engineering productivity measurement research team engineering productivity measurement research...

Engineering Productivity Measurement


Research Team


Research Team

Bob ShoemakerBE&K

Bob ShoemakerBE&K

CPI Conference 2001


Bob Shoemaker

BE&K

Bob Shoemaker

BE&K

CPI Conference 2001

Engineering Productivity Measurement Research Team

Engineering Productivity Measurement Research Team

Bob Shoemaker BE&K, ChairJohn Atwell BechtelBill Buss Air ProductsLuh-Maan Chang Purdue UniversityGlen Hoglund Ontario HydroDuane McCloud FPL EnergyDeb McNeil DowNavin Patel ChemtexJohn Rotroff U.S. SteelKen Walsh Arizona State UniversityDenny Weber Black & VeatchTom Zenge Procter & Gamble

Bob Shoemaker BE&K, ChairJohn Atwell BechtelBill Buss Air ProductsLuh-Maan Chang Purdue UniversityGlen Hoglund Ontario HydroDuane McCloud FPL EnergyDeb McNeil DowNavin Patel ChemtexJohn Rotroff U.S. SteelKen Walsh Arizona State UniversityDenny Weber Black & VeatchTom Zenge Procter & Gamble

Problem StatementProblem Statement

• Engineering productivity measurement is a critical element of project performance

• Present practices do not work well in driving the improvement that today's design tools offer

• Surprisingly little effort has been expended in the engineering productivity arena

• Engineering productivity measurement is a critical element of project performance

• Present practices do not work well in driving the improvement that today's design tools offer

• Surprisingly little effort has been expended in the engineering productivity arena

Research ObjectivesResearch Objectives

• Determine present practices and why they do not work well

• Find productivity improvement success stories in other industries and learn from them

• Develop an Engineering Productivity Model that addresses shortcomings of present methods

• Test new model with pilot study

• Develop implementation plan

• Determine present practices and why they do not work well

• Find productivity improvement success stories in other industries and learn from them

• Develop an Engineering Productivity Model that addresses shortcomings of present methods

• Test new model with pilot study

• Develop implementation plan

Productivity LiteratureProductivity Literature

• Focuses on manufacturing, construction

• Little on engineering profession

• Biased toward tools or techniques

• Abundance of conclusions; lack of data

• Service professions focus on profit-based measures

• The software industry approach has applicability to engineering

• Focuses on manufacturing, construction

• Little on engineering profession

• Biased toward tools or techniques

• Abundance of conclusions; lack of data

• Service professions focus on profit-based measures

• The software industry approach has applicability to engineering

Software IndustrySoftware Industry

Lines of Code/hour did not work well

• Defined clear starting point

• Adjusted for complexity

• Adjusted for defects

• Developed standardized scoring system

• This proven methodology has driven significant improvement in the software delivery process

Lines of Code/hour did not work well

• Defined clear starting point

• Adjusted for complexity

• Adjusted for defects

• Developed standardized scoring system

• This proven methodology has driven significant improvement in the software delivery process

Present PracticesPresent Practices

Most companies:

• Track production of drawings and specifications versus budget

• Use % TIC as target engineering budget

• Use earned value concept in some form

• Have no uniform system of measurement

Most companies:

• Track production of drawings and specifications versus budget

• Use % TIC as target engineering budget

• Use earned value concept in some form

• Have no uniform system of measurement

Problems with Present Practices

Problems with Present Practices

• Lack of standards for format and content

• Difficulty in tracking actual effort dedicated to each deliverable

• No correlation between number of deliverables and installed quantities or effectiveness

• Computer-based tools:- Schematics and specs from database

- Physical drawings replaced by models

• Lack of standards for format and content

• Difficulty in tracking actual effort dedicated to each deliverable

• No correlation between number of deliverables and installed quantities or effectiveness

• Computer-based tools:- Schematics and specs from database

- Physical drawings replaced by models

Levels of ProductivityLevels of Productivity

Company EPC Work Process

Project

Overall Engineering

Deliverable

Individual

Discipline

Levels of ProductivityLevels of Productivity

Discipline


Project

Overall Engineering

Deliverable

Individual


Project

Overall Engineering

Deliverable

Individual

DisciplinesDisciplines

1.Civil/Structural

2.Architectural

3.Project Management

4.Procurement

5.Mechanical

6.Piping

7.Chemical Process

8.Mechanical Process

9.Electrical

10. Instrument/Controls

1.Civil/Structural

2.Architectural

3.Project Management

4.Procurement

5.Mechanical

6.Piping

7.Chemical Process

8.Mechanical Process

9.Electrical

10. Instrument/Controls

Engineering Productivity Model


Input Quality Factor


Scope & Complexity

Factor

Scope & Complexity

FactorXX XX

Hours Installed Qty.


Effectiveness Factor


ProjectDefinitio

nRatingIndex

ProjectDefinitio

nRatingIndex

Project Characteristic

s


s

% Field Rework% Field Rework

Focus of Piping Pilot

XXRaw

Productivity

RawProductivit

y

ProjectDefinitio

nRatingIndex

ProjectDefinitio

nRatingIndex





Scope & Complexity

Factor

Scope & Complexity

FactorXX XX XX

RawProductivit

y

RawProductivit

y






s


s






Scope & Complexity

Factor

Scope & Complexity

FactorXX XX XX

RawProductivit

y

RawProductivit

y






s


s


ProjectDefinitio

nRatingIndex

ProjectDefinitio

nRatingIndex







Scope & Complexity

Factor

Scope & Complexity

FactorXX XX XX

RawProductivit

y

RawProductivit

y




s


s


ProjectDefinitio

nRatingIndex

ProjectDefinitio

nRatingIndex







Scope & Complexity

Factor

Scope & Complexity

FactorXX XX XX




s


s


ProjectDefinitio

nRatingIndex

ProjectDefinitio

nRatingIndex

RawProductivit

y

RawProductivit

y

Testing the Modelfor Piping DisciplineTesting the Model

for Piping Discipline

Projects analyzed: 40

Objectives- Screen for dominant influence factors- Verify input/output correlation for hrs/ft

Results- Established number of equipment pieces as a

dominant scope/complexity variable- Established good correlation between hrs/ft

and dominant variable

Learning- Valuable data is being ignored in detail

design phase of projects

Projects analyzed: 40

Objectives- Screen for dominant influence factors- Verify input/output correlation for hrs/ft

Results- Established number of equipment pieces as a

dominant scope/complexity variable- Established good correlation between hrs/ft

and dominant variable

Learning- Valuable data is being ignored in detail

design phase of projects

SummarySummary

This quantity-based model:

• Addresses shortcomings of present methods

• Allows progress tracking with present engineering tools

• Engineering and Construction on same project control basis

• Focuses engineering effort on capital investment

• Uses data already collected for construction productivity

• Is applicable to all industries and project types.

• Will continuously improve with use

This quantity-based model:

• Addresses shortcomings of present methods

• Allows progress tracking with present engineering tools

• Engineering and Construction on same project control basis

• Focuses engineering effort on capital investment

• Uses data already collected for construction productivity

• Is applicable to all industries and project types.

• Will continuously improve with use

What’s NextWhat’s Next

• Call to companies with expertise and interest in this previously neglected arena

• Develop detailed models for each discipline

• Implement on projects

• Industry use of standardized system for internal improvement and external benchmarking

Stake goes well beyond engineering cost

• Call to companies with expertise and interest in this previously neglected arena

• Develop detailed models for each discipline

• Implement on projects

• Industry use of standardized system for internal improvement and external benchmarking

Stake goes well beyond engineering cost

Implementation Session Panel

Implementation Session Panel

Deb McNeil Dow, Moderator

John Atwell Bechtel

Ken Walsh Arizona State

Tom Zenge Procter & Gamble

Deb McNeil Dow, Moderator

John Atwell Bechtel

Ken Walsh Arizona State

Tom Zenge Procter & Gamble

Implementation SessionImplementation Session

• Learn how the software industries’ experience validates the approach

• See what benefits to effective project delivery the future holds

• Learn the many different ways you can contribute to a significant improvement step in the EPC industry

• Learn how the software industries’ experience validates the approach

• See what benefits to effective project delivery the future holds

• Learn the many different ways you can contribute to a significant improvement step in the EPC industry

engineering productivity measurement research team engineering productivity measurement research...

Documents

engineering profession

target engineering budgetuse

significant improvement

installed quantities

track production of

software industry approach

profitbased measures

database physical drawings