How to Collect Data in the Measure Phase of the DMAIC Process

Six Sigma professionals rely on the DMAIC method to create efficiencies and improve productivity. DMAIC methodology is a quality improvement approach based on data that is used to improve business operations. DMAIC stands for “define”, “measure”, “analyze”, “improve”, and “control”. Six Sigma specialists can utilize the DMAIC cycle to enhance every aspect of an organization, from production to customer service.

This article will focus on the Measure Phase, which is the second step in the process. Gathering as much information as you can about the present processes involved in a problem is the goal of this phase. Read on to learn more.

On this page:

• What is the Measure Phase?
• Importance of the Measure Phase
• Tools in the Measure Phase
• Outputs from the Measure Phase
• Example of Measure Phase
• Summary

What is the Measure Phase?

The DMAIC process’s second step is the Measure phase. If you need information regarding the way things are going right now, the Measure stage is where you’ll do it. The DMAIC Process’s first step, “Define,” provides a framework within which this information is gathered. The Define stage is when the project’s objectives and evaluation-based metrics are established. The third stage, analysis, is when you’ll start to look at the data you acquired in the Measure stage to see where the process may use some tweaking.

In the Measurement Phase, Six Sigma professionals look for root causes, evaluate measurement systems, outline a Data Collection Plan, acquire data, perform a process capability analysis, draft operational definitions, evaluate “as is” / current state data, create and implement sampling plans, analyze data, and if necessary, revise the Project Charter.

This stage centers around gathering information on the operation as it now stands, which is then used to target improvement areas. The first step in gathering this information is to settle on suitable metrics for measuring the process.

Key factors when selecting measurement methods

Key factors to consider when selecting measurement methods and criteria are:

• Is the data relevant to the customer’s requirements?
• Will the data support the improvement goals?
• Will the data support the broader organizational goals?
• How difficult will it be to collect accurate and representative data?
• How much data will be required to support the analysis and decision-making process?
• What are the data sources, accuracy, and availability for the data needed?
• Is the Current State Map robust enough to show process variation points and waste?

After establishing the metrics, the next step is to gather information about them. Multiple techniques, including surveys, interviews, direct observation, and even process logs, can be used to collect this information.

A Data Collection Plan should be created to identify the data sources, the degrees of difficulty in retrieving data, and identify any roadblocks that may exist.

When developing the Data Collection Plan, keep the following in mind:

• What is the knowledge needed from the process?
• What are the potential sources of variation in the process?
• How readily available is the desired data?
• Who will be collecting the data?
• How much time will be required to collect the data?
• How will the measurement system be analyzed to ensure accuracy and integrity of the data in light of the measurement system?
• What types of data errors should be considered and guarded against?
• How can the data be displayed and analyzed?

Importance of the Measure Phase

The Measure Phase of DMAIC is important because it allows you to collect data about the current process. This data will be used to identify areas in need of improvement. Without this data, it would be difficult to improve any part of an operation.

The primary output of this stage should be data regarding the present process. Other outputs might include a list of metrics to be used to measure the operation as well as a strategy for collecting data on these metrics.

Six Sigma professionals should conclude the Measure stage with a detailed process map that illustrates how the process in question is being carried out at the present time, as well as statistics and charts that demonstrate how effectively the operation satisfies customer needs or company objectives. The data collected during the Measure phase is a crucial component of the next step in the DMAIC process, which is to analyze the data to determine what is causing the operation performance issues.

Tools in the Measure Phase

Various tools can be used during the Measure Phase. Six Sigma professionals can use these tools to gather information about the process in question. Surveys, interviews, observation, process logs, and flowcharts are all useful in this stage.

Some of the most common tools and methods used at this stage are:

• Brainstorming
• Cause and Effect Diagrams
• Cause and Effect Matrix
• Failure Mode Effect Analysis (FMEA)
• Sampling
• Pareto Analysis
• Statistical Process Control (SPC)
• Process Capability Analysis
• Measurement Systems Analysis
• Process Mapping creation and maturity

Outputs from the Measure Phase

Here are a few common deliverables from this stage of the DMAIC process:

Measurement System Analysis (MSA)

MSA is crucial to the measurement process. The goal of an MSA is to isolate the factors that contribute to observed measurement variability. Before making a decision based on data, an MSA is performed to ensure that the measuring system is accurate.

Data Collection Plan

A data collection plan for the specified variables must be established to make sure the data is useful and valid. It provides the specific processes and sequence for acquiring Six Sigma project data. This plan includes delegating specific data collection tasks.

Operational Definition Information

Having a well-defined set of operations is crucial for collecting good data. An Operational Definition specifies what is to be measured in this step of DMAIC. This ensures dependability and consistency during the measurement process, which are key objectives for the DMAIC Measure phase.

Example of Measure Phase

Example: Improving the customer service process

For this scenario, a Six Sigma expert would define the project’s objectives and the measurements to be used in the Measure stage. Levels of customer satisfaction, phone wait times, and average handling times are all examples of metrics that might be used. At this point, the team is ready to begin collecting data on the newly specified metrics. The team can gather this information by conducting surveys, in-depth interviews, observation, or process logs. After the Six Sigma specialist has gathered this information, they can begin to evaluate it to find areas in need of improvement. 

Summary

The Measure Phase requires a substantial amount of effort. Because of how important this effort is to the success of later stages, it is crucial that the deliverables be comprehended and applied. The tone for the remainder of the steps in the process improvement initiative is established by the actions taken during this step in the DMAIC method. Therefore, Six Sigma practitioners should have a detailed understanding of this step.