Six Sigma has been around for decades, yet it remains one of the most popular and effective process improvement methodologies used by leading companies around the world. In this comprehensive guide, we‘ll explore what Six Sigma is, why it still matters, how it works, and the role of technology in Six Sigma today.
What is Six Sigma?
Six Sigma is a rigorous, data-driven approach to eliminating defects and variances in business processes. It utilizes statistical and quality management methods to dramatically improve process performance, capabilities, and quality by systematically identifying and removing the root causes of errors and minimizing variability.
The term "Six Sigma" originates from the Greek letter sigma, which represents standard deviation in statistics. The Six Sigma methodology aims to improve a process so that errors or defects occur at a rate of no more than 3.4 instances per million opportunities.
To visualize this concept of six sigma capability, here is a graph showing how six sigma equates to six standard deviations between the process mean and the closest specification limit:
Source: Lean Six Sigma Definition
At this Six Sigma level, processes are extremely well controlled and optimized, producing negligible defects or failures. Here are some real-world examples of Six Sigma levels achieved and their associated defect rates:
- Duplicate lab test orders in a hospital: 40,000 errors per million tests (3.4 sigma level)
- Incorrect prescription medication labels: 2 errors per million labels (5.2 sigma level)
- Voter ballot issues in 2018 Iowa elections: 6 cases per 1.6 million votes (6 sigma level)
As these examples illustrate, Six Sigma enables processes to reach incredible levels of accuracy, far beyond what is possible with common statistic process control techniques. For perspective, even world-class processes typically operate at a 4–5 sigma level. Reaching 6 sigma capability demonstrates truly elite process performance and control.
Why and How Did Six Sigma Start?
The foundations of Six Sigma trace back to the quality control work of pioneers such as William Deming and Joseph Juran. However, Six Sigma as a named methodology originated at Motorola in the 1980s as a metric and goal for measuring and improving quality.
Engineer Bill Smith recognized that the traditional quality measurement of parts-per-thousand (ppt) was not adequate for the complexity of modern electronics manufacturing. He proposed the Six Sigma metric and goal of 3.4 defects per million opportunities as a bold aim for achieving near-perfect process quality.
When applied to manufacturing processes, the statistical and quality tools bundled into the Six Sigma methodology helped Motorola realize powerful improvements. By 1987, Motorola reported over $16 billion in savings attributed to Six Sigma implementation across their operations.
Impressed by Motorola‘s results, other companies like General Electric, Honeywell, and Caterpillar rapidly adopted Six Sigma in the 1990s. Under CEO Jack Welch, GE experienced tremendous success from applying Six Sigma, not just to manufacturing, but also to critical management processes. GE‘s profits rose by over 60% to $13 billion annually within five years of deploying Six Sigma.
Given these results, Six Sigma quickly became standard practice for Fortune 500 companies andothers seeking process excellence. Today, Six Sigma is used globally across virtually all industries. There are various Six Sigma certifications for practitioners such as Green Belt and Black Belt.
Why is Six Sigma Still Relevant Today?
While popularity has waned from its peak in the 1990s and early 2000s, Six Sigma remains highly relevant for several key reasons:
Understanding Current Processes
Six Sigma leverages data and analysis to provide insight into real-world processes as they are actually functioning. This helps uncover hidden problems, waste, bottlenecks and defects. Especially with processes that have become more complex over many years and iterations, Six Sigma helps cut through assumptions and impressions to objectively understand how things work now.
Standardizing Processes Across Locations
Given globalized operations, Six Sigma aims to reduce variability and inconsistencies across locations. With complex supply chains and business processes spanning countries or continents, this standardization is crucial for maintaining quality, efficiency and compliance consistently everywhere. Six Sigma provides the rigor and discipline to prevent processes from drifting over time or between sites.
Creating a Culture of Continuous Improvement
Six Sigma instills an organizational mindset and culture focused on continual improvement, not just temporary fixes. In today‘s fast-changing world, standing still means falling behind. Six Sigma equips organizations with data-driven tools to keep systematically improving processes over time, not just reacting when problems arise.
Maximizing Customer Satisfaction
By minimizing defects and variability, Six Sigma increases reliability and perceived quality from a customer perspective. Especially for product companies, preventing issues from reaching customers is crucial for retention and loyalty. Six Sigma builds robust, repeatable processes to maximize customer satisfaction.
Increasing Profitability
Six Sigma implements process changes that directly impact the bottom line, such as reduced waste and rework, faster cycle times, higher yield, lower costs, etc. Combined across large scale operations, even small improvements at the process level deliver enormous financial gains.
How Does Six Sigma Work?
The primary structured methodology behind Six Sigma is called DMAIC, an acronym which stands for Define, Measure, Analyze, Improve and Control.
By following the rigorous DMAIC approach, teams can rapidly solve problems and improve any process. Here is a step-by-step breakdown of what each phase entails:
Define
Clarify the problem statement, goals, project scope, timeline, stakeholders, and available resources. Gather background data to understand what is already known versus still unknown about the process.
Measure
Identify key metrics to measure current performance of the process. Begin gathering accurate data on relevant variables, such as cycle times, defect rates, costs, outputs, etc.
Analyze
Examine the process data to find trends, patterns and correlations to uncover root causes of defects. Leverage statistical analysis tools to pinpoint vital inputs causing variability or errors.
Improve
Brainstorm potential solutions and implement targeted changes to address root causes. Solutions may involve process redesign, automation, training or other areas. Pilot changes on small scale first.
Control
Embed controls such as process monitoring, audits, training etc. to sustain improvements. Monitor key metrics to ensure changes have delivered expected performance results.
This data-driven, scientific approach helps identify and rectify the vital few sources causing the most critical problems, rather than getting distracted by the trivial many.
The DMAIC sequence drives continuous learning about the process and guides optimal analysis for sustainable solutions. For entirely new processes or products, a variant called DMADV is used instead: Define, Measure, Analyze, Design, Verify.
Have We Reached Peak Six Sigma?
While massively popular in the 1990s and early 2000s, interest in Six Sigma has declined from its peak according to Google Trends:
Source: Google Trends
Several factors have contributed to this drop in hype:
- Novel process ideas like Lean, Agile, DevOps have gained mindshare
- Focus on innovation over efficiency and quality as priority
- Management fads come and go – as leaders change so do popular approaches
- Perception of being overly complex and statistical
Large pioneers like General Electric have scaled back internal Six Sigma training and requirements. However, many companies still successfully apply Six Sigma today, especially in industries where quality is paramount like manufacturing, healthcare, and engineering.
And while Googling of Six Sigma has reduced, its global market size continues to grow at over 8% CAGR, projected to exceed $2.5 billion annually by 2025. Clearly, Six Sigma retains strong enterprise adoption and relevance.
Key Benefits of Six Sigma
When appropriately applied, Six Sigma delivers immense value and ROI including:
- 50-70% reduction in process defects and errors
- 20-40% improvement in cycle time efficiency
- 30-50% decrease in process variability and inconsistencies
- 10-30% gains in productivity and capacity
- Over 50% reduction in customer complaints
This data published by iSixSigma demonstrates the immense potential for quantitative and qualitative improvements. Across large-scale operations, the compound impact generates hundreds of millions in financial value annually.
According to Harvard Business Review research, companies can expect a return on investment from Six Sigma projects of $100,000 to $250,000 per Black Belt. Certified Black Belts, who receive rigorous training in Six Sigma statistical tools, can lead or participate in dozens of such high-value projects year after year.
Beyond hard cost savings in quality, time and productivity, Six Sigma also unlocks softer benefits:
- Improved understanding of real problems and priorities
- Greater process control and predictability
- Standardized best practices across the organization
- Higher employee engagement and collaboration
- Continuous improvement culture and mindset
However, realizing these benefits requires proper oversight, commitment, training and cultural adoption – without which, Six Sigma risks becoming merely an empty buzzword.
Potential Disadvantages and Limitations
While a proven methodology, Six Sigma does have some inherent challenges and limitations to be aware of:
- Narrow focus on incremental improvement and optimization can crowd out innovation.
- Over-reliance on statistical tools sometimes at the expense of pragmatism and simplicity. Not everything can or should be numerically measured and analyzed.
- Significant training investment to develop in-house experts like Black Belts and Master Black Belts. Not easily plug-and-play.
- Cultural misalignment with environments focused on flexibility, spontaneity, and experimentation over process discipline.
The extensive focus on reducing variation and chasing perfection can unintentionally suppress creativity, flexibility, and bold innovation. Management guru Nassim Taleb has called Six Sigma "charlatanism" and believes its pursuit of statistical control leads to fragility in complex systems.
Leading digital firms like Netflix, Spotify, and Amazon rarely tout Six Sigma capabilities, though they share a passion for understanding customers, experimenting rapidly, and making data-driven decisions.
While Six Sigma analytics appeal to engineers and statisticians, the complex tools and technical jargon can impede wider organizational adoption. Requirements like achieving Green Belt or Black Belt certification erect barriers to involvement and engagement by non-technical staff.
So while a proven methodology, Six Sigma should be judiciously applied in cases where incremental quality and efficiency gains are needed but not potentially at the expense of breakthrough innovation.
The Role of Technology
Emerging technologies can significantly enhance Six Sigma effectiveness and efficiency, providing advanced tools for data-driven analysis as well as techniques like machine learning.
Statistical Analysis Software
Packaged statistical analytics tools such as Minitab, JMP, and SigmaXL can simplify the complex statistical calculations needed for measurement, analysis, and reporting. This expands access to Six Sigma techniques beyond just technical specialists.
Data Collection and Extraction
Collecting accurate input data is crucial for proper analysis. Technologies like IoT sensors, business intelligence platforms, and ETL tools feed the measurement phase with timely, trustworthy data at scale.
Process Mining
Process mining utilizes digital event log data to construct visual process models and analyze bottlenecks or deviations. This complements the Measure and Analyze steps of DMAIC with real-world process insights.
Machine Learning
AI techniques like supervised learning and neural networks can conduct rapid root cause analysis and even suggest improvements. Machines can model complex systems and dynamics that elude human analysis.
Simulation Tools
Running computational simulations enables cheap and rapid what-if analysis for the Improve phase. Simulating proposed changes via digital twin models predicts impact and identifies optimal solutions.
Combined appropriately, these technologies dramatically amplify the analytical power and real-world effectiveness of the Six Sigma methodology. Advanced software removes barriers to adoption while machine intelligence scales analysis to new levels.
Key Takeaways and Recommendations
Six Sigma, while not as hyped today as decades ago, remains one of the most effective process excellence frameworks used globally. Here are key recommendations:
Continue using Six Sigma for mission-critical processes demanding near-zero defects. In operations where safety, compliance, and reliability are critical, Six Sigma offers proven methods for world-class quality, consistency, and precision.
View Six Sigma as one tool among many, not a silver bullet solution. Use it tactically in targeted situations vs blindly across the organization. Recognize its limits regarding innovation.
Utilize modern technology like process mining, predictive analytics and simulation to boost Six Sigma effectiveness and minimize manual effort. Make insights more accessible to all.
Adapt and customize Six Sigma for unique organizational needs; avoid overly rigid textbook deployments. Right-size training and complexity.
Apply Six Sigma for quick wins first to demonstrate value. Let tangible financial returns fuel further buy-in and cultural adoption.
Use Six Sigma principles of reducing variability, even if you avoid the branding. Testing and incrementally improving processes never goes out of style.
Six Sigma delivers immense value for optimizing complex mission-critical processes. Combined judiciously with design thinking, innovation, and digital capabilities, it remains a vital toolkit for operational excellence.
