SDPM in Brazil - 2007

PMI COS 5th Conference, May 4-7 2008, Chicago

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The Application of Success Probabilities, Success Driven Project Management, and Some Critical Chain ConceptsTo the Oil & Gas Industry in Brazil

Russell D. Archibald, USAVladimir Liberzon, Russia

Peter Berndt de Souza Mello, Brazil


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Presentation Outline The Need to Manage Uncertainties Success Driven Project Management/SDPM

Methodology Unique Features of SDPM Comparison with Critical Chain Monte Carlo versus using 3 point

estimates Experience to date in Brazil Conclusions


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THE NEED FOR MANAGING UNCERTAINTIES, RISKS, & RESOURCE

RESTRICTIONS IN PROJECTS

These occur in all complex projects The need is to identify, monitor and

control risks and resources They must be reflected in plans &

schedules Methods to accomplish this developed in

Russia are now being applied in Brazil (and 21 other countries


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Success Driven Project Management (SDPM)

Planning Stage: Calculate finish dates & costs with the

required probabilities of their successful

achievement

Determine the Resource Critical Path/RCP

Set target dates, costs & other restrictions

Calculate success probabilities

Determine contingency reserves


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Success Driven Project Management (SDPM)

Execution and Control: Calculate current probabilities of

achieving goals

Track success probability trends

Manage contingency reserves


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Resource Critical Path/RCP

True (resource) critical path must reflect ALL schedule constraints: resource, finance, supply, calendar, & imposed dates

All constraints must be considered in both forward & backward passes


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Success Probability

1. System forecasts resulting required resources & contingency reserves based on user defined acceptable probability of success to meet specific scope, schedule & cost targets

2. System calculates the probability of meeting imposed targets (success probabilities)


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Eight Integration Methods Used

1. Systematic scope definition (several indentured structures/WBS)

2. Network planning (CPM/PDM)3. Resources:

• Consumable, renewable, utilized & produced• Units, teams/crews, interchangeable units or

crews• Assigned to project activities• Constraints in both forward & backward

passes


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Eight Integration Methods (Cont’d)

4. Activity durations calculated: scope or volume ÷ rate using range estimates with or without Monte Carlo

5. True (resource) critical path calculated:• Logical & schedule constraints• Resource, financial & supply limitations in

both the forward and backward passes


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6. Risk & uncertainties simulated: probability distribution for main project results (project & its main phases finish dates, costs, resource requirements)

7. Actuals reported & compared, contingency reserves tracked


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8. Current probabilities of success calculated and trends determined for:

Schedules Costs Resources


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Methods Unique to SDPM

• Multiple breakdown structures• Resource information & analysis• Activity duration calculated or estimated• Resource critical path, resource floats, &

resource contingency reserves• Risk simulation & success probability

analysis• Success probability trends predicted and

tracked


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SDPM versus CCM Resource Critical Path:

All schedule constraints Activity & resource

assignment reserves Total floats: forward &

backward passes Different ‘drum

resources’ for various project phases

Critical Chain: One ‘schedule drum

resource’ defines the ‘schedule constraint’ and one ‘critical chain’

Resource-leveled schedule set first, then determine the ‘critical chain’


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SDPM versus CCM (cont’d) Many potential RCPs

and paths with small floats may exist

‘Feeding buffers’ not necessary:

Don’t ‘protect’ any chain/path

Project time and resource buffers, yes: ‘contingency reserves’

CC is the only single sequence that shall not change during project execution

‘Feeding buffers’ may postpone planned dates, creating holes in CC


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SDPM versus CCM (cont’d) Risk Evaluation & Prediction Monte Carlo or

range estimates Predict user

defined success probabilities to meet targets

Project buffers Recommend

using optimistic schedule dates

CCPM recommends using 50% probability duration, all extra time at end of CC: chain buffer

CC “shall never change”

CC says nothing about cost!


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SDPM versus CCM (cont’d) Progress Evaluation & Decision Making Project

performance and buffer usage monitored by trends in success probabilities

Up = good New risks are

included as they occur

Buffer usage estimated qualitatively

Approach is linear No quantification Nothing on cost


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SDPM versus CCM (cont’d) Project Portfolio Management Planned as one

large project Projects in Portfolio

may have different priorities for resource allocation

Simulate performance using portfolio success prob. trends

Projects in a portfolio shall be pipelined to avoid multi-tasking

Priorities not discussed


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SDPM versus CCM (cont’d) Periodic Schedule & Cost Performance Evaluation SDPM approach

based on regular recalculations of project and portfolio schedules, costs, and success probabilities and their trends

Recalculations shall be minimized

Regular adjustment of schedule is “firefighting”

“People are free to finish the work as soon as possible”


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MC vs Using 3 Estimates: Inputs

Monte Carlo: 3 estimates

made, prob. distributions assumed

Risk events ID’d, prob. Estimated

Conditional links may be used

Using 3 Estimates: 3 estimates

made, durations and costs

Opt. 10% Most prob. Pess. 90%


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MC vs Using 3 Estimates: Process Methods Project execution

simulated many times, activity durations and risk events via random number generator

Prob. curve set by number of cases for each duration

3 scenarios calculated with res. leveling & budgeting

Prob. distr. set via predetermined curve

Any reasonable shape may be used


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MC vs Using 3 Estimates: Completion Date Project finish date

set to match desired probability under the defined distribution curve

The same


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MC vs Using 3 Estimates: Progress Evaluation Repeat process

periodically, plot success prob. Trends Rising trend=good Falling trend=bad

The same


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MC vs Using 3 Estimates: Pro More accurate Can show

complex curves with more than one max

Fast and precise Distribution may

not be correct but results are repeatable, with consistent errors

Success prob. trend analysis is accurate


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MC vs Using 3 Estimates: Cons Time consuming If activities are

performed by same resources, results are not accurate

Corrective actions are not reflected in the simulations; results not accurate

Estimations are less accurate

Merge bias: see next slides


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MC vs Using 3 Estimates: Using a Summary Model For large projects

people sometimes use a summary network

This loses links between activities, cannot simulate resources properly, produces low accuracy

Summary networks not required


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MC vs Using 3 Estimates: Merge Bias Question Exists when using

summary models Many paths

merging at the end Merge bias within

summary tasks not considered

Corrective actions cannot be modeled

Merge bias inside the project is ignored

Merge bias within a portfolio is considered

Not important: success probability trends are useful and accurate


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The Russian Approach to Project Planning

Soviet Union roots Universal coding system “Scientific Work Organization” Use of norms and standards Emphasis on resource planning

and schedule optimization

Is this the real critical chain ?(Photo in Amazon, enjoying a couple of days off the Urucu/Manaus Project – Peter Mello,

2007)

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Experience to Date:SDPM & RCP in Brazil First known application of SDPM

happened at Urucu/Manaus Pipeline in October 2006 The project had started in 2004 and was

facing major delays due to a segmented view of the project, with several separated set of schedules for different regions (geographic division) and different areas (scope, costs, logistics and supplies).


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Experience to Date:SDPM & RCP in Brazil First known application of SDPM happened

at Urucu/Manaus Pipeline in October 2006 An integrated schedule and the use of

simulations with resource restrictions helped Petrobras to criticize and complement new contractors’ plans for project recovery, with significant gains in productivity.

Subprojects started in 2007 included requests to new contractors to apply lessons learned with the use of RCP [PMI Global 2007, Cancún]


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Slowing Down to Speed Up !!

What is expected with the adoption of Success Driven Project Management is the ability to identify what phases of the project should be delayed to make critical resources available to other critical phases, thus expanding the productivity in areas of greater working dependencies with other teams.


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Fragnets

Fragnets are modeled phases of the project that are carefully planned to be applied to the whole project.

One example is the modeling of “one km of pipeline”


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Fragnets

By using automated scheduling optimization and simulation, activities in each fragnet are reorganized to the best sequence to increase global production.


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Fragnets

Schedule optimization


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Fragnets

800 meters per day800 meters per day 1150 meters per day1150 meters per day

Slow down

Speed up


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Scheduling optimizationin a few words

Almost any network of activities can be improved if we simply try the alternatives. Jane takes 4 days to write a quality plan

and 2 days to write a communication plan for the project.

If both plans are reviewed by her boss, who spends 3 days for each document, how long does this project take ?


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9 DAYS

10 DAYS


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SDPM is expanding in Brazil

STD is an engineering company developing several projects around Brazil for oil & gas. Starting October 2007, their project managers have been receiving training in PM based on PMI best practices and SDPM application concepts. A successful five day planning project for a hot-swap in a gas

pressure reduction city-gate proved the importance of simulating schedules with corrective actions (optimistic x probable x pessimistic). After that training, all their new projects undergo a new planning phase with detailed scheduling never applied in their projects before.


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Three new projects have started in January 2008. The average size of each of these projects is twice the size of the projects they had during 2006/2007.

There are a total of 22 on-going projects with a total value of R$ 35 million (US$20.7 million) (61% of the company’s portfolio)

The three new projects surpass a total value ofR$ 22 million (US$13 million) (39% of the company’s portfolio)


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Several shared resources are still the same as the ones available for previous projects, but scheduling based in the Eight Integration Steps of SDPM has permitted portfolio resource planning with significant cost reduction.

All new projects are planned under SDPM recommendation

All on-going projects are being re-evaluated to guarantee portfolio resource sharing


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Before SDPM: Schedules had an average of 5 levels of detailing in the WBS and less than 2,000 tasks.

After SDPM: Schedules have multiple WBS, sometimes with over 9 levels

of detailing and accurate resource planning. A new “project interface phase” was introduced to reflect

activities under the responsibility of the customer and subcontractors (to guarantee immediate analysis of project deviations due to external dependencies).


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After SDPM: Acquisition of parts are planned using fragnets with

estimates for early and late deliveries. A “top-management summary schedule” with an average

of 30-50 control points is used by the PMO and customer to follow project progress.

Detailed planning now surpasses 15,000 activities Activities from many functional areas are now included in

the planning for resource critical path analysis.


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Three point estimates

Most Probable applied

Pessimistic applied

Most Probable Planning

Pessimistic

Planning

Optimistic

Planning


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Optimistic with Critical Schedule Calculated


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Success Probability


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TipicalSchedul

eThe real world

Bufferprotectio

n


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Success Probability – The paradox

As Project Managers, we want all the time and resources made available (pessimistic readiness) Over-protected projects aren’t cost effective

and we cannot afford having results behind our competitors.

Unprotected projects (single estimate) will simply take longer and be more expensive than planned, leading us to unpredictable results.


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Success Probability – The paradox

As Project Managers, we want all the time and resources made available (pessimistic readiness) Over protected projects aren’t cost effective

and we cannot afford having results after our competitors.

Unprotected projects (single estimate) will simply take longer and be more expensive than planned.

SDPM will create calculated critical schedules that willestablish the necessary balance between

cost & time effectiveness and the expected successprobability, according to goals agreed with

stakeholders.


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Conclusions

1. Effective project planning and scheduling requires the identification of the Resource Critical Path (as defined in this paper)

2. Risk management and success probability trend analysis must be integrated into daily work of project planning, scheduling, and controlling


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Conclusions (Cont’d)

3. PM maturity must be measured for PM processes and also available data banks

4. Progress evaluation through success prob. trend analysis is effective using 3 estimate approach; merge bias is not important


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Conclusions (Cont’d)

5. Monte Carlo approach has practical limitations and unknown inaccuracies when applied to summary networks

6. RCP and SDPM are proving to be practical and effective in the field in Brazil

7. Western PM software vendors should include resource constraints in both forward and backward passes for network analysis


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A Few Useful Links

http://www2.petrobras.com.br/ingles/index.asp http://www.spiderproject.com.br [go to ‘seminars’] http://www.spiderproject.ru/aboutus_e.php http://www.russarchibald.com/ [go to ‘author>recent papers’] to

download this present paper plus: Liberzon, Vladimir, and Russell D. Archibald, “From Russia with Love: Truly

Integrated Project Scope, Schedule, Resource and Risk Information,” PMI World Congress- The Hague, May 24-26, 2003;

Archibald, Russell D., Peter Berndt de Souza Mello, & Jefferson Guimarães, “The Application of SDPM, Critical Chain and Portfolio Project Management Principles to the Construction of the 670 km Urucu/Manaus (Petrobras) Pipeline,” PMI World Congress-Latin America, Cancun, MX, Nov. 12-14 2007

http://www2.petrobras.com.br/ingles/index.asp

http://www.spiderproject.com.br/

http://www.spiderproject.ru/aboutus_e.php

http://www.russarchibald.com/

Russell ArchibaldPrincipal - Archibald Associates, USA/Mexico [email protected]

Vladimir Liberzon General Director, Spider Project Team, Russia

"Vladimir Liberzon" <[email protected]>

Peter Berndt de Souza MelloDirector - X25 Treinamento e Consultoria, [email protected]


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SDPM in Brazil - 2007

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