARY:Palisade Series Part III: Turning Expert Opinion into Defensible Distributions
DESCRIPTION:This webinar will provide an in-depth coverage of subjective probability assessment\, to include a discussion of considerations for interviewing experts and minimizing the effect of biases like anchoring and adjustment\, followed by a demonstration of how to use @RISK to identify the best fitting distribution from interview results. \nThis series of webinars is intended to provide @RISK users with guidance on settings to use in the Fit Distributions to Data dialog box\, and insight necessary for narrowing down the often-overwhelming candidate list of probability distributions available in @RISK for modeling inputs. Even users who have attended regional training and/or watched relevant on-demand webinars may still be unclear about: \n1. what settings to use in the multiple tabs and radio buttons/drop down boxes within the Fit Distributions to Data dialog box\n2. how to know which test result(s) to pay the most attention to\n3. nuances of the distribution choice that involve both art and science\n4. subtle differences between the triangular and PERT distributions\n5. how to interview experts\, avoid biases associated with subjective probability assessment\, and turn interview results into a defensible input distribution\nWhether a newcomer to @RISK and input distribution selection or an experienced user seeking amplification on these topics\, this three-part\, deep-dive series was developed with you in mind.
URL:https://www.iceaaonline.com/calendar/palisade-series-part-iii-turning-expert-opinion-into-defensible-distributions/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200819T120000
DTEND;TZID=America/New_York:20200819T130000
DTSTAMP:20260502T164355
CREATED:20200612T130141Z
LAST-MODIFIED:20200612T130141Z
UID:14129-1597838400-1597842000@www.iceaaonline.com
SUMMARY:Advanced Data Analytics for Maintenance & Repair Reporting
DESCRIPTION:Advanced Data Analytics for Maintenance & Repair Reporting\nPaul Hardin\nAlexander LoRusso\nTyler Staffin\nWebinar Presentation: Wednesday August 19\, 2020 at 12:00pm EST \n \nThe 1921-M/R (Maintenance & Repair Parts Data Report) is the DoD system for collecting actual maintenance event and repair part data in the Cost and Software Data Reporting (CSDR) system. This paper will employ the R Shiny package\, which is used for the construction of interactive web applications\, to demonstrate the analytical value of -M/R data. Additionally\, this paper will explore the mechanics of the R Shiny framework within the environment of advanced data analytics.
URL:https://www.iceaaonline.com/calendar/advanced-data-analytics-for-maintenance-repair-reporting/
ATTACH;FMTTYPE=image/png:https://www.iceaaonline.com/wp-content/uploads/2020/06/CCEA-logo-060320.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20200826T120000
DTEND;TZID=America/New_York:20200826T130000
DTSTAMP:20260502T164355
CREATED:20200612T130243Z
LAST-MODIFIED:20200612T130243Z
UID:14131-1598443200-1598446800@www.iceaaonline.com
SUMMARY:Improving Software Estimating Relations for Army Software Sustainment Data
DESCRIPTION:Improving Software Estimating Relations for Army Software Sustainment Data\nCheryl Jones\nBradford K. Clark\nJames Doswell\nWebinar Presentation: Wednesday August 26\, 2020 at 12:00pm EST \n \nNew approaches were employed to improve Army software sustainment cost estimation: causal analysis and annualization of release data. Causal analysis examines the cause/effect relationships between factors that indicate which CERs should be derived. Converting multi-year data to annualized values has improved CERs. This presentation shows what was discovered using causal analysis and the resulting improved CERs.
URL:https://www.iceaaonline.com/calendar/improving-software-estimating-relations-for-army-software-sustainment-data/
ATTACH;FMTTYPE=image/png:https://www.iceaaonline.com/wp-content/uploads/2020/06/CCEA-logo-060320.png
END:VEVENT
END:VCALENDAR