Extracting Insight from Data in the DMAIC Analyze Phase
If you are familiar with the Six Sigma methodology and DMAIC process, then you know that data is your best friend. Data can tell you a lot about your customers, site usage, advertising results, and more. But how you choose to evaluate that information can affect just how much insight you gain. In the DMAIC (Define, Measure, Analyze, Improve, and Control) methodology, one of the more important phases is the Analyze Phase, which is where Six Sigma specialists extract insight from data. In this article, you’ll learn more about this important step of the DMAIC process.
On this page:
- What is the Analyze Phase?
- Importance of the Analyze Phase
- Tools in the Analyze Phase
- Common Pitfalls in the Analyze Phase
- Example of the Analyze Phase
What is the Analyze Phase?
The DMAIC process consists of five stages, the third of which is “Analyze,” following the Measure Phase. This phase of DMAIC is where you analyze the information that will help you move forward with your project. You’ll use this information to decide whether or not to continue with the improvement effort and, if so, what kind of improvements to make. Six Sigma practitioners gather and examine information in this stage to determine the cause of the problem. They then use this information to design solutions that will improve the procedure.
The purpose of this step is to make sense of collected data so you can develop a clear picture of the current situation and how factors impact each other. The primary goal of the Analyze Phase is to identify the origins of issues and process inefficiencies so that the project team can concentrate on fixing the most urgent problems. Then, if necessary, the team can make changes to the project charter.
This phase prevents the project team from rushing to a conclusion about how to proceed without first collecting and analyzing relevant facts and thoroughly investigating the problem’s core causes.
Importance of the Analyze Phase
This DMAIC step is crucial to the success of an improvement project. It helps the team understand their process’s current state and identify improvement opportunities. The expected outcome from the Analyze phase is to pinpoint the root causes of issues so Six Sigma specialists can resolve them in the subsequent DMAIC stage. This information is essential for designing process-enhancing solutions.
Once the information has been collected, it must be analyzed to reveal any underlying trends or patterns. A number of techniques, including methods such as root cause analysis, process mapping, and statistical analysis, can be used for this purpose. Once analyzed, it is then possible to use this information to develop solutions that will improve the procedure.
This phase gives you all the information you need to make informed decisions about how to improve your process. Finally, you’ll turn your findings into actionable items by creating specific goals and objectives to solve inefficiencies.
Some common outputs and deliverables include:
- Root Cause Analysis (RCA)
- Identifying a Critical Root Cause
- Data analysis to support the RCA work
- Revised Project Charter as needed
- Prioritization of process failure points
- Review supplier-generated waste and defect
- Correlations between inputs and process variation
Tools in the Analyze Phase
Some common statistical tools and techniques used during this phase include:
Cause and Effect Diagram
The purpose of a cause-and-effect diagram is to graphically display, in increasing detail, the several potential reasons for a given problem or result, thereby implying causal links between different ideas. The Ishikawa diagram and the fishbone diagram are two common examples.
The 5 Whys Exercise
Apply the 5 Whys exercise as a basic root cause analysis technique. Getting to the bottom of a problem requires breaking it down to its origin so you can eradicate it at its source.
Graphical Analysis Tools
Six Sigma teams typically deal with large volumes of information, so much so that it is impractical to transmit the information using the raw data alone effectively. Therefore, Six Sigma practitioners should divide the information to then plot it for easier analysis. To better understand the patterns and the relationship between process parameters, graphical analysis creates visual representations of the data. Some of these tools include Histograms, Dot Plots, Box Plots, Time Series Plots, Spaghetti Diagrams, and Circle (Inter-relationship) Diagrams.
Process Map Maturation
A process map is a graphical representation of the activities, decisions, and other elements that make up a procedure. It’s a visual representation of the “as-is” state of a procedure, detailing each stage, input, and output in sequential order. During this stage, you can add more details to the process map.
Pareto Charts / Pareto Principle Application
Pareto Analysis is a simple approach for prioritizing and evaluating the relative importance of potential solutions to multiple issues simultaneously. The most noticeable changes can often be seen when using a Pareto Chart to determine which issues need to be addressed first.
Failure Mode Effects Analysis (FMEA)
To determine which aspects of a process are most in need of modification, Six Sigma specialists can conduct a Failure Modes and Effects Analysis (FMEA) to determine the most likely failure points and the severity of those failures.
Statistical Process Control (SPC)
Measurement, monitoring, and control of a process can be achieved through the use of statistics using a technique known as Statistical Process Control (SPC). This scientific visual method aims to monitor, control, and improve the process by eliminating special cause variations in a process.
Common Pitfalls in the Analyze Phase
There are a few pitfalls to watch for in this phase:
- Assuming Root Causes without appropriate data collection and analysis
- Poor data analysis
- Poor evaluation of process failure points and the impacts on quality
- Overlooking supplier and input-generated defects and waste
- Failure to revisit the Project Charter for needed changes
- Incorrectly identifying Critical Root Causes
Example of the Analyze Phase
The following is a real-world example of how this DMAIC step could involve a company that is trying to improve its customer service process:
In this scenario, Six Sigma specialists would gather information on metrics like call wait times, average handle times, and customer satisfaction. Any patterns or trends in this data would subsequently be determined through analysis. If, for instance, the data showed that customers were dissatisfied due to high wait times, that would be an indication of a root cause. Finding the root cause of a problem is the first step in devising a strategy to fix it. For example, hiring more customer care agents could help reduce call waiting times in this situation. However, DMAIC’s fourth step (Improve Phase) is where actual solutions are developed.
Data can be a powerful tool in your Six Sigma toolbox. This milestone in the DMAIC methodology is where the information that was collected in the Measure Phase gets analyzed to find the root cause of a problem. This can include everything from trends in a process to how customers interact with each page on a website. The important thing here is that you take some time to really examine your data using the right statistical tools and let it guide your decisions.