problem solving using dmaic

The Easy Guide to Solving Problems with Six Sigma DMAIC Method

The most commonly used methodology in Six Sigma is the DMAIC process. Many use it to solve problems and identify and fix errors in business and manufacturing processes.

In this post, we will look at how to use the DMAIC process to solve problems. You will also find useful and editable templates that you can use right away when implementing DMAIC problem-solving in your organization.

• What are 5 the Steps of Six Sigma

DMAIC Process and Problem-Solving

Common mistakes to avoid when using six sigma dmaic methodology, how to use the dmaic methodology for problem solving in project management, what are the 5 steps of six sigma.

DMAIC is one of the core methodologies used within the Six Sigma framework. It is a data-driven method used to systematically improve the process. The approach aims to increase the quality of a product or service by focusing on optimizing the process that produces the output. This way DMAIC seeks to provide permanent solutions when it comes to process improvement.

It provides a structured problem-solving framework to identify, analyze, and improve existing processes. DMAIC guides practitioners through a series of steps to identify the root causes of process issues, implement solutions, and sustain the improvements over time.

Following we have listed down the 5 phases of the DMAIC process along with the steps you need to take when using it to solve problems. Different tools for each phase is provided with editable templates.

Step 1: Define the Problem

So there’s a problem that affects your customer or your company processes. In this first step of the DMAIC problem solving method , you need to focus on what the problem is and how it has affected you as a company.

There are a few steps you need to follow in this phase.

• Create a problem statement which should include a definition of the problem in quantifiable terms and the severity of the problem.

•  Make sure necessary resources such as a team leader and competent team members, and funds etc. are available at hand.

•  Develop a goal statement based on your problem statement. It should be a measurable and time-bound target to achieve.

•  Create a SIPOC diagram which will provide the team with a high-level overview of the process (along with its inputs, outputs, suppliers, and customers) that is being analyzed. You can also use a value stream map to do the same job.

•  Try to understand the process in more in-depth detail by creating a process map that outlines all process steps. Involve the process owners when identifying the process steps and developing the map. You can add swimlanes to represent different departments and actors responsible.

Step 2: Measure the Problem

In this step, you should measure the extent of the problem. To do so you need to examine the process in its current state to see how it performs. The detailed process map you created in the ‘Define’ phase can help you with this.

The baseline measurements you will need to look into in this phase, are process duration, the number of defects, costs and other relevant metrics.

These baseline measurements will be used as the standards against which the team will measure their success in the ‘Improve’ phase.

Step 3: Analyze the Problem

The analyze phase of the DMAIC process is about identifying the root cause that is causing the problem.

•  Referring to the process maps and value stream maps you have created, further, analyze the process to identify the problem areas.

•  Visualize the data you have collected (both in the ‘Measure’ phase and the analyze phase) to identify signs of problems in the processes.

•  Use Pareto charts, histograms, run charts etc. to represent numerical data. Study them with team leaders and process owners to identify patterns.

•  With the results of your process analysis and your data analysis, start brainstorming the root causes of the problem. Use a cause and effect diagram/ fishbone diagram to capture the knowledge of the process participants during the session.

 •  Using a 5 whys diagram, narrow down your findings to the last few causes of the problem in your process.

Step 4: Improve (Solve the Problem)

In this phase, the focus is on mitigating the root cause identified and brainstorming and implementing solutions. The team will also collect data to measure their improvement against the data collected during the ‘Measure’ phase.

•  You may generate several effective solutions to the root cause, but implementing them all would not be practical. Therefore, you will have to select the most practical solutions.

To do this you can use an impact effort matrix . It will help you determine which solution has the best impact and the least effort/ cost.

 • Based on different solutions, you should develop new maps that will reflect the status of the process once the solution has been applied. This map is known as the to-be map or the future-state map. It will provide guidance for the team as they implement changes.

•  Explore the different solutions using the PDCA cycle and select the best one to implement.  The cycle allows you to systematically study the possible solutions, evaluate the results and select the ones that have a higher chance of success.

Step 5: Control (Sustain the Improvements)

In the final phase of the DMAIC method , the focus falls on maintaining the improvements you have gained by implementing the solutions. Here you should continue to measure the success and create a plan to monitor the improvements (a Monitoring plan).

You should also create a Response plan which includes steps to take if there’s a drop in the process performance. With new process maps and other documentation, you should then proceed to document the improved processes.

Hand these documents along with the Monitoring plan and the response plan to the process owners for their reference.

Insufficiently defining the problem can lead to a lack of clarity regarding the problem statement, objectives, and scope. Take the time to clearly define the problem, understand the desired outcomes, and align stakeholders' expectations.

Failing to engage key stakeholders throughout the DMAIC process can result in limited buy-in and resistance to change. Ensure that stakeholders are involved from the beginning, seeking their input, addressing concerns, and keeping them informed about progress and outcomes.

Collecting insufficient or inaccurate data can lead to flawed analysis and incorrect conclusions. Take the time to gather relevant data using appropriate measurement systems, ensure data accuracy and reliability, and apply appropriate statistical analysis techniques to derive meaningful insights.

Getting caught up in analysis paralysis without taking action is a common pitfall. While analysis is crucial, it’s equally important to translate insights into concrete improvement actions. Strive for a balance between analysis and implementation to drive real change.

Failing to test potential solutions before implementation can lead to unintended consequences. Utilize methods such as pilot studies, simulation, or small-scale experiments to validate and refine proposed solutions before full-scale implementation.

Successful process improvement is not just about making initial changes ; it’s about sustaining those improvements over the long term. Develop robust control plans, standard operating procedures, and monitoring mechanisms to ensure the gains achieved are maintained and deviations are identified and corrected.

Applying DMAIC in a one-size-fits-all manner without considering the organization’s unique culture, context, and capabilities can hinder success. Tailor the approach to fit the specific needs, capabilities, and culture of the organization to enhance acceptance and implementation.

In the project management context, the Define phase involves clearly defining the project objectives, scope, deliverables, and success criteria. It entails identifying project stakeholders, understanding their expectations, and establishing a project charter or a similar document that outlines the project’s purpose and key parameters.

The Measure phase focuses on collecting data and metrics to assess the project’s progress, performance, and adherence to schedule and budget. Key project metrics such as schedule variance, cost variance, and resource utilization are tracked and analyzed. This phase provides insights into the project’s current state and helps identify areas that require improvement.

The Analyze phase involves analyzing the project data and identifying root causes of any performance gaps or issues. It aims to understand why certain project aspects are not meeting expectations. Techniques such as root cause analysis, Pareto charts, or fishbone diagrams can be used to identify factors impacting project performance.

In the Improve phase, potential solutions and actions are developed and implemented to address the identified issues. This may involve making adjustments to the project plan, reallocating resources, refining processes, or implementing corrective measures. The goal is to optimize project performance and achieve desired outcomes.

The Control phase focuses on monitoring and controlling project activities to sustain the improvements made. It involves implementing project control mechanisms, establishing performance metrics, and conducting regular reviews to ensure that the project remains on track. Control measures help prevent deviations from the plan and enable timely corrective actions.

What are Your Thoughts on DMAIC Problem Solving Method?

Here we have covered the 5 phases of  Six Sigma DMAIC and the tools that you can use in each stage. You can use them to identify problem areas in your organizational processes, generate practical solutions and implement them effectively.

Have you used DMAIC process to improve processes and solve problems in your organization? Share your experience with the tool with us in the comment section below.

Also, check our post on Process Improvement Methodologies to learn about more Six Sigma and Lean tools to streamline your processes.

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FAQs about Six Sigma and DMAIC Approaches

DMAIC and DMADV are two methodologies used in Six Sigma. DMAIC is employed to enhance existing processes by addressing issues and improving efficiency, while DMADV is utilized for creating new processes or products that meet specific customer needs by following a structured design and verification process.

• Used for improving existing processes
• Define, Measure, Analyze, Improve, Control
• Identifies problem areas and implements solutions
• Focuses on reducing process variation and enhancing efficiency
• Used for developing new products, services, or processes
• Define, Measure, Analyze, Design, Verify
• Emphasizes meeting customer requirements and creating innovative solutions
• Involves detailed design and verification through testing

Problem identification : When a process is not meeting desired outcomes or experiencing defects, DMAIC can be used to identify and address the root causes of the problem.

Process optimization : DMAIC provides a systematic approach to analyze and make improvements to processes by reducing waste, improving cycle time, or enhancing overall efficiency.

Continuous improvement : DMAIC is often used as part of ongoing quality management efforts. It helps organizations maintain a culture of continuous improvement by systematically identifying and addressing process issues, reducing variation, and striving for better performance.

Data-driven decision making : DMAIC relies on data collection, measurement, and analysis. It is suitable when there is sufficient data available to evaluate process performance and identify areas for improvement.

Quality control and defect reduction : DMAIC is particularly useful when the primary objective is to reduce defects, minimize errors, and enhance product or service quality. By analyzing the root causes of defects, improvements can be made to prevent their occurrence.

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Amanda Athuraliya is the communication specialist/content writer at Creately, online diagramming and collaboration tool. She is an avid reader, a budding writer and a passionate researcher who loves to write about all kinds of topics.

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DMAIC Model | The 5 Phase DMAIC Process to Problem-Solving

• 5 mins to read
• July 1, 2020
• By Reagan Pannell

Summary: An Introduction to DMAIC

Dmaic – the dmaic model.

The 6 Sigma DMAIC model remains the core roadmap for almost all Lean Six Sigma problem-solving approaches that drive quality improvement projects. It is used to ensure a robust problem-solving process is followed to give the best chance of the best solution being found.

A note about the structure and the approach used in this article.

Our approach to DMAIC follows Quentin Brook’s book “Lean Six Sigma & Minitab” which for anyone wishing to study Lean Six Sigma is a must for the  Green Belt Course  and the  Black Belt Course .

What is the DMAIC Model?

DMAIC is short for: Define, Measure, Analyse, Improve and Control. These are the key phases that each project must go through to find the right solution. This flow is the concept behind DMAIC Analysis of an issue and its the DMAIC cycle all projects must go through.

As you can quickly see from the 5 DMAIC phases they follow a logical sequence as we will go through in more detail below. But they also make sure you do not try to jump to implementing a solution before you have properly, defined and measured what you are going to be an improvement.

We all love to jump to solutions, but the DMAIC problem-solving structure helps us have a more rigorous approach so that we do not short cut the process and perhaps miss the best solution or perhaps implement the wrong solution as well. It can help companies better structure their problem-solving approaches and be more robust in their approach. 

DMAIC – The 5 DMAIC Process Phases

The phases throughout the DMAIC model have and can be broken down in many different ways. One of the best approaches we have found is from Opex Resources which shows how to examine the existing processes, and with a project team, and the sigma improvement process, we can solve complex issues.

DMAIC Define Phase

The purpose of the Define phase is ultimately to describe the problems that need to be solved and for the key business decision-makers to be aligned on the goal of the project. Its about creating and agreeing the project charter .

All too often, teams have identified solutions without actually defining what it is they will actually be trying to do or perhaps not do. This can lead to internal confusion and often solutions which completely miss the business requirements and needs.

• Define the Business Case
• Understand the Consumer
• Define The Process
• Manage the Project
• Gain Project Approval

We can’t solve problems by using the same kind of thinking we used when we created them” Albert Einstein Tweet

DMAIC Analyse Phase

The goal of the DMAIC Analyse phase with the lean six sigma improvement process is to identify which process inputs or parameters have the most critical effect on the outputs. In other words, we want to identify the root cause(s) so that we know what critical elements we need to fix.

During this phase, the teams need to explore all potential root causes using both analytical approaches, statistical approaches or even graphical tools such as VSM’s and Process maps to uncover the most important elements which need to be changed/fixed.

The Analyse phase can be broken down into:

• Analyse the Process
• Develop Theories and Ideas
• Analyse the Data
• and finally, Verify Root Causes 

DMAIC Improve Phase

The goal of the improvement phase is to identify a wide range of potential solutions before identifying the critical solutions which will give us the maximum return for our investment and directly fix the root cause we identified.

During this phase, the team brainstorm, pilot, test and validate potential improvement ideas before finally implementing the right solutions. With each pilot, the team can validate how well it improves the key measures they identified back in Define and Measure. When the team finally roll out the solution, the results should be seen if the right solution has been found and implemented correctly.

The Improve phase can be broken down into:

• Generate Potential Solutions
• Select the Best Solution
• Assess the Risks
• Pilot and Implement

DMAIC Control Phase

The final part of the DMAIC Model is the Control phase where we need to ensure that the new changes become business as normal and we do not revert to the same way of working as before.

During this phase, we want to ensure that we close the project off by validating the project savings and ensuring the new process is correctly documented. We also need to make sure that new measures and process KPI’s are in place and, finally that we get the business champion to sign off on both the project and the savings. We may need to redesign the workplace following the 5S principles .

The Control phase can be broken down into:

• Implement Ongoing Measurements
• Standardise Solutions
• Quantify the Improvement
• Close The Project

The key closing documents of the Control Phase is a Control Plan that documents all the changes and process steps with key risks, standard work instructions and the Project Close-Out document signed by the business owners to accept the change and the validated benefits.

Our approach to DMAIC follows Quentin Brook’s book “Lean Six Sigma & Minitab” which for anyone wishing to study Lean Six Sigma is a must for the  Green Belt Course  and the  Black Belt Course .

The dmaic model vs. a3 management vs. 8d problem solving.

The DMAIC model is not the only project management roadmap. Two others which are important is the A3 format which originally comes from Toyota and is very Lean focused and the 8D which draws more of the DMAIC structure but with the 1-page idea of the A3.

Everyone has their own preference but each method is interchangeable. The DMAIC Structure lends its self naturally to a multi-slide Powerpoint presentation. Whereas the A3 is a single-page document which is perfect for internal communication and adding into War Rooms and Control Towers.

What’s important is that every problem-solving approach follows the PDCA (Plan, Do, Check and Act) Scientific Problem Solving format. The reset is just a preference or using the right tool in the right circumstances.

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Reagan Pannell

Reagan Pannell is a highly accomplished professional with 15 years of experience in building lean management programs for corporate companies. With his expertise in strategy execution, he has established himself as a trusted advisor for numerous organisations seeking to improve their operational efficiency.

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DMAIC: The Complete Guide to Lean Six Sigma in 5 Key Steps

One of the core techniques behind any process improvement, particularly in Six Sigma, is DMAIC.

This handy approach, pronounced duh-may-ik, is the key to employing Six Sigma and beginning your journey to being a process hero. We’re going to cover each step in the process and detail how to effectively enact every section.

This guide will lead you through from start to finish and get you ready to start employing lean Six Sigma within your business!

What is DMAIC?

DMAIC stands for:

DMAIC is a data driven improvement cycle designed to be applied to business processes to find flaws or inefficiencies – particularly resulting in output defects – and to combat them. The goal of employing DMAIC is to improve, optimize, or stabilize existing processes.

The development of the DMAIC methodology is credited to Motorola , but is largely a further expansion of systems developed by Toyota. You can read more about how Toyota has employed their process improvement techniques in our article  How Toyota Saved Children’s Lives with Process Implementation .

What we’re going to do is look at each stage of the process and consider what needs to be explored and what kinds of tools and methodologies you might use throughout.

Before you dive in, consider reading this DMAIC Case Study to give yourself an overview of the process from start to finish with handy graphs. This case study should help you be able to visualize each step we undertake throughout the article within a broader context.

When do we use DMAIC?

Though we’re not formally recognizing that step within this article, it would be remiss to not appreciate the importance of this addition.

DMAIC cannot be used in all situations. It pertains to specific opportunities for process improvement.

So what are these specific conditions?

There are three main things worth considering when assessing a situation for whether DMAIC would fit:

• There is an obvious problem of some form with an existing process or set of processes.
• The potential is there to reduce variables like lead times or defects while improving variables like cost savings or productivity.
• The situation is quantifiable; the process itself involves measurable data and the results can be appropriately understood through quantifiable means.

Once you’ve recognized whether or not your process is a good fit for DMAIC, you can get started!

Define: Map the project and understand your aims

The Define stage is essentially the planning part of the exercise.

It consists of 7 key sections:

Define Customers and Requirements

How you carry out this stage depends on who your customers are. There are two subsections of customers, either internal customers or external customers .

Internal customers are levels of management within your organization or other departments who are reliant on the output of the particular process you are attempting to improve.

External customers would be the end users of your product or services. These would normally be your business clients but could also be the company’s shareholders.

We tend to divide the expectations of these customers into two related categories: needs and requirements. Needs refer to the end goals of a product: someone buys an air-conditioning unit because they want to keep a room cold. Requirements refer to features or aspects of a product: an air-conditioning unit needs to have a thermostat of some description in order to deliver the cold room the customer needs.

When judging the output of a process, we analyze who the customers are, what their needs are, and what the requirements are to fulfill these needs.

Develop Problem Statement, Goals and Benefits

The next step is to bring that customer information into actionable steps.

We want to develop a clear Problem Statement in order to communicate the purpose of the process and to help us understand how our actions will relate directly to the end results. This should not look to define the solution, but instead focus on the following aspects :

• What is the pain point?
• Where is it hurting?
• When has it been hurting? Is it long term or short?
• What is the extent of the pain?

The Six Sigma Institute provide the following example problem statement:

“In the last 3 months (when), 12% of our customers are late, by over 45 days in paying their bills (what) . This represents 20% (magnitude) of our outstanding receivables & negatively affects our operating cash flow (consequence) .”

In doing so, we should clearly define what our ultimate goals will be from the process improvement work we undertake. This might be identifying something simple like a need to increase output per hour from 100 units to 200 units. Or it might be improving clearly measurable rates of customer satisfaction or other similar quantifiable variables. In a pure Six Sigma approach, your goal would be to improve your Sigma baseline and reduce whatever your defined defects are – but we’ll come to all that later.

The goal statement should be SMART: Specific, Measurable, Attainable, Relevant and Time Bound.

The Six Sigma Institute example:

To reduce the percentage of late payments to 15% in next 3 months, and give tangible savings of 500K USD/ year.

Identify Champion, Process Owner and Team

In order for us to implement this process improvement, we need to determine the roles of different employees in bringing the project to completion. Different companies will put differing emphasis on roles, so take the following as an example as much as a definition.

If you’re familiar with lean methodologies like Scrum, this will quickly make sense to you.

The Process Owner is the person who is responsible for the process improvement project. This is the hands on position where the person involves themselves with each team involved in the process, analyzes and tracks data and output, and looks to manage the process from above from the first step to the last. The Process Owner’s primary function is to provide the planning and overview to allow everyone else to flourish.

The Process Champion is an individual within the organization who has the power to make key decisions and facilitate the work of the Process Owner. This would likely be an executive who can help allocate resources to serve the needs of the Process Owner. The Champion aims to remove barriers which the Process Owner is facing and help facilitate the process improvement project from another step above.

The team in this context are the employees who will be putting the desired changes into action and helping monitor the effects of these changes. The main person in this team is the Black Belt; the project manager for the team. The other employees who focus on the Six Sigma process might be referred to as Green Belts (at this point it starts to feel a little like a karate kid cosplay).

Define Resources

In order to undertake this process improvement project, we need to know what resources are available for the Process Owner to utilize.

This might include a budget for contracting external services, purchasing additional tools, or travel expenditures. It might also refer to how many staff will be needed in order to make this change effectively; do staff need to be brought in from other departments, or will new staff need to be hired?

The amount of resources required will be defined by the problem and goal statements. You don’t want to spend $1 million to save the company half a million. We need to understand what resources are needed to tackle the project and what resources are reasonably available.

Evaluate Key Organizational Support

Now you know what resources you need to begin the project, you need to know what support you can gather from other actors within your organization.

The Process Champion will be in charge of attempting to mobilize this support from other areas of the company. In order to do this, the Process Champion will likely try to create a Business Case.

The purpose of a Business Case is to demonstrate the importance of this process to the broader operations of the company. The Six Sigma Institute give us an example of 7 questions which a Business Case should answer:

• Why is the project worth doing? Justify the resources necessary to engage in the project.
• Why is it important to customers?
• Why is it important to the business?
• Why is it important to employees?
• Why is it important to do it now?
• What are the consequences of not doing the project now?
• How does it fit with the operational initiatives and targets?

The Institute also provides us with an example Business Case:

By reducing the average transaction length, the queue would be able to enhance the Speed of Resolution and assist the end-users in fastest possible manner. This will not only help in achieving client targets but also increase end-user satisfaction score by offering lesser turn-around time.

… although a full Business Case should include more detail and more clearly address each of the above questions.

Develop Project Plan and Milestones

We should now be in a position where we understand the different requirements, the available resources, and role allocation.

At this point, we can begin to develop a detailed project plan with attainable and realistic milestones.

The first step of our project planning is to develop our project scope. In doing so, it is useful to use both longitudinal and lateral scoping. Longitudinal scoping relates to the length of the process, whereas lateral scoping refers to the breadth.

For example, if I was to analyze the process I use to write articles, the longitudinal scope would stretch from having the idea for the article to the moment the article goes live. That’s the scope of the process I would be investigating; with a clear start and end date.

The lateral scope would be the scope of my investigation. Am I going to analyze only the process of writing this article? Am I going to analyze the process repeatedly over a period of 6 weeks? Am I going to analyze my process and the same longitudinal process of my colleagues over that period too?

Think of it as the scope of the process vs the scope of the investigation.

Once we have this in place, we can look to lay out milestones for when different key moments in the DMAIC process will be achieved. What date will we begin the first step of the Measure stage? What date will we commence the Improve stage? When will we complete the DMAIC process?

It is recommended to set aggressive milestones as efficiency savings benefit from being brought in sooner rather than later, naturally. However, setting milestones which are too aggressive can result in what’s called “band-aid” solutions; where quality is sacrificed in order to reach arbitrary targets.

Develop High Level Process Map

This will serve to demonstrate to each individual player where they fit within the process and how their role relates to the next.

You can use tools like LucidChart to help you create process maps and diagrams simply and effectively.

If you want to read more about process mapping and other in-depth process overview techniques you can read this article of ours:  BPMN Tutorial: Quick-Start Guide to Business Process Model and Notation

Measure: Gather the data to understand performance

In the next few subsections we’re going to look at some key Six Sigma terms to understand what we’re measuring, then we’ll develop a research methodology and put it into practice.

This step is all about gathering our data!

Define Defect, Opportunity, Unit and Metrics

At the beginning of the Measure stage, we need to first define what we should be measuring.

To do this, we’ll need to understand a couple of key terms :

• Unit in the Six Sigma context refers to a single item of the product. This is our smallest indivisible point of reference.
• Defect refers to a problem with the product which has arisen from an issue in the process.
• Opportunity refers to the potential points within a process where the possibility for a defect occurring is present.

Once we understand these terms, we can see how they start to fit together to help us make decisions:

• Defects per unit (DPU) : number of defects / total number of units
• Defects per opportunity (DPO) : number of defects / (number of units x number of defect opportunities per unit)
• Proportion defective (p) : number of defective units / total number of units

Work out all the possible opportunities for problems and then begin to filter that list to remove extremely rare events, or to group problems with related causes together. This should give you a workable estimation for your Opportunity.

Develop Data Collection Plan

In order for us to make the necessary calculations, we need to gather our data about the process.

To do so we will create a data collection plan which will outline our approach and help us clarify our methods.

This analysis will focus on the minutiae of what exactly we want to measure, how the data will be collected, and the methodology by which we want to handle the data, including:

• How many observations are needed
• What time interval should be part of the study
• Whether past, present, and future data will be collected

If this process improvement project is geared toward internal processes then your  customer – another department, for example – might also be gathering this data. This is useful to check because it gives you a control against which you can verify your data once it has been collected, provided any variables are taken into consideration.

The difficulty of this data collection could lie in translating the outcomes into numerical values. For a manufacturing process it is fairly straightforward to understand the process and its outcomes in numerical terms, but less grounded processes can prove trickier. This is why it is important to plan carefully at this stage.

It’s also important to note that while historical data can be used in this analysis, it will likely not have been collected via the same structures and methodologies as you’re creating in this step. This presents a problem as it de-standardizes the data; use historical data with caution.

Having a standardized data collection process gives better data and ultimately better results.

Research 101.

Validate the Measurement System

Well done, you have a research methodology!

But don’t get too excited – we’re not quite ready yet.

Like any piece of research, it is vital to test the methodology – or measurement system – before releasing it into the wild. As a researcher might conduct a pilot study, so too must we test our research methods and review them on a couple of key areas.

There are 4 specific things we want to test before we launch our data gathering project in full:

• Repeatability : If the same operator reaches pretty much the same outcome multiple times on the same item with the same equipment, we can see an adequate level of repeatability.
• Reproducibility : This becomes reproducible if multiple operators measuring the same items with the same equipment end up with the same outcomes.
• Accuracy : It’s a little trickier to be certain on accuracy, but we can broadly say that this can be seen in the difference between an observed average measurement and the associated known standard value.
• Stability : The level of stability is, in a sense, a further extension of repeatability and reproducibility. Stability can be seen by what extent the same operator gets the same outcomes from measuring the same item with the same equipment over a longer period of time. One of the things this stability check is looking for is whether there are external variables which can impact reproducibility over time.

The best way to test your measurement system is to undertake a Gage Repeatability and Reproducibility Study (GR&R), which you can read more about here in this mini library of GR&R materials from iSixSigma .

Once we’re sure that our methodology is clearly defined and we’ve validated our measurement system, we can begin to collect our data!

Collect the Data

Not too much needs to be written about the actual data collection as all the previous steps have been building up to this point.

The key thing to remember is simply to stick to your plan as you defined it and to adhere stringently to the research practices and methods which you validated.

The Black Belt should be the primary point of command in this data collection process, making sure that all procedures are adhered to. The Black Belt needs to take responsibility for all the Green Belts understanding the necessary steps, definitions, and goals.

Begin Developing Y=f(x) Relationship

This is where things will start to sound a little technical. But don’t worry, we’ll walk through it.

Think of Y as representing the output of a process. It doesn’t technically refer to Yield at this point, but we’ll come to that later on.

So, Y is the output of a process and X is the input. The f represents the function of the variable X.

Y is the output we care about and X can be multiple different variables which impact on Y. Here’s an example from iSixSigma :

For example, if you call your major department store to ask a question, the ability to have your question answered (Y) is a function (f) of the wait time, the number of people answering the phones, the time it takes to talk with the representative, the representative’s knowledge, etc. All of these X’s can be defined, measured and improved.

At this point, you don’t need to work out the Y=f(x) relationship in full, but you can start bearing it in mind. It is considered best practice to keep work oriented around the Y=f(x) formula.

Estimate the Sigma Baseline

Again, we can prepare ourselves for the future stages by running a quick calculation.

To work out your Sigma, you can calculate your Defects per Million Opportunities (DPMO) and run it through a handy conversion chart.

You calculate your DPMO by simply multiplying your DPO by a million.

To make it all easier, just use this straightforward Sigma Calculator .

Analyze: Understand where the problems in your process lie

The analysis step is where we have to dig in deep into the existing processes and work out the root causes of the problems.

Finding these causes should allow us to tackle them in our Improve stage. It’s all about finding the pertinent Xs for the Y=f(x) formula we mentioned above.

Define Performance Objectives

Having measured the process in the previous steps, we should be in a position where we roughly know what it is we want to improve.

Before we begin analyzing in depth, we should lay out what our objectives are so that these goals can guide us. Think through the process and the data you have to calculate what the key performance objectives would be.

These objectives can prove slightly flexible as your analysis moves forward but it is always better to start with clear goals.

Develop a Detailed Business Process Map

We’ve already mentioned in this article how you can use strategies like BPMN to map business processes, but it isn’t the only approach. A very similar approach might be to use an As Is Process Map, which can incorporate BPMN elements but is not defined by it.

This business process map can help show us the granular make up of the company process we are analyzing and reveal factors like which process steps are value added and which are non-value added. Identifying non-value added steps at this stage opens up the potential for us to eliminate waste in our process improvements.

This process map should be analyzed for potential areas of variation. These variations, or potentials for variation, will likely lead us to the root causes behind our Opportunities (for defects).

Determine Root Cause(s)

There are many different techniques you can utilize in order to attempt to dig down into what the root causes of a variation are, and we’re going to look at three specific examples of methods you can use:

The 5 Whys Analysis

The Fishbone Diagram

• The Pareto Chart

This is a fairly simple technique to start you off. The idea is that you ask “why?” five times to dig deep into the root of a problem. The logic behind it is that in the first few questions you will find one of the causes of the problem, and by the 5th question you will see the process failure behind that problem. This example from Wikipedia does an excellent job of conveying it:

The vehicle will not start. (the problem) Why?  – The battery is dead. (First why) Why?  – The alternator is not functioning. (Second why) Why?  – The alternator belt has broken. (Third why) Why?  – The alternator belt was well beyond its useful service life and not replaced. (Fourth why) Why?  – The vehicle was not maintained according to the recommended service schedule. (Fifth why, a root cause)

This approach takes 6 different variable categories and feeds the information together to help you visualize what factors within the business operations are contributing collectively to the same problem. One of the advantages of this method is that it forces us to view the problem holistically, rather than the potentially blinkered approach of the 5 Whys.

According to the Six Sigma Institute , the 6 key variables are:

Machine : This category groups root causes related to tools used to execute the process. Material : This category groups root causes related to information and forms needed to execute the process. Nature : This category groups root causes related to our work environment, market conditions, and regulatory issues. Measure : This category groups root causes related to the process measurement. Method : This category groups root causes related to procedures, hand-offs, input-output issues. People : This category groups root causes related people and organizations.

You might already be familiar with the Pareto Chart. The purpose of the Pareto approach for us is to understand which variations have the highest impact on our output; it helps us determine the Vital Few.

If the other techniques assist in finding variations and identifying potential root causes, the Pareto Chart allows us to prioritize which root causes to target first to have the greatest impact on improvement in relation to our stated objectives.

Determine the Y=f(x) Relationship

Once we’ve identified the Vital Few, we’re able to return to our Y=f(x) formula.

Remember, Y is simply a variable which is defined by the relationship between our Xs and their functions. So, if we want to improve Y then we should identify which X has the biggest impact on the Y value and improve that X.

Our ultimate aim is to better understand the relationship represented by this formula and to round out errors from it. For example, there may be an X which has a major impact on Y but is not due to a process problem but simply a natural or unchangeable element of the manufacturing process. In which case, we need to identify that this particular X, while important, is not one we can tackle as part of our process improvement.

Our job isn’t just to find the Xs which contribute to Y, but to find the right Xs.

Improve: Work out how defects could be reduced

The improve section of the DMAIC process is where we take advantage of all the preparatory work we’ve done so far.

Our goal here is to highlight our Xs and look to maximize the performance of those inputs. The key element of the Six Sigma approach is the importance of doing this through mathematical and scientific means.

Perform Design of Experiments

Our Design of Experiments (DOE) is probably the key step to getting this right and achieving the improvements we want to make.

This DOE approach highlights the relationships between different Xs and the output (Y). Factorial experiments are one of the crucial methods to show how different Xs can relate to each other.

Controllable input factors .

These are your Xs. These are variables within the process which we can experiment with and change. In baking a cake this might include the number of eggs or the amount of flour.

Uncontrollable input factors .

These are variables which may have arisen earlier in the investigation but we can’t act upon. In a baking scenario it might refer to the resting temperature of the kitchen. Or, to make an infrastructural analogy, the capacity of the oven – a factory might produce more goods if it was bigger, but increasing its size might be prohibitively expensive, for example.

Responses .

This is the extent to which the output services the customer needs and wants. In baking this could refer to a simple taste test. This factor, like the others, would need to be quantified. “Good or bad” is not enough; a score out of 10 from the customer averaged out as a final percentage figure from all testing would be a more effective approach.

Hypothesis testing .

In a hypothesis test there are two potential outcomes: null and alternative. A hypothesis test focuses the accuracy of a hypothesis with each test. The null hypothesis is valid if the status quo is true. The alternative hypothesis is true if the status quo is not valid. We get our results by analyzing significance which means results are based on probabilities – so get your p-values at the ready!

In baking, we might have a brand name cake mix which declares that it takes on average 30 minutes to bake. You might classify this as your hypothesis. The null hypothesis would be that the average amount of time it takes to bake this particular cake is in fact 30 minutes. But you can’t have a null hypothesis without an alternative hypothesis. You should select your alternative hypothesis in advance in order to construct the experiment properly. We have 3 choices of alternative hypotheses to choose from:

• The average time to bake the cake is not 30 minutes (not equal)
• The average time to bake the cake is more than 30 minutes (greater than)
• The average time to bake the cake is less than 30 minutes (less than)

The formula for checking whether the average baking time is 30 minutes or not would be:

Ho:μ=30  versus  Ha:μ≠30

Blocking and Replication .

Blocking and replication are fortunately much simpler concepts. Blocking is just about making sure the conditions for each experiment are the same; use the same stirrer and tray to bake the cakes with. And replication is simply the principle of running the experiment multiple times to gain more accurate results – a great excuse to bake extra cakes.

Interaction .

This refers to a situation where an experiment has three or more variables and the simultaneous influence of two of the variables on the third is not additive. Sadly, my knowledge of baking has let the analogy down on this one. My bad.

Two-Level Factorial Design

This experiment will be constructed to look at 3 variables where each can be tested at a low or high level. This kind of structure gives us the ability to investigate deeper into a process yet is still simple enough for us to see how the experiment works.

Consider our process to be baking a cake. Our three variables are the Vital Few we identified in our Analysis stage. They are:

• Brand of flour
• The temperature of baking
• The baking time

Taste-testing will be a score out of 10 with the average multiplied by 10 to give a percentage result. The crust-formation will be measured by weight with lighter crusts being the goal.

The simplest overview of ANOVA tables can be found here , and it gives us this handy summary:

It doesn’t look at the differences between pairs of group means; instead, it looks at how the entire collection of group means is spread out and compares that to how much you might expect those means to spread out if all the groups were sampled from the same population (that is, if there were no true differences between the groups).

Which means roughly that our ANOVA table on taste testing will look at how all the results impact on taste to see how each group should impact on taste and then tells us how each group performs relative to that expected impact; higher or lower impact.

All this is conveyed through the F Ratio which tells us about the levels of variance between the groups relative to the variance within the groups.

If the null hypothesis is true, then F should be close to 1. The further F is from 1 the more it suggests the alternative hypothesis to be true. In the case of our experiments, the higher F is the more important an input factor is on output.

Develop Potential Solutions

With a strong working knowledge of your business processes and systems, you’re now able to develop solutions which can tackle the key issues hindering output within the business.

The results of the DOE tests can also assist in that optimization process as the visual graph above shows. This data gathered from varying iterations of your key potential Xs, provides a series of potential avenues to explore.

When constructing the different options for solutions make sure to propose enough to test and evaluate.

These solutions should be rooted in the deep analysis you’ve undertaken.

Assess Failure Modes of Potential Solutions

Failure Modes and Effects Analysis is a method which can identify risk ahead of time. This quasi-predictive process analysis tool can help you evaluate the details of your proposed business process solutions.

You can read more about FMEA in a previous article of mine:  FMEA: The Analysis Method to Prevent the £100m British Airways Catastrophe .

Validate Potential Improvement by Pilot Studies

Lastly, to complete the Improve section of our DMAIC process, it’s important to test out the solutions which have made it to this point.

The few solutions you’re left with can be part-deployed live in controlled conditions as part of a pilot study to gage their relative effectiveness.

The Process Owner can map out the design for these pilots and the Black Belt can manage the pilots in practice.

The performance of the proposed solutions should leave you with an overall best performing process improvement solution based on output. To measure these proposed solutions effectively, try to calculate the Sigma Baseline as before.

Control: Plan out how you will implement your solutions

The Control section is all about putting processes and procedures in place to make sure the implementation of the new solution runs smoothly and can be tracked and optimized over time.

Ultimately, the rest of the DMAIC process prior to this stage was dedicated to the Xs whereas the Control stage is devoted to the Y; the output.

Standardize and Document Processes

This is the most obvious step and echoes what we always discuss in our articles on Process Street .

To implement a new process, you need to make sure each step is documented thoroughly and it is mapped out in a way which is actionable and provides space for measurement.

These processes should be consistent at all times and this can be achieved through simply standardizing approaches across teams.

Prepare Implementation Plan

This task may be planned by the Process Owner and implemented by the Black Belt, though different companies might look to do it in different ways.

The important factors here concern how the new process can be effectively integrated into the company workflow .

• What teams within the company need to adapt to suite the new process?
• Does this change need to be simultaneous or can it be rolled out iteratively?
• Do we require multiple Six Sigma advocates to embed into each team for implementation?
• What budget or resources does the Champion need to secure to ensure effective rollout?
• When does implementation begin?
• What is the target date for complete implementation of the new process?

All of these questions should be answered in the drafting of a report so that the company can act upon our DMAIC work.

Additionally, it is important to create a Response Plan which tackles the what ifs of managing the process. This would come under the realm of risk management as it looks at putting processes and procedures in place for if problems occur within the process or are seen in the output.

Implement Statistical Process Control

Once your process is standardized and documented, implementation must undergo monitoring. One industry standard approach to process monitoring is Statistical Process Control.

Statistical Process Control (SPC) was originally developed in 1924 by Walter Shewhart. It is used to monitor and control the output parameters of a process.

A short definition is given to us by InfinityQS :

Quality data in the form of Product or Process measurements are obtained in real-time during manufacturing. This data is then plotted on a graph with pre-determined control limits. Control limits are determined by the capability of the process, whereas specification limits are determined by the client’s needs.

This basically means that we gather quantifiable data about the process and look at the size of the output vs the quality of the output.

On the graph you make, you’ll set control limits. These define an acceptable range which your process should operate within. When data points start appearing outside of this range, this acts as a red flag to show us that variations are occurring.

If done properly, these red flags should catch variations before variations result in defects; allowing us to tackle process problems before they result in output or product problems.

Use DMAIC to help you reach your Six Sigma goals

Once you’ve successfully undertaken your DMAIC project, you might think your job is done.

A crucial part of any lean Six Sigma process is to keep the principle of continuous improvement in mind. Within lean philosophies we might refer to this as Kaizen. In Japanese this translates to “change for better”, but within the world of process improvement it has come to reflect a continuous iterative model for gradual change.

Once one Six Sigma project is done, it is likely time to move onto the next.

If you can reach your goal of Six Sigma then your processes will be functioning at the highest industry standards and your business will be in the best position it can be.

It’s up to you to make sure the rest of the business runs as effectively as your best processes!

Are you a Six Sigma enthusiast? Have you employed DMAIC in your business before? Let me know in the comments your experiences, tips, and tricks!

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Adam Henshall

I manage the content for Process Street and dabble in other projects inc language exchange app Idyoma on the side. Living in Sevilla in the south of Spain, my current hobby is learning Spanish! @adam_h_h on Twitter. Subscribe to my email newsletter here on Substack: Trust The Process . Or come join the conversation on Reddit at r/ProcessManagement .

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Six Sigma Certification & Training

How to use the DMAIC Methodology: 5 Steps + Example

DMAIC is a popular Six Sigma process in the world of statistics and business. There’s a good chance you’ve heard the term before, but what exactly is it? Each letter represents a particular part of the methodology. DMAIC stands for Define, Measure, Analyze, Improve, and Control.

Whether the industry is manufacturing, marketing, retail, military, or HR, Six Sigma practitioners can use the DMAIC process for improvement projects. Following the five steps allows businesses to systematically find and fix issues, ultimately boosting productivity and quality. This article will explain the DMAIC process steps and provide a DMAIC process example.

On this page:

Why the DMAIC Process is Important

5 steps in the dmaic process, dmaic process example.

The DMAIC process is important because it allows you to improve your business by creating a systematic approach for identifying problems, creating solutions, and measuring the success of your product or process improvement project.

First, the DMAIC process helps you get an overview of the situation and identify potential problems with your product or service. It’s also important to understand what success looks like in order to know how to measure it.

Second, the DMAIC process helps you look at your resources and see what you have available to tackle the problem. This will help you decide what’s feasible and what isn’t—and that’s especially important if you have a budget or timeline to stick to for improvements.

Third, the DMAIC process gives you a plan for tackling those issues so that when you’re looking at your data and making decisions about moving forward, they’re based on facts rather than feelings or assumptions.

In the DMAIC Define Phase , you will define the problem or opportunity. You’ll define what you want to improve in your process. This involves defining the goal and developing an understanding of what success will look like. You will also identify the current situation and how it compares to your desired outcome. This includes identifying any constraints or limitations and determining if there is adequate support for achieving success.

In the DMAIC Measure Phase , you will measure key aspects of the current process by collecting data to obtain quantitative evidence about its current state. You’ll compare it with the ideal state. You’ll measure defects or other metrics that indicate problems with your process. This evidence helps you identify where improvement opportunities exist to drive future actions.

In the DMAIC Analyze Phase , you will analyze the data to identify root causes. You’ll analyze trends in your data using statistical techniques such as control charts or ANOVA analysis to determine if there are any factors impacting quality that you can eliminate from your process. You may also use decision models such as Pugh charts or cause-and-effect diagrams to evaluate alternatives and select appropriate solutions for implementation.

In the DMAIC Improve Phase , you will improve the process by implementing solutions based on what you learned during the analysis. These solutions require clear specifications so they can be implemented consistently. In addition, you should document these changes in case they need to be replicated later.

In the DMAIC Control Phase , you will control the new process to prevent problems from recurring. You’ll monitor results after making improvements to ensure they are working as planned.

So how does this all come together in a real-life scenario? Let’s walk through a hypothetical scenario of how a nonprofit organization uses DMAIC methodology .

Let’s say the nonprofit company wants to increase its fundraising success with outbound calls made to clients who signed up for newsletters on their website but chose not to make an online donation.

1. Define Stage:

The company would first need to define what success looks like with outbound calls and how it will be measured.

In this case, the company aimed to increase conversion rates from 45% to 50%. The company used the length of contact and conversion metrics to define successful and unsuccessful calls. They defined a successful call as lasting longer than two minutes. Additionally, they defined conversion as when a donation was made during a call.

2. Measure Stage:

Key aspects of the call experience would then be identified and monitored.

Now that the Six Sigma project team has defined the goal and metrics, they must collect data about the successful and unsuccessful calls. In this case, the company created a process map to understand the current process. They recorded data regarding several factors, such as the script used during the call, the time of day the outbound team made the call, and how much time had passed since the user had signed up for the newsletter before the outbound team made the call.

The project team brainstormed potential explanations for the unsuccessful calls. The conversion rate was the primary metric, so a fishbone diagram was utilized to depict the link between the many factors at play.

3. Analyze Stage

Data would be collected and analyzed to identify any areas where the calls were more likely to lead to a successful call or a conversion.

After gathering information, the next step is to analyze it statistically. The project team devised a preliminary hypothesis testing the call data. This testing revealed that the time of day the outbound team made the call and the time lag between the newsletter sign-up and the outbound call both had a substantial impact on the success of the call and the conversion rate.

Design of experiment (DOE) tools assessed the significant factors from hypothesis testing. The designed experiment optimized critical factors and responses. The DOE results showed how critical factors interacted and affected the main measure, including the time of day and the appropriate sign-up-to-call lag time.

This analysis showed that afternoon calls made within 24 hours of the online sign-up were most effective.

4. Improve Stage

Implement solutions to improve the call experience in those areas.

There was initially at least a 24-hour lag between sign-up and follow-up calls because the outbound team had been using a third-party firm to compile lists of users who had signed up for the newsletter but had not donated. With the help of the newly implemented internal reporting system, the outbound team could generate this list within hours, significantly reducing call times. The outbound team also began prioritizing afternoon calls.

The team documented these changes and updated the process map to reflect the improvements.

5. Control Stage

New processes would be monitored to ensure that successful calls and conversions continue.

The Six Sigma project team completed three months of monitoring after the company implemented the improvement measures. According to an analysis, the project’s conversion rate increased to 52% from 45%, achieving the project goal.

The Six Sigma DMAIC process is an effective tool that can be used in any industry. It gives businesses the ability to analyze and improve their processes, leading to better results. By reviewing the example and following the five steps of the DMAIC Process – Define, Measure, Analyze, Improve and Control – businesses can create meaningful changes in their operations.

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The History of Six Sigma

Originally developed by Bill Smith at Motorola in 1986, the Six Sigma Training program was created using some of the most innovative quality improvement methods from the preceding six decades. The term “Six Sigma” is derived from a field of statistics known as process capability. The term 6 Sigma refers to the ability of manufacturing processes to produce a very high proportion of output within specification. Processes that operate with “six sigma quality” over the short term are assumed to produce long-term defect levels below 3.4 defects per million opportunities. Six Sigma’s goal is to improve overall processes to that level of quality or better.

• Your Project

What is DMAIC?

DMAIC is a 5-Stage Problem solving tool, based on Data analysis .

• It analyzes the Variables and Processes involved in a given Problem, proposes different Solutions and establishes Controls to prevent recidivism.

This tool is commonly used in Continual Improvement Processes such as Kaizen, 8D or 6-sigma.

Its name is an acronyms of its 5 Stages:

Let’s see what they mean:

DMAIC Five Steps

1. Define :   In this Stage, you have to Define your Problem or Goal .

• What is your final Objective.

2. Measure :  In this Stage, you have to Define your Variables .

• What are the variables involved and what measurement system will you use.

3. Analyze :  In this Stage, you have to Define your Potential Scenarios .

• What can be done, and what would be the result.

4. Improve : In this Stage, you have to Implement your Solution .

• Once you have analyzed all your potential scenarios, you have to choose your final scenario.

5. Control :  In this Stage, you have to Implement your Controls .

• This Controls should guarantee that the final solution is optimal, and avoid recidivism problems.

DMAIC Steps explained.

Let’s see the first example so that you understand it better:

• We’ll give you a much more detailed example later.

DMAIC example

Let’s imagine you own an e-commerce Site .

Your Site sells handmade products.

• Sales depend exclusively on the users you receive: you just sell through your Site.

Lately, you have been experiencing a decrease in sales.

• You receive fewer visitors to your Site.

Since you are decided to solve this issue, you decide to develop a DMAIC process:

• This is a synthesized DMAIC.
• That is your ultimate Goal.
• It is not the same as users received: if you had more users but they didn’t see your products, you wouldn’t sell anything .
• We recommend you to visit our “ Ishikawa Fishbone Diagram ” Page.
• Receive more users organically .
• Promote your products in other Sites .
• Create more content.
• Start a YouTube channel showing how your products are made.
• You also decide to promote your products on other specialized Websites , paying a small commission.
• This way, you’ll be able to study if the measures taken are effective and which one is better.

Check how, by pointing the correct Variable, the analysis and the conclusions obtained can be very different .

• If you had focused on profitability, you may have had to increase prices, for example.

There are always almost infinite “solutions” to one same problem.

• It all depends on how you approach it .

Why is DMAIC important?

There are different reasons why DMAIC is one of the best Problem Solving tools.

Here are some of them:

• Not just the problem or what you want to solve.
• Other methods just focus on the problem itself.
• Often, even more important that the variables themselves.
• We all tend to settle for the first option we find.

And, most important of all: it is a Step-by-Step framework that anyone can follow.

Think about this: when you want to solve something… do you usually follow any guidelines?

What do the best engineers do when they have a problem in an airplane turbine (for example)?

• We’ll tell you: they have a sequence of steps to follow .

Now, let’s explain when you should use the DMAIC process:

When should you use the DMAIC process?

As we mentioned in other Problem-Solving methods:

• Whenever you have a Problem you want to solve .
• When you have a Goal that you want to achieve .

You shouldn’t be using DMAIC just at work.

We recommend that you to use this methodology in your day to day .

• That way, you’ll get used to being strict and methodical when solving problems .

Let’s see some examples:

DMAIC examples

Now, we’ll use the DMAIC process in one day-to-day problem: Baking the perfect Bread .

We’ll explain each Step individually so that you understand the entire process perfectly.

Let’s begin:

Define Step - DMAIC example

In the first Step, you Define which is your Problem and your Goal:

You are tired of baking mediocre breads:

• You want to make the perfect Bread .

You have tried several times and each time you make bread you have a different result .

You want to obtain the perfect recipe .

Measure Step - DMAIC example

In this Stage, you decide to develop an Ishikawa Fishbone Diagram to find out the Main variables involved.

• Check our “ Ishikawa Fisbone ” Page.

Ishikawa Fishbone Diagram – DMAIC Measure Stage.

According to the Ishikawa diagram, the most important variables to study are:

• Oven Temperature.
• Kneading method.
• Final form of the Dough.
• Room Temperature and Humidity.

All these variables can be easily measured, with the exception of the Kneading and Final shape of the dough.

• You’ll evaluate these variables at a glance.

Analyze Step - DMAIC example

In this Stage, you test :

• Different water/ flour ratios.
• Different temperatures.
• Different rest times.
• Different Kneading methods.
• Different Final forms.

For each test , you write down:

• Quantities.
• Temperatures.
• Fluffiness.
• Crust Crunchiness.

This tests take time, of course.

• But remember: This recipe will be the best possible, and you’ll have it forever.

Improve Step - DMAIC example

Once you have the results, you decide which one you will use.

You can make this decision based just on Taste, Crunchiness and Fluffiness, but you can also consider:

• Imagine that you find a very good recipe, but it takes 8 hours to develop while the 2nd best option only takes 45 mins.
• Imagine that you find an amazing recipe, but you need a type of flour that is very expensive and difficult to find.

Since your Goal is literally “to Bake the perfect Bread” , you decide to judge the result according to Taste, Crunchiness and Fluffiness.

• If your goal was “an affordable, good quick-to-make bread” perhaps you could consider other variables.

Control Step - DMAIC example

Since weather changes, you decide that:

• As soon as summer arrives (or winter) you’ll recheck the variables related to room temperature .

The quantity of flour, water, etc… aren’t affected by weather conditions.

If you see any noticeable changes, you’ll define different recipes for different seasons.

• Maybe, you could link the resting time of the dough to room temperature .

Summarizing

If you have a Goal, or want to solve a Problem, you should consider developing a DMAIC process.

The DMAIC tool is a 5-Stage Problem solving method that focuses on Data Analysis.

Its name is an acronym for the 5 Stages on which it is based:

Even though it may seem obvious to some people, it offers a step-by-step guidance that can be very helpful for reaching your goals.

And there nothing better than being methodical and strict when you want to achieve something .

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• Jennifer Holbus
• Oct 23, 2023
• 10 min read

DMAIC - The 5 Phases of Lean Six Sigma

What is DMAIC?

DMAIC stands for Define, Measure, Analyze, Improve, and Control. It is a structured problem-solving methodology commonly used in Six Sigma and process improvement initiatives. DMAIC provides a systematic approach for identifying and addressing problems, improving processes, and achieving measurable results.

Why use the DMAIC process?

DMAIC provides a structured and systematic approach to problem-solving and process improvement. It offers a clear roadmap with defined steps, ensuring that the improvement efforts are focused and organized.

DMAIC emphasizes the collection and analysis of data to understand the current state of the process and identify the root causes of problems. By relying on data, organizations can make informed decisions rather than relying on subjective opinions or assumptions.

The Analyze phase of DMAIC focuses on identifying the root causes of process issues. By understanding the underlying factors contributing to problems, organizations can implement effective and targeted solutions rather than simply addressing symptoms.

DMAIC encourages the use of key performance indicators (KPIs) and measurement systems to assess process performance. This focus on measurement allows organizations to track improvements over time, quantify the impact of changes, and ensure that the desired outcomes are achieved.

DMAIC promotes a culture of continuous improvement within an organization. By following the DMAIC process, organizations can identify opportunities for improvement, implement changes, and then monitor and control the process to sustain the improvements achieved. It establishes a cycle of continuous learning and refinement.

DMAIC provides a standardized framework that can be applied consistently across different projects and teams. This ensures that best practices are followed, knowledge is shared, and lessons learned from one project can be applied to future initiatives.

DMAIC emphasizes the importance of understanding customer requirements and expectations. By defining and measuring customer needs, organizations can align their improvement efforts to deliver products or services that meet or exceed customer expectations.

What’s the difference between Six Sigma and DMAIC?

In essence, Six Sigma is a broader concept that encompasses various principles, tools, and techniques for quality improvement. The DMAIC methodology is a specific process used within Six Sigma projects to guide teams through the problem-solving process. DMAIC is one of the most commonly used methodologies in Six Sigma, but there are other methodologies as well.

History of DMAIC

The concept of Six Sigma was first introduced by Motorola in the early 1980s as a quality improvement framework. The term "Six Sigma" refers to a statistical measure of process variation, with the goal of reducing defects and improving quality.

In the 1990s, under the leadership of Bill Smith, a Motorola engineer, the DMAIC methodology was developed as a problem-solving framework within the Six Sigma approach. DMAIC was designed to provide a structured approach for organizations to identify and solve process-related problems.

Six Sigma gained significant popularity and adoption in various industries during the 2000s, particularly with the success stories of companies like General Electric and Honeywell. DMAIC became a widely used methodology within the Six Sigma framework, helping organizations achieve significant improvements in quality, cost savings, and customer satisfaction.

Throughout the 2000s and beyond, DMAIC continued to be refined and adapted by practitioners and organizations, incorporating various statistical and quality improvement tools. It became a cornerstone of Six Sigma implementation, providing a systematic and data-driven approach to problem-solving and process improvement.

Today, DMAIC remains a popular and widely used methodology for process improvement, not only within the Six Sigma context but also in other quality management and continuous improvement initiatives including lean manufacturing and project management. It has been applied across a range of industries, including manufacturing, healthcare, finance, and services, with the aim of achieving operational excellence and delivering value to customers.

The Five DMAIC Phases

Define phase.

In this initial stage, the project goals, scope, and objectives are defined. The focus is on understanding the problem or opportunity for improvement and aligning it with the organization's overall objectives. Key activities in this stage include defining the project charter, identifying stakeholders, understanding customer requirements, and setting specific improvement goals.

Measure Phase

The second stage involves gathering data to establish a baseline and understand the current state of the process. Key performance indicators (KPIs) are identified, and data collection plans are developed. Data is collected, validated, and analyzed to quantify the current performance of the process and identify areas of improvement.

Analyze Phase

In the analyze stage, the collected data is analyzed to identify the root causes of the problem and understand the sources of process variation. Various tools and techniques, such as statistical analysis, cause-and-effect diagrams, and process mapping, are used to explore the relationships between variables and determine the most influential factors affecting the process. The aim is to gain insights and knowledge that will guide the improvement efforts.

The fourth stage focuses on generating and implementing solutions to address the identified root causes and improve the process performance. In this stage, potential improvement ideas are generated, evaluated, and selected based on their expected impact. The selected solutions are tested and implemented on a smaller scale to assess their effectiveness. The focus is on achieving measurable improvements in key process metrics and meeting the defined improvement goals.

Control Phase

The final stage of DMAIC is the control stage. Once the process improvements have been implemented, control mechanisms are put in place to sustain the improvements and prevent the recurrence of the problem. Control plans are developed to define the monitoring and control activities, establish performance targets, and implement appropriate process controls. Ongoing monitoring and measurement ensure that the process remains stable and continues to deliver the desired results.

How Do You Use DMAIC In A Project? An Example

XYZ International, a multinational conglomerate with diverse global businesses, needed to improve its supply chain efficiency as a response to increasing customer complaints. The company decided to use the DMAIC model to address this challenge.

Define: The project team defined the goal as reducing lead time and improving inventory management within its global supply chain. They identified key performance indicators (KPIs) such as fulfillment time for orders, inventory turnover, and on-time delivery.

Measure: The team collected data on KPI performance across business units. They analyzed the data to establish current order lead times, possible bottlenecks and issues with inventory stockouts. They also gathered VOC (Voice of the Customer) and created several process maps of key processses.

Analyze: Using statistical analysis tools, did some root cause analysis to pinpoint the factors contributing to long lead times, excessive inventory, and delivery delays.

Improve: Based on the analysis, the team developed optional improvement strategies. For instance, they could implement demand forecasting systems, optimize transportation routes, establish strategic supplier partnerships, or introduce lean inventory management practices such as Kanban or replenishment pull systems. They prioritize the solutions based on their potential impact on lead time reduction and inventory optimization.

Control: The team implemented the selected improvements and established control measures to sustain the gains. They continued to monitor KPIs. They set up continuous improvement mechanisms, such as supplier performance reviews, periodic process audits, and ongoing training to ensure the changes are maintained and further refined.

The structured approach of DMAIC helped identify and address inefficiencies, enhanced data-driven decision-making, and fostered a culture of continuous improvement within XYZ’s supply chain processes.

DMAIC Tollgate Reviews

DMAIC tollgate reviews, also known as project tollgates or phase reviews, are checkpoints or milestones that occur at the end of each DMAIC stage. These tollgate reviews serve as formal decision points to assess the progress and success of the project and determine whether it should proceed to the next stage. They ensure that the project is on track, aligns with organizational objectives, and justifies the allocation of resources for further stages. The specific structure and content of tollgate reviews can vary between organizations.

What are some tools used during DMAIC?

DMAIC utilizes a variety of tools and techniques to support problem-solving, data analysis, and process improvement efforts. Here are some commonly used tools within each phase of the DMAIC methodology:

● Project Charter

● Voice of the Customer (VOC) Analysis

● SIPOC (Supplier, Input, Process, Output, Customer)

● Process Mapping

● Data Collection Plan

● Measurement System Analysis (MSA)

● Control Charts

● Takt time

● Cause-and-Effect (Fishbone) Diagram

● Pareto Chart

● Statistical Analysis (Hypothesis testing, linear regression)

● Process capability (Cpk)

● Histogram

Improve Phase

● Brainstorming

● Failure Mode and Effects Analysis (FMEA)

● Design of Experiments (DOE)

● Control Plan

● Statistical Process Control (SPC) Charts

● Standard Operating Procedures (SOPs)

● Risk analysis

These are just a few examples of the tools used in DMAIC. The selection of tools depends on the specific project and the nature of the problem being addressed. DMAIC offers a wide range of tools and techniques to support problem-solving, data analysis, and process improvement throughout the different phases of the methodology.

Can you use DMAIC outside of Six Sigma?

Yes. DMAIC is a methodology while Six Sigma is a more encompassing management philosophy. DMAIC can be used, under appropriate situations, any time your organization has a problem that needs to be fixed or a process that needs continuous improvement.

3 DMAIC best practices

1. clearly define the problem.

At the beginning of the DMAIC project, be sure to clearly define the problem or opportunity for improvement. Be sure that your problem statement is specific, measurable, achievable, relevant, and time-bound (SMART). As you learn more about your problem, you may need to redefine it later on.

2. Utilize cross-functional teams

DMAIC projects are enhanced by getting input from a wide array of subject matter experts, process customers and other stakeholders across a variety of departments and functions.

3. Use data to drive your decisions

DMAIC relies on data and facts to drive decision-making. Collecting accurate and relevant data is essential for understanding process performance, identifying root causes, and evaluating improvement efforts. Best practices include defining appropriate metrics and measurement systems, using statistical tools for data analysis, and establishing data collection protocols. By making data-driven decisions, organizations can effectively prioritize improvement opportunities, measure the impact of changes, and sustain improvements over time.

Should I use DMAIC for every problem-solving effort?

While DMAIC is a widely applicable problem-solving and process improvement methodology, there are certain situations where it may not be the most suitable approach. Here are a few instances when DMAIC may not be the best fit:

Non-Repetitive or Unique Situations

DMAIC is designed for addressing recurring or repetitive problems and improving processes over time. If you're dealing with a one-time or unique situation that does not have a clear process or data-driven approach, DMAIC may not be the most appropriate methodology.

Immediate Crisis or Urgent Situations

DMAIC projects require time for data collection, analysis, and implementation of improvements. If you're facing an urgent crisis or immediate situation that requires rapid decision-making and immediate action, DMAIC may not provide the level of responsiveness needed.

Exploration of New Opportunities

DMAIC is primarily focused on problem-solving and process improvement. If you're in the exploratory phase of identifying new opportunities, designing new products or services, or entering new markets, DMAIC may not be the ideal methodology.

Lack of Data Availability

DMAIC heavily relies on data collection, analysis, and measurement for making informed decisions. If the necessary data is unavailable, unreliable, or too costly to obtain, DMAIC may face significant limitations.

Resistance to Change or Limited Resources

DMAIC projects often require strong leadership support, stakeholder engagement, and allocation of resources. If there is significant resistance to change, lack of necessary resources, or inadequate support from key stakeholders, implementing DMAIC may face challenges.

Is DMAIC the only problem-solving methodology to consider using?

There are several alternative problem-solving methodologies and frameworks that can be used to address business problems, depending on the nature of the problem and the specific context. Here are a few commonly used approaches:

PDCA (Plan-Do-Check-Act)

Also known as the Deming Cycle or the Shewhart Cycle, is a simple and iterative problem-solving method. It involves planning, implementing, evaluating, and adjusting actions to continuously improve processes. PDCA is particularly effective for small-scale improvement efforts and rapid problem-solving cycles.

A3 Problem Solving

The A3 problem-solving method, derived from Toyota's management practices, is a structured approach that involves using a single A3-sized sheet of paper to capture problem-solving efforts. It emphasizes problem clarification, root cause analysis, solution development, and action planning in a concise and visual format.

Kaizen (Kaizen Event or Kaizen Blitz), which means "continuous improvement" in Japanese, is a philosophy and method that focuses on making small, incremental improvements in processes on a continuous basis. It involves involving all employees in problem-solving, encouraging suggestion systems, and fostering a culture of continuous improvement.

In Six Sigma, "quick wins" refer to small-scale improvements that can be implemented relatively quickly and yield noticeable results in a short period. These quick wins are important for building momentum, demonstrating the value of the Six Sigma approach, and generating enthusiasm for further improvement efforts. This is best used when the solution has little, if any, need for capital investment, can be implemented quickly, and can be easily reversed if needed.

Frequently asked questions about DMAIC

What does dmaic stand for.

DMAIC stands for Define, Measure, Analyze, Improve, and Control.

What is the purpose of DMAIC?

The purpose of DMAIC is to provide a structured methodology for problem-solving and process improvement. It aims to identify and address process issues, reduce variation, improve performance, and achieve measurable and sustainable results.

How is DMAIC different from Six Sigma?

Six Sigma is a broader quality management approach, while DMAIC is a specific problem-solving and improvement methodology within the Six Sigma framework. DMAIC is one of the most commonly used methodologies in Six Sigma and follows a structured five-step approach.

What are the key benefits of using DMAIC?

Using DMAIC can lead to several benefits, including improved process efficiency, reduced defects, enhanced product or service quality, increased customer satisfaction, cost savings, and a culture of continuous improvement.

How Can I Learn More About Lean Six Sigma?

A quick Google query resulted in 43,700,000 links in .49 seconds. From there you can find a wide array of sites dedicated to Lean Six Sigma. If you wish to narrow your search, two excellent sites for information about Lean Six Sigma are

isixsigma.com/dictionary/dmaic

https://sixsigmatrainer.com/blog

How Can I Get Certified In Lean Six Sigma?

Sign up with an IASSC accredited organization like https://www.sixsigmatrainer.com/courses-and-certifications

Determine Your Desired Certification Level

Lean Six Sigma certifications are available at different levels, such as White Belt, Yellow Belt, Green Belt, Black Belt, and Master Black Belt. Assess your skills, experience, and career goals to determine the appropriate certification level for you.

Choose a Certification Body

There are various organizations and institutions that offer Lean Six Sigma certifications. Research and select a reputable certification body that aligns with your needs and requirements.

Training and Education

Enroll in Lean Six Sigma training programs or courses that are specific to your desired certification level. These training programs provide the necessary knowledge and tools for Lean Six Sigma methodologies and techniques. You can choose from online courses, in-person workshops, or university programs. Ensure that the training program is delivered by experienced instructors and covers the relevant concepts and methodologies.

Hands-on Experience

Lean Six Sigma certifications often require practical application of the concepts and tools. Gain hands-on experience by working on real-world projects or case studies that apply Lean Six Sigma principles. This experience will help you better understand the methodologies and strengthen your problem-solving skills.

Examination

Once you have completed the training and gained the necessary experience, you will need to pass a certification exam. The exam typically assesses your understanding of Lean Six Sigma concepts, tools, and their application. The format and requirements of the exam may vary depending on the certification body you choose.

Certification Maintenance

Some certification bodies require you to maintain your certification by earning continuing education credits or participating in ongoing professional development activities. Understand the requirements for maintaining your certification and fulfill them to ensure that your certification remains valid.

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DMAIC Methodology - The Ultimate Guide

• Published on Sep 30 2023

Table of Contents

What is dmaic an overview, why the dmaic process, how to use the dmaic methodology, before starting dmaic: select a good project, the 5 phases of dmaic | dmaic methodology and phases, common mistakes to avoid when using six sigma dmaic methodology, tools used for dmaic, dmaic process with lean six sigma certification training, faqs about six sigma and dmaic approaches.

The DMAIC methodology stands as an example of structured quality for the process improvement and quality enhancement for businesses using Lean Six Sigma for Quality Management. This approach has been widely adopted across industries to achieve improvements in performance and reduce defects.

DMAIC stands for "Define, Measure, Analyze, Improve, and Control." This powerful framework for process improvement and quality management begins with the application of the DMAIC Methodology. The subsequent phases involve data gathering and analysis to identify root causes, followed by implementing improvements and establishing controls for sustainability.

DMAIC is favored for its structured, data-driven approach, enabling organizations to enhance consistency, reduce costs, satisfy customers, boost efficiency, and drive innovation. First, let's understand why DMAIC is crucial in the world of quality management and process improvement.

The DMAIC Process is a vital tool in the domain of quality management and process improvement. Following are a few important concepts:

Structured Problem Solving

One of the crucial reasons organizations adapt DMAIC is its structured problem-solving approach. It provides a clear path to follow when tackling complex issues. This structure ensures that no critical steps are missed in the quest for improvement. Instead of resorting to guesswork or implementing quick fixes, DMAIC guides teams through a well-defined process, increasing the probability of sustainable solutions.

• Data-Driven Decision Making

In today's digital world, the ability to make data driven decisions is crucial. DMAIC places a strong emphasis on data collection and analysis. By gathering and analyzing data at each stage of the process, organizations can make evidence-based decisions. This data-driven approach not only leads to more accurate problem identification but also helps in sharing the impact of improvements, making it easier to justify investments.

Focus on Root Cause Analysis

One common pitfall in problem-solving is addressing symptoms rather than root causes. DMAIC, especially in its "Analyze" phase, encourages organizations to dig deep and identify the underlying issues. This emphasis on root cause analysis ensures that improvements are substantive and lasting, rather than superficial fixes that lead to recurring problems.

Alignment with Six Sigma and Lean Principles

Many organizations have already adopted Six Sigma and Lean principles to enhance efficiency and reduce defects. DMAIC seamlessly aligns with these methodologies, making it a natural choice for organizations that have already embraced these quality management approaches. It provides a systematic way to apply Six Sigma and Lean principles in practice.

The DMAIC methodology is a structured approach to process improvement. In the "Define" phase, the problem is identified, objectives are set, and project scope is determined. The "Measure" phase involves collecting data and establishing a baseline, while the "Analyze" phase delves into root cause analysis. In the "Improve" phase, solutions are generated, tested, and implemented, and the "Control" phase ensures sustainability through monitoring, documentation, and training.

DMAIC is a data-driven, systematic approach that aligns with Six Sigma and Lean principles, fostering continuous improvement and enhancing customer satisfaction. DMAIC is also an iterative process that not only solves immediate issues but also cultivates a culture of continuous improvement within organizations.

To effectively use DMAIC, it is essential to follow a step by step approach for an effective application.

Selecting the right project also plays a vital role in the process of implementing DMAIC methodology. It’s essential to ensure that the project you choose is not only worthy of your time and resources but also aligned with your organization's strategic goals. Here's how you can select a good DMAIC project:

Strategic Alignment

Assess project alignment with organizational strategy, addressing pain points, KPIs, and long-term goals. Aligned projects gain support and resources.

Define the Problem

Define the problem or opportunity using a SMART (specific, measurable, achievable, relevant, and time-bound) statement. Consider its impact on stakeholders and the organization.

Feasibility

Evaluate project feasibility, including data, resources, and expertise availability. Anticipate and plan for potential roadblocks and challenges in the DMAIC process.

Impact and Benefit

Estimate project impact: cost savings, efficiency, product quality, and customer satisfaction. Clear benefits justify project investment.

Data Availability

Ensure relevant, accessible, and high-quality data for DMAIC methodology. Insufficient data hampers progress; verify data sources and collection capabilities.

By carefully selecting a good DMAIC project, you set the stage for a successful process improvement journey. Keep in mind that not all projects are suitable for DMAIC. Now, let’s dive deep into the details of DMAIC Methodology and its each phase.

Now that the primary step to considering a DMAIC project is taken care of, lets us now explore the core methodology of DMAIC. The following is a brief breakdown of each phase of the 5 DMAIC Phases:

1. DMAIC Define Phase

The primary goal of the "Define" phase is to define the problem or opportunity for improvement. This phase sets direction for the entire DMAIC process.

Key Activities:

- Problem Definition: Craft a precise problem statement that outlines the issue to be addressed.

- Project Objectives: Define measurable objectives that align with the problem statement.

- Scope Definition: Determine the boundaries of the project to avoid scope creep.

- Stakeholder Identification: Identify all relevant stakeholders and their roles.

The "Measure" phase focuses on gathering data and establishing a baseline to understand the current state of the process.

- Data Collection: Collect data related to the process using appropriate measurement methods.

- Metric Selection: Choose key metrics and performance indicators that align with project objectives.

- Data Analysis Tools: Utilize statistical tools and techniques to analyze and summarize the data.

Baseline Creation: Create a baseline to represent the current performance level.

In the "Analyze" phase, the emphasis is on identifying the root causes of the problem or inefficiencies within the process.

- Root Cause Analysis: Investigate potential causes of the identified problem using techniques like Fishbone diagrams, 5 Whys, or Pareto analysis.

- Hypothesis Testing: Formulate hypotheses about the root causes and test them to confirm their validity.

- Data Validation: Ensure data accuracy and reliability for sound analysis.

- Data Visualization: Use visual representations to communicate findings effectively.

The "Improve" phase is where solutions are developed and implemented to address the root causes identified in the previous phase.

- Solution Generation: Brainstorm and generate potential solutions or improvements.

- Pilot Testing: Test selected solutions on a smaller scale to validate their effectiveness.

- Implementation: Roll out the approved changes across the entire process or organization.

- Monitoring and Adjusting: Continuously monitor the improvements and make necessary adjustments.

The final phase, "Control," focuses on sustaining the improvements achieved and preventing regression.

- Monitoring Systems: Establish systems and processes to monitor the ongoing performance of the improved process.

- Documentation: Document the new processes, procedures, and best practices.

- Standardization: Ensure that the improvements are standardized and consistently applied.

- Training and Communication: Provide training and communicate changes to relevant stakeholders.

Throughout the DMAIC process, it is crucial to adapt data-driven approaches implementing using statistical tools and techniques. Each phase creates a structured improvement cycle by building upon the pervious phase.

Objectives of DMAIC Methodology

As we proceed exploring the DMAIC methodology, it's again crucial to understand the objectives that it aims to achieve. DMAIC isn't just a series of steps; it's a strategic framework designed to deliver tangible results in process improvement. Let's understand the key objectives of DMAIC:

1. Problem Identification and Definition

DMAIC's first objective: identify, define, and communicate the problem or opportunity for clarity and targeted solutions.

2. Data-Driven Decision Making

DMAIC emphasizes data collection, analysis, and informed decision-making. Data serves as the compass for improvement, replacing intuition and anecdotal evidence.

3. Root Cause Analysis

DMAIC's key goal: uncover root causes, not just symptoms, to eliminate underlying process issues. Long-lasting improvements result from addressing root causes.

4. Process Optimization

DMAIC aims to optimize processes for peak performance: streamline, reduce variation, enhance efficiency. Results in better quality, reduced waste, and cost savings.

5. Continuous Improvement

DMAIC fosters a culture of continuous improvement, with its iterative approach ensuring ongoing efforts to refine processes and maintain high performance levels, even as circumstances change.

6. Standardization

DMAIC emphasizes standardization: effective documented improvements ensure consistency, prevent regression, and enable future replication of success.

Understanding these objectives is crucial for successful implementation of DMAIC. Each phase of the methodology serves to satisfy these objectives, and together they form a comprehensive approach to process improvement and quality management. Let’ now explore how the knowledge to apply these objectives benefit the DMAIC methodology effectively.

Benefits of DMAIC: Why It’s Needed

DMAIC is not just a hype. Its potential is not noticed until after the implementation of this methodology into your organization. Understanding the benefits of DMAIC will highlight its relevance and importance in process improvement and quality management.

• Structured Problem-Solving

One of the primary benefits of DMAIC is its structured problem-solving approach. It provides a clear and systematic path for organizations to follow when tackling complex issues. This structured methodology ensures that critical steps are not overlooked and that the problem-solving process is efficient and effective.

• Data-Driven Decision-Making

In today's data-driven world, the ability to make informed decisions is paramount. DMAIC places a strong emphasis on data collection, analysis, and interpretation. This data-driven approach ensures that organizations base their decisions on factual information, reducing the risk of making decisions based on intuition or incomplete information.

• Customer Satisfaction

Customer satisfaction is a critical benefit of DMAIC, particularly in customer-centric industries. By meeting or exceeding customer expectations through improved processes and products, organizations can build customer loyalty and gain a competitive edge.

• Enhanced Product or Service Quality

Improving processes and reducing defects often leads to enhanced product or service quality. This, in turn, can result in higher customer satisfaction, increased customer loyalty, and a stronger competitive position in the market.

• Alignment with Strategic Goals

DMAIC projects are typically selected based on their alignment with an organization's strategic goals. This ensures that process improvement efforts are directed toward achieving key objectives and driving the organization forward.

• Cost Reduction

Reducing costs is a common objective of DMAIC projects. By eliminating waste, minimizing defects, and optimizing processes, organizations can achieve significant cost savings. These savings can be reinvested in further improvements or contribute to higher profitability.

Despite the DMAIC methodology being a powerful tool, there are a few common mistakes that organizations must be aware of to ensure successful implementation. Avoiding these mistakes helps maximizing the benefits of DMAIC. Let's explore a few mistakes and their solutions:

• Lack of Top-Down Support

Mistake: One of the most common mistakes is embarking on DMAIC projects without strong leadership support from top management.

Solution: Ensure that top management is fully committed to the DMAIC process. Their support provides the necessary resources, removes obstacles, and demonstrates the importance of the initiative to the entire organization.

• Poorly Defined Problem Statements

Mistake: Initiating DMAIC projects with vague or poorly defined problem statements can lead to confusion and ineffective problem-solving.

Solution: Invest time in crafting clear, specific, and measurable problem statements. Use tools like the "5 Whys" technique to dig deeper and uncover the root causes.

• Skipping the "Measure" Phase

Mistake: Rushing through or neglecting the "Measure" phase can result in inaccurate baseline data and flawed analysis.

Solution: Give the "Measure" phase the attention it deserves. Ensure that data collection methods are reliable, and baseline data accurately reflects the current state of the process.

• Ignoring Stakeholder Involvement

Mistake: Failing to involve key stakeholders, including employees who work directly with the process, can lead to resistance and implementation challenges.

Solution: Engage stakeholders from the outset. Their input is invaluable for understanding the process intricacies and gaining buy-in for proposed improvements.

• Overlooking Data Quality

Mistake: Using incomplete or inaccurate data for analysis can lead to incorrect conclusions and ineffective solutions.

Solution: Prioritize data quality. Verify data sources, ensure accuracy, and address any gaps or inconsistencies before analysis begins.

• Rushing the "Analyze" Phase

Mistake: The "Analyze" phase requires careful examination of data and root cause analysis. Rushing through this phase can lead to missed insights.

Solution: Allocate adequate time for thorough analysis. Use data visualization tools and techniques to aid in identifying patterns and root causes effectively.

• Neglecting the "Control" Phase

Mistake: After implementing improvements, some organizations neglect the "Control" phase, which can lead to regression and loss of gains.

Solution: Prioritize the "Control" phase to ensure that the improvements are sustained. Establish monitoring systems, document processes, and provide ongoing training.

• Focusing Solely on Tools

Mistake: Relying solely on DMAIC tools without fostering a culture of continuous improvement can limit the methodology's impact.

Solution: Emphasize both the tools and the mindset. Encourage employees to embrace a culture of continuous improvement where they actively seek opportunities for enhancement.

Avoiding these common mistakes ensures organizations success with the implementation of the DMAIC methodology. DMAIC is a powerful approach for driving process improvements and achieving strategic goals when applied correctly and with careful consideration of such potential pitfalls.

The DMAIC methodology relies on a range of tools and techniques to facilitate each phase of the process. These tools are instrumental in gathering data, analyzing processes, identifying root causes, and implementing improvements. Let's explore some of the key tools commonly used in each phase of DMAIC:

• Define Phase Tools
• Project Charter: A project charter is a document that formally authorizes the DMAIC project. It outlines the project's scope, objectives, team members, stakeholders, and timelines. It serves as a reference point throughout the project.
• SIPOC Diagram: A SIPOC (Suppliers, Inputs, Process, Outputs, Customers) diagram provides a high-level view of the process, highlighting its key components and relationships. It helps in understanding the process context.
• Measure Phase Tools
• Check Sheets: Check sheets are simple data collection tools used to tally and record the frequency of specific events or defects. They help in gathering data systematically.
• Pareto Chart: A Pareto chart is a bar chart that displays data in descending order of frequency or importance. It's useful for identifying the most significant issues to address first.
• Control Charts: Control charts are used to monitor process stability over time. They help distinguish between common cause and special cause variation.
• Analyze Phase Tools
• Fishbone Diagram (Ishikawa or Cause-and-Effect Diagram): This tool helps in identifying potential causes of a problem by categorizing them into major categories, such as people, process, equipment, and materials.
• 5 Whys Analysis: The 5 Whys technique involves asking "Why?" repeatedly to delve deep into the root causes of a problem. It helps in uncovering underlying issues.
• Scatter Diagram: Scatter diagrams are used to explore relationships between two variables. They can reveal patterns or correlations that may not be immediately apparent.
• Improve Phase Tools
• Brainstorming: Brainstorming sessions involve generating a large number of ideas or solutions to a problem. It encourages creativity and diverse thinking.
• Failure Mode and Effects Analysis (FMEA): FMEA is a structured approach for evaluating the potential failure modes of a process, their severity, occurrence, and detectability. It helps prioritize improvements.
• Design of Experiments (DOE): DOE is a statistical technique used to systematically vary factors within a process to identify their impact on the output. It helps optimize processes efficiently.
• Control Phase Tools
• Control Plan: A control plan outlines the steps and procedures to maintain the improvements achieved in the DMAIC process. It includes details on monitoring, measurement, and response plans.
• Statistical Process Control (SPC) Charts: SPC charts, such as control charts and run charts, are used to monitor the stability and performance of a process over time.
• Standard Work: Standard work documents the new, improved procedures and practices. It ensures that everyone follows the standardized process to maintain consistency.

These are just a selection of the many tools available for each phase of DMAIC. The choice of tools depends on the nature of a project, the problem, and the data available. Successful DMAIC projects involve a combination of these tools to gather and analyze data, resulting in effective decision-making.

Limitations in DMAIC Tools

While the DMAIC methodology is a valuable approach to quality management, it's also essential to recognize its limitations and challenges. Understanding these limitations can help organizations optimize their DMAIC projects. Here are some common limitations in DMAIC tools:

1. Data Quality and Availability

Limitation: DMAIC relies heavily on data-driven decision-making. If data quality is poor or if relevant data is unavailable, the effectiveness of the methodology is compromised.

Mitigation Strategy: Prioritize data quality. Verify data sources, clean and preprocess data, and establish robust data collection methods. If data is missing, consider data imputation techniques or explore alternative data sources.

2. Complexity of Tools

Limitation: Some DMAIC tools, such as Design of Experiments (DOE) or advanced statistical techniques, can be complex and require specialized expertise.

Mitigation Strategy: Ensure that the project team includes individuals with the necessary expertise or consider providing training to team members. For simpler projects, choose tools that align with the team's skills and capabilities.

3. Resource Intensive

Limitation: DMAIC projects can be resource-intensive in terms of time, personnel, and financial resources.

Mitigation Strategy: Carefully select projects based on their potential impact and alignment with strategic goals. Conduct a resource assessment before starting a project to ensure that the necessary resources are available.

4. Resistance to Change

Limitation: Resistance to change from employees or stakeholders can pose challenges during the implementation of DMAIC improvements.

Mitigation Strategy: Involve stakeholders from the outset, communicate the benefits of the changes, and address concerns proactively. Engage employees and provide training to ensure a smooth transition.

5. Focus on Symptomatic Solutions

Limitation: Without thorough root cause analysis, DMAIC projects may address symptoms rather than the underlying causes of problems.

Mitigation Strategy: Prioritize root cause analysis in the "Analyze" phase. Use techniques like the Fishbone diagram and the 5 Whys to delve deep into the causes of issues.

6. Cultural Barriers

Limitation: Some organizations may have a culture that is resistant to change or that does not value data-driven decision-making.

Mitigation Strategy: Work on changing the organizational culture by promoting a culture of continuous improvement. Encourage open communication, reward innovation, and lead by example.

Practical DMAIC Examples

To gain a deeper understanding of how the DMAIC (Define, Measure, Analyze, Improve, Control) methodology works in practice, let's explore two practical examples that illustrate how DMAIC can be applied to real-world scenarios.

Example 1: Improving Order Processing in an E-commerce Company

• Problem: High order processing times leading to customer complaints and delays.
• Objectives: Reduce order processing time by 50% within six months.
• Scope: Order processing from order placement to shipping.
• Data Collection: Collect data on order processing times for the past six months.
• Key Metrics: Average order processing time, number of customer complaints related to delays.
• Root Cause Analysis: Use the Fishbone diagram and 5 Whys technique to identify root causes such as inefficient workflows, lack of automation, and staff training gaps.
• Data Analysis: Analyze historical order data to identify patterns and bottlenecks.
• Solutions: Implement process improvements, including workflow automation, staff training programs, and optimized order routing.
• Pilot Testing: Test the changes on a small scale to ensure effectiveness.
• Monitoring: Continuously monitor order processing times and customer complaints.
• Documentation: Document the new procedures and workflows.
• Standardization: Ensure that the improvements are standardized across the organization.
• Training: Provide ongoing training to staff on the new processes.

Example 2: Enhancing Patient Care in a Hospital

• Problem: High patient readmission rates within 30 days of discharge.
• Objectives: Reduce readmission rates by 20% within one year.
• Scope: The entire patient care process from admission to post-discharge follow-up.
• Data Collection: Collect data on patient readmissions and reasons for readmission.
• Key Metrics: 30-day readmission rate, primary causes of readmission.
• Root Cause Analysis: Use the Fishbone diagram and consult with healthcare professionals to identify root causes such as inadequate discharge planning, medication errors, and patient education gaps.
• Data Analysis: Analyze patient data and readmission patterns.
• Solutions: Implement improvements such as enhanced discharge planning, medication reconciliation processes, and patient education initiatives.
• Pilot Testing: Test the changes on specific patient groups to assess their impact.
• Monitoring: Continuously monitor readmission rates and causes.
• Documentation: Document the new care protocols and processes.
• Standardization: Ensure that the improvements are consistently applied across patient care teams.
• Training: Train healthcare staff on the new protocols and communication procedures.

These practical DMAIC examples showcase how the methodology can be effectively applied to specific issues within organizations, whether in the context of improving call center operations or enhancing manufacturing efficiency. DMAIC's structured approach, rooted in data analysis and continuous improvement, empowers organizations to achieve measurable results and address challenges proactively.

To ensure that the product’s progression is on the right tracks of succession, it is also essential for organizations to ensure the implementation of adequate process improvement methodologies. This in turn generates a demand for professionals mastering the lean six sigma principles.

Master the DMAIC methodology to solve problems and improve product quality with Sprintzeal's Lean Six Sigma certification courses!

Our comprehensive training programs are designed to equip you with the skills and knowledge needed to excel in static domain of quality management. From beginners to experienced professional, our courses cater to various levels, ensuring that you receive the right training for your needs.

Join thousands of successful Lean Six Sigma practitioners who have transformed organizations through process improvements. Enroll in Sprintzeal's Lean Six Sigma courses today and accelerate your career!

Q.1 Can DMAIC be used outside of Six Sigma?

Absolutely, DMAIC is a versatile problem-solving methodology that can also be applied outside of the traditional Six Sigma framework. While DMAIC is closely associated with Six Sigma due to its historical roots in quality management, organizations from various industries adopt DMAIC to enhance processes and drive improvements. Here are some scenarios where DMAIC can be effectively used outside of Six Sigma:

• General Process Improvement
• Lean Manufacturing
• Information Technology (IT)
• Project Management
• Supply Chain Management

Q.2 What Are the Advantages of Using the DMAIC Model?

DMAIC offers numerous advantages for organizations to help enhance quality and achieve strategic objectives. Here are the key advantages:

• Structured Approach to Problem Solving
• Root Cause Analysis
• Continuous Improvement Culture
• Cost Reduction and Efficiency
• Enhanced Quality
• Risk Mitigation

Q.3 Who can benefit from Six Sigma and DMAIC training?

A: Six Sigma and DMAIC training can benefit professionals from various industries, including manufacturing, healthcare, finance, IT, and more. Anyone interested in improving processes, reducing defects, and enhancing decision-making skills can benefit from these methodologies.

Q.4 What are the different Lean Six Sigma belt certifications?

A: Lean Six Sigma offers various belt levels, including Yellow Belt, Green Belt, Black Belt, and Master Black Belt. Each belt level represents a different level of expertise and responsibility in leading and participating in process improvement projects. Visit Sprintzeal.com to know more.

Q.5 Can Lean Six Sigma be applied to non-manufacturing industries?

A: Absolutely! Lean Six Sigma principles and DMAIC can be applied to any industry or sector, including services, healthcare, education, and government. The methodology's versatility makes it applicable across diverse fields.

Q.6 How long does it typically take to complete Lean Six Sigma certification?

A: The duration of Lean Six Sigma certification programs varies depending on the level and training provider. Typically, Yellow Belt programs can be completed in a few days, Green Belt in weeks, and Black Belt in a few months. Master Black Belt certification may take longer due to its advanced nature.

Q.7 Can Lean Six Sigma certification be pursued online?

A: Yes, many accredited training providers offer Lean Six Sigma certification programs online. Online training provides flexibility and allows you to learn at your own pace.

DMAIC is a powerful tool that offers a structured and data-driven approach to process improvement. It helps organizations identify and address issues systematically, optimize operations, and align with strategic goals. By utilizing a diverse set of tools, DMAIC empowers organizations to avoid common pitfalls.

This blog has further helped you with practical DMAIC examples on how this methodology can be effectively applied to real-world challenges. Additionally, for individuals seeking to master such impactful methodologies, Sprintzeal's Lean Six Sigma certification course is your best choice.

Sprintzeal offers Lean Six Sigma Green Belt and Lean Six Sigma Black Belt certification courses to help equip you with the skills and knowledge needed to excel in project quality improvement. Our expert instructors, with over a decade of experience training professionals, provide top-notch training.

Join our immersive community of learners for shared knowledge of key concepts and to excel in quality management.

Enroll in Sprintzeal's Lean Six Sigma courses today to earn a globally recognized certification.

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Our technical content writer, Sushmith, is an experienced writer, creating articles and content for websites, specializing in the areas of training programs and educational content. His writings are mainly concerned with the most major developments in specialized certification and training, e-learning, and other significant areas in the field of education.

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DMAIC Process explained

DMAIC process: this article explains DMAIC Process in a practical way. This article contains a general defintion of the DMAIC Process, associated steps and practical examples. After reading you will understand the basics of this Six Sigma and problem solving tool. Enjoy reading!

What is a DMAIC Process? The basics explained

The DMAIC Process is a data driven problem solving tool that can be used to improve, optimize and stabilize business processes. This cyclical problem solving model seeks to improve the processes performance within an organization. The acronym of this Lean Six Sigma tool stands for: Define, Measure, Analyse, Improve and Control.

The base of this problem solving tool is founded by Shingeo Shingo during the development of Poka Yoke .

Five basic steps of the DMAIC Process cycle

The DMAIC Process consists of five steps that match the cycle process perfectly. It is recommended to make DMAIC an integral part of every project or organization. It can be applied to any existing processes.

Figure 1 – the DMAIC Process Cycle

The problem is defined in this first step.Furthermore, it is important to recognize and define the following elements:

• who are the customers?
• what are the critical stages in the process?
• what is the objective and what are the related business processes?

The purpose of the measure phase of the DMAIC Process is to establish the most important aspects of the current process and to collect relevant data. The following aspects are important in this:

• analyse the output and the input
• define the measurement plan
• test the measurement system

Subsequently, the data that was collected in the previous step is analysed. The purpose of this step is to identify the root cause relationships. The deeper causes of defects and errors are investigated. Basic tools are used to:

• identify the gap between current and required performance
• identify the input and the output
• list and prioritize potential opportunities to improve

The current process is improved by using techniques and creative solutions.  Brainstorming sessions can be a useful tool. Other, obvious solutions are:

• innovative ideas
• focus on the simplest and easiest solutions
• create a detailed implementation plan
• implementation of improvements
• identify errors and causes using an Ishikawa diagram

This step does not only focus on control but on monitoring as well. Control ensures that any deviations can be corrected in the future. Monitoring leads to sustainable improvements and guarantees long-term success. Permanent monitoring is therefore required.

Linking the DMAIC Process Cycle with business processes

To supplement the standard DMAIC Process, it is recommended to implement this step-by-step plan in other business processes as well. By sharing experiences and new knowledge with other departments, changes can be effected more easily within the entire organization.

It is important that employees have a good understanding of the usefulness of the procedure of the DMAIC process, that they discuss it with each other and that they are willing to share their experiences.

The DMAIC Process Cycle versus Six Sigma

Initially, the DMAIC process was linked to Six Sigma . Six Sigma was developed by Motorola and General Electrics to improve the quality of process outputs.

This is done by identifying and removing the causes of errors. The process is not exclusive to Six Sigma and can therefore be used to improve processes in other organizations.

Comparison of the DMAIC Process with the PDCA cycle (Deming)

DMAIC is actually an application of Deming’s PDCA cycle . The DMAIC Process takes a project based approach, whereas the PDCA cycle has a wider application.

This means it is can also be applied to one project. The DMAIC process analyses the root cause of the problem whereas the PDCA cycle focuses on the entire operation and it unearths other causes as well.

Benefits of using the DMAIC Process Cycle

The DMAIC Process is based on framework thinking within for example a product group, customer group or service. The strengths of this problem solving approach lie in the addressing and optimizing of the root causes in a process.

For a creative change in which an organization changes course completely, however, the model is less applicable. When going through the steps of the process, there may not be any overlaps. The best results are achieved with a plan-led team approach.

Example of the DMAIC Process

Let us look at a car garage with 50 locations who specialise in car tyres as an example. So far, in each branch, they have plenty of stock in various types of summer and winter tyres.

This enables them to quickly help the customer, delivering customer satisfaction and good word-of-mouth advertising. It now appears that the costs of the car company where very high last year. Management then decides to speak with all 50 branches in order to find out why.

The costs have risen sharply due to employee costs, renting space for 50 branches and inventory.

The costs are compared to that of last year and it turns out the costs are 20% higher, without creating more revenue.

Together with all 50 branches, the biggest cost item is examined. Several different factors are then identified. On average, it appears that inventory costs were 15% higher than in the previous year, among other things due to insufficient variety whereby ‘older’ models are left longer in the warehouse.

Together with the 50 branches, management looks at methods for improvement. For example, they propose to work from a central warehouse, supplying the branches 3x per week. Another option is to only have conventional tyres in stock while keeping specific tyre types in the central warehouse. The first solution is chosen unanimously.

After a test period an evaluation takes place with all branches and management. It turns out that employees have to cancel a sale more often or only help customers after a few days.

It’s Your Turn

What do you think? Is the DMAIC Methodology applicable in today’s modern economy and companies? What is your experience? What tips can you share to help others being successful in applying the DMAIC process?

Share your experience and knowledge in the comments box below.

More information

• de Mast, J., & Lokkerbol, J. (2012). An analysis of the Six Sigma DMAIC method from the perspective of problem solving . International Journal of Production Economics, 139(2), 604-614.
• Pyzdek, T., & Keller, P. A. (2003). The six sigma handbook . McGraw-Hill .
• General Electric. (2006). Six Sigma . Available at: https://www.ge.com/sixsigma/. Accessed March 7, 2006.

How to cite this article: Mulder, P. (2013). DMAIC Process . Retrieved [insert date] from Toolshero: https://www.toolshero.com/problem-solving/dmaic-process/

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Patty Mulder

Patty Mulder is an Dutch expert on Management Skills, Personal Effectiveness and Business Communication. She is also a Content writer, Business Coach and Company Trainer and lives in the Netherlands (Europe). Note: all her articles are written in Dutch and we translated her articles to English!

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Daniel Croft

Daniel Croft is an experienced continuous improvement manager with a Lean Six Sigma Black Belt and a Bachelor's degree in Business Management. With more than ten years of experience applying his skills across various industries, Daniel specializes in optimizing processes and improving efficiency. His approach combines practical experience with a deep understanding of business fundamentals to drive meaningful change.

• Last Updated: February 29, 2024
• Learn Lean Sigma

Process improvement requires a structured, systematic approach to ensure success. DMAIC, standing for Define, Measure, Analyze, Improve, and Control, offers such a framework, integral to Six Sigma and widely applicable across various industries for enhancing operational efficiency and quality. This guide delves into the DMAIC methodology, explaining the tools and strategies pertinent to each phase. From initial problem identification to the sustainable implementation of solutions, the following sections will guide you through the path to achieving measurable, lasting improvements in your organization’s processes.

Table of Contents

What is dmaic.

The DMAIC methodology is a data-driven quality strategy used to improve processes. It is an integral part of Six Sigma but is also used independently in process improvement efforts. DMAIC stands for Define, Measure, Analyze, Improve, and Control. Each phase has specific objectives and tools designed to achieve these objectives. This guide will explore the tools used at each stage of the DMAIC process to provide a clear understanding of how to effectively implement process improvements.

Define Phase in DMAIC

The Define phase is the foundational pillar in the DMAIC methodology, setting the basis for all subsequent efforts in process improvement. This phase is important for aligning the project with business objectives and customer expectations. Let’s go deeper into the objective of the Define phase and examine the tools used to achieve its goals.

The objective of the Define phase is to establish a clear, comprehensive understanding of the project at hand. This involves identifying the specific problem or opportunity for improvement, understanding the needs and expectations of customers, and setting achievable goals that align with both customer expectations and business objectives. The Define phase ensures that the project team, stakeholders, and anyone else involved have a shared understanding of what the project aims to accomplish, thereby setting a clear direction for all subsequent phases of the DMAIC process.

To achieve the objectives laid out in the Define phase, several key tools are employed, each serving a specific purpose in laying the groundwork for successful project execution:

Project Charter

The Project Charter is akin to a project’s constitution. It is a document that formally outlines the project’s scope, objectives, and participants. The charter serves multiple purposes: it provides a high-level overview of the project for stakeholders , it acts as a contract between the project team and the organization’s leadership, and it serves as a constant reference point for the project’s goals and boundaries. By clearly defining what is in and out of scope, the Project Charter helps prevent project scope creep and ensures that all team members are aligned on the project’s objectives.

Take a look at our Project Charter template to help you get started.

SIPOC Diagrams

SIPOC Diagrams are a tool used to map out the high-level view of a process, illustrating the Suppliers, Inputs, Process, Outputs, and Customers involved. This visual tool is instrumental in the early stages of a project because it helps the team and stakeholders understand the current state of the process at a glance. By identifying these key components, SIPOC diagrams facilitate a common understanding among all project participants, ensuring that everyone has the same baseline knowledge of the process being improved. This tool is especially useful for identifying critical areas of focus and potential areas where problems may arise.

Voice of the Customer (VOC)

Voice of the Customer (VOC) techniques are used to capture and understand customer requirements, needs, and expectations. VOC can be gathered through various means, including surveys, interviews, focus groups, and feedback forms. The essence of VOC is to ensure that the project’s objectives are closely aligned with what the customers value most. It is a critical component in defining the problem because it shifts the perspective from internal process metrics to customer impact. Understanding the VOC helps the project team prioritize improvements based on what will have the most significant effect on customer satisfaction and loyalty.

Process map of the voice of the customer

Measure Phase in DMAIC

The Measure phase is a critical step in the DMAIC process that builds directly on the foundation established in the Define phase. It transitions the project from the conceptual understanding of problems and requirements to a quantitative analysis of the current process. This phase is where data takes center stage, offering insights into the process’s performance and laying the groundwork for targeted improvements. Let’s explore the objective of the Measure phase and the key tools used to achieve its goals.

The primary objective of the Measure phase is to accurately quantify the current state of the process being improved. This involves collecting data on key performance indicators (KPIs) to establish a baseline measurement. The aim is to measure the extent of the problem identified during the Define phase, using data to understand the current process capability. This quantitative understanding is crucial for identifying the gap between the current process performance and the desired state, setting the stage for focused analysis and improvement in subsequent phases. It ensures that any decisions made are data-driven and grounded in the reality of the process’s current state.

To achieve the objectives of the Measure phase, several specific tools are utilized, each facilitating a different aspect of the data collection and analysis process:

Data Collection Tools

Data collection tools such as check sheets, data capture forms, and software tools are essential for gathering accurate and relevant data efficiently. Check sheets are simple yet powerful tools for collecting data on the frequency of specific events or problems. Data capture forms are designed to gather more detailed information in a structured format, ensuring consistency and accuracy in data collection. Software tools can automate data collection processes, providing real-time data capture and storage capabilities. These tools are the backbone of the Measure phase, ensuring that the data collected is reliable, relevant, and sufficient for analysis.

Process Mapping

While SIPOC diagrams provide a high-level overview, detailed process mapping dives deeper into each step of the process. This tool visually represents every action, decision, and delay in the process, offering a comprehensive view of the current state. Detailed process maps are invaluable for identifying variations, inefficiencies, and bottlenecks within the process. They serve as a visual aid that enhances understanding among team members and stakeholders, facilitating a more targeted and effective approach to data collection and analysis.

Detailed sub process map

Statistical Software

Statistical software tools like Minitab , JMP, or R are employed to analyze the data collected. These tools offer powerful capabilities for understanding data patterns, variations, and the process’s initial capability. Through descriptive statistics, process capability analysis, and graphical representations, statistical software helps in identifying trends, outliers, and areas of concern. This analysis provides a quantitative foundation for the Analyze phase, where data-driven insights guide the identification of root causes.

As a free option we have developed some statistical analysis tools in our tools section of the website.

Analyze Phase in DMAIC

The Analyze phase is a critical juncture in the DMAIC methodology, marking the transition from understanding the problem to actively seeking its root causes. This phase is where the gathered data from the Measure phase is scrutinized to uncover the underlying reasons for process deficiencies. Let’s explore the objective of the Analyze phase and the tools that play pivotal roles in achieving its aims.

The primary objective of the Analyze phase is to identify the root causes of defects or inefficiencies within the process. This phase is dedicated to digging beneath the surface of observable symptoms to discover the fundamental reasons for process problems. By accurately identifying the root causes, organizations can ensure that the solutions they implement in the Improve phase are targeted and effective, rather than merely addressing symptoms. The Analyze phase is crucial for ensuring that efforts are focused on changes that will have a meaningful impact on process performance and customer satisfaction.

Several analytical tools are employed during the Analyze phase, each designed to facilitate a deeper understanding of the process problems. These tools help in systematically breaking down the data and issues to uncover the root causes:

Cause-and-Effect Diagrams (Ishikawa or Fishbone)

The Cause-and-Effect Diagram, also known as the Ishikawa or Fishbone diagram , is a visual tool used to systematically explore potential causes of a specific problem. The diagram resembles a fish’s skeleton, with the problem at the head and the potential causes branching off the spine into categories such as Materials, Methods, Machines, People, Environment, and Measurement. This tool is particularly useful for team brainstorming sessions, as it encourages the exploration of all possible sources of variation or defects, categorizing them in a manner that is easy to understand and analyze further.

The Five Whys technique is a straightforward but powerful tool for root cause analysis. It involves asking “Why?” repeatedly (typically five times) to peel away the layers of symptoms and get to the core of the problem. Each answer forms the basis of the next “Why?” question. This method is effective because it promotes a deeper investigation into the process issues and helps avoid the trap of addressing superficial symptoms instead of the underlying causes. The simplicity of the Five Whys makes it accessible for teams of all levels of expertise, fostering a culture of inquiry and continuous improvement.

Hypothesis Testing

Hypothesis Testing is a statistical approach used to determine the likelihood that a given hypothesis about a process or data set is true. This tool is invaluable in the Analyze phase for validating or disproving assumptions made about the root causes of problems. By applying statistical tests, such as t-tests, chi-square tests , or ANOVA , teams can objectively evaluate the evidence for or against potential root causes, based on the data collected. Hypothesis testing helps in making informed decisions about which factors are truly contributing to process variations or defects, ensuring that improvements are data-driven.

Improve Phase in DMAIC

The Improve phase is a critical stage in the DMAIC methodology, where the insights and root causes identified in the Analyze phase are translated into actionable solutions. The focus shifts from understanding the problem to implementing changes that lead to substantial improvements in process performance. This phase is about innovation, experimentation, and optimization, with the ultimate goal of enhancing quality, efficiency, and customer satisfaction. Let’s delve into the objective of the Improve phase and the strategic tools employed to achieve successful outcomes.

The main objective of the Improve phase is to develop and deploy solutions that address the root causes of deficiencies identified earlier in the DMAIC process. This involves designing innovative changes to the process, testing these changes to ensure they produce the desired outcomes, and then implementing the changes in a way that results in significant performance improvements. The challenge in this phase is not only to find solutions that solve the identified problems but also to ensure that these solutions are sustainable and do not introduce new issues into the process.

A variety of tools and techniques are used in the Improve phase to facilitate effective solution development and implementation:

Pilot Studies

Pilot studies are small-scale experiments or trials conducted to evaluate the feasibility, duration, cost, risk, and adverse effects of an improvement solution before it is rolled out on a larger scale. This approach allows teams to test the impact of changes in a controlled environment, minimizing risk and allowing for adjustments before full implementation. Pilot studies provide valuable insights into how a solution performs in the real world and can help identify potential issues or resistance that may not have been evident during the planning stages.

Design of Experiments (DOE)

Design of Experiments (DOE) is a statistical method that allows teams to systematically and efficiently explore the relationships between multiple input variables and their impact on output variables. This tool is invaluable for optimizing processes because it can identify the combination of factors that lead to the best possible outcome. DOE helps in understanding the interaction between variables, thereby enabling the development of solutions that are robust and optimized for performance. By using DOE, teams can ensure that improvements are based on empirical evidence and statistical rigor, leading to more effective and predictable process enhancements.

Lean tools, such as 5S (Sort, Set in order, Shine, Standardize, Sustain), Kanban (visual signal or card), and Value Stream Mapping (VSM) , are employed to streamline processes, eliminate waste, and enhance flow. These tools are grounded in the principles of Lean management, which focuses on maximizing value for the customer while minimizing waste. 5S is used to create organized workspaces that improve efficiency and quality. Kanban helps in managing workflow and inventory with visual cues, ensuring that work progresses smoothly without bottlenecks . Value Stream Mapping is a tool for visualizing the flow of materials and information as a product or service makes its way through the value stream, highlighting areas of waste and opportunities for improvement. By applying these Lean tools, teams can make significant strides in improving process performance, reducing cycle times, and increasing customer satisfaction.

Control Phase in DMAIC

The Control phase is the final, yet perpetually critical phase of the DMAIC methodology. It is where the improvements made in the previous phases are solidified into the standard operating procedure, ensuring the longevity and sustainability of these gains. The primary focus shifts to monitoring and controlling the process to prevent regression, maintaining the enhanced performance levels over time. Let’s delve into the objective of the Control phase and examine the tools that are essential for its successful execution.

The main objective of the Control phase is to ensure that the improvements and changes implemented during the Improve phase are maintained and that the process does not revert to its previous state. This phase is about embedding the new practices into the daily operations of the organization, ensuring that the process continues to operate at its new, improved level of performance. It involves close monitoring of the process to quickly identify and correct any deviations from the target performance. The Control phase is critical for realizing the long-term benefits of the DMAIC project, making the improvements truly sustainable.

To achieve the objective of the Control phase, several key tools are employed, each designed to facilitate effective monitoring, controlling, and documentation of process performance:

Statistical Process Control (SPC)

Statistical Process Control (SPC) is a method of using statistical tools and control charts to monitor and control a process. SPC charts are invaluable for identifying when a process is behaving as expected or when it has deviated from set parameters, signaling the need for intervention. These charts can monitor various aspects of process performance, such as mean, range, and defects, providing real-time data that helps in maintaining process stability. SPC is a cornerstone of the Control phase, enabling ongoing oversight of the process and ensuring that improvements are sustained over time.

Control Plans

Control Plans are comprehensive documents that outline the specific practices, metrics, and processes that need to be followed to maintain the improvements achieved. They detail the control points, specifications, and monitoring activities required to ensure that the process remains under control. Control Plans serve as a blueprint for process management post-improvement, guiding the daily activities of process operators and ensuring that everyone involved is aware of their roles in maintaining process performance. These plans are dynamic documents that may be updated as processes evolve or as new improvements are made.

Standard Operating Procedures (SOPs)

Standard Operating Procedures (SOPs) are updated to reflect the changes made during the Improve phase, ensuring that the new, more efficient processes are clearly documented. These documents provide step-by-step instructions on how to perform process tasks, ensuring consistency and quality in the execution of these tasks. By updating the SOPs, the organization ensures that the process changes are formally communicated to all stakeholders, embedding the improvements into the regular workflow. SOPs are essential for standardization, training new staff, and serving as a reference for process activities, contributing to the sustainability of improvements.

Example of Standard Work Instructions

By systematically applying these tools at each stage of the DMAIC process, organizations can effectively address and solve problems, leading to significant improvements in process quality, efficiency, and customer satisfaction. The key to successful DMAIC implementation is not just in using these tools but in understanding the interconnectivity between phases and how each tool contributes to a holistic improvement strategy.

• Berardinelli, C.F., 2012.  TO DMAIC or not to DMAIC? .  Quality Progress ,  45 (11), p.72.
• De Mast, J. and Lokkerbol, J., 2012.  An analysis of the Six Sigma DMAIC method from the perspective of problem solving.  International Journal of Production Economics ,  139 (2), pp.604-614.

Q: What is DMAIC and why is it important in process improvement?

A: DMAIC stands for Define, Measure, Analyze, Improve, and Control. It is a data-driven quality strategy used for improving, optimizing, and stabilizing business processes and designs. DMAIC is important because it provides a structured, systematic approach to problem-solving, which helps organizations identify and address inefficiencies, reduce defects, and improve overall quality, leading to enhanced customer satisfaction and operational excellence.

Q: Can DMAIC be used outside of manufacturing environments?

A: Yes, DMAIC can be applied in various sectors beyond manufacturing, including services, healthcare, finance, and IT. The methodology is versatile and can be adapted to any process or industry where there is a need to improve efficiency, reduce waste, or solve problems related to quality and process performance.

Q: How does the Define phase set the stage for the rest of the DMAIC process?

A: The Define phase sets the foundation for a DMAIC project by clearly identifying the problem, project goals, and scope. It involves understanding customer requirements and establishing clear objectives for the improvement effort. This phase ensures that all team members and stakeholders have a shared understanding of the project’s purpose and scope, which is crucial for guiding the project’s direction and focus throughout the subsequent phases.

Q: In the Measure phase, how do you ensure data collected is reliable and accurate?

A: To ensure data reliability and accuracy in the Measure phase, it’s important to define data collection methods and tools clearly, train team members on these methods, and use standardized procedures for data collection. Validating the measurement system itself through techniques like gauge R&R (Repeatability and Reproducibility) can also help ensure that the data collected reflects the true performance of the process being analyzed.

Q: What makes the Control phase critical to the DMAIC process?

A: The Control phase is critical because it ensures that the improvements made during the Improve phase are sustained over time. Without effective control measures, processes may drift back to their original state, negating the improvements achieved. By implementing tools like SPC charts, Control Plans, and updated SOPs, organizations can monitor process performance, make adjustments as necessary, and embed the improvements into daily operations, ensuring lasting benefits from the DMAIC project.

Daniel Croft is a seasoned continuous improvement manager with a Black Belt in Lean Six Sigma. With over 10 years of real-world application experience across diverse sectors, Daniel has a passion for optimizing processes and fostering a culture of efficiency. He's not just a practitioner but also an avid learner, constantly seeking to expand his knowledge. Outside of his professional life, Daniel has a keen Investing, statistics and knowledge-sharing, which led him to create the website learnleansigma.com, a platform dedicated to Lean Six Sigma and process improvement insights.

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The DMAIC Model

In this article:

The DMAIC model is a problem-solving method used to identify flaws and improve inefficiencies in business processes.  

One challenge of day-to-day business is resolving problems. Imagine you run a small business that sells products online, and a quarterly review reveals a significant drop in orders.  

In a situation like this, you might look at customer feedback to find and fix the problem. You could also use your experience to try to resolve the problem. But what happens if the problem is complex and resurfaces because you haven’t properly resolved it?

Some problems are more complex than we first think. To solve the problem and get the business back on track, we need a structured problem-solving approach.

This is where DMAIC comes in. DMAIC stands for Define, Measure, Analyze, Improve, and Control. It is a data-driven iterative approach that you can use to improve a process or fix a problem. 

DMAIC is Part of Six-Sigma

DMAIC is a core part of the six-sigma quality improvement methodology.  

Six-Sigma is a business management strategy that aims to improve the output of processes by removing variation and errors in both manufacturing and business processes. With a focus on continuous improvement, it uses a series of quality management methods. DMAIC is one of those methods.

Bill Smith created Six-Sigma whilst working for Motorola in 1980. The methodology became popular after Bill Welch made it the central focus of the business strategy at General Electric.

The five steps of the DMAIC model are: 

• Define phase: where you understand the problem you want to address.
• Measure phase: where you collect data to help you make an informed decision about what’s causing the problem.
• Analyze phase: where you examine and interpret the collected data to attempt to identify the root cause of the problem.
• Improve phase: where you fix the root cause of the problem.
• Control phase: where you put in place a mechanism to ensure the improvements you’ve made are sustained.

Each step builds on the previous step in the sequence. As you use the DMAIC model and come to understand the bigger picture of an improvement project, you may need to iterate through the whole process or a subset of it several times.

Let’s take a closer look at each step of the DMAIC framework and how to use it in day to day business.

1. Define Phase 

The define phase aims to understand the problem and determine the need for a project that resolves the challenge the problem presents. A business problem is most often represented by some financial or performance challenges.  

Some questions to ask to define the project are:

• What is the problem?
• How often does it happen?
• What are the current inputs and outputs?
• What is the impact of the problem?
• Who is the customer?
• What is the customer saying?
• Who are the stakeholders?
• Who is on the project team to address the issue?
• What are the goals of this project?

The gathered information is used to create a high-level project plan. This plan becomes the guiding document for the project. 

2. Measure Phase 

The measure phase aims to gather reliable information to quantify the problem. The data collected in this phase will establish a baseline to compare against improvement later.

Some questions to ask in this phase include:

• How do we measure the problem?
• What is the current process performance?
• What data do we collect to measure it?
• Who or what needs to be surveyed?
• Is the data consistent?

Some useful tools to assist in this phase are basic Pareto charts, trend charts, and process flowcharts.

3. Analyze Phase 

This phase aims to find the root cause of the problem under investigation. Some questions to ask when analyzing the project are:

• How does the process work?
• What does the data say?
• How can the data help us understand the root cause?
• How does this affect performance? 
• Why are we having problems?

In this phase, you can use tools like brainstorming, fishbone diagrams,  or the 5-Whys to help you find the root cause.

4. Improve Phase

The aim of the improve phase is to implement one or more solutions to address the root cause of the problem.

Many different factors can influence a solution, so a well-designed solution most likely to resolve the root cause is what you’re looking for.

5. Control Phase 

The control phase aims to ensure that the improvements continue to meet the performance objectives over time.  

Ongoing monitoring ensures the process continues to meet your performance expectations in the future.  

DMAIC Model Example

Imagine you are a luxury watch manufacturer. Following a quarterly review, you learn that your profit margins are lower than you’d expect but you are not sure why. 

You decide to use the DMAIC model to help you to get to the bottom of the problem. 

Step 1: Define

The first step is to define the problem as best as you can.

For our example, we know that margins are going down even though the price we charge hasn’t changed. Our aim is to find and rectify the situation quickly.

During this step we also decide to put a team together, representing all the different parts of the business, to investigate the problem and ensure that no stone is left unturned.

Step 2: Measure 

Next, we need to collect the data we think will give us the most insight into what’s causing the problem. 

For our watch manufacturer, we decide to map out the entire production process and monitor the time it takes to move between each and every step.

Step 3: Analyze 

Once we’ve collected all of the data the next step is to analyze it with the aim of identifying the root cause of the problem.

Tools that are frequently used during this step include The 5 Whys and Fishbone diagrams . Both of these tools are useful for finding the root cause of a problem.

For our example, we decide to hold a brainstorming session and use the 5 Whys technique to attempt to identify the root cause of the problem. During this process, we uncover that a stage in the middle of the manufacturing process is taking much longer than we would expect. 

Upon further investigation, we find that this is happening because a small but necessary component is often out of stock. When this happens the team creating the watches has to wait until more stock arrives before they can resume the manufacturing process. According to the team, this is happening because the supplier is unreliable.

Step 4: Improve

In this step, we decide how to fix the root cause of the problem. For our example, there are many ways in which this could be done, including:

• Hold more stock to iron out the delivery inconsistencies.
• Switch to a different supplier.
• Create an SLA (Service Level Agreement) with the supplier to ensure you always get stock from the supplier when you expect.

You decide to always hold a high level of stock for the component so that the problem doesn’t happen again.

Step 5: Control

The final step is to ensure that the problem doesn’t happen again, or that if it does happen you know about it almost immediately.

To do this, you decide to hold a weekly review meeting to monitor all of the data regarding how long each part of the manufacturing process takes. If there is a large negative change from one week to another then it will be obvious that there has been a problem and you can step in and take corrective action.

DMAIC Model Template

We have created a DMAIC Model Template in PDF format, which you can use to perform your own DMAIC project. You can download it here .

Advantages and Disadvantages

The main advantages of the DMAIC method are:

• The structured approach is useful in any situation where you need to improve a complex process.
• The DMAIC method aims to analyze a process before implementation, and this reduces the chance of fixing the wrong issue.
• It helps to improve team and organization communications. This leads to improved performance overall, and ultimately this can filter through to happier customers.

The main disadvantages of the DMAIC method are:

• A one size fits all approach does not suit an organization that relies on creativity.
• Without awareness, during the implementation of DMAIC, it is easy to become too focused on using the tool, rather than finding the right solution.
• It is cumbersome for simple and obvious problems.

DMAIC Model Summary 

The DMAIC model is a framework for fixing a business problem or improving a business process. DMAIC stands for Define, Measure, Analyse, Improve, and Control. It is part of the six-sigma continuous improvement methodology.

Each step follows and builds upon the previous step to define the problem, and then resolve it in a way that will result in lasting improvement.  

Cite this article

Minute Tools Content Team, The DMAIC Model, Minute Tools, Apr, 2020 https://expertprogrammanagement.com/2020/04/the-dmaic-model/

Originally hailing from Dublin, Denis has always been interested in all things business and started EPM in 2009. Before EPM, Denis held a leadership position at Nokia, owned a sports statistics business, and was a member of the PMI's (Project Management Institute’s) Global Executive Council for two years. Denis now spends his days helping others understand complex business topics.

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Six Sigma Basics: DMAIC Like Normal Problem Solving

Published: February 26, 2010 by Chew Jian Chieh

What is the usual way most people go about solving problems? Most people and organizations consciously or unconsciously use this method, as illustrated in Table 1 below.

This is not a bad method, provided what one thinks is causing the problem is really causing the problem. In this case, if a person is fat simply because they do not exercise enough and eat too much, then by exercising and eating less, they should weigh less. And if they do lose weight after taking such action, then the theory is validated. People solve a fair number of problems in this manner – using conventional wisdom and gut theories that also happen to be correct. In those cases, there is little need for Six Sigma – it is just a waste of time. Just do the above.

How Six Sigma Problem Solving Is Different

How is the Six Sigma problem-solving methodology different? Actually it is really not so different from how people normally go about solving day-to-day problems, except in Six Sigma, nobody knows what is really causing the problem at the beginning of the project. And because all attempts to solve the problem in the past have failed, largely because conventional wisdom and gut theories were wrong about the cause of that problem, people conclude that the problem cannot be solved.

These types of problems are really the best candidates for Six Sigma. The Six Sigma DMAIC methodology differs from conventional problem solving in one significant way. There is a requirement for proof of cause and effect before improvement action is taken. Proof is required because resources for improvement actions are limited in most organizations. Those limits preclude being able to implement improvement actions based on 100 hunches hoping that one hits the mark. Thus, discovering root causes is at the core of the methodology.

Here are the steps in the DMAIC process:

• Define phase: Understand what process is to be improved and set a goal.
• Measure phase: Measure the current state.
• Analyze phase: a) Develop cause-and-effect theories of what may be causing the problem; b) Search for the real causes of the problem and scientifically prove the cause-and-effect linkage
• Improve phase: Take action.
• Control phase: a) Measure to verify improvement has taken place; b) Take actions to sustain the gains.

Using a More Mathematical Language

The above steps can be phrase in another way – using more mathematical language (Table 2). (This kind of mathematical language should not put anyone off. If it is a concern initially, a person just needs to remember than whenever a Y shows up in any sentence, just replace it with word “effect,” or the phrase “outcome performance measure.” And whenever an X shows up , just replace it with the word “cause.”)

The key assumption in Six Sigma is this: If the true causes of any problem can discovered, then by controlling or removing the causes, the problem can be reduced or removed. Now is that not just common sense?

A Series of Common Sense Questions

In summary, Six Sigma DMAIC methodology is really just a series of common sense questions that one asks in order to solve any problem and eventually sustain the gains that come from solving the problem.

• Define: What is the Y that is not doing well?
• Measure: What is Y’s current performance?
• Analyze: What are the potential Xs? What are the real Xs?
• Improve: How can the real Xs be controlled or eliminated?
• Control: How can the Xs continue to be controlled to sustain the gains in Y?

Six Sigma’s DMAIC methodology is nothing but a search for the real causes of problems. With this understanding, what remains for those learning Six Sigma are the various tools and techniques used to answer these questions.

About the Author

Chew Jian Chieh

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The Basics of Structured Problem-Solving Methodologies: DMAIC & 8D

Topics: Minitab Engage

When it comes to solving a problem, organizations want to get to the root cause of the problem, as quickly as possible. They also want to ensure that they find the most effective solution to that problem, make sure the solution is implemented fully, and is sustained into the future so that the problem no longer occurs. The best way to do this is by implementing structured problem-solving. In this blog post, we’ll briefly cover structured problem-solving and the best improvement methodologies to achieve operational excellence. Before we dive into ways Minitab can help, let’s first cover the basics of problem-solving.

WHAT IS STRUCTURED PROBLEM-SOLVING?

Structured problem-solving is a disciplined approach that breaks down the problem-solving process into discrete steps with clear objectives. This method enables you to tackle complex problems, while ensuring you’re resolving the right ones. It also ensures that you fully understand those problems, you've considered the reasonable solutions, and are effectively implementing and sustaining them.

WHAT IS A STRUCTURED PROBLEM-SOLVING METHODOLOGY?

A structured problem-solving methodology is a technique that consists of a series of phases that a project must pass through before it gets completed. The goal of a methodology is to highlight the intention behind solving a particular problem and offers a strategic way to resolve it. WHAT ARE THE BEST PROBLEM-SOLVING METHODOLOGIES?

That depends on the problem you’re trying to solve for your improvement initiative. The structure and discipline of completing all the steps in each methodology is more important than the specific methodology chosen. To help you easily visualize these methodologies, we’ve created the Periodic Table of Problem-Solving Methodologies. Now let’s cover two important methodologies for successful process improvement and problem prevention: DMAIC and 8D .

8D is known as the Eight Disciplines of problem-solving. It consists of eight steps to solve difficult, recurring, or critical problems. The methodology consists of problem-solving tools to help you identify, correct, and eliminate the source of problems within your organization. If the problem you’re trying to solve is complex and needs to be resolved quickly, 8D might be the right methodology to implement for your organization. Each methodology could be supported with a project template, where its roadmap corresponds to the set of phases in that methodology. It is a best practice to complete each step of a given methodology, before moving on to the next one.

MINITAB ENGAGE, YOUR SOLUTION TO EFFECTIVE PROBLEM-SOLVING

Minitab Engage TM was built to help organizations drive innovation and improvement initiatives. What makes our solution unique is that it combines structured problem-solving methodologies with tools and dashboards to help you plan, execute, and measure your innovation initiatives! There are many problem-solving methodologies and tools to help you get started. We have the ultimate end-to-end improvement solution to help you reach innovation success.

Ready to explore structured problem-solving?

Download our free eBook to discover the top methodologies and tools to help you accelerate your innovation programs.

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Problem solving process according to the DMAIC model

DMAIC model - how to solve problems according to Six Sigma concepts and the DMAIC? Learn about the tasks you should complete at each stage!

Process concept

Understanding what a process is is fundamental to using the DMAIC model effectively in practice. Therefore, we will first look at the concept of process itself.

A process is a set of activities that has one or more types of inputs and transforms them into outputs that represent value to the customer. - M. Hammer, J. Champy

Any process can be described as a function of the relationship of output characteristics to input factors. The task of a project team solving a problem is to understand the impact of X’s (input factors) on Y (output characteristics), and then to introduce appropriate actions for improving the process and solving the problem.

What is the DMAIC model?

DMAIC is a data and statistics-based approach to problem solving. DMAIC helps to gradually implement process improvements and optimize processes. The approach was developed in the 1980s as part of the Six Sigma concept and is still used today in companies in various industries around the world. The author of the DMAIC method was Bill Smith – an employee of Motorola.

What does DMAIC stand for?

The name of the DMAIC method is formed from an acronym of five consecutive words that correspond to the various stages of project implementation:

• M – Measure
• A – Analyze
• I – Improve
• C – Control

Appropriate activities, tools and methods are assigned to each stage. Implementation of individual tasks in a specific time frame allows to achieve better and more sustainable results improving processes.

DMAIC Model

Assigning tasks to the various stages of the DMAIC model

Define phase.

• Defining the problems to be solved in a given project (for example, using SIPOC ),
• Defining the client’s CTQ,
• Defining the project objectives,
• Selecting the project team and assigning specific roles to team members,
• Developing a process map .

The result of the above tasks is the developed project charter.

Measure phase

• Developing a data acquisition plan,
• Performing measurement system variability analysis (e.g., Gage R&R, Kappa),
• Acquiring data for analysis,
• Calculating process capability,
• Analyzing data.

Analyze phase

• Generating improvement ideas (e.g., using brainstorming),
• Identifying potential X’s,
• Checking the relationship of X to Y,
• Finding key X’s,
• Performing a preliminary diagnosis of the problem.

Improve phase

• Identifying potential solutions to the problem,
• Conducting solution testing and risk analysis (e.g., use FMEA ),
• Improving process-relevant X’s,
• Drawing up a target process map .

Control phase

• Confirming the effect of the changes made,
• Developing an inspection plan,
• Preparing control cards and SPC ,
• Determining new sigma and specification limits,
• Preparing project documentation.

NOTE: After a successful project, the company should reward team members for their good work. Many organizations that want to improve processes using the DMAIC methodology send their employees to Six Sigma training courses. Among Six Sigma training courses, the most popular is the Six Sigma Green Belt level, after completion of which participants receive prestigious certificates. And at the stage of implementing projects to optimize processes in their companies, they receive the full support of an experienced project mentor. A person who completes Six Sigma Green Belt training is capable of independently coordinating projects in accordance with the DMAIC methodology in the future.

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Using the DMAIC Process for Problem-Solving

Most people think of the DMAIC process as a waterfall methodology. 

They couldn’t be more wrong. DMAIC can be used in an Agile team and works well when done correctly. Let's say you are a Product Owner who wants to use the DMAIC process in your agile team . The first step is understanding DMAIC and how it can help you. 

DMAIC stands for Define, Measure, Analyze, Improve, and Control. It is a lean Six Sigma methodology that helps businesses improve their processes. The goal of DMAIC is to improve quality and reduce waste. 

This article will shed some light on how you can use the DMAIC process in an Agile team and what benefits it can bring.

What is the DMAIC process?

By definition, the DMAIC process is a data-driven approach to problem-solving. It is used to improve existing processes or to develop new ones. The goal of DMAIC is to increase quality and reduce waste. 

The DMAIC process has five steps: 

• Define: In this step, you will define the problem you want to solve and set the goals for your project. You will also identify the stakeholders who will be involved in the project.
• Measure: You will then collect data about your current processes. This data will help you understand how the process works and identify areas that need improvement.
• Analyze: Afterwards, you will analyze the data you collected in the previous step. This will help you identify the root cause of the problem.
• Improve: In this step, you will develop and implement solutions to improve the process. 
• Control: Finally, you will establish controls to ensure that the improvements are sustainable. You will also monitor the process to ensure it continues to operate effectively.

The DMAIC model is iterative, meaning you can go back to any previous steps at any time. 

Why is the DMAIC process useful in decision-making?

The DMAIC process is a useful tool for decision-making because it helps you systematically improve your processes. It also helps you to identify and solve problems quickly. 

For example, suppose the team is struggling to meet its Sprint goals . In that case, Agile teams can use DMAIC to identify the root cause of the problem and develop solutions to improve their productivity . 

Here are some of its benefits:

• The DMAIC process is data-driven, so it relies on facts and evidence to make decisions. This makes it an objective and unbiased approach to decision-making. 
• The DMAIC process is iterative, which means that you can go back to any of the previous steps at any time. This makes it a flexible approach that you can adapt to changing circumstances. 
• The DMAIC process is designed to help you solve problems quickly. It is a fast and efficient way to identify and implement solutions. 

How to use the DMAIC process?

Let's look at how each phase of the DMAIC process can be applied in an Agile team setting. 

The first step is to define the problem you are trying to solve. This is important because it will help you focus your efforts on the right things. This stage has two steps: 1) the project selection and scope, and 2) the definition of the defect. 

You need to decide which project you want to work on and what its scope will be. This is important because you don't want to bite off more than you can chew. Here are the things that you don't want to skip when selecting a project and scope:

• Find the organizational values that define it
• Find opportunities
• Investigate the possibilities in the list
• Identify the project’s scope and objectives
• Set the projects' priorities

While defining the defect can be self-explanatory, it's often misunderstood. A defect is not just a bug – it's anything that causes the process to deviate from the target. 

To find the defects, you must first understand the target. This can be anything from customer satisfaction to cycle time . Once you know what the target is, you can start looking for defects. 

There are two ways to find defects: 

1. Look at the data: This is probably the most common way to find defects. You can use DMAIC tools like cause-and-effect diagrams to help you identify potential causes of defects. 

2. Look at the process: This is less common, but it's still a valid way to find defects. You can use process mapping to help you understand how the process works and identify potential areas for improvement. 

The second step is to measure the current state of the process. This is important because it will help you understand where the process is today and where it needs to be. This stage has three steps: 

1. Collect data: The first step is to collect data about the process. This data can be collected in many different ways, but the most common way is to use process mapping. 

2. Analyze data: The next step is to analyze your collected data. This analysis will help you understand the current state of the process and identify opportunities for improvement. 

3. Set a target: The last step in this phase is to set a target for the process, such as customer satisfaction. Afterward, you can start working on improving the process. 

You can use many tools for analysis, but the most common ones are cause-and-effect and fishbone diagrams . 

GoRetro's 5 Whys template for problem solving is an excellent tool for this stage. It provides in-depth guidance on how to use the 5 Whys technique to find the root cause of a problem. 

Remember that term, "root cause." This is what you're looking for when analyzing complex problems and processes. The root cause is the underlying reason why a problem exists. It's often not obvious, and it can take some time to locate.

The fourth step is to improve the process. This is where you'll make changes to your processes to address the problems that you've found. There are many ways to improve, but the most common one is to use process mapping. This tool helps you understand how a process works and identify potential areas for improvement. 

The fifth and final step is to control the process. This is where you'll put in place controls to ensure that your improvements are sustainable.

Although it is the last stage, this is where most product owners fail. Why? Because they think that once the improvements are made, they're done. That's hardly the case. 

You must ensure that the process stays in their new, improved state. This is often done by creating standard operating procedures (SOPs) and a control plan. 

If you fail to control the process, it will eventually revert to its old state, and your efforts will be wasted.

DMAIC Examples

DMAIC can be used to solve a variety of problems in Agile development. For example, suppose you are working on a project that is behind schedule. You can use DMAIC to help you figure out why the project is behind schedule and what you can do to get it back on track.

First, you would need to define the problem – in this case, the project is behind schedule. Next, you would need to measure how far behind schedule the project is and what factors are contributing to the delay. You can measure the project's progress against its original schedule, as well as the progress of similar projects.

Once you have collected data on the problem, you can begin to analyze it to look for trends and root causes. In this case, you might find that the project is behind schedule because there are not enough people working on it. Alternatively, you might find the project is behind schedule because the deadlines are too tight.

After you have analyzed the data and identified root causes, you can begin to develop solutions. Possible solutions, in this case, could include hiring more people to work on the project, or extending the deadline. Once you have developed potential solutions, you need to test them to see if they actually work.

In our example, we would need to monitor the project's progress and compare it to its original schedule. If we found that the project was still behind schedule after implementing our solution, we would need to go back and try another one.

Finally, once you have implemented a solution and verified that it works, you need to document it so that others can learn from your experience. This documentation should include what went wrong, what was done to fix it, and how well the fix worked.

DMAIC vs. DMADV

The DMAIC process is often confused with DMADV. Both are Six Sigma processes, but they are used for different purposes. 

DMAIC is used when you have a process that isn't working as well as it should, and you need to find a way to improve it. 

Meanwhile, DMADV is used to design a new process from scratch. 

If you're unsure which one you need, ask yourself this question: Do I need to improve an existing process (DMAIC) or create a new one (DMADV)? 

DMAIC vs. PCA Cycle

The DMAIC process is also sometimes confused with the PCA cycle. PCA stands for problem clarification, data collection, analysis, and action.

While DMAIC is very similar to the PCA cycle, it has a few key differences:

• DMAIC is more structured, while the PCA cycle is more flexible and allows for more creativity and innovation.
• DMAIC is more focused on solving specific problems. Meanwhile, the PCA cycle is more general and can be used to solve different problems.
• DMAIC is more results-oriented, while the PCA cycle is more process-oriented.
• The DMAIC process has five phases, while the PCA cycle has four.

Where to find useful DMAIC resources?

There are a lot of great resources out there that can help you learn more about the DMAIC process, but our go-to is GoLeanSixSigma.com . It offers a wealth of resources, tools, templates, and training to help you improve your problem-solving skills.

Final Thoughts

DMAIC is a powerful problem-solving tool that teams can use to improve any process. It's a structured approach that helps you focus on the root cause of the problem and provides a framework for finding and implementing a solution. 

If you want to improve your problem-solving skills, we highly recommend checking out GoLeanSixSigma.com. They offer a wealth of resources to help you master the DMAIC process. 

And if you're looking for a tool to help you track and manage your DMAIC projects, then look no further than GoRetro . GoRetro is a flexible and easy-to-use tool that you can apply to your retrospectives. This can be very useful for identifying issues early on and help you track your progress over time – a perfect tool to complement your DMAIC processes.

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The Six Sigma Strategy's DMAIC Problem-Solving Method

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Six Sigma is a business management strategy that was initially developed by Motorola in the 1980s and is used by many Fortune 500 companies today. It is primarily used to identify and rectify errors in a manufacturing or business process.

The Six Sigma system uses a number of quality methods and tools that are used by Six Sigma trained professionals within the organization. The DMAIC problem-solving method can be used to help with any issue that arises, usually by professionals in the organization who have reached the "green belt" level.

The DMAIC Method

The DMAIC problem-solving method is a roadmap that can be used for any projects or quality improvements that need to be made. The term DMAIC stands for the five main steps in the process: Define, Measure, Analyze, Improve, and Control.

• Define: It is important in Six Sigma to define the problem or project goals. The more specific the problem is defined, the greater the chance of obtaining measurements and then successfully completing the project or solving the problem. The definition should describe the issue accurately with numeric representation. For example, “damaged finished goods from the production line have increased 17 percent in the last three months." The definition of the problem or project should not be vague, such as, “quality has fallen.” As part of the definition stage, the scope of the project or issue should be defined, as well as the business processes involved.
• Measure: When the project or problem has been defined, decisions should then be made about additional measurements required to quantify the problem. For example, if the definition of the problem is “damaged finished goods from the production line have increased 17 percent in the last three months,” then additional measurements might need to be looked at. This includes what finished goods are being damaged, when they are being damaged, and the level of damage.
• Analyze: Once the measuring stage has defined the additional measurements, the data is then collected and analyzed. At this point, it is possible to determine whether the problem is valid or whether it is a random event that does not have a specific cause that can be corrected. The data that has been collected can be used as a base level to compare against measurements after the project has been completed to ascertain the success of the project.
• Improve: After measurements have been taken and analyzed, possible solutions can then be developed. Test data can be created and pilot studies launched to find which of the solutions offers the best improvements to the issue. The team should also look at the results to ensure that there are no unanticipated consequences to the selected solution. When the most appropriate solution is selected, then the team can develop an implementation plan and a timeline for the completion of the project.
• Control: After the implementation of the solution or project, a number of controls must be put in place so that measurements can be taken to confirm that the solution is still valid and to prevent a recurrence. The control measurements can be scheduled for specific dates, e.g., monthly, daily, and yearly. The solution should also be well documented and any other related process documentation updated.

The DMAIC problem-solving method can produce significant improvements for an organization that is using the Six Sigma methodology and tools. The method offers a five-step plan that gives organizations a roadmap to follow so that issues can be resolved using a structured methodology.

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Using DMAIC to Solve Problems Manufacturers Alliance Podcast

If you want to improve performance and feel great about it along the way your going to appreciate this conversation with Scott Helgeson and Andrew Maruska with Chart Industries. They will walk you through their 6 Sigma projects and how they helped improve quality and communication. Download the Leaders Guide

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