What is Six Sigma?
Six Sigma is a continuous process improvement methodology based on statistical concepts. It increases company profitability through one key motivation: zero defects in a product’s lifecycle.
Companies using Six Sigma, e.g., General Electric and Motorola, made the methodology famous by saving millions of dollars a year. They also boast quality levels of 3.3 defects per 1000 000 opportunities.
The name’s mathematical roots
“Sigma” is a letter in the Greek alphabet: σ, used in statistics to represent the deviation from an expected outcome or the mean.
Example If you flipped a coin 10, 100, 1000, or 10000 times, you’d expect the result to be 50-50% between heads and tails, so a mean of 50%. Though that seems a logical expectation, the actual result, if you conducted a trial and recorded the outputs, could appear, for example, like this:
|No. of times a coin is flipped||No. of heads||No. of tails|
It shows that the more times a coin is flipped, the closer we come to the mean, the expected 50% for heads and tails.
The deviation from the mean is in how far the results differ from the expected return. In statistics, 6 σ would be the deviation between -3 points and +3 points from the mean.
And in the Six Sigma process improvement methodology, the six stands for the number of possible levels of a process rating, achieved through a DPMO calculation (defects per million opportunities). The rating corresponds to the reduction in the number of defects a company achieved.
Defects are costly
Customers and suppliers do business with companies they can trust. If a company achieved a 6 sigma rating in their process, it means that out of 1000 000 opportunities in it, only 3.3 would differ from the expected result. It indicates that, at the very least, 999 996 customers were satisfied.
Defects - variations from the mean - are costly to a business. When customers don’t get what they were expecting, there are costly consequences. They typically manifest in customers who are:
- demanding refunds
- requesting discounts
- bad-mouthing the company
- issuing items for a re-work.
All of the above will likely reduce the revenue of the business. For that reason, ensuring that a company’s processes achieve the highest Sigma rating possible will yield immediate financial benefits.
How will Six Sigma help your Kanban-based Lean operation?
Six Sigma has a defined project methodology for improving any process. While working with your Kanban team, you will collect data that can point to specific required changes. Cycle times may constantly vary, or there might be a lack of standardization.
A Kanban practitioner can address their process improvement through the 5S, Gemba walks, or Poka-Yoke, alongside Six Sigma’s statistical control. However, keep in mind that given Six Sigma’s requirement of mathematical analysis expertise, it is not the recommended first choice when tackling the low-hanging fruits in process improvement. You first need to have the right team on board and enough data to use the method appropriately.
Lean Six Sigma combines Lean and Six Sigma, and uses performance and improvement methods to eliminate the seven kinds of waste. It does it through the DMAIC (define, measure, analyze, improve and control) processes in the improvement cycles.
How to use the DMAIC method?
Six Sigma practitioners suggest using the define - measure - analyze - improve - control method to ensure the changes you bring are correct and lasting.
Step 1: Define
At this stage, you and your team should identify the problem, detail its nature, name the stakeholders it affects, and mark the proposed high-level fix timeline. It’s good to map it out on a chart to gain a complete understanding of what you want to achieve.
You might decide to look at the design process because it’s the one with the most variability. The chart could look as follows:
|In scope||Look at the design process from start to finish.|
|Out of scope||Testing process.|
|Problem statement||The design process varies, from 1 to 7 weeks. The number of iterations in designs can range from 2 to 10. That leads to development times taking longer and delayed time to market.|
|Objective/goal||Look at ways to standardize and bring predictability into the design phase.|
|Schedule||3 months: Jan - Mar|
Step 2: Measure
All steps of the DMAIC process matter. However, it is Six Sigma’s heavy reliance on statistical data that grounds it in objectivity. The Measure phase is where your team baselines the process to measure the improvements after making changes.
Your design process stage lasts between 1 to 7 weeks. You need to find an objective starting point for your comparison data: gather information on where the 1-7 weeks data came from, how far back was this cycle time being measured, how does it distribute across the range, and decide if that’s enough data, or if you need to draw additional metrics before you can move on.
Step 3: Analyze
In this phase, you should try to determine what is causing defects in the process. To help with the task, Six Sigma practitioners commonly use Pareto charts, histograms, run charts, or an FMEA, as a last resort, due to its high cost and time consumption. The goal is to find proof that what you’ve analyzed was the cause of the problem.
The information found might lead to an iterative process of updating the data in Measure and perhaps even Define phases.
You could determine that it’s the time taken to receive feedback from stakeholders and the number of design iterations that lead to the variance of 1 to 7 weeks.
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Step 4: Improve
Only here is where the improvement team implements its new solutions. The DMAIC method shows that defining, measuring, and analyzing are important enough to precede the implementation of a solution. It’s recommended to be done through trying and testing, and a good idea is to introduce one change at a time.
For their design process, the team might decide to pilot 2 iterations on proposed designs and reserve the third iteration for the approved design.
Step 5: Control
Now your team can create the foundation for process disciplines, update the required ways of working, establish metrics to continue to be measured, and determine benefit realization as well as a hand over process to the process owner.
The team could decide to build a limit of 2 design iterations into their Kanban board, and measure the time taken to complete reviews. A roadshow could be done with the stakeholders to explain the new ways of working and their benefits.
How are Six Sigma and Lean different?
We can see that Six Sigma is different from Lean. While both methods focus on the quality increase and reduction of errors and variation, Six Sigma is a lot more data-driven.
Lean is a combination of various methods aimed at bringing more value to the customer. Six Sigma is a toolbox with multiple statistical analysis methods focused on reducing defects and errors in a process. Lean, in its mindset, is a bottom-up approach, driving improvement from the ground levels up, while Six Sigma is a top-down avenue of running improvement projects to crack the tough nuts.
Process managers quickly saw the opportunities of synergizing Six Sigma with Lean to reduce errors and waste while continuously improving all aspects of a process to advance a company’s position and service offering. Although there is no necessity in joining the two approaches, their combination can reap benefits when done right and coordinated by skilled managers.
Thanks to marrying the 2 methods: Lean and Six Sigma, you should be able to:
- Achieve a more grounded and defined vision for your projects,
- Create a defined framework for measuring progress effectively,
- Increase profits by cutting down waste and reducing the cycle time,
- Find ways to improve the processes continuously.