This could involve collecting a few samples every hour. For example, when applications are processed by a team of associates, you can conduct a dip-stick audit at regular intervals. In case your Lean Six Sigma Green Belt or Black Belt project aims to improve any process, then you can employ process sampling there. Hence in this case, it would be better to stratify the applications by source and then randomly sample within each strata. So we need to sample each strata separately and draw estimates depending on their contribution to the overall population. For example, in your Lean Six Sigma Green Belt or Lean Six Sigma Black project, if the applications are received through 3 different channels such as Physical Applications, Web Application Form and Applications from Mobile App, then its likely the sources of error are different and hence the error rates are also likely to be different. If your lot is not homogeneous but has different strata (or groups) within it, you will employ stratified random sampling. For example, in your Lean Six Sigma Green Belt or Black Belt Project, if you wish to sample a few applications from a lot of 100 applications to find how many are incomplete, you can deploy this method. This is the most common method of population sampling. As mentioned earlier, broadly there are 4 methods of sampling, 2 in each Population Sampling and Process Sampling. Once this is clear, the next step will be to decide exactly which method of sampling will you deploy. Depending on the nature of the problem or improvement you wish to bring about using Lean Six Sigma, the sampling method will have to be decided. In the Measure Phase of DMAIC, you will have to decide what data is to be collected and how this data collection will be executed. This concept will be very useful if you are running a Lean Six Sigma Green Belt or Black Belt project. Thus as an example, if you have a lot of parts or applications to be processed, you can employ population sampling to evaluate incoming quality and process sampling to evaluate the quality of the output the process is generating. On the other hand, when there is a process (manufacturing, service or tech) which is continuously producing output and you wish to sample in between the process steps or at the end of the process, so that you can check the health of the process and accordingly alter the process parameters, then you will deploy process sampling methods. This is because we don’t have any idea of how this lot or population was built. If you wish to assess some characteristic of the 100 applications, then you can employ sampling, but the results will only be conclusive for those 100 applications. For example, if you have 100 applications, that becomes the population. A population refers to a lot or collection of items which can be parts, documents, transactions, etc. We will now get to the details of selecting the right sampling method.įirst understand if you are dealing with a Population or a Process in which sampling has to be performed.

There are few more intricate sampling techniques, but these 4 should suffice in most of the scenarios. There are broadly 4 sampling techniques that are commonly used. If these risks have to be minimized, then one of the things we need to ensure the right sampling method is adopted. But it comes with certain risks of drawing wrong conclusions, from the data so collected through sampling. If you are a Lean Six Sigma Green Belt or Lean Six Sigma Black Belt, or just an aspirant or a Quality Engineer, you will encounter several scenarios where you have to sample the data during data collection in the Measure Phase of DMAIC project.īefore selecting the right method for sampling, it’s important to understand why sampling needs to be done, what is the objective of the data collection and what are the expected outcomes from the data collected through sampling.ĭata sampling saves a lot of time and effort in data collection. There are different reasons why you would go for sampling. Selecting the Right Sampling Method for LSS Projects

Six sigma black belt project examples