What is Six Sigma?
Six Sigma is a quality management methodology used to help businesses improve current processes, products, or services by discovering and eliminating defects. The goal is to streamline quality control in manufacturing or business processes, so there’s little to no variance throughout. While Six Sigma has its origins in manufacturing to oversee quality control in production, it’s since evolved into a common business practice in industries such as technology, finance, and healthcare.
Six Sigma was trademarked by Motorola in 1993, and the name references the Greek letter sigma, which is a statistical symbol that represents a standard deviation. Motorola used the term because a Six Sigma process is expected to be defect-free 99.99966% of the time, allowing for 3.4 defective features for every million opportunities. Motorola initially set this goal for its own manufacturing operations, but it quickly became a buzzword and widely adopted standard.
Six Sigma is specifically designed to help large organizations with quality management. In 1998, GE CEO Jack Welch helped thrust Six Sigma into the limelight by donating upward of $1 million as a thank you to the company, recognizing how Six Sigma positively impacted GE’s operations, and promoting the process for large organizations. After that, Fortune 500 companies followed suit, and Six Sigma has been popular with large organizations ever since. While Six Sigma remains a popular and valuable methodology, other quality improvement frameworks have popped up in its wake, such as Agile and Lean.
How AI can be used in Six Sigma
The Six Sigma methodology has evolved along with the technology industry, shifting to embrace AI for data-driven decision-making, data analysis, process automation, and predictive modeling. The adoption of AI tools has created a shift in the Six Sigma framework, improving the measure and analyze phases of the DMAIC framework, and allowing organizations to process large data sets faster. AI can also help organizations identify new insights and patterns that might be missed by more traditional analysis methods.
AI can support the Six Sigma methodology by improving accuracy of data analysis, processing large datasets at faster speeds, and identifying subtle or hidden patterns that aren’t immediately obvious. In the pursuit of efficiency and quality management, AI can help make up for human error, offload time consuming data retrieval projects from data workers, and help businesses make better informed decisions. As AI continues to evolve, it’ll become a more integral part of quality management to alleviate some of the manual work that goes into QA, and reduce the impact of human error.
1.5 Sigma Shift
In the Six Sigma methodology, the 1.5 Sigma Shift is the idea that a process will often shift from its target by 1.5 standard deviations over time. Acknowledging this allows organizations to design processes that’ll account for any minor unexpected variations that can and will occur throughout the production process. Six Sigma methodology helps organizations design development processes that account for these natural variations, which happen when producing services and products, factoring some degree of error into the overall business goals.
For organizations, the 1.5 Sigma Shift helps build processes with a more realistic picture of their longevity and long-term capabilities. It also helps organizations avoid overestimating performance based on short-term data by delivering proactive improvement, improved defect reduction, and better alignment with Six Sigma principles. In the Six Sigma methodology, errors and defects are expected to occur, so it’s natural to account for some level of variation to build strong processes.
Six Sigma principles
The goal in any Six Sigma project is to identify and eliminate any defects that cause variations in quality by defining a sequence of steps around a certain target. The most common examples you’ll find use these three targets:
- Smaller is Better creates an upper specification limit, such as having a target of zero for defects or rejected parts.
- Larger is Better involves a lower specification limit, such as test scores where the target is 100%.
- Nominal is Best looks at the middle ground — a customer service rep needs to spend enough time on the phone to troubleshoot a problem, but not so long that they lose productivity.
The process aims to bring data and statistics into the mesh to help objectively identify errors and defects that’ll impact quality. It’s designed to fit a variety of business goals, allowing organizations to define objectives around specific industry needs.
You’ll also find similar principles in Lean Six Sigma, which combines the core tenets of Six Sigma with the Lean methodology. Incorporating Lean into Six Sigma brings a heightened focus on reducing waste, defects, and variance, while also staying ahead of schedule and under budget. Lean also helps organizations stay more agile and flexible while focusing on establishing long-term processes. Plus, it adds a stronger focus to defects, overproduction, waiting, nonutilized talent, transportation, inventory, motion, and extra-processing. The idea is that by addressing these issues, companies can solve problems faster, improve efficiency, and boost productivity.
Six Sigma methodologies
In practice, Six Sigma follows one of two sub-methodologies: DMAIC and DMADV.
TheSix Sigma DMAIC project methodology includes five phases, each represented as a letter in the DMAIC acronym. These include:
- Define the problem, customer, project requirements, and ultimate goals and expectations of the customer. During this phase, projects are selected, research is conducted to determine various opportunities and possibilities, and the scope of the project is established.
- Measure performance of the current process by establishing a data collection plan to determine defects and gather metrics. At this stage, it’s important to establish performance baselines, future goals, and how performance will be measured.
- Analyze the process to establish root cause of variations and defects to identify issues with the current strategy that stand in the way of the end goal. During the analyze phase, it’s important to use data to identify parameters and inputs that have the most significant impact on the final process.
- Improve the process by eliminating root causes of defects through innovative solutions. During the improve phase, the focus is on testing the best potential solutions identified in the earlier phases. It’s important to consider performance, cost, implementation demands, and risks or disruptions that may arise.
- Control the new process to avoid falling into old habits and to ensure it stays on track. During this final phase, all changes made to the process are documented, the root cause of every problem is explained, and a schedule is established for continued monitoring.
The Six Sigma DMADV framework, also known as the Design For Six Sigma (DFSS), includes five stages:
- Define realistic goals that suit customer requirements or the business strategy. In this stage, project goals are established, schedules and guidelines are drafted for review, and risks are identified. A clear plan for the project should emerge by the end of this stage, and the overall strategy should be aligned with customer expectations.
- Measure and identify the customer’s critical to quality (CTQ) requirements and translate these into project goals. During this stage, the team identifies requirements, market comparisons, key design elements, and any necessary design components for the project. By the end of this stage, it’s important to have a set of metrics to align with customer requirements and overall project goals.
- Analyze multiple options and alternatives for the customer along with the estimated total life cycle of the project. This stage is all about building conceptual designs, identifying the best requirements and components, and determining the total cost of the project. The analyze stage is intended to set up the project with a defined design option that can be tested and prototyped.
- Design the process at a high level before moving onto a more detailed version that’ll become the prototype to identify errors and make modifications. During the design stage, the final details are established, and a model is built that’s one step away from a functioning prototype.
- Verify that the final iteration of the product or process is approved by all customers and clients — whether internal or external. The final design is presented to all key stakeholders to ensure it’s the right fit and will be effective in real-world use cases. This is the stage where you’ll document the process, all changes, and plans to implement the process so it’s scalable and sustainable.
DMAIC vs. DMADV: The DMAIC and DMADV methodologies seem similar, but they have different use cases. The DMAIC methodology is designed for existing process or products that aren’t meeting customers’ needs or performing to standards. When a business needs to develop a product or process that doesn’t already exist or when a product has been optimized but still falls short, that’s when you want to use DMADV.
Determining a Six Sigma project
To find projects in your organization that would benefit from Six Sigma, they need to fit some criteria:
- Each project needs to have a clear process of inputs and outputs.
- Don’t go into the project with a pre-determined solution — that means you already know the fix.
- Focus on reducing operation variation to make it easier for untrained operators.
- A project needs to be approached with knowledge of variations in process inputs, and how to control and eliminate defects.
iSixSigma offers the example of a slow cycle time at Station 30 due to defective parts coming from Station 20. A non-Six Sigma solution would attempt to rebalance the assembly line, while re-doing the work, keeping cycle time low and not spending on labor. A Six Sigma solution would be to investigate and control key inputs that contribute to defective parts coming from Station 20 to keep it from happening again in the future. In this case, the Six Sigma approach focuses on proactively eliminating the defect, while a non-Six Sigma approach simply reacts to the problem without identifying the cause. For a closer look at where to apply Six Sigma, see How to find the perfect project for Six Sigma success.
Six Sigma implementation roles
A key concept in Six Sigma is the idea of establishing clear leadership roles and a hierarchy for quality management. The key roles for Six Sigma implementation include:
- Executive leadership: This involves the CEO and other executive management charged with developing the vision for Six Sigma implementation. Leaders should also be responsible to encourage new ideas and supply the resources to act on innovation.
- Champions: Typically found in upper management, champions are those responsible to act on executive leadership’s vision and act as mentors to Black Belts.
- Master Black Belts: These workers spend all their time on Six Sigma methodology, either by guiding Black or Green Belts or helping champions. They’re picked out by champions and are tasked with ensuring consistency in the Six Sigma strategy.
- Black Belts: Working below Master Black Belts, Black Belts are responsible to execute on the Six Sigma strategy and typically act as leaders for specific tasks.
- Green Belts: Guided by Black Belts, Green Belts are new to the Six Sigma methodology and start learning it while maintaining their other job responsibilities.
You may find other belts like white, yellow, and orange. These are adopted by organizations to represent employees with some Six Sigma training but aren’t involved in the overall project.
Six sigma certification and training
Typically, Six Sigma certification and training is offered directly by businesses, with GE and Motorola being the first to develop Six Sigma certification programs to verify proficiency in the methodology. Large companies and universities followed suit, offering their own versions of a Six Sigma certification program. However, there isn’t much oversight to what qualifies as Six Sigma certification, and the criteria for Green Belt and Black Belt certifications can vary. Certification programs are offered through businesses, universities, professional associations, and for-profit training organizations.
Some organizations offer Six Sigma accreditation. For example, the IASSC offers Lean Six Sigma credentialing and accredited training providers. The Council for Six Sigma Certification also offers a list of accredited Six Sigma providers. Ultimately, when choosing a Six Sigma certification or training program, it’s important to do your research to ensure the organization, university, or third-party vendor offers the right training for your needs and has the right qualifications.
For more IT management certifications, see 17 IT management certifications for IT leaders.