Since the early days of manufacturing, businesses look for ways to improve the quality of their processes and reduce the number of defective products. Between many quality control approaches, Six Sigma has become a popular technique that applies to a wide range of industries, besides manufacturing. Considering today’s complex processes and the advances in the latest technology, Six Sigma is still a relevant approach for process improvement.
In this article, we provide a comprehensive guide on Six Sigma and why it is still relevant for process improvement.
What is Six Sigma?
Six Sigma is a set of data-driven quality control techniques that aims to improve business processes by reducing the likelihood of defects and reducing the variations in processes. It offers statistical methods that reduce variance and help identify the root causes of errors for more effective and efficient processes.
The name comes from the Greek symbol “sigma” or “σ,” a term that defines the deviation from the mean in statistics. In business terms, you can think that it is the process deviation from your target where one sigma means you are a single standard deviation from the target. Six-sigma is the target limit where you need to keep your process in to reduce the probability of any defects. At the six-sigma level, the likelihood of errors is 3.4 per million products.
For example, you manufacture a product that must have a thickness between 10.32 and 10.38 inches. Then, your target (or mean) is to have a width of around 10.35 inches. If you keep your standard deviation less than 0.005, then your upper/lower limits will satisfy product requirements, and the probability of having defects will be very unlikely.
On the below table, there are some real-life sigma level examples to illustrate the probability of having defects at the six-sigma level.
Why and how did it get started?
The methodology is founded to eliminate product defects in manufacturing processes. In the mid-1980s, Motorola engineers thought that the traditional quality assessment techniques weren’t accurate enough since they measured defects in thousands of products. Thus, they developed a new method called “Six Sigma” and started to measure defects in million products. After the implementation of Six Sigma, Motorola has documented more than $16 billion in savings in twelve years.
Motorola then realized that they could apply this method, which previously used to achieve fewer defects in parts manufacturing to other business functions. Other large companies like Texas Instruments and General Electric have also started to adopt this methodology. In the 1990s, General Electric introduced this approach in management processes to reduce deviations in processes. This provided desired results for General Electric as the company’s annual profit increased by 66%, to $13.6 billion in the five years to 2001.
Today, it is an industry standard with certifications offered to practitioners.
Why is it important now?
Since the 1980s, Six Sigma methodology has become a popular technique widely applied in many industries. Considering today’s complex processes, Six Sigma can be a powerful solution approach to understand actual processes and reducing possible errors in highly complex situations. Here are the key reasons why adopting Six Sigma philosophy to your business is important now:
Understanding the full-picture of processes
While Six Sigma focuses on reducing the deviation in processes, it is a data-driven approach that enables businesses to measure their performance metrics to understand processes. With the implementation of new strategies and updates in procedures, companies might not be fully aware of their “actual” processes. Even they know what their processes should look like, they need to have an “as-is” picture of processes that can be achieved by data-driven analysis.
Six Sigma benefits from the increasing amount of data to help businesses to gain insights about their processes. These insights allow them to take accurate action to improve process performance.
The increased complexity of today’s processes creates more room for variations between the same tasks. This situation makes it harder to track business performance and causes more errors to occur. By adopting Six Sigma methodology, businesses can maintain their complex processes standardized, even if new integrations and requirements are added to procedures. Standardization will allow companies to reduce errors while handling their tasks.
Businesses should be able to improve their performance continuously, considering today’s fast-growing business strategies. To do that, business leaders first need to have control over their processes at any time and be aware of areas of improvement by benefiting from real-time data. Six Sigma uses a data-driven approach to detect problems and bottlenecks in processes and helps businesses improve their performance continuously.
How does it work?
The Six Sigma uses an approach called DMAIC, which stands for define, measure, analyze, improve, and control. It is a statistically driven methodology that is used for improving, optimizing, and stabilizing business processes. Here are the steps of DMAIC:
This step aims to explain clearly the business problem, the goal, potential resources, project scope, and timeline of the high-level project. You need to identify what you currently know, set objectives for your business, and form the project team.
The necessary data is identified and collected in this step. The initial metrics of the situation are measured. These metrics can show what may cause the problem, give insights to the team for understanding the full picture, and help set the process performance baselines.
In this step, the team identifies the root cause of process errors. To do that, each input is isolated and tested as the cause of the problem during analysis.
This step aims to improve process performance. After the analysis step, possible solutions are discussed and implemented in the process for eliminating the errors.
The team adds controls to the process to ensure that the solution works, and the process doesn’t become ineffective again.
Six Sigma can also be used in another approach called DMADV, which is used to design or re-design different processes of product manufacturing or service delivery. DMADV stands for define, measure, analyze, design, and validate. This approach is used while adopting Six Sigma when existing processes do not meet customer requirements, even after optimization, or when the implementation of new methods is needed.
Have we reached peak Six Sigma?
Six Sigma has been a popular term since the early 2000s (or even earlier), and we have definitely reached and passed the peak. Since then, Six Sigma has been losing its popularity as seen in Google Trends. This is possibly due to 3 trends:
- New process improvement approaches like Agile
- Recently increased focus on innovation as technology accounts for an increased share of the economy
- The fact that these approaches are like management fads and that as managers change, new approaches gain popularity
With the popularity of Six Sigma declines, General Electric discontinued company-wide Six Sigma requirements for promotions more than a decade ago. However, in businesses like air travel that prioritize reliability and safety over innovation, Six Sigma is still a popular approach.
What are its disadvantages?
Companies, like individuals that make them up, can only focus on a certain number of topics. If quality improvement and efficiency through meticulous measurement is the focus, then innovation can suffer. Innovation is notoriously hard to measure; however, this research suggests that focusing on efficiency indeed limits innovation.
Thus, excessive focus on Six Sigma might prevent businesses from innovation. According to Mike Pino, a technology strategist at PwC, disruptive innovation is discouraged in the businesses built around Six Sigma. While Six Sigma reduces process deviations and provides higher quality processes, companies need to follow innovation opportunities and evaluate their position to reach the desired outcomes. Without innovation, they might not make riskier and more radical changes in processes, potentially missing out on more significant benefits.
How does the latest technology impact Six Sigma?
The latest advances in technology help Six Sigma to impact businesses even greater. With the help of data collection techniques, companies can now collect more data to understand their current position better. While machine learning methods contribute enhanced data collection, they also help in converting unstructured data to structured data and conduct root-cause analysis about processes. The improvements in these technologies impact Six Sigma as the performance of methodology gets better, as well.
AI algorithms can also support Six Sigma and offer solutions for process improvement. With automated data processing, AI algorithms, like neural networks, can understand the “as-is” processes, their bottlenecks and make suggestions to eliminate bottlenecks. Explore more on how to pair these process technologies with six sigma.
Below you can find more specific technologies which can directly impact Six Sigma philosophy:
Process mining boosts the Six Sigma approach and improves business performance by identifying bottlenecks and reasons for them. By using process mining tools, businesses can see their “as-is” processes, compare them with the desired processes, and detect root-causes by analyzing the discrepancies. By that, process mining enables the Six Sigma methodology to reduce deviations in processes much faster.
Here is how process mining can impact the DMAIC cycle step by step:
- Define: Businesses can see their “as-is” processes to have a clear understanding of their current position. With that, they can set more precise objectives and prepare a well-prepared timeline.
- Measure: Benefiting from event logs, process mining tools can rapidly provide performance metrics and allow businesses to set performance benchmarks.
- Analyze: By comparing the actual and desired processes, process mining tools can identify root-causes of the variations within the processes and provide data-driven evidence.
- Improve: Process mining tools can provide insights into how to make improvements to reduce deviations.
- Control: By working in real-time, process mining tools continuously check if the changes give the expected results and validate that the process is improved.
By adopting a process mining software, BridgeLoan, a South African insurance company, has achieved 40% faster processes and is now able to react quickly to possible problems in processes. To read more case studies, you can visit our process mining case studies article.
You can read our in-depth process mining guide to understand how it works and why it is needed for process improvement.
With the advances in data extraction, businesses can collect data from various resources and convert unstructured data to structured data accurately. This enables companies to have more data about their processes and allows them to conduct more precise analysis to understand their processes better. Data extraction technologies help Six Sigma methodology work with higher-quality data, ensuring a more accurate analysis and better process improvement.
To have more information about data extraction, feel free to read our in-depth data extraction guide.
Discover other methodologies and process intelligence tools that help improve your processes by reading:
- What is Process Intelligence & 5 Reasons Why It Matters?
- Lean Process Improvement in 2022: What it is & How it works
- What is Process Workflow & 4 Reasons Why Businesses Need it
If you believe your business need to leverage any tool for process improvement, go over our comprehensive and data-driven process mining, process modeling and business process management software vendor lists.
If you have questions about how Six Sigma process approach can help your business, feel free to ask us:
Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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