REMINDER

Check in on the

COLLABORATE mobile app

Mitigating Cost and Schedule Risk With Oracle Primavera Risk Analysis

Prepared by:

Eric Torkia, MASc

Executive Partner – Analytics Practice

Technology Partnerz Ltd.

How to get results through better risk analysis

Session ID#: 15461

Technology Partnerz Ltd. provides strategy, business analysis, solution

selection and organizational change management support for the rapid

adoption of predictive analytics tools and practices in a variety of business

functions, sectors and industries.

A little about us.

We support our clients in improving decisions and business outcomes by

providing:

Success in analytics is more than just software and geeks…

Who we do it for…

Eric Torkia MASc is a senior management consultant/trainer and

business analyst. He has collaborated with some of the worlds

most recognized organizations to ensure the optimal design and

delivery of enterprise systems, analytics as well as new forecasting

and decision making processes. His skills and expertise include:

Meet your presenter: Eric Torkia, MAsc

• Project Risk Analysis, Project Feasibility and Financial Valuations for projects of over 1+ billion dollars.

• Project Feasibility and Financial Valuations

• Portfolio Optimization

• Supply Chain Modeling and Risk Analysis

• Organizational Change Management consulting, training and instructional design

• Time Series Forecasting

• Spreadsheet Modeling and VBA automation for simulation, forecasting and optimization

• Certified Monte Carlo Simulation and Optimization Trainer & Consultant for Oracle Crystal Ball, Vose ModelRisk, Palisade @Risk, Frontline Solver

SOME NOTABLE CLIENTS

How can risk analysis translate into ROI?

■ Averages vs. Range Estimates

■ Challenges and opportunities that risk analysis and simulation address?

■ How to make better decisions with risk information

BEWARE OF Averages

AVERAGES Conceal Risk

Range estimates address hidden risk

-20 345 47 335

Single-Point Estimate

More information, Better decisions

142.5K

Ranges show the full spectrum of possibilities

116.25K

Range informationProbability of occurrence

Or this one?Would you pick this project?

Only ranges can describe risk

■ Definition: Ranges define a range of potential occurrences and are necessary to obtain and communicate more meaningful and relevant information.

■ Where to start? Range Estimates…

▪ Can and should be derived from historical data

▪ Can be known statistical distributions

▪ Can be estimated by experts using 2 or 3 points (Min, Max and

Most-Likely)

Simulation models for better decisions require ranges as inputs

Analytics to improve project process performance

■ More than 50% of projects fail to meet EXPECTATIONS!

■ Why are so many projects challenged?

■ The cost of challenged projects

■ How can we break the 50% barrier?

■ Other barrier crashing opportunities

More than 50% of projects fail to meet EXPECTATIONS!

Sources: http://www.ibm.com/developerworks/rational/library/feb06/marasco/index.html, http://www.softwaremag.com/L.cfm?Doc=newsletter/2004-01-15/Standish, http://www.softwaremag.com/archive/2001feb/CollaborativeMgt.html

Simulation and Optimization WILL improve project success

Recent Trends from the Chaos Report …

“Initial cost and schedule estimates for major projects have invariably been over-optimistic. The risk that cost and schedule constraints will not be met and cannot bedetermined if cost and schedule estimates are given in terms of single points ratherthan distributions.” – Final Report of the USAF Academy Risk Analysis Study Team, August 1971

Trend State

Successful: The project is completed on time and on budget, with all features and functions originally specified.

Challenged: The project is completed and operational, but overbudget, late, and with fewer features and functions than initially specified.

Failed: The project is canceled before completion, or never implemented.

Without taking into account risks and probabilities, it is impossible to :

■ Identify truly Critical Tasks and Resources

■ Set appropriate funding and budget levels from the beginning

■ Understand the factors that drive potential delivery dates to better manage risk

Why are so many projects challenged?

Plan for budget AND schedule risk using simulation

■ Costly rework

■ Slow down project execution

■ Makes managing scope creep very difficult

■ Higher project failure rates

■ Diminished returns and benefits

■ Negative impact on the project team’s credibility

the cost of challenged projects

Addressing risk saves money and builds credibility

The 50% Barrier for challenged projects

•Cost Assessments

•Time-to-Replacement

•Failure Modes

Estimation

•Resource Costs

•Labor

•Critical Path Analysis

•Identify Resource Constraints

Project Plan(s)•Consolidated Project Financials

•NPV & IRR Analysis

•Go/No Decisions

•Success Criteria

•Real Options

Capital Projects

•Execution Scenarios

•Consolidated view of all projects

•Resource Constrained Strategies

•Optimization

Portfolio Plan

How can we break the 50% barrier?

Operational Tactical Strategic

BUILD PLANNING

Operational Tactical Strategic

EXECUTE PLANNING

By leveraging risk analysis opportunities in both the planning & execution processes

Other barrier crashing opportunities

■ Project Feasibility

■ Project Selection

■ Bid Analysis

■ Project Scheduling

■ Resource Planning

■ Risk Identification

■ Project Financing

■ …

■ Critical Path Optimization

■ Benefits and Valuations

■ Asset Management & Replacement Strategies

■ R&D and Software Development Projects

And many, many more…

Simulation – where the rubber hits the road

■ Introduction to the concepts of Monte-Carlo Simulation

■ How does simulation fit in with the business?

■ Enhancing the modeling process with simulation and optimization

■ Case and Example Simulation

■ Quantify the effects of variation in your current “as-is” scenario

■ Predict a scenario’s probability of occurrence

■ Identify critical input variables that drive uncertainty or variability in your project plan

■ Determine an optimum and robust solution for your new “to-be” planning scenarios

What do simulation analytics do?

X3

2

1

PRA’s Monte-Carlo approach

Primavera Risk Analysis is a tool that facilitates simulation, sensitivity, statistical and analysis of complex project plans from most leading Project Management Systems.

Distributions are applied to costs, time, and resources in

Primavera Risk Analysis

InputsOutputs

Data

Finish Date of:

Entire Plan

Analysis

Simulation: Latin Hypercube

Iterations: 1000

Convergence at mean

Mean Plan Finish Date:

Converged in 200 iterations

(variation < 1% over 100 iterations)

Mean Total Plan Cost:

Converged in 200 iterations

(variation < 1% over 100 iterations)

Statistics

Minimum: 04 Oct 02

Maximum: 29 Oct 02

Mean: 15 Oct 02

Std Deviation: 4.037

Bar Width: day

Highlighters

50% 16 Oct 02

Deterministic 3%

50% 16 Oct 02

80% 18 Oct 02

04 Oct 02 09 Oct 02 14 Oct 02 19 Oct 02 24 Oct 02 29 Oct 02

Distribution (start of interval)

0

20

40

60

80

100

120

140

Hit

s

0% 04 Oct 02

5% 09 Oct 02

10% 10 Oct 02

15% 11 Oct 02

20% 11 Oct 02

25% 14 Oct 02

30% 14 Oct 02

35% 14 Oct 02

40% 15 Oct 02

45% 15 Oct 02

50% 16 Oct 02

55% 16 Oct 02

60% 16 Oct 02

65% 17 Oct 02

70% 17 Oct 02

75% 17 Oct 02

80% 18 Oct 02

85% 18 Oct 02

90% 21 Oct 02

95% 22 Oct 02

100% 29 Oct 02

Cu

mu

lati

ve F

req

uen

cy

House ConstructionEntire Plan : Finish Date

18%

22%

22%

22%

22%

26%

30%

33%

39%

49%0120 - ROOF FINISH

0100 - ROOF TRUSSES

0080 - BRICKWORK

0160 - Wall B

0220 - SNAGGING

0200 - DECORATE

0190 - FINISH PLUMBING

0090 - INSTALL WINDOWS

0150 - Wall A

0170 - Wall C

House ConstructionDuration Sensitivity: Entire Plan - All tasks

05 Oct 02 07 Oct 02 09 Oct 02 11 Oct 02 13 Oct 02 15 Oct 02 17 Oct 02 19 Oct 02 21 Oct 02 23 Oct 02 25 Oct 02 27 Oct 02 29 Oct 02

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Cu

mu

lati

ve P

rob

ab

ilit

y

Distribution Analyzer

House Construction - Entire Plan - Finish Date

A Project Plan

• Using traditional

forecasting methods to

establish a base case

using historical data

• What-If Analysis on

Extreme Cases

Time Series Forecasting

Typical project planning process

Traditional analysis

stops here!

AB CDE

TOOLS

ACTIVITIES

PROCESS

• Meetings with SMEs &

Stakeholders

• Define problem and

Model objectives

• Obtain planning logic

• Establish sources for

historical data

• Based on the feedback

and material provided

in the previous step,

develop a preliminary

model

What-If Analysis

DefineProject

Objectives

Develop a project plan

Base case projections

Risk enabled planning process

Define Assumptions & Forecasts

Dynamic Monte-Carlo Simulation

Planning Optimization

Update Analysis and Build Reports

TOOLS

ACTIVITIES

PROCESS

Primavera Risk Analysis

• Meetings with SMEs &

Stakeholders to build a

model

• Document business

assumptions/rules +

build assumptions using

historical data

• ID model drivers and

influences

• Assess model behavior,

risk and volatility

• Model Validation

• Refine project strategy

using risk information

• Assess additional time

and budget scenarios

• Generate/Update

analysis

• Build risk reports

18%

22%

22%

22%

22%

26%

30%

33%

39%

49%0120 - ROOF FINISH

0100 - ROOF TRUSSES

0080 - BRICKWORK

0160 - Wall B

0220 - SNAGGING

0200 - DECORATE

0190 - FINISH PLUMBING

0090 - INSTALL WINDOWS

0150 - Wall A

0170 - Wall C

House ConstructionDuration Sensitivity: Entire Plan - All tasks

Data

Finish Date of:

Entire Plan

Analysis

Simulation: Latin Hypercube

Iterations: 1000

Convergence at mean

Mean Plan Finish Date:

Converged in 200 iterations

(variation < 1% over 100 iterations)

Mean Total Plan Cost:

Converged in 200 iterations

(variation < 1% over 100 iterations)

Statistics

Minimum: 04 Oct 02

Maximum: 29 Oct 02

Mean: 15 Oct 02

Std Deviation: 4.037

Bar Width: day

Highlighters

50% 16 Oct 02

Deterministic 3%

50% 16 Oct 02

80% 18 Oct 02

04 Oct 02 09 Oct 02 14 Oct 02 19 Oct 02 24 Oct 02 29 Oct 02

Distribution (start of interval)

0

20

40

60

80

100

120

140

Hit

s

0% 04 Oct 02

5% 09 Oct 02

10% 10 Oct 02

15% 11 Oct 02

20% 11 Oct 02

25% 14 Oct 02

30% 14 Oct 02

35% 14 Oct 02

40% 15 Oct 02

45% 15 Oct 02

50% 16 Oct 02

55% 16 Oct 02

60% 16 Oct 02

65% 17 Oct 02

70% 17 Oct 02

75% 17 Oct 02

80% 18 Oct 02

85% 18 Oct 02

90% 21 Oct 02

95% 22 Oct 02

100% 29 Oct 02

Cu

mu

lati

ve F

req

uen

cy

House ConstructionEntire Plan : Finish Date

Risk Strategy

Adding variance in your projectEstimation

Project Plan(s)

Capital Budget

Portfolio Plan

Mgmt. Questions

• Does my scheduling plan work?

• How long will my project take?

• What are the biggest drivers I should be planning for?

• What is real critical tasks?

Recommended Best Practice in the PMBOK

Estimating cost / budgets with risk

Management

Questions

• How much should I budget for contingency?

• Which work package is the riskiest?

• Will this impact my planning?

EstimationProject Plan(s)

Capital Budget

Portfolio Plan

Probabilistic cash flows

Mgmt. Questions

• What is the impact of my project budget on IRR?

• How likely is it that I will beat 15% IRR Hurdle Rate

• What are the biggest drivers I should be planning for?

• How will NPV look over time?

EstimationProject Plan(s)

Capital Budget

Portfolio Plan

+ &

Project Portfolio Modeling

Mgmt. Questions

• What Project Portfolio will give me the highest NPV

• What is the riskiest / high returns portfolio?

• What is the safest portfolio?

EstimationProject Plan(s)

Capital Budget

Portfolio Plan

Project Portfolio Management

+ &

Contact US

550 Sherbrooke St. W., West Tower, Suite 1650Montreal, Qc., CanadaH3A 1B9

888-879-8440 / 514-278-2221(Sales & Customer Support)

www.technologypartnerz.com

Please complete the session evaluationWe appreciate your feedback and insight

You may complete the session evaluation either

on paper or online via the mobile app