Presented by Joe Bauer

1. JUNE 19 – 21, Bethesda, MD

2. Predictive Power of “Should Pricing”
Joe Bauer, Solutions Consultant
PRICE Systems, LLC

3. Agenda
 Background
 Pricing Methodologies
 Predictive Analytics
 Case Studies
 Lessons Learned
 Next Steps

4. Background
 “Should Price” analysis developed by DoD; embedded in FAR
 Assists contracting dept in determining fair & reasonable price
 Involves determining product price based on:
– Materials
– Labor
– Overhead
– Profit
– Escalation
– Competition
– Quantity purchased
– Market supply
– Market demand
– Obsolescence
– Mission requirements
– Other financial factors

5. Pricing Methodologies
 Three methods for determining fair and reasonable price:
– Open market research
– Data analysis of past procurement
– Parametric estimating using predictive analytics
“What are others paying?” “What have I paid before?” “What should I pay?”

6. Pricing Environment
 Pricers are contracting pros…not estimators or engineers
 “Fair and reasonable price” determination can be 30-45 days
 Workload ranges from paper clips to space ships
 Limited access to technical and programmatic data
 Overarching belief that government pays too much
 Any parametric model better be simple, fast and accurate!

7. Predictive Analytics
 Key consideration: Am I paying a
fair and reasonable price?
 Preferred method is market based
pricing (what others pay)
 Parametric estimating using
predictive analytics is a valid
alternative when market based info
is unavailable

8. Parametric Modeling
 Generate cost or price based on technical / programmatic
description of deliverable
What is it?
Material type?
Technology type?
How heavy?
How many?
Translate technical and
programmatic inputs
into cost model inputs

9. Case Studies
 Aircraft solenoid valve
 Oil pump gear
 Air data computer
 Auxiliary power unit (2 types)
 Inertial measurement unit
 Missile clock oscillator
 Aircraft memory server
 Data loading kit
 Diesel engine and shipping
container
 Aircraft engine component (2 types)

10. Results

11. Inputs Affected
 Labor rates
 Quantities
 Weights
 Technology
 Production line considerations
Average time per
case study ~
1 hour

12. Lessons Learned
 Pricer and coster parallels
– Same end goal
– Same challenges regarding data
– Obvious need for collaboration
 Applications exist to make your job easier
 There is an entire community of experts on your side

13. Next Steps
 Onsite “proof of concept”
– Wright-Patterson AFB (Dayton, OH)
– DCMA CIG (Indianapolis, IN)
 Capability briefing to pricing leadership
 Address nuances of pricing versus costing activities

14. Mr. Joe Bauer is a Solutions Consultant with
PRICE Systems. He is the primary technical
focal point for Air Force customers, several
defense contractors in the US, and
government agencies in Canada. Joe earned
a Master of Science degree in Cost Analysis
from the Air Force Institute of Technology in
2009. He earned an MBA in 2005. Joe is also
a Certified Cost Estimator / Analyst (CCEA)
with the International Cost Estimating and
Analysis Association (ICEAA).
Joe Bauer 937-258-7187
PRICE Systems, LLC. Joe.bauer2@pricesystems.com
Questions?