Steve Bonacorsi's profile

What it takes to be a Good Deployment Leader

Steve Bonacorsi
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PEX Network Videocast Steven Bonacorsi Lean Six Sigma Process Excellence John Murphy deployment leader Process Excellence Awards CSX freight Transport rail train railroad transporation BPM kaizen report whitepaper free Case Study Events webinar podcast Blog interviews presentations tools templates Book Reviews forums polls Jobs promotions summits symposium conference Workshop Awards executive ben taylor ISLSS ASQ isixsigma WCBF Forrester mikel harry jim bowie Ashley Rowe Diana Davis Vanessa Lovatt International Standards for Lean Six Sigma International Quality and Productivity Center continuous improvement operational excellence change management Project Management PMP Agility toc theory of constraints sigmaxl ezsigma leansigmaedge minitab mindpro pharmaIQ FinanceIQ Supply Chain SAAS Author papers research networking community Professionals black belt Green Belt Master Black Belt MBB bb CLSS gb Yellow Belt YB White Belt Lean manufacturing lei Lean Enterprise institute IIE institute of Industrial engineers Analysis exam certification training define measure analyze improve control DMAIC DFLSS DFSS 5s Value Steam Map BMGI i-nexus 3M AB Dick Adolph Coors Advanced Micro Devices Allied Signal Alcoa Aerospace Corp Abbotts Labs Apple computer Bank of USA Beatrice Foods Bell Helicopter Boeing bristol myers squibb City of Dallas Campbell Soup Chevron Citicorp clorox danon Dow Fidelity intel Ford General Dynamics ge general electric hp Hewlett Packard honeywell kaiser aluminum Kraft General Foods Lear Astronics Lockheed Martin McDonnell Douglas motorola nasa Northrop Corp pentagon Parkview Hospital Rockwell Int Rohm and Haas Seagate Sony Star Quality texaco Texas Instruments trw US ARMY US AIR FORCE united technologies US Navy UPS Xerox Eli Lilly pfizer Universal American HERTZ GILLETTE NAVAIR NAVSUP accenture cognizant affinity diagram ANOVA Analysis of Variance statistical test Variances Attribute Data Data Discrete average MEAN arithmetic average sample values Calculated bar chart graphical Method Team Leader solving problems champion Breakthrough Improvement rate of improvement near 70% baseline performance as-is process capability operation width system actual performance width percentage Yield defect rate DPM dpmo index CP CPK PP ppk sigma score (Z) Cause and Effect Diagram pictorial diagram FISHBONE process output measure Central Tendency clustered Median support successful completion Lean Six Sigma projects accountable business roadmap Six Sigma performance span of control characteristic process input output measured and monitored Common Causes of Variation random complexity number of inputs interactions uncertainty involved Control Chart Statistical Process Control Run Chart statistically determined upper and lower Control Limits Center Line upper and lower bounds Special cause Common Cause ±3 standard deviation Correlation Coefficient linear relationship Cost of Poor Quality COPQ costs financial qualification product service capability index capability score proportion process center specification target Critical to Quality Critical X customer Cycle Time total amount of elapsed time defect time length color finish quantity temperature defective Deployment launch Implementation management Design of Experiments discipline Efficient Structured proven approach interrogating maximizing the gain system knowledge Design For Six Sigma Lean Six Sigma thinking Tools and Methods design of products release performance ongoing reliability life-cycle cost business problems data and analytical methods Defects per Million Opportunities parts per million Defects per Million (DPM) entitlement best demonstrated performance existing configuration empirical demonstration improvement potential Epislon e Greek symbol residual error experimental design Failure Mode and Effects Analysis FMEA mitigate risks Failure Modes Finance Representative independent evaluation Project Leaders Fishbone Diagram flowchart flow of activities material Gage R Quantitative assessment REPEATABILITY reproducibility measurement system total variation Black Belt projects Hidden Factory operation Corrective non-value-added histogram frequencies plotted bars Implementation Team cross-functional executive team documenting practices operating policies input resource consumed Input-Process-Output ipo input arrows Isikawa Diagram Least Squares curve-fitting squared deviations fitted curve Long-Term Variation observed variation Lower Control Limit LCL Lower Specification Limit measured quantification Measurement Accuracy repeated measurement known standard Measurement Precision Measurement Systems Analysis MSA accuracy precision obtaining measurements middle value ascending or descending order Metric key indicator of performance goals or objectives monitored Natural Tolerances of a Process Nominal Group Technique rank a list of ideas Non-Value Added nva changing the form FIT function willing to pay Normal Distribution smooth bell-shaped curve Gaussian Distribution Objective Statement opportunities out of control pattern of variation CTQ CCR Pareto Chart Bar Chart for Attribute categorical Data categories order of frequency Pareto Principle general principle Vilfredo Pareto Poka-Yoke Japanese term mistake-proof Probability Problem Statement information flow transforms Process Characterization performance capability Process Certification Process Member Process Owner responsibility Quality Function Deployment QFD customer requirements range Regression Analysis mathematical relation simple Multiple Linear Regression instrument rework Risk Priority Number RPN aggregate score severity frequency of occurrence ability to be detected Rolled Throughput Yield zero defect R.U.M.B.A Reasonable understandable measurable Believable Achievable performance over time scatter plot Screening Experiment potential factors Short Term Variation Sigma Score short-term Standard Deviation Center of a process specification limit sigma Significant Y Six Sigma Leader activities optimal results Six Sigma Project analytical tools project management techniques reporting methods management techniques powerful problem solving business improvement methodology Special Cause Variation non-random causes of variation process documentation Stability pattern of change Special Causes of variation population square root of the variance Statistical Problem Facts data analysis methods SPC continuously improving statistical control Statistical Solution data driven solution confidence risk levels supplier trend gradual systematic change TSSW Thinking the Six Sigma Way mental model cause and effect relationship Two-Level Design low and high Upper Control Limit Upper Specification Limit Variability variables variable data Continuous data meaningfully subdivided decimal subdivisions variance VOB Voice of the Business key stakeholders revenue growth market share voc Voice of the customer VOP Voice of the Process customer needs efficiency metric effectiveness metric
PEX Network Videocast Steven Bonacorsi Lean Six Sigma Process Excellence John Murphy deployment leader Process Excellence Awards CSX freight Transport rail train railroad transporation BPM kaizen report whitepaper free Case Study Events webinar podcast Blog interviews presentations tools templates Book Reviews forums polls Jobs promotions summits symposium conference Workshop Awards executive ben taylor ISLSS ASQ isixsigma WCBF Forrester mikel harry jim bowie Ashley Rowe Diana Davis Vanessa Lovatt International Standards for Lean Six Sigma International Quality and Productivity Center continuous improvement operational excellence change management Project Management PMP Agility toc theory of constraints sigmaxl ezsigma leansigmaedge minitab mindpro pharmaIQ FinanceIQ Supply Chain SAAS Author papers research networking community Professionals black belt Green Belt Master Black Belt MBB bb CLSS gb Yellow Belt YB White Belt Lean manufacturing lei Lean Enterprise institute IIE institute of Industrial engineers Analysis exam certification training define measure analyze improve control DMAIC DFLSS DFSS 5s Value Steam Map BMGI i-nexus 3M AB Dick Adolph Coors Advanced Micro Devices Allied Signal Alcoa Aerospace Corp Abbotts Labs Apple computer Bank of USA Beatrice Foods Bell Helicopter Boeing bristol myers squibb City of Dallas Campbell Soup Chevron Citicorp clorox danon Dow Fidelity intel Ford General Dynamics ge general electric hp Hewlett Packard honeywell kaiser aluminum Kraft General Foods Lear Astronics Lockheed Martin McDonnell Douglas motorola nasa Northrop Corp pentagon Parkview Hospital Rockwell Int Rohm and Haas Seagate Sony Star Quality texaco Texas Instruments trw US ARMY US AIR FORCE united technologies US Navy UPS Xerox Eli Lilly pfizer Universal American HERTZ GILLETTE NAVAIR NAVSUP accenture cognizant affinity diagram ANOVA Analysis of Variance statistical test Variances Attribute Data Data Discrete average MEAN arithmetic average sample values Calculated bar chart graphical Method Team Leader solving problems champion Breakthrough Improvement rate of improvement near 70% baseline performance as-is process capability operation width system actual performance width percentage Yield defect rate DPM dpmo index CP CPK PP ppk sigma score (Z) Cause and Effect Diagram pictorial diagram FISHBONE process output measure Central Tendency clustered Median support successful completion Lean Six Sigma projects accountable business roadmap Six Sigma performance span of control characteristic process input output measured and monitored Common Causes of Variation random complexity number of inputs interactions uncertainty involved Control Chart Statistical Process Control Run Chart statistically determined upper and lower Control Limits Center Line upper and lower bounds Special cause Common Cause ±3 standard deviation Correlation Coefficient linear relationship Cost of Poor Quality COPQ costs financial qualification product service capability index capability score proportion process center specification target Critical to Quality Critical X customer Cycle Time total amount of elapsed time defect time length color finish quantity temperature defective Deployment launch Implementation management Design of Experiments discipline Efficient Structured proven approach interrogating maximizing the gain system knowledge Design For Six Sigma Lean Six Sigma thinking Tools and Methods design of products release performance ongoing reliability life-cycle cost business problems data and analytical methods Defects per Million Opportunities parts per million Defects per Million (DPM) entitlement best demonstrated performance existing configuration empirical demonstration improvement potential Epislon e Greek symbol residual error experimental design Failure Mode and Effects Analysis FMEA mitigate risks Failure Modes Finance Representative independent evaluation Project Leaders Fishbone Diagram flowchart flow of activities material Gage R Quantitative assessment REPEATABILITY reproducibility measurement system total variation Black Belt projects Hidden Factory operation Corrective non-value-added histogram frequencies plotted bars Implementation Team cross-functional executive team documenting practices operating policies input resource consumed Input-Process-Output ipo input arrows Isikawa Diagram Least Squares curve-fitting squared deviations fitted curve Long-Term Variation observed variation Lower Control Limit LCL Lower Specification Limit measured quantification Measurement Accuracy repeated measurement known standard Measurement Precision Measurement Systems Analysis MSA accuracy precision obtaining measurements middle value ascending or descending order Metric key indicator of performance goals or objectives monitored Natural Tolerances of a Process Nominal Group Technique rank a list of ideas Non-Value Added nva changing the form FIT function willing to pay Normal Distribution smooth bell-shaped curve Gaussian Distribution Objective Statement opportunities out of control pattern of variation CTQ CCR Pareto Chart Bar Chart for Attribute categorical Data categories order of frequency Pareto Principle general principle Vilfredo Pareto Poka-Yoke Japanese term mistake-proof Probability Problem Statement information flow transforms Process Characterization performance capability Process Certification Process Member Process Owner responsibility Quality Function Deployment QFD customer requirements range Regression Analysis mathematical relation simple Multiple Linear Regression instrument rework Risk Priority Number RPN aggregate score severity frequency of occurrence ability to be detected Rolled Throughput Yield zero defect R.U.M.B.A Reasonable understandable measurable Believable Achievable performance over time scatter plot Screening Experiment potential factors Short Term Variation Sigma Score short-term Standard Deviation Center of a process specification limit sigma Significant Y Six Sigma Leader activities optimal results Six Sigma Project analytical tools project management techniques reporting methods management techniques powerful problem solving business improvement methodology Special Cause Variation non-random causes of variation process documentation Stability pattern of change Special Causes of variation population square root of the variance Statistical Problem Facts data analysis methods SPC continuously improving statistical control Statistical Solution data driven solution confidence risk levels supplier trend gradual systematic change TSSW Thinking the Six Sigma Way mental model cause and effect relationship Two-Level Design low and high Upper Control Limit Upper Specification Limit Variability variables variable data Continuous data meaningfully subdivided decimal subdivisions variance VOB Voice of the Business key stakeholders revenue growth market share voc Voice of the customer VOP Voice of the Process customer needs efficiency metric effectiveness metric
What it takes to be a Good Deployment Leader
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Steve Bonacorsi's profile

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Steve Bonacorsi's profile
Londonderry, NH, USA

What it takes to be a Good Deployment Leader

John Murphy, Assistant Vice President Process Excellence at rail transport company CSX, offers his views on what it takes to be a great deploymen Read More

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