Download - Acumen Fuse World Tour 2012
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// Acumen Fuse World Tour
2012
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// World Tour Overview Acumen Fuse
◦ The tour ◦ 10 countries: 24 locations
◦ Fuse & Fuse 360
◦ Fuse 3.1 launch ◦ Acumen Cloud™, New Schedule Cleanser™; New
forensics, enhanced P6 integration
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// Dr. Dan Patterson, PMP
◦ Legacy:
◦ 20 years of PPM experience
◦ WelcomHome, WelcomRisk, TerraFirma
◦ Pertmaster
◦ Thought Leader:
◦ Project analytics
◦ Project Risk analysis
◦ S1>S5™ schedule maturity framework
◦ Founder of Acumen, inventor of Fuse
President and CEO, Acumen
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// Acumen
◦ Project Management Software Company
◦ Insight into challenges & use of
analytics to overcome them
◦ Core Concepts:
1. Project success requires a sound plan
2. Planning requires risk consideration
Proven Project Analytics
Product Offerings
Risk Workshops
Acumen Fuse®
Software Training
Realistic Scheduling
Critiqued
The Base
Risk-Adjusted
Optimized
Team-Aligned // S5
// S4
// S3
// S2
// S1
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// Schedule Maturity Framework Acumen S1 > S5
S1 • Schedule Basis • Owner/contractor schedule
S2 • Cri/qued Schedule • Ensure structural integrity
S3 • Risk-‐Adjusted Schedule • Account for risk/uncertainty
S4 • Op/mized Target Scenarios • Schedule accelera>on
S5 • Team Validated Scenario • Buy-‐in on op>miza>on 0
1
2
3
4
5
6
0 1 2 3 4 5 6
Chan
ce of S
ucess
Maturity Level
Measure quality through the Fuse Schedule Index™
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// Case Studies
1. Owner/contractor alignment [S1>S2]
2. Bidding competitiveness [S1>S2]
3. Acceleration/risk reduction [S3>S5]
4. Performance tracking
5. Dispute resolution
6. Portfolio analysis
The benefits of Fuse
May 16, 2012
Subcontractors Contractors
Joint Venture 3rd Party Assessors
Owners
• All leads to: • More realistic, achievable plans
• Many X faster/easier than manual approach
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// Acumen Fuse Platform
◦ Fuse: analytics platform
◦ Improves schedule quality
◦ Insight into performance
◦ Fuse 360: goal-based acceleration
◦ Schedule Acceleration
◦ Decision-support
Enterprise Project Analysis
May 16, 2012
Metric Analyzer
Logic Analyzer
Forensic Analyzer
Schedule Cleanser
Schedule Accelerator
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// Measuring Schedule Quality The Fuse Schedule Index™
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// Better Planning Drives Project Success Proven Correlation
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Prob
ability of O
n-‐Time Co
mple/
on
Fuse Schedule Index™
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// Metric Analysis
Slice & Dice
May 16, 2012
Benefit:
" Pinpoint shortcomings
" Project characteristics
" Slice and dice
About:
" 300+ metrics
" Percentage: context
" Threshold: acceptability
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// Types of Project Metrics
Schedule
• Logic • Float • Dura>on
Cost
• Overrun • Capacity • Burn rates
Performance
• Status • Completed • Delayed
Characteris>cs
• Level of detail • Constrained • Riding Data Date
Earned Value
• CPI/SPI • Trending • Earned schedule
Risk
• Exposure • Hot spots • Hidden paths
Fuse Metric Libraries
• Project management best practices
• Industry/corporate standards: PMI, AACE, NDIA
• Fuse-specific: Logic Density™, Hotspot, Redundancy
• Compliance: DCMA 14 Point, DoD
• Create your own!
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// Customizable Metrics Fuse Metric Editor
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// Acumen-Specific Metrics
Logic Density™ • Measure of complexity/completeness
Logic Hotspot™ • Timely start?
Float Ra>o™ • Degree of flexibility per day of work
Redundancy Index™ • Non-‐needed logic
Advanced Project Insight
Finish Compliance™ • Accurate measure of performance
Insufficient Detail™ • Ac>vity V project dura>on
Milestone Ra>o™ • Detail V repor>ng
Broad Risk Range • Check for erroneous risk input
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// Logic Density™
◦ Measure of complexity & soundness
◦ Dual-band threshold: 2 to 6…
◦ Determine Logic Hotspots™ in schedule
◦ Trending: determine timing of shortcomings
Integrity Check
More definition
needed
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// Fuse Schedule Cleanser™ Actionable Insight
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// Project Forensics Insight into Schedule Cleanse
May 16, 2012
16
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// Claims Analysis
◦ Advanced forensics
◦ Fuse gives meaning to the
impact of changes
◦ Pinpoints changes to critical/
driving path
◦ Every single project attribute
can be checked
◦ Calendar definition changes
Insight into project variances
May 16, 2012
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// Reporting
Executive Briefing!• Summary of
analysis results!
Analyst Report!• To do list!
Dashboard!• Interactive
charts & graphs"
API & Custom Reports"• Automation
of existing reports"
Publish Analysis Results
May 16, 2012
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// Integration
Schedule, Cost, Risk, Performance, EV
May 16, 2012
MS Project
P3/P6
Open Plan
Asta Cobra Prism G2
PRA
Excel/XML
Na>ve tool not required
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// Case Study #1
• Houston-based oil/gas owner
• Objective:
• More on-time completion for projects over $250MM
• Encourage more mature contractor schedules
• Overcome “brain drain” in scheduling
• How achieved:
• Mandated contractor Fuse Schedule Index of 75+
• Gave contractor opportunity to self-assess
Owner/contractor Alignment
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// Case Study #1
◦ Metric analysis view
◦ Slice and dice analysis
◦ Executive briefing and Analyst reporting
◦ Logic analysis
◦ Schedule cleanser™
◦ Score comparison
◦ Forensic analyzer
◦ Executive dashboard
◦ Exporting fixed schedule
Fuse Modules
// Fuse Demo
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// Case Study #1
• Outcome:
• Contractor achieved 75+ Fuse Schedule Index
• Schedule was more realistic
• Schedule was earlier!
• Owner gained confidence in the contractor
• Better collaboration & alignment between stakeholders
Owner/contractor Alignment
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// Acumen Cloud™
◦ Communitized benchmarking
◦ Means of determining:
◦ Schedule quality?
◦ How this ranks with other projects?
◦ How does this align our project for on-time completion?
◦ 100% anonymous, secure (SSL)
◦ Continuously getting more intelligent
◦ New libraries can be pushed to Fuse!
Project Benchmarking
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// Acumen Cloud™ Architecture
Knowledge Base
Dynamic Cloud Libraries Client-based
analysis Benchmarking
Fuse 3.1
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// Acumen Cloud The Fuse Schedule Index™
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// Case Study #2
• EPC bids for a utility turnaround
• Three competing bidders
• Objective:
• Owner wanting to make informed award decision
• Cheapest? Fastest? Most achievable?
• How Achieved:
• Compared schedule, cost, quality metrics
• Benchmarked using Acumen Cloud™
Bidding Competitiveness
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// Case Study #2
◦ Importing multiple scheduling platforms
◦ Timeline view
◦ Cost/duration comparison
◦ Driving logic analyzer
◦ Acumen Cloud benchmarking
Fuse modules
// Fuse Demo
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// Case Study #2
• Outcome:
• Contractor B fastest, cheapest but poorest quality
• Contractor A cheapest but fundamental logic flaw
• Contractor C was most expensive but…
• Had highest quality score
• Had a true continuous driving path
• Had sound cash flow
• Ranked highly with regards to benchmarking
• Was awarded the contract!
Bidding Competitiveness
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// Case Study #3
◦ GasCom
◦ LNG Pipeline & Facility Owner
◦ Early FEED stage
◦ Project Details
◦ Readying for sanction approval
◦ Expected First Gas Date: Dec. 2013
◦ Gas sales contract already established
◦ Using Primavera P6
Schedule Acceleration/Risk Reduction
Realistic Scheduling
Critiqued
The Base
Risk-Adjusted
Optimized
Team-Aligned // S5
// S4
// S3
// S2
// S1
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// S1 > S2
◦ Sanction Board Requirements
◦ Risk-adjusted forecast P75
◦ Fuse Schedule Index 75+
◦ Project Status
◦ S1 showing Dec 13 first gas
◦ Risk assessment not yet conducted
Schedule Review
Realistic Scheduling
Critiqued
The Base
Risk-Adjusted
Optimized
Team-Aligned // S5
// S4
// S3
// S2
// S1
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// S1 > S2 Schedule Critique
◦ Validated multiple sub-projects
◦ Test to ensure true path to First Gas
◦ Analysis showed break in path around Early Works
◦ Fixing this, First Gas moved to the right by 2 months
◦ Schedule cleanse: further 3 months adjustment
Sound Basis of Schedule
May 16, 2012
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// Removal of Logic Redundancy Simplification of Schedule
8% redundancy
Removal of redundancy led to a cleaner, more robust schedule
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// S1 > S2
◦ S2 First Gas date: May 2014
◦ Schedule Critique Details:
◦ Missing Logic was added
◦ Lags converted to activities
◦ Float analysis
◦ Showed padding of early activities
Summary
Realistic Scheduling
Critiqued
The Base
Risk-Adjusted
Optimized
Team-Aligned // S5
// S4
// S3
// S2
// S1
5 months S2: May 2014 S1: Dec 2013
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// Float Analysis
◦ S1 showed high float in early stage of project
◦ S2 resolved schedule showed the opposite
◦ Early acceleration opportunity went away
GasCom
0
20
40
60
Q1 2011
Q2 2011
Q3 2011
Q4 2011
Q1 2012
Q2 2012
Q3 2012
Q4 2012
Q1 2013
Q2 2013
Q3 2013
Q4 2013
Q1 2014
Q2 2014
Q3 2014
Q4 2014 S1 Average Float S2 Average Float
Originally perceived opportunity
for making up lost time through
float absorption in early stage of
project
Resolved schedule not
offering early stage schedule
acceleration
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// S2 > S3
◦ Objective:
◦ Determine a P75 First Gas date
◦ Conducted Risk Workshop
Risk Analysis
Realistic Scheduling
Critiqued
The Base
Risk-Adjusted
Optimized
Team-Aligned // S5
// S4
// S3
// S2
// S1
Uncertainty
Risk Events
Schedule
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// GasCom Perception of Risk Exposure Risk Inputs & Outputs
0% 10% 20% 30% 40% 50% 60% 70%
Team Percep>on
Actual Risk Hotspots
Uncertainty Factor Best Case (Optimistic) Worst Case (Pessimistic) Very Conservative 50% 100%
Conservative 75% 105%
Realistic 90% 110%
Aggressive 95% 125%
Very Aggressive 100% 150%
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// Risk Insight Risk Inputs
Aggressive • Skew to the right
Conserva>ve • Skew to the lef
Broad Risk Range • Range <> dura>on
Ques>onable Range • Accidently includes risk events
No Risk • Missed ranging
Average Risk Range • Degree of uncertainty
No upside • Can only be later
No Downside • Can only be earlier
Wrong • Inputs don’t align
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//
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// Risk Insight Risk Exposure
High cri>cality • Risk indicator
Hidden cri>cal paths • Unique insight
Risk Hotspots™ • Risky & complex logic
Schedule risk drivers • True risk metric
High Con>ngency • How much buffer needed?
Average Risk exposure • Risk Trending/path
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//
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//
◦ P75 risk-adjusted First Gas: Oct 2014
◦ 10 months later than board expectations
◦ Identified key risk hot spots
◦ Long Lead procurement items
◦ Hidden path identified
◦ Driven by land acquisition delaying
pipeline early works
S2 > S3 Summary
Realistic Scheduling
Critiqued
The Base
Risk-Adjusted
Optimized
Team-Aligned // S5
// S4
// S3
// S2
// S1
S1: Dec 2013
S2: May 2014 5
S3: Oct 2014 10
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//
◦ Risk Mitigation:
◦ Response plan identified for key risks
◦ Response plans added to schedule
◦ Assessed cost/benefit of mitigation
◦ $100MM investment to save 1 month
S3 > S4 Getting back to Dec 2013
Realistic Scheduling
Critiqued
The Base
Risk-Adjusted
Optimized
Team-Aligned // S5
// S4
// S3
// S2
// S1
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//
◦ Schedule Acceleration details:
◦ LNG Pipeline ready for hookup: Feb 13
◦ LNG Facility ready to receive gas: Nov 13
◦ Focus needed:
◦ Accelerating the LNG facility
◦ Could afford to slow down pipeline/
field work by months…
S3 > S4 Getting back to Dec 2013
Realistic Scheduling
Critiqued
The Base
Risk-Adjusted
Optimized
Team-Aligned // S5
// S4
// S3
// S2
// S1
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// LNG Facility
◦ Criteria set drives acceleration
◦ Reduce duration
◦ More resources
◦ Changed calendars
◦ Contractor incentive
◦ Delay Train 2
Acceleration Criteria Set
LNG Facility
Script Objec/ve “accelerate Facility by 6
months”
Step 1 Accelerate Jeoy construc>on
Step 2 Delay Train 2 ac>vi>es
Step 3 Introduce 6 day working week/larger camp
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// How did this work?
◦ CPM simulation
◦ Critical path focus
◦ Incremental push
◦ Prioritize
◦ Earliest/latest
◦ Longest durations
◦ Least resistance
Fuse 360 Acceleration
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//
◦ LNG Facility:
◦ Accelerated sufficiently
◦ No longer the driving path
◦ S4 Deterministic First Gas: Aug 2013
◦ 4 months earlier than S1
◦ 12 months earlier than S3
◦ P75 risk-adjusted: Feb 2014
◦ S5 Team Buy-in
◦ Final 2 months achieved through more
aggressive mitigation
S3 > S4 > S5 Summary
Realistic Scheduling
Critiqued
The Base
Risk-Adjusted
Optimized
Team-Aligned // S5
// S4
// S3
// S2
// S1
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// GasCom Case Study
◦ Fully vetted, bought-into schedule
◦ Risk-adjusted
◦ LNG Facility accelerated to align with pipeline
◦ Mitigation plan sponsored by board
◦ Sanction awarded!
The Result
S4: Accelerated Aug 1 2013
S1: Target 1st Gas Dec 1 2013
S2: Resolved Schedule May 1 2014
S3: Risk-Adjusted Oct 1 2014
P75 S4: Feb 2014
S5: Mitigated Dec 1 2013
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// GasCom First Gas Dates
0
1
2
3
4
5
6
7
8
9
10
S1 -‐ base S2 -‐ resolved S3 -‐ risk-‐adjusted S4 -‐ accelerated S5 -‐ mi>gated
0
5
10
2 0
P75 Sche
dule Delay From Dec 2013 1st G
as (m
onths)
Scenario
Resolved, risk-adjusted,
accelerated, mitigated
Evolution of Schedule Model
May 16, 2012
60
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// Case Study #3
ü Float analysis
ü Risk Metrics
ü Fuse 360
Fuse Modules
// Fuse 360 Demo
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// Acceleration Efficiency™
◦ 2 day project acceleration
◦ Requires 2 days of reduction
◦ Acceleration Efficiency =2/2 100%
◦ 2 day project acceleration
◦ Requires 2 days of reduction
◦ Acceleration Efficiency=2/3 67%
Example 2
2 day project acceleration
2 day project acceleration
2 day activity reduction 2 day activity
reduction
1 day activity reduction 3
Measure of Acceleration Effort
Example 1
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// Case Study #4: Measuring Project Performance
◦ Traditional measures include: ◦ Earned value: heavy time investment to implement
◦ Earned schedule: similar to EV
◦ % complete: what does this really tell us?
◦ Ahead/behind baseline: too granular a scale…
◦ Baseline Compliance™ ◦ Determine how close schedule is executed against baseline
◦ Measure of change during planning phase
◦ Measure of well the plan is being executed
◦ More than just date comparison
◦ Looks at period-compliance
Baseline Compliance™
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// Baseline Compliance Index™
Examines how many ac>vi>es fell within the expected
repor>ng period
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// Developing Baseline Compliance Index
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// Finish Compliance Index™
0% 20% 40%
60%
80%
100%
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// Better Planning Drives Project Success Proven Correlation
0%
10%
20%
30%
40%
50%
60%
70%
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90%
100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Prob
ability of O
n-‐Time Co
mple/
on
Fuse Schedule Index™
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//
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