How to analyze data

Data analysis refers to the process of analyzing a large amount of collected data using appropriate statistical analysis methods, extracting useful information and forming conclusions, and then conducting detailed research and summary of the data. This process is also a supporting process of the quality management system. In practical terms, data analysis helps people make judgments so that appropriate actions can be taken.

The mathematical foundation of data analysis was established in the early 20th century, but it was not until the advent of computers that practical operations became possible and data analysis was promoted. Data analysis is a combination of mathematics and computer science. (Recommended learning: PHP Video Tutorial)

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

Identify needs

Identifying information needs is the first condition to ensure the effectiveness of the data analysis process, and can provide clear goals for collecting and analyzing data. It is the responsibility of managers to identify information needs. Managers should identify information needs based on decision-making and process control needs. As far as process control is concerned, managers should identify the need to use information to support the review of process inputs, process outputs, rationality of resource allocation, optimization of process activities, and discovery of abnormal process variations.

Collecting 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. When planning, you should consider:

Convert the identified needs into specific requirements. For example, when evaluating a supplier, the data that needs to be collected may include its process capabilities, measurement system uncertainty and other relevant data;

Make it clear who collects data when, where, through which channels and methods;

The record form should be easy to use;

Take effective measures to prevent data loss and false data from damaging the system interference.

Analyzing data

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

, usually using the following methods :

The old seven tools are Pareto chart, Cause and Effect diagram, Hierarchical method, Questionnaire, Walk chart, Histogram, Control chart;

Seven new tools, namely correlation diagram, system diagram, matrix diagram, KJ method, plan review technology, PDPC method, matrix data diagram;

Process Improvement

Data analysis is the foundation of the quality management system. Managers of the organization should, when appropriate, evaluate its effectiveness by analyzing the following issues:

Whether the information provided for decision-making is sufficient and credible, and whether there are insufficient, inaccurate, or delayed information that lead to decision-making. Problems with errors;

Whether the role of information in continuously improving quality management systems, processes, and products is consistent with expectations, and whether data analysis is effectively used in the product realization process;

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

Whether the data analysis method is reasonable and whether the risks are controlled within an acceptable range;

Resources required for data analysis Is it guaranteed?

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