As we’ve discussed, Six Sigma is a set of techniques and tools for process improvement originally developed for assuring quality by decreasing manufacturing defects. It has evolved into a scientific method for project development.
When an organization that follows Six Sigma undertakes a project, it uses a system known as DMAIC as a framework. DMAIC allows a team to develop the project from its inception. It is sufficiently flexible to be applied to performance tuning.
What is DMAIC?
As Craig Gygi, Bruce Williams, and Neil DeCarlo, authors of Six Sigma for Dummies explain, it is “a formalized problem-solving process of Six Sigma.” The five steps can be easily applied to any business procedure. These five steps are:
- Define: Set the context and objectives for your improvement project.
- Measure: Determine the baseline performance and capability of the process or system you’re improving.
- Analyze: Use data and tools to understand the cause-and-effect relationships in your process or system.
- Improve: Develop the modifications that lead to a validated improvement in your process or system.
- Control: Establish plans and procedures to ensure that your improvements are sustained.
Each of these steps is equally important in the Six Sigma process. When you assign more importance to one step, you risk giving short shrift to another. The “Control” step is a prime example since it often is overlooked by project managers who would like to wrap up and move on (however, that’s a conversation best left to another post).
How does DMAIC apply to database management?
Defining a problem is not always so simple. A way to think about this is to identify improvements that you or the customer — not always an external entity, but perhaps a department or group your organization is supporting — wants as a result of this process. What goals should be met with this project? Do you want fewer data entry errors? Should queries be returned faster?
How do you measure the improvements you’re striving for? You need to outline exactly what data needs to be measured and find the tools or applications that are able to collect data and measure the results.
“Analyze” is a critical step in DMAIC, but no more important than any other in this process. Analysis allows performance to be stripped to its essence. How does the actual performance of the database or some aspect of the database, for example, differ from that of the target? Is there room for improvement? Should the process be changed? Does the process affect data output? How can improvements be reached?
The “Improve” step drives the quest for quality forward. What solutions can help improve the targeted process? Testing is an integral part of this DMAIC stage. As we know, testing is very important to make sure a performance-tuning effort doesn’t trigger a cascade of unintended consequences.
“Control” is an essential part of the process. The project must be monitored to see if changes have taken root as outlined, and that the entire project is indeed moving forward successfully. This might be making sure that policies and procedures for data entry are adhered to, that a new tool is effective, or that training for a new project is successful. A project is not simply checked off as “finished,” but steps are taken to ensure results are maintained.
What are your experiences with applying the DMAIC framework within your organization? Let us know.
Image credit: 1tjf / 123RF.
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