Make short work of profit inhibitors and customer value destroyers
Many internal processes run on autopilot. Before you know it, they can become profit inhibitors that destroy your customer value. The Lean Six Sigma method lets you smartly redesign those processes in a data-driven way to maximize their effectiveness. The goal being:
- Greatly reducing waste in the process.
- Reducing lead times using Lean.
- Reducing the number of mistakes in the process: Six Sigma.
In doing so, your profitability and customer satisfaction can reach the desired levels. And your employees will experienced renewed joy in their work.
How does Lean Six Sigma justify the required investment?
You may be considering implementing this method, which has proven its success in many organizations. But you might have some questions, such as:
- How does Lean Six Sigma justify the required investment? How do I mount a business case?
- What’s my project approach, and who should I involve?
- How can I secure the results, creating a continuous improvement process?
- How do I make Lean data-driven, and what do I need to do that?
A comprehensive, data-driven approach with 4 pillars
Our comprehensive, data-driven approach to Lean Six Sigma promises visible results on the short term. We’re not just talking about operational excellence, but especially about adding value for customers. Lean Six Sigma focuses on four core pillars:
- Increasing customer value.
- Reducing lead times in processes.
- Improving the reliability of your processes.
- Reducing every form of waste (8 types).
Six Sigma and smart data
The Six Sigma part focuses on reducing the variance in process output. This is also called error reduction. Six Sigma (6σ) refers to the standard deviation of the acceptable number of mistakes. Taken literally it refers to an error margin of 0,00034%.
This is a thorough process optimization. Even with an error rate of six times the standard deviation, the results are still good from the customer’s perspective. The odds of a successful process is then at least 99,9997%. The chance of a defect is less than 3,4 in a million.
- Six Sigma is mainly applied in situations where a lot of data is available, and you want to reduce mistakes with great precision.
- Lean is also applied data-driven. We mainly focus on lead times and improving customer value and customer satisfaction.
Wherever data is available and people work together, Lean & Lean Six Sigma deliver tremendous results.
Data and process mining
One prerequisite for successful Lean Six Sigma application is the collection of data about the input and output of your processes. The next step is analyzing the data and visualizing it. Based on, for example, data mining and process mining, we can combat the output variance and randomness.
Data and facts form the foundation for both Lean and Six Sigma. With Six Sigma, we use a much greater volume of data, also called Big Data. That’s how we can make your results, performance, and quality measurable and open it up for discussion.
Other improvement methods
The DMAIC cycle is the foundation of Lean Six Sigma, data-driven improvement, and optimization. Other improvement methods strongly resemble this, or they use the same cycle. Our Lean improvement specialists also have years of experience with:
What is Lean Six Sigma?
Lean Six Sigma has proven its worth worldwide. This popular method focuses on achieving and maintaining operational excellence. That puts the focus on what your customers really value. From the customer’s perspective, we get rid of every form of waste and redundancy in the process. And of course, we won’t forget to tackle the mistakes and errors. This is done based on the DMAIC cycle:
- Define: define the questions and the problem, test it based on your business strategy.
- Measure: make their most essential parameters measurable (using KPIs).
- Analyze: analyze the data using BI tools (simple analyses and data mining).
- Improve: solve the problem and improve the process.
- Control: check whether or not the desired improvement works, stick with it, and keep improving.
In practice, this last step is often missing. It’s essential to embed the results of your improvement efforts. Doing so prevents repeating past mistakes. Completing the circle every time creates a robust, data-driven learning environment. Of course, management is actively involved in this Lean Six Sigma process.
The DMAIC cycle
The DMAIC cycle is a simple guideline for improving processes in a data-driven way. It bears a striking resemblance to the PDCA cycle. It’s an iterative process that provides structure and guidance. Project managers and Lean Six Sigma practitioners apply the right tools within DMAIC. They use those to analyze the data sets and KPIs to reveal potential points for improvement.
We’ll set up measurements, study the variance, and reduce it. The next step is improving your processes. The results: better performance, fewer mistakes, and greater efficiency and productivity.
Figure: the DMAIC cycle is the backbone of every process improvement
The steps are logical and easy to understand. Process improvement projects are the norm within many organizations nowadays. Every (project) manager will sooner or later be confronted with the need to improve KPIs. Therefore, every manager should be proficient in applying the DMAIC cycle.
1. Define: the problem, the scope, the KPIs, and the stakeholders
This step is focused on setting up the project to succeed. During this step, you have to secure upper management’s commitment to the project. Determine the scope, the stakeholders, and the team members. And you’ll plan and host a successful kick-off meeting.
The project manager will, together with the team, make a process map of the current situation. In doing so, you’ll ensure that your team has a shared perspective on the process. Using the same process, you’ll define the problematic aspects of the steps of the process. You’ll also determine the activities and KPIs that don’t add value. During this step, the team will also receive Lean Six Sigma training and an explanation of the DMAIC principles.
2. Measure: the data, data quality, and data visualization
Many teams skip this step, which is one of the biggest mistakes improvement teams can make. They make decisions based on gut feeling, intuition, or anecdotal information. It’s absolutely essential to make decisions based on facts and reliable data. This is the most important goal of this step. During this step, the team will:
- define and establish the most important KPIs.
- make a plan for the collecting and processing of data.
- ensure the data’s accuracy.
- convert the data to graphs and tables.
This last part lets the team see where the mistakes and long lead times are located.
3. Analyze: the root causes, verification, and solutions
This step is about getting to the root of the problem. Too often, people focus on symptoms, rather than causes. During this step, tools and techniques will help the team expose said causes. Value analysis, statistical analysis, cause and effect diagrams, and more are used here.
Then, the team collects data about the root causes to determine whether or not there’s a causal relationship to the problem. Verifying the cause and effect is a crucial step in this phase. Too often, this step is skipped. Opinions often end up unjustly trumping facts.
4. Improve: the right solutions, verification, and validation
After going through the previous three steps, your team will have the only correct perspective. Now you know how to solve the problem in an innovative way. During this step, you’ll develop and test this creative solution. The most important product of this step is a verifiable, measurable improvement. The best ideas should be implemented on a small scale in order to determine if they’re going to lead to lasting improvements. When the improvements show themselves in the measurements, you can share them with stakeholders. They’ll be more eager to accept and want to implement improvement suggestions.
This step removes emotion from the decision-making process. Improving is about verifying and validating the recommendations. Too often, teams make the mistake of thinking they know what the solution is, and implementing it blindly without testing it. In most cases, that doesn’t result in a measurable or sustainable improvement.
5. Control: the recommendations, reasoning, implementation, and securing
The real strength of the DMAIC cycle is in the Control step. Too often, teams work hard to improve the process and the results, but the implementation of the improved process doesn’t go as they envisioned. All the while, there’s pressure to keep going. Then they don’t spend any time to get a buy-in for the complete implementation. The result is that the initial improvement is hard to sustain.
The goal of the Control step is the successful implementation of the team’s recommendation, so that it leads to long-term results. The new process is laid out in flow charts and the new working methods are standardized. The results continue to be measured, so that you can see any backslides and act proactively. The Control step is about redistributing responsibilities. You should also make plans for long-term process control.
How do you recoup the Six Sigma costs?
We advise using your own people as much as possible. Their skills and knowledge will be actively used. This saves costs and greatly improves the chance of success. You’ll definitely need support when seeking out new knowledge and experience through training courses. The short-term profit of Lean Six Sigma can be variable. But you can be sure that it always makes its money back when applied effectively. That’s our guarantee.
The most important hallmarks of our Lean Six Sigma approach
✓ Data-driven decisions based on facts (business intelligence).
✓ A structured project approach with agile components.
✓ Spark enthusiasm with well-trained, internal improvement teams.
✓ Emphasis on speed, customer needs, and reducing variance and waste.
✓ High priority with management.
Do you want to increase customer satisfaction?
Take our unique 3-day Lean training or contact us to talk about what our Lean Six Sigma expertise can mean for your organization.