Basic of Data Process Collection
A statistical analysis of the data collection process. All calculations for the process in the world you are trying to measure to understand the behavior will not compensate. Number is not all settled. Some things will be discovered in the context. For example, "we really have problems when it rains."
Consequently, data collection plan to collect data that are needed to optimize its usefulness to embody the four properties. These properties, the ability of the data represent the performance of the process has to do with.
Enough to see the process data should be treated.
Data must be relevant.
Data should be representative of normal operation conditions.
Data must be relevant.
Enough
There are quite changes and get out of comments in the process of change in central tendency should be to see the models. A plan to collect data as part of the building, the process history of the team "so that changes are expected to capture all sources will seek to understand.
It also should be given to show the difference in the size of the team is trying to measure. As the gap size becomes smaller, the difference with a statistical confidence measure increases the number of samples needed.
Data problem
Data problem that is being studied should be relevant to. For example, if a back injury has been associated with process analysis, data security probably will not be about the availability of relevant glasses. The central purpose behind the question or data collection plan will be developed so that data is needed.
Data must be related to an important business metric. Since data collection is an expensive process, the project team because they want to collect data to verify the accuracy of the work should be. Buy in from stakeholders and process owners to falter if they discover the team's focus away from the central core of the project.
Representative
Process the data should represent all the real operating conditions. For example, the cycle time to fund the study, the data is representative of shipments to customers of all levels.
Operating conditions may include a multitude of factors. Some examples are the time of day, or sales promotions, employee experience, the process of inputs, and so turns. Project team will brainstorm a list of chip potential factors that must be considered when planning data collection.
Relevant
Relevant information that the situation around us, but are not part of the process related and can affect its performance. The information we collected data to add interest. For example, the extraction cycle time than was usual on a given day, how you too cashiers were in service and what customers are buying and weather can. It focuses on how processes behave in different situations.
Reduce costs and improve efficiency of data to tell stories, a comprehensive collection of data will be needed. Participation will improve the quality of master planning process. Process owners can make a valuable contribution because they are external also directly to the processes (or the impact of the forest trees) in an effort to improve are not included.
Consequently, data collection plan to collect data that are needed to optimize its usefulness to embody the four properties. These properties, the ability of the data represent the performance of the process has to do with.
Enough to see the process data should be treated.
Data must be relevant.
Data should be representative of normal operation conditions.
Data must be relevant.
Enough
There are quite changes and get out of comments in the process of change in central tendency should be to see the models. A plan to collect data as part of the building, the process history of the team "so that changes are expected to capture all sources will seek to understand.
It also should be given to show the difference in the size of the team is trying to measure. As the gap size becomes smaller, the difference with a statistical confidence measure increases the number of samples needed.
Data problem
Data problem that is being studied should be relevant to. For example, if a back injury has been associated with process analysis, data security probably will not be about the availability of relevant glasses. The central purpose behind the question or data collection plan will be developed so that data is needed.
Data must be related to an important business metric. Since data collection is an expensive process, the project team because they want to collect data to verify the accuracy of the work should be. Buy in from stakeholders and process owners to falter if they discover the team's focus away from the central core of the project.
Representative
Process the data should represent all the real operating conditions. For example, the cycle time to fund the study, the data is representative of shipments to customers of all levels.
Operating conditions may include a multitude of factors. Some examples are the time of day, or sales promotions, employee experience, the process of inputs, and so turns. Project team will brainstorm a list of chip potential factors that must be considered when planning data collection.
Relevant
Relevant information that the situation around us, but are not part of the process related and can affect its performance. The information we collected data to add interest. For example, the extraction cycle time than was usual on a given day, how you too cashiers were in service and what customers are buying and weather can. It focuses on how processes behave in different situations.
Reduce costs and improve efficiency of data to tell stories, a comprehensive collection of data will be needed. Participation will improve the quality of master planning process. Process owners can make a valuable contribution because they are external also directly to the processes (or the impact of the forest trees) in an effort to improve are not included.
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