The four steps of data analysis are

The main activities of the data analysis process consist of identifying information needs, collecting data, analyzing data, and evaluating and improving the effectiveness of data analysis.

First, identify needs. Identifying information needs is the first condition to ensure the effectiveness of the data analysis process. It can provide clear goals for collecting and analyzing data. (Recommended learning: PHP Video Tutorial)

Identifying information needs is the responsibility of managers. Managers should put forward information needs based on the needs of decision-making and process control. As far as process control is concerned, managers should identify the needs and use that information to support the review of process inputs, process outputs, the rationality of resource allocation, the optimization of process activities and the discovery of abnormal process variations.

Second, collect data. Purposeful collection of data is the basis for ensuring the effectiveness of the data analysis process. Organizations need to plan the content, channels, and methods for collecting data.

Third, analyze data. Analyzing data is to process, organize and analyze the collected data into information.

Usually used methods are:

The seven old tools, namely arrangement chart, cause and effect diagram, hierarchical method, questionnaire, walk chart, histogram, control chart;

New seven tools, namely correlation diagram, system diagram, matrix diagram, KJ method, plan review technology, PDPC method, and matrix data diagram.

Fourth, process improvement and data analysis are the foundation of the quality management system.

Managers of the organization should, when appropriate, evaluate its effectiveness by analyzing the following issues:

First, whether the information provided for decision-making is sufficient, credible, and whether it exists Problems with decision-making errors due to insufficient, inaccurate, and lagging information;

The second is whether the role of information in continuously improving quality management systems, processes, and products is consistent with expected values, and whether it is effective in the product realization process Use data analysis;

The third is whether the purpose of collecting data is clear, whether the collected data is true and sufficient, and whether the information channels are smooth;

The fourth is whether the data analysis method is reasonable and whether the risks are controlled Within an acceptable range; whether the resources required for pragmatic data analysis are guaranteed.

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