1. Six-Sigma : DMAIC Cycle & Application

2. Background
Dr. Walter A. Shewhart, a statistician with Bell Laboratories, first developed the concept of a ‘continuous improvement cycle’ in the 1920’s.
This cycle, which is referred to as the PDSA cycle (or the PDCA cycle as Deming called it), consists of the following steps designed to improve a process:
Plan how to make changes in the process based on data that has been collected.
Do what you have planned on a trial basis.
Study (or Check in PDCA) the results of the trial to determine the effect of the change.
Act on the results observed by taking action or by standardizing the improvement.

3. Background
The PDSA cycle was developed to decrease the gap between process performance and customer expectations.
Unfortunately, the PDSA cycle lacks tools and methods often needed to tackle more complicated problems.

4. The Six-Sigma version of the PDSA cycle is referred to as the DMAIC process.

5. Key Steps in the DMAIC process
Phase
Define the Team
Define
Define the Problem/Opportunity
Train the Personnel .
Step one; Define the problem D phase
Step two; Characterize it M & A phases
Step three; is to Optimize I & C phases
Definition of DMAIC: Define, Measure, Analyze, Improve, and Control
Identify VOC & Convert to CTQ

6. Key Steps in the DMAIC process
Focus
Phase
Select Product or Process Key Characteristic(s); e.g..., Customer Y Y
Define Performance Standards For Y Y
Measure
Validate Measurement System for Y Y
There are some key steps in the Six Sigma DMAIC process.
The first step in the process is to look at Outputs (Y’s) to specifically determine;
What outputs should be improved
What the present levels are
Whether we are REALLY able to measure these levels accurately
How much variability there is in these levels
How much we should improve these levels
What the sources of variation are.
Establish Process Capability of Creating Y Y
Define Improvement Objectives For Y Y
Analyze
Identify Variation Sources In Y Y

7. Key Steps in the DMAIC process continued…
Validate Measurement System For xi
Establish Operating Tolerances On Vital Few xi
Discover Variable Relationships Between Vital Few xi
x1, x2, ... xn
Vital Few xi
Determine Ability To Control Vital Few xi
Implement Process Control System On Vital Few xi
Screen Potential Causes For Change In Y & Identify Vital Few xi
Control
Improve
The second step is to look at the inputs (x’s) that affect the output.
Key steps in this phase of the Six Sigma process are to;
Determine which inputs have the most effect on the output
Discover the relationship between the inputs and the output
Determine how much variability permissible in the inputs
Ensure that we can measure the inputs accurately
Determine our ability to control the inputs
Implement a process control system based upon the inputs

8. DMAIC:
If we cannot express what we know about a process in numbers, we do not know much about it.

9. D M A I C Define Characterize Measure DMAIC Analyze Improve Optimize
Control

10. Key Questions D M A I C Team Has the right team been assigned?
Have they all been trained?
Customers
Has the customer been identified (CTQs)?
Have customer needs been translated into measurable requirements?
Critical “Ys”
Does this project address a key business goal?
Problem Statement
Has problem been sufficiently defined?
Is project scope specific enough?
Timing / Results
Is completion date reasonable?
Does team have sufficiently aggressive goal? Is it fact-based (e.g. with external benchmarks)?
Six-Sigma Ideal Future State
Has team identified Six-Sigma vision for process (e.g. lot size = 1)?

11. Key Questions D M A I C Project Measures:
What are the key performance metrics of process (input, process, output)? What will be the measure of success?
Are they directly related to project scope and CTQs
Data Collection / Data Quality
What is the data collection plan?
Was a Measurement System Analysis (MSA) conducted?
Was Current State Value Stream Map completed? Was product portfolio well defined for the Value Stream?
Have other data quality issues been addressed (accuracy, calibration, linearity, and process stability)
Performance baseline
What is the current process performance?
Are there any “low hanging fruit” for improvement?
What is process entitlement?

12. D M A I C Key Questions Data Analysis: Root Cause
Was benchmarking conducted to identify process capability?
What are the gaps between process performance and customer requirement (cycle-time, variation, inventory, cost, delivery, etc.)?
Was a Future State Value Stream Map developed?
Was a flow analysis conducted (takt, balancing, WIP, kanban)?
Were waste & variation clearly identified?
Root Cause
What are the key causes of the performance gap (Pareto, etc.)?
Were all likely causes evaluated?
Quantifying Performance Gap
Is original savings opportunity still valid?
Are there additional opportunities?
Should the project scope be revised?

13. Key Questions D M A I C Generating Solutions: Selecting Solutions
Has team generated sufficient list of possible solutions?
Was the process creative (finding “out of the box” solutions)?
Selecting Solutions
What tools were used to ensure that the best solution was selected?
Does the cost/benefit equation look right? Is too much Capital used?
Was the solution modeled or piloted for effectiveness?
Does the solution meet performance objective? What is the resulting DPM, cost, cycle time, takt time, inventory, etc.?
Designing the Implementation Plan
Was Future State Value Stream validated? Is it feasible?
Is implementation plan robust? Complete?
Has error-proofing (poke-yoke) been utilized?
Has communications been included in planning?
How will the organization know that the plan has worked (i.e. metrics, visual controls, process changes)?

14. Key Questions D M A I C Control Strategy: Process Monitoring
What specific tools will be used to ensure process control (Poke Yoke, SPC, work procedures, inspection/test, automation)?
Process Monitoring
Is a robust monitoring in place? How often? What data? What is the data collection technique? Where in the process?
Feedback & Corrective Actions
What is the signal to indicate performance beyond desired level?
Is a strong corrective action process in place to ensure results?
Transfer of ownership
How will day-to-day responsibilities be transferred to process owner?
What is the recommended audit cycle?
What is the process-level KPI (e.g. changeover time)? Who, specifically, owns this KPI? What is the review cycle?
What is the financial KPI (e.g. cost per transaction, expense-ending cost). Who, specifically, owns this KPI? What is the review cycle.

15. Leadership of DMAIC
The power of DMAIC is in the appropriate and rigorous use of the methodology.
Conclusions
Every business problem can be addressed through the DMAIC process ---do not accept that DMAIC is too complex or too simple.
Complex processes may need a multi-generation plan & several DMAIC projects to achieve full potential.
DMAIC, like other problem solving methodologies, is only as good as the people who use the tool. Six-Sigma Experts, Mentors, and Champions need to know when and how to apply the approach

16. What to look for: Leadership
Priorities
What are the Y’s?
Does each Y have a specific metric and goal?
Projects:
Is there a clear set of projects which collectively meet the goal for each Y?
Staffing
How many Full-time Expert2s/BB’s are in place? Is this sufficient to address all of the projects?
Is there an Project Member training plan sufficient to staff all projects?
Results
What are the YTD Six-Sigma cost savings?
What are the YTD results against each Y metric?
Involvement:
How many hours per week are spent by leader reviewing projects:
In-process projects (DMAIC status)
Completed projects (process KPI, financial KPI)