Engineering Productivity Measurement Research Team Engineering Productivity Measurement Research Team Bob Shoemaker BE&K Bob Shoemaker BE&K CPI Conference 2001

Engineering Productivity Measurement Bob Shoemaker BE&K Bob Shoemaker BE&K CPI Conference 2001

Engineering Productivity Measurement Research Team Bob ShoemakerBE&K, Chair John AtwellBechtel Bill BussAir Products Luh-Maan ChangPurdue University Glen HoglundOntario Hydro Duane McCloudFPL Energy Deb McNeilDow Navin PatelChemtex John RotroffU.S. Steel Ken WalshArizona State University Denny WeberBlack & Veatch Tom ZengeProcter & Gamble Bob ShoemakerBE&K, Chair John AtwellBechtel Bill BussAir Products Luh-Maan ChangPurdue University Glen HoglundOntario Hydro Duane McCloudFPL Energy Deb McNeilDow Navin PatelChemtex John RotroffU.S. Steel Ken WalshArizona State University Denny WeberBlack & Veatch Tom ZengeProcter & Gamble

Problem 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 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 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 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 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 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 Productivity Company EPC Work Process Project Overall Engineering Deliverable Individual Discipline

Levels of Productivity Company EPC Work Process Project Overall Engineering Deliverable Individual Discipline

Levels of Productivity Company EPC Work Process Project Overall Engineering Deliverable Individual Discipline

Levels of Productivity Discipline Company EPC Work Process Project Overall Engineering Deliverable Individual Company EPC Work Process Project Overall Engineering Deliverable Individual

Disciplines 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 X X X X Hours Installed Qty. Hours Installed Qty. Effectiveness Factor Project Definition Rating Index Project Definition Rating Index Project Characteristics % Field Rework Focus of Piping Pilot X X Raw Productivity Raw Productivity

Project Definition Rating Index Project Definition Rating Index Engineering Productivity Model Input Quality Factor Scope & Complexity Factor X X X X X X Raw Productivity Raw Productivity Hours Installed Qty. Hours Installed Qty. Effectiveness Factor Project Characteristics % Field Rework

Engineering Productivity Model Input Quality Factor Scope & Complexity Factor X X X X X X Raw Productivity Raw Productivity Hours Installed Qty. Hours Installed Qty. Effectiveness Factor Project Characteristics % Field Rework Project Definition Rating Index Project Definition Rating Index

Hours Installed Qty. Hours Installed Qty. Engineering Productivity Model Input Quality Factor Scope & Complexity Factor X X X X X X Raw Productivity Raw Productivity Effectiveness Factor Project Characteristics % Field Rework Project Definition Rating Index Project Definition Rating Index

Hours Installed Qty. Hours Installed Qty. Engineering Productivity Model Input Quality Factor Scope & Complexity Factor X X X X X X Effectiveness Factor Project Characteristics % Field Rework Project Definition Rating Index Project Definition Rating Index Raw Productivity Raw Productivity

Testing 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

Summary 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 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 Deb McNeilDow, Moderator John AtwellBechtel Ken WalshArizona State Tom ZengeProcter & Gamble Deb McNeilDow, Moderator John AtwellBechtel Ken WalshArizona State Tom ZengeProcter & Gamble

Implementation 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