Dmaic Method From Six Sigma

¶ … DMAIC method from Six Sigma is a five-phase improvement cycle. The phases of the DMAIC process are to define, measure, analyze, improve and control (Chieh, 2009). The problem-solving method can be used to improve any process. In the context of a biotechnology company, one process that can be improved is with respect to bringing new drugs to market.

The process is complicated, but in the time that it takes to receive FDA approval and begin production, other biotech firms may be developing their own similar treatments or drugs, and capturing first mover advantages in the marketplace. The first step in DMAIC is to define the problem. For the process we are improving (guiding new products through the approvals process to market) we begin with a problem statement: Our products are taking too long to receive regulatory approval.

We have to define the key resources we will use to deal with this issue. For example, we have staff on hand whose job is to shepherd the products through this process. Thus, we need to evaluate our human resources with respect to this. Also in the defining process we need to determine a process owner or champion. This is the person who will take charge of improving this process.

In this case, a relevant VP, such as marketing or R&D will be utilized to champion this process improvement. We must determine the key sources of support within the organization. For this project, marketing and R&D can both be involved, as can the CEO and other top executives. Executive support at the highest level is required because the firm needs to show full commitment both internally and to the regulators with whom we will be working. The main source of external support will be the regulators.

We must also determine the deliverables. Our customers in this case are the end users, and we must set objectives such as delivering new treatments and products in half the time as we are currently able. The second step is the measurement process. We must define the defect we are measuring. This will involve analyzing why some our of submissions to the FDA are rejected -- we are making errors at some point in the process. We must then collect data on our current practices.

This will give us an indication not just with regard to the type of errors but how often they occur. Now that we have a data collection in place for the past, we must use that in the future to track our progress. As we implement changes to address the defects in our approval process, we must track how those changes impact the outputs, for example in terms of rejections and in terms of time elapsed before regulatory approval is granted.

Lastly, the measurement process demands that we set a baseline. For example, we understand that there will always be some rejections and delays that are out of our control. The baseline should be set, however, at the point where we believe our system is at its best. That is, at a.