Trading Lose = Potential
Statistical analysis is closely related to the Six Sigma concept (PROCESS IMPROVEMENT). Six Sigma is derived from statistical quality control in production, which helps to identify the problem, measure the problem, reduce variability in the process, and guide towards process stability. Six Sigma aims mainly to hit the customer’s specification (quality, delivery, cost, performance) and to develop stability, i.e. the sigma level. All this occurs while reducing the company’s costs and capital investments.
Importantly, measuring the problem is performed here with the use of statistical analysis, which is based first on formulating hypotheses about the phenomenon, and then on a numerical representation of the examined (often unlucky) process. Secondly, the indicated numerical data, the relationships between them are illustrated with charts. What are the benefits of it? Well, it consists of:
- Efficient and clear verification of the hypotheses.
- Clear visualization of the process by analyzing the collected data.
- Searching for dependencies between selected process factors and obtained results.
- Possibility to make conclusions about losses – deviations as well
- directions of changes – possibilities.
Statistical analysis can be used for all kinds of data, both numerical and qualitative. Measurable and qualitative data can come from various industries, both manufacturing and service. Importantly, statistical analyzes used in (Lean) Six Sigma research make it possible to predict the phenomenon.
Lean Management is an extension of the Six Sigma concept. Lean searches for waste, thus limits losses, gives the possibility of quick improvement actions, and thus accelerates the process by reducing its complexity. Integrating Six Sigma with Lean allows you to increase the speed of the process. Lean and Six Sigma are complementary concepts, and consequently future-proof!
WE COUNT – MEASURE – ANALYZE – CHANGE!