The M in DMAIC is for measure. Measure, measure, and measure. In organizations based on Six Sigma principles, measurements are an ongoing activity. The organization is always measuring, always collecting data. Data is the key to knowing how things are going, how things are really going. Considered measurement is the best way to amass the right data in the right manner.
As you saw in the previous sections, for a Six Sigma project, you create a series of plans, including a Data Collection Plan. This is where you map out what process elements and components you'll be measuring. The objective with this activity is to capture an empirical picture of current performance. These are three general steps involved here:
Figure 7-4 illustrates the measure phase.
Figure 7-4. In the measure phase of DMAIC, the objective is to begin executing the project according to plan. The first field activity is typically to collect the data. This involves preparing the organization for data collection activities, performing the measurement activities and assembling the raw data, and then ensuring that the integrity of the data is continually protected.
7.5.1. Prepare to Measure
Measuring can be an invisible activity, or it can be an intrusive activity. If you're measuring air pressure, temperature, and humidity, a barometer sitting silently on a wall will do the job. If you're measuring worker efficiency or workflow variation or other such subtle activities, you may need a stronger presence. When your measurements call for you and your team to enter the work environment in a way that might impact what it is you'll measure, you will need to prepare the environment for your visits. And so when it comes to measuring, you want to accomplish three things:
Preparing to measure is an activity that should be thought out in part in the planning stages. The first steps you take here are going to prepare you to measure properly. You want to measure the right things, the things that will help you make significant process improvements.
188.8.131.52. Create (or reference) detailed process maps
Process maps are depictions of your processes that show the detailed ins, outs, and flows of the system. A good process map will show you all the "joints" of your system, and this will help you determine good points to plan for and collect measures. Well-documented systems should have process maps available for your review and planning purposes. If the documentation is not available, you may find that it is advisable to create it. This will, of course, require extra work on your part. Maybe a good bit of extra work. But the one caveat that Six Sigma springs from is the concept that you already have processes in place. Six Sigma is not at heart a process-creation program. It is a process improvement program. And to improve a process, you've got to know what it's supposed to do and what it is doing. This requires documentation.
Use the process maps in your planning activities to decide where you can measure activity efficiently and cleanly. And then plan your measurement activities appropriately.
184.108.40.206. Validate the process maps
As you review the process maps, keep the idea of currency in mind. This is an administrative reminder. You want to validate that the documentation is still current, that it really does reflect the way the system works. This is a common problem. Documentation tends to collect dust after a while, especially with systems that change over time. And so before you begin designing the kinds of measurements you'll take of the system and before you use the process maps to determine what points you'll focus on to collect the metrics, confirm that what's in the process maps is really what's happening on the floor.
220.127.116.11. Validate the measurement system
A counterpoint to validating the process documentation is to validate that the measurement system you plan to use is also valid. Some kinds of measures are appropriate for certain kinds of situations. Others work for different situations. If you want to determine the performance of a process in which pressure molds plastic, it may be accurate to measure the temperature of the injection mold, but it may be more valid to measure foot-pounds of pressure instead. People can identify ways to measure many things. And they can collect all kinds of measures of those things. The key is to validate that the measures you plan to take are in line with the current state of the system.
18.104.22.168. Coordinate moving about the floor
This is a tactical step. It's probably also a courtesy. Before you begin collecting the measurements, it's a good idea to coordinate the collection activities with the process owners and with the people who may have to help you with the activity. This should be done with appropriate advance notice. Let the relevant parties know what is about to transpire. Seek their acquiescence if that's appropriate. Explain the purpose of the activity and what goal you are seeking to achieve. And then let them know the schedule of when the measuring will begin and how they can help in the effort.
Now go get the data. If you've examined the processes and planned for the kinds of metrics that will help you analyze performance, and if you've cleared the way with relevant parties to move into the field to get the data, then the actual measurement collection should be a relatively straightforward affair.
A couple of tips here. Collect data from many similar sources. Measure over time and hold on to the time sequence. This is essential to protecting data integrity. The data as it emerges over time tells a time-sequence story that you can use when making improvement decisions.
Just as important, use new measures. Fresh data is important. You may have access to existing or archived data, but this may not accurately portray the current situation. Use your judgment when it comes to existing measures if they are available, but at the very least, augment this with an adequate amount of current measures.
7.5.3. Protect the Data
This is an important concept, and yet it's one that is often not emphasized enough for Six Sigma projectsor for that matter, for many technology projects. When an organization elects to use data as the basis for making decisions and when it plans to subject that data to detailed analysis, it's critical to know that the data it's got is good. And so when you collect data, you should do so with two things in mind. The first is to guarantee the integrity of the data. In systems development, teams typically employ configuration management and version control as mechanisms to protect data. The same concept applies here. Your measurement teams should work to ensure that the data they collect is protected in a way that ensures it stays viable for the analyses to come.
And there is the consideration of data confidentiality. This is also not stressed often enough. We might get permission to collect reams of data, and it's possible that this data will pile up quickly over a short period of time. We may have so much of it and such easy access to it that we begin to take it for granted. But it's important to remember that data tells a story. It tells a performance story. It tells an efficiency story. It tells a success story. And so we should consider that any data is sensitive data and should be treated confidentially.