The battle of operational excellence methodologies: DMADV vs. DMAIC

Over the past five years, the pressure on companies to increase profits has intensified. Though the specific reasons why vary from industry to industry, inflation, economic uncertainty, global competition and aggressive pricing strategies have made achieving profitability increasingly more difficult for many

As revealed in the PEX Report 2024, organizations are embracing classic operational excellence methodologies a such as Six Sigma, a data-driven methodology and set of tools and techniques used for process improvement and quality management. By identifying and eliminating causes of defects and minimizing variability in business processes, Six Sigma is a powerful tool to increase efficiency, effectiveness and operational agility.

At the core of Six Sigma lies two decision-making frameworks: DMAIC (define, measure, analyze, improve and control) and DMADV (define, measure, analyze, design and verify). In this article, we will define, compare and contrast these two frameworks.

What is DMAIC?

DMAIC is a highly effective, data-driven, five-step approach to identifying and eliminating process variations. It is used applied to define, analyze and optimize existing processes that may be inefficient, but are not broken beyond repair.

The DMAIC cycle can be broken down into 5 phases :

Define

To begin, the project team defines the goals and objectives of the improvement project. This involves identifying the problem or opportunity for improvement, understanding customer requirements and expectations, and establishing a clear project scope. Project boundaries are defined, including starting and stopping points, the process flow is mapped out.

Measure

Once the project's objectives are clearly defined, the measure phase involves gathering data and information related to the existing process. This phase aims to establish a baseline by quantifying the current performance and identifying key process parameters that need to be measured and controlled. Data collection methods and measurement systems are validated to ensure accuracy. Examples of tools that can be especially helpful in this phase include process capability measurement, Pareto charts, trend charts, process flowcharts and Gage R & R.

Analyze

During this phase the project team uses value steam mapping to visualize and analyze the data collected in the measure phase to identify patterns, trends and potential root causes of variations, bottlenecks or other issues in the process. The goal is to gain a deep understanding of the current process and its limitations. Statistical tools and techniques such as failure modes and effects analysis (FMEA), hypothesis testing, 5-whys and root cause analysis, are often used in this stage.

Improve

Based on the insights gained from the analysis, the improve phase involves developing and implementing solutions to address the identified issues and improve the process. The team generates and tests potential solutions, often using experimentation and pilot projects. The goal is to optimize the process and achieve the desired improvements in quality, efficiency and effectiveness. Kaizen, voice of the customer, design of experiments (DOE) and regression analysis are examples of tools used in this stage.

Control

In the final phase of DMAIC, the project team establishes controls and monitoring systems to sustain the improvements achieved in the improve phase. This includes developing standard operating procedures, setting up key performance indicators (KPIs) and implementing process controls to ensure that the process remains stable and continues to meet the desired objectives. Continuous monitoring and periodic reviews are part of the control process to detect and address any deviations.

Why DMAIC for operational excellence?

One of the benefits of DMAIC is that, with a little training, most people can easily understand and leverage the methodology to break down and systematically address complex process challenges. Though DMAIC is closely associated with Six Sigma, it can be leveraged on its own to guide problem-solving.

However, if a process is especially dysfunctional, the DMAIC method can fall short. In the case that DMAIC fails to deliver the desired outcome, DMADV is often the next step.

*The DMAIC Song (with lyrics), https://www.youtube.com/watch?v=vpI3udi6OJg

What is DMADV?

DMADV is a Six Sigma method for designing new processes and improving processes that are too broken to fix with DMAIC and must be extensively re-engineered. The goal is to ensure these new processes are high-quality, reliable and defect-free outcomes from inception. In addition, DMADV helps organizations better understand customer needs and wants, ensuring design processes are tailor-made to meet customer expectations.

Similar to DMAIC, DMADV can be broken down into 5 phases:

Define

The purpose of this phase is to establish a clear definition of what the project is in terms of purpose, scope and customer deliverables. A project plan or charter should be created that outlines timelines, measurable goals, roles, budget and process governance. 

Measure

The goal of the measure stage is to understand the customer’s needs (often through customer complaint information and surveys) and translate them into measurable design requirements. In addition, any existing process should be measured and analyzed to establish a performance baseline. Tools such as CTQ trees, House of Quality and Kano Models are frequently used in these phases.

Analyze

The primary objective of this phase is to identify the critical factors that influence the process currently being designed. These factors, known as Critical to Quality (CTQ) elements, are the heartbeat of any project. Tools such as CTQ trees, Quality Function Deployment (QFD), process mapping and benchmarking analysis are frequently leveraged in this stage.

Design

During this phase, the team develops and designs the new process, product or service based on the insights gained from the previous phases. This phase involves creating detailed plans, prototypes and designs that address the identified issues and meet the customer requirements. It also includes developing strategies for implementation and testing.

Verify

Finally, the last phase of DMADV focuses on validating the newly designed process before full-scale implementation. This may involve pilot testing or prototyping to ensure that the new process meets the desired objectives, quality standards and is capable of delivering the expected results.

Why DMADV for operational excellence?

While DMAIC is ideal for driving improvements within pre-existing parameters, DMADV is more suitable for projects that require radical change. As DMADV emphasizes the design phase, it encourages creativity, innovation and the exploration of new ideas and solutions. It is particularly useful when the company is looking for innovative, out-of-the-box solutions.

Another benefit of DMADV is that, because processes are built from scratch, it offers a higher level of control over the process parameters. DMADV is also more suitable for long-term projects where the organization is planning a new product launch, entering a new market or making a significant strategic shift.

As the first 3 phases of DMADV are essentially the same as DMAIC, some organizations may decide to simply stick with DMAIC to ensure continuous improvement projects are approached in a single, standardized way. In addition, as DMAIC projects move faster, it is more suitable for small or time-sensitive projects that require quick wins.

*Six Sigma - DMAIC and DMADV Explained Using Real World Example, https://www.youtube.com/watch?v=fv7O-pyo-oI&t=282s