Critical Considerations During the DMAIC Measure Phase

Organizations turn to the Six Sigma business methodology to reduce variation, eliminate defects, and make operations more efficient and effective. One of the cornerstones of Six Sigma is the DMAIC process improvement cycle. DMAIC stands for define, measure, analyze, improve, and control.

More specifically, the five phases are:

Define – Define the problem that needs to be addressed

Measure – Assess the extent of the problem and quantify it with objective data

Analyze – Use the data to find the root cause of the problem

Improve – Implement changes that eliminate the root cause

Control – Maintain the improvements you've achieved with the changes

Each phase comes with a set of goals and tools used to support them. For example, in the first phase, define project leaders, gather the team, identify a problem, and set goals. 

In the Measure phase, the team begins to dive deeper into data. That will be the focus of this post.

Milestones for the Measure Phase

Each stage of DMAIC has a series of milestones. These critical junctures mark the deliverables that teams must achieve to be successful. In the Measure stage, there are three significant milestones.

1. Document the performance indicator identification, which details what teams will measure in a process. The goal is to find the key performance indicators that appear as early in the process as possible.
2. Create a data collection plan that defines the methods and procedures for collecting data.
3. Identify a baseline performance measure that indicates how well the organization is currently doing to illustrate the importance of the project. Keep in mind that the goal is to achieve Six Sigma, fewer than 3.4 defects per million opportunities.
   
   

Problem Statement

The problem statement serves multiple purposes in a DMAIC improvement cycle:

1. It clarifies the current situation by clearly stating the problem and its severity, location, and economic impact.
2. It serves as an internal communication tool, helping to get buy-in and support from the relevant stakeholders.
3. When problem statements are expertly written, people quickly understand and concur with what you're trying to accomplish.

A well-crafted problem statement will include:

• A succinct description of the problem and the metric used to quantify the problem
• The source of the problem is occurring by process name and location
• The time frame over which the problem has been observed
• The size or quantity of the problem
  
  

Data Collection Plan

The measure phase is one of Six Sigma's most critical, longest-lasting, and highly scrutinized elements. Everything in the measure phase flows from the data collection plan. Therefore, understanding current performance is essential to effective and sustained improvement.

The data collection plan consists of specific instructions on precisely what data will be gathered. It outlines who will collect the data, as well as where and how they will accomplish it. The plan ensures that the data collected is accurate, clean, and relevant to the problem the team has identified.

The amount of data and the period covered depend on several factors, including the cost of data collection, the cadence of measurement, and the urgency of the problem.

Measurement Systems Analysis

Measurement Systems Analysis (MSA) is a method for analyzing the variation present in each type of measurement, inspection, and test equipment. It is the process of assessing the quality of the measurement tools. In short, it allows teams to make sure that the variation in their measurement is minimal compared to the variation in their process.

Keep in mind that the goal of DMAIC is to remove defects from processes by limiting variation. But variation comes in two groups, process variation and measurement variation. 

For example, let's say that you and a friend are making a cookie recipe that calls for one cup of all-purpose flour. You know that a cup of flour weighs 120 grams, so you carefully measure what you add to the recipe. Your friend just eyeballs it. Even if you follow the same recipe and process, your results may vary. The difference between the amount of flour you added and what your friend added is measurement variation, and any baker can tell you it can make a big difference.

Capability Analysis

The capability analysis establishes the framework for determining whether the current operation is meeting specifications. In addition, capability analysis gives the team a statistical measurement of the variability in a particular process characteristic. Capability analysis is vital because reducing variation is one of the main goals of Six Sigma.

Process capability can be categorized under two types:

Short Term Capability: Short-term capability is calculated with data gathered over a short period when there is no external impact on the process (i.e., a shift change, operator change, temperature change, or other controllable influence). Short-term capability gives you insight into the technology of the process. 

Long Term Capability: Long-term capability represents the real-world performance of a process over time. It is calculated from data gathered over a long enough period such that external factors do influence the process. Thus, it gives you insight into both the technical capability of the process and the elements that process operators and managers control.

DMAIC Measure Phase Tools

There are several Six Sigma tools and techniques that can be valuable during the measure phase. They include:

Pareto Charts: A Pareto Chart is a cause analysis tool. It represents statistics in a bar visualization, with the length of bars indicating the frequency of errors and the costs in both time and money. The longest bars are usually on the left, with the shortest on the right. A Pareto Chart is especially helpful for analyzing the frequency of errors or focusing on one specific area if there are multiple concurrent problems.

Control Charts: Control charts represent the performance of a process over time against a mean, an upper control limit, and a lower control limit. They help identify common cause variation vs. special cause variation and help teams sort out what is expected and what is cause for concern.

The 5 Whys: The 5 whys technique is a method for determining the root cause of a problem. Teams ask "why" as often as necessary to uncover the underlying issue. Usually, five times does the trick.

It is no doubt that the DMAIC Measure phase is a long, involved process. But the above tools and techniques can help your team manage the process better. Reliable data is critical to the next phase of DMAIC, Analyze, in which teams begin to identify the root causes of process problems.