What Is Six Sigma?: A Complete Overview

IKeeping in tune with emerging markets and processes, the American company Motorola developed a concept of quality management process in 1986. Over the years, it has been refined and polished into a sound theory of principles and methods, aimed at business transformation through a clearly defined process. This finished product is Six Sigma.

What is Six Sigma?

Six Sigma is a set of management tools and techniques designed to improve business by reducing the likelihood of error. It is a data-driven approach which uses a statistical methodology for eliminating defects.

The etymology is based on the Greek symbol “sigma” or "σ," a statistical term for measuring process deviation from the process mean or target. “Six Sigma” comes from the bell curve used in statistics, where one Sigma symbolizes a single standard deviation from the mean. If the process has six Sigmas, three above and three below the mean, the defect rate is classified as “extremely low.”

The graph of the normal distribution below underscores the statistical assumptions of the Six Sigma model. The higher the standard deviation, the higher is the spread of values encountered. So, processes where the mean is minimum 6σ away from the closest specification limit are aimed in Six Sigma.

The 5 Key Principles of Six Sigma

The concept of Six Sigma has a simple goal – delivering near-perfect goods and services for business transformation for optimal customer satisfaction (CX).

Goals are achieved through a two-pronged approach:

Six Sigma has its foundations in five key principles:

1. Focus on the customer. This is based on the popular belief that the “customer is the king.” The primary goal is to bring maximum benefit to the customer. For this, a business needs to understand its customers, their needs, and what drives sales or loyalty. This requires establishing the standard of quality as defined by what the customer or market demands.
2. Measure the value stream and find your problem. Map the steps in a given process to determine areas of waste. Gather data to discover the specific problem area that is to be addressed or transformed. Have clearly defined goals for data collection, including defining the data to be collected, the reason for the data gathering, insights expected, ensuring the accuracy of measurements, and establishing a standardized data collection system. Ascertain if the data is helping to achieve the goals, whether or not the data needs to be refined, or additional information collected. Identify the problem. Ask questions and find the root cause.
3. Get rid of the junk. Once the problem is identified, make changes to the process to eliminate variation, thus removing defects. Remove the activities in the process that do not add to the customer value. If the value stream doesn’t reveal where the problem lies, tools are used to help discover the outliers and problem areas. Streamline functions to achieve quality control and efficiency. In the end, by taking out the junk, bottlenecks in the process are removed.
4. Keep the ball rolling. Involve all stakeholders. Adopt a structured process where your team contributes and collaborates their varied expertise for the purposes of problem-solving. Six Sigma processes can have a great impact on an organization, so the team has to be proficient in the principles and methodologies used. Hence, specialized training and knowledge are required to reduce the risk of project or re-design failures, and ensure that the process performs optimally.
5. Ensure a flexible and responsive ecosystem. The essence of Six Sigma is business transformation and change. When a faulty or inefficient process is removed, it calls for a change in the work practice and employee approach. A robust culture of flexibility and responsiveness to changes in procedures can ensure streamlined project implementation. The people and departments involved should be able to adapt to change with ease, so in order to facilitate this, processes should be designed for a quick and seamless adoption. Ultimately, the company that has an eye fixed on the data examines the bottom line periodically, and adjusts its processes where necessary, can gain a competitive edge.

The Six Sigma Methodology

The two main Six Sigma methodologies are DMAIC and DMADV. Each has its own set of recommended procedures to be implemented for business transformation.

DMAIC is a data-driven method, used to improve existing products or services for better customer satisfaction. It is the acronym for the five phases: D – Define, M – Measure, A – Analyse, I – Improve, C – Control. DMAIC is applied in the manufacturing of a product or delivery of a service.

DMADV is a part of the Design for Six Sigma (DFSS) process, used to design or redesign different processes of product manufacturing or service delivery. The five phases of DMADV are: D – Define, M – Measure, A – Analyse, D – Design, V – Validate. DMADV is employed when existing processes do not meet customer conditions, even after optimization, or when it is required to develop new processes. It is executed by Six Sigma Green Belts and Six Sigma Black Belts and under the supervision of Six Sigma Master Black Belts. We’ll get to the belts later.

The two methodologies are used in different business settings, and professionals seeking to master these methods and application scenarios would do well to take an online certificate program taught by industry experts.

The Six Sigma Process of Business Transformation

Although Six Sigma uses various methods to discover deviations and solve problems, the DMAIC is the standard methodology used by Six Sigma practitioners. Six Sigma uses a data-driven management process used for optimizing and improving business processes. The underlying framework is a strong customer focus and robust use of data and statistics to draw conclusions.

The Six Sigma Process of the DMAIC method has five phases:

Each of the above phases of business transformation has several steps:

1. Define: The Six Sigma process begins with a customer-centric approach.
   1. The business problem is defined from the customer perspective.
   2. Goals are set. What do you want to achieve? What are the resources you will use in achieving the goals?
   3. Map the process. Verify with the stakeholders that you are on the right track.
2. Measure: The second phase is focused on the metrics of the project and the tools used in the measurement. How can you improve? How can you quantify this?
   1. Measure your problem in numbers or with supporting data.
   2. Define performance yardstick. Fix the limits for “Y.”
   3. Evaluate the measurement system to be used. Can it help you achieve your outcome?
3. Analyze: The third phase analyzes the process to discover the influencing variables.
   1. Determine if your process is efficient and effective. Does the process help achieve what you need?
   2. Quantify your goals in numbers. For instance, reduce defective goods by 20%.
   3. Identify variations, using historical data.
4. Improve: This process investigates how the changes in “X” impacts “Y.” This phase is where you identify how you can improve the process implementation.
   1. Step 1: Identify possible reasons. Test to identify which of the “X” variables identified in Process III influence “Y.”
   2. Step 2: Discover relationships between the variables.
   3. Step 3: Establish process tolerance, defined as the precise values that certain variables can have and still fall within acceptable boundaries, for instance the quality of any given product. Which boundaries need X to hold Y within specifications? What operating conditions can impact the outcome? Process tolerances can be achieved by using tools like robust optimization and validation set.
5. Control: In this final phase, you determine that the performance objective identified in the previous phase is well implemented and that the designed improvements are sustainable.
   1. Step 1: Validate the measurement system to be used.
   2. Step 2: Establish process capability. Is the goal being met? For instance, will the goal of reducing defective goods by 20 percent be achieved?
   3. Step 3: Once the previous step is satisfied, implement the process.

Six Sigma Techniques

The Six Sigma methodology also uses a mix of statistical and data analysis tools such as process mapping and design, and proven qualitative and quantitative techniques, in order to achieve the desired outcome.

The Six Sigma Tools

1. Cause and Effect Analysis
2. Flow Chart
3. Pareto Chart
4. Histogram
5. Check Sheet
6. Scatter Plot
7. Control Chart