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Presentation on theme: "Www.viasimcorp.com Slide 1 Archived File The file below has been archived for historical reference purposes only. The content and links are no longer maintained."— Presentation transcript:

1 www.viasimcorp.com Slide 1 Archived File The file below has been archived for historical reference purposes only. The content and links are no longer maintained and may be outdated. See the OER Public Archive Home Page for more details about archived files.archivedOER Public Archive Home Page

2 www.viasimcorp.com Slide 2 PI Aging Simulation Model

3 www.viasimcorp.com Slide 3 The Current Problem: “Success to the Successful” More Funds to Older, Experienced PI’s Allocation to Older, Experienced PI’s Instead of Younger, Inexperienced PI’s Lower Success of Younger, Inexperienced PI’s Less Funds to Younger, Inexperienced PI’s Higher Success of Older, Experienced PI’s

4 www.viasimcorp.com Slide 4 Basic Structure for Age Group PIs in the system that have “aged” enough to move to the next age group. New PIs (i.e., first-time) that enter the NIH pool in this age group. PIs of this age group that leave the “system.” Represents the number of PIs in the total pool that are in this age group. PIs in the system that have “aged” enough to move into this age group.

5 www.viasimcorp.com Slide 5 Connecting Age Groups

6 www.viasimcorp.com Slide 6 Differences Between Models OB: Spreadsheet methodology Statistical Focuses on data Static No feedback loops OER: System Dynamics (SD) methodology Operational simulation Focuses on activities Dynamic Feedback loops

7 www.viasimcorp.com Slide 7 Limitations of Simulation Model Data begins in FY80, so “momentum” inherent in system prior to FY80 is not captured. Data available for approximately 65% of the R01 equivalents only: –Age data invalid for roughly one-third of R01 data set. “Length of Service” averages based on total years of service rather than continuous years of service. Currently, there are no “feedback mechanisms” incorporated into the model: –All trends are based on data and do not change dynamically or in relation with other variables.

8 www.viasimcorp.com Slide 8 Simulations Baseline (FY80-FY06): –FY80-FY06 entrance rate data. –FY80-FY86 duration averages, FY87-FY06 uses FY86 duration averages. Scenario 1 (FY80-FY16): –Same as Baseline except FY07-FY16 entrance rates use trends based on FY97-FY06 entrance rates. Scenario 3 (FY80-FY16): –Same as Scenario 2 except FY07-FY16 entrance rates specified to try to keep the PI age distribution consistent with FY06.

9 www.viasimcorp.com Slide 9 Average Length of Service

10 www.viasimcorp.com Slide 10 Baseline Results

11 www.viasimcorp.com Slide 11 Total Number of PI’s (FY80-FY06)

12 www.viasimcorp.com Slide 12 Baseline: 1991 Actual Simulation Avg Age = 42.7 Avg Age = 45.6

13 www.viasimcorp.com Slide 13 Baseline: 1996 Actual Simulation Avg Age = 44.7 Avg Age = 47.3

14 www.viasimcorp.com Slide 14 Baseline: 2001 Actual Simulation Avg Age = 46.3 Avg Age = 49.0

15 www.viasimcorp.com Slide 15 Baseline: 2006 Actual Simulation Avg Age = 47.5 Avg Age = 50.8

16 www.viasimcorp.com Slide 16 Scenario 1 Results

17 www.viasimcorp.com Slide 17 Total Number of PI’s (FY80-FY16)

18 www.viasimcorp.com Slide 18 Scenario 1: 1991 Avg Age = 42.7

19 www.viasimcorp.com Slide 19 Scenario 1: 1996 Avg Age = 44.7

20 www.viasimcorp.com Slide 20 Scenario 1: 2001 Avg Age = 46.3

21 www.viasimcorp.com Slide 21 Scenario 1: 2006 Avg Age = 47.5

22 www.viasimcorp.com Slide 22 Scenario 1: 2011 Avg Age = 48.3

23 www.viasimcorp.com Slide 23 Scenario 1: 2016 Avg Age = 49.8

24 www.viasimcorp.com Slide 24 Scenario 2 Results

25 www.viasimcorp.com Slide 25 Scenario 2: Approach Objective is to keep average age and approximate age distribution consistent with 2006 values: –Average age = 47.5 Possible policy changes to test: –No new PI’s older than 65 – minimal impact –Forced retirement at 70 – minimal impact –Forced distribution of 1500 new PI’s: No new PI’s at all All new PI’s <40, evenly spread for each age All new PI’s forced to fit a specific age distribution

26 www.viasimcorp.com Slide 26 Scenario 2, No New PI’s: 2006 Avg Age = 47.5

27 www.viasimcorp.com Slide 27 Scenario 2, No New PI’s: 2011 Avg Age = 50.5

28 www.viasimcorp.com Slide 28 Scenario 2, No New PI’s: 2016 Avg Age = 54.3

29 www.viasimcorp.com Slide 29 Scenario 2, All New PI’s <40: 2006 Avg Age = 47.5

30 www.viasimcorp.com Slide 30 Scenario 2, All New PI’s <40: 2011 Avg Age = 44.0

31 www.viasimcorp.com Slide 31 Scenario 2, All New PI’s <40: 2016 Avg Age = 41.3

32 www.viasimcorp.com Slide 32 What Does This Tell Us? We have a model that is capable of forecasting the age distributions of the PI pool given assumptions on influxes and tenures. Making dramatic changes can have dramatic impacts.

33 www.viasimcorp.com Slide 33 Scenario 2: New PI Distribution 1 Constant rate of 1500 New PI’s Age 25-35: 25% Age 36-40: 20% Age 41-45: 20% Age 46-50: 15% Age 51-55: 10% Age 56-60: 10% Age 61-80: 0%

34 www.viasimcorp.com Slide 34 Scenario 2, New PI Distribution 1: 2006 Avg Age = 47.5

35 www.viasimcorp.com Slide 35 Scenario 2, New PI Distribution 1: 2011 Avg Age = 47.6

36 www.viasimcorp.com Slide 36 Scenario 2, New PI Distribution 1: 2016 Avg Age = 48.2

37 www.viasimcorp.com Slide 37 What Does This Tell Us? The “ideal” age distribution for the PI pool is still an unknown target. With changes that occur due to feedback loops in the system, the established age distribution policy for new PI’s for future years will likely change every few years. In other words, there is no constant age distribution policy for incoming new PI’s that will provide the “ideal” PI pool age distribution over the long run.

38 www.viasimcorp.com Slide 38 Additional Test Scenarios for Final Workforce Group Meeting November 14, 2007

39 www.viasimcorp.com Slide 39 Test Scenario: Effect of the Number of New PIs on the Average Age of the Total Pool Age Distribution 24-35: 25% 36-40: 20% 41-45: 20% 46-50: 15% 51-55: 10% 56-60: 10% 61-90: 0%

40 www.viasimcorp.com Slide 40 Test Scenario: Effect of the Number of New PIs on the Average Age of the Total Pool Age Distribution 24-35: 25% 36-40: 20% 41-45: 20% 46-50: 15% 51-55: 10% 56-60: 10% 61-90: 0%

41 www.viasimcorp.com Slide 41 Distribution #1 Distribution #3 Distribution #2 24-35: 25% 36-40: 20% 41-45: 20% 46-50: 15% 51-55: 10% 56-60: 10% 61-90: 0% 24-35: 25% 36-40: 40% 41-45: 15% 46-50: 10% 51-55: 5% 56-60: 5% 61-90: 0% 24-35: 25% 36-40: 60% 41-45: 10% 46-50: 5% 51-55: 0% 56-60: 0% 61-90: 0% Test Scenario: Small Changes in the Age Distribution of the New PI pool

42 www.viasimcorp.com Slide 42 Distribution #1 Distribution #3 Distribution #2 1100 New PIs 1500 New PIs Test Scenario: Small Changes in the Age Distribution of the New PI pool

43 www.viasimcorp.com Slide 43 Test Scenario: Extreme Case – Replacing the PI Pool

44 www.viasimcorp.com Slide 44 Conclusions The model in its current state matches historical data “qualitatively”, but could use some improvement with “quantitative” accuracy. The current “backbone” aging model needs to be enhanced to increase the quantitative weaknesses. The simulation could be improved with the addition of “recycling” of PI’s as well as feedback loops regarding how individuals and institutions act/react to changes in NIH policies. With improvements, the simulation model could be very useful in understanding the short-term and long-term consequences of NIH policies. The ideal “age distribution” for the PI pool is still undetermined.

45 www.viasimcorp.com Slide 45 Next Steps Based on feedback from the final workforce group meeting, develop a list of specific model enhancements to be incorporated in a follow-on effort. On this next effort, focus on increasing the quantitative accuracy of the model compared to historical data. Report back to workforce modeling group on results from enhanced model.


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