What Steps Can You Take to Obtain Unbiased Data?
Data collection is essential for decision making in the organization. The management needs to ensure that accurate data is collected by the research team to enable the management to make the right decision. Biased information may result in decisions that may affect the organization negatively rather than correcting the problems facing the organization. Accurate and unbiased data is collected from a sample depending on the methods the researcher will use to collect the data. The sample size also contributes adequately to the quality of data collected. The researcher should ensure adequate distribution of the sample before compiling the results of the research.
Data collected from a sample field will always be subject to errors from the researcher or the tools used to collect the data. The quality of the measurement tool determines the reliability of the data collected for decision making. The initial step in collecting data free from bias would be to acknowledge that the human instrument is flaw. Accepting this fact will enable the researcher to compensate for this error in a research thus reduce the bias associated with the sample. For data collected on a regular basis, the company can use a data template to ensure consistency in the data collected.
The second step in eliminating bias in a research is to ensure that the organization uses decision tree I decision making. Decision making trees determine the variables affecting the research thus compensate for the bias. The purpose of the decision tree is to integrate variables that affect the research thus increasing the reliability of the data collected. Decision trees make the process of decision making easy as the incorporation of variables in the decision results in a defined result. The purpose of the decision tree is to evaluate the way different managers in the firm will react to the problem facing the research.
Research should be conducted in an open information environment where the value of input is recognized in ensuring that the accurate data is collected. The researcher should be open-minded when collecting data for decision making. This clears the researcher mind and eliminates the possibility of bias in information collection. A rigid researcher will tend to focus his research on a specific area thus the overall information collected from the research will be biased to the area being focused. Open information environment enables the researcher to gain learning and instructional strengths which help to reduce bias in the research.
Understanding the Vroom-Yetton model enables the researcher to become aware of the bias associated with collective data. The model assists the researcher to balance decision quality, team development, efficiency and commitment. The use of decision tree encourages consensus in the group as a way of reducing bias in the decision made. Discussions between the team members will reduce the likelihood of bias in the final decision thus the quality of the final decision made will be high. The decision tree allows consultation between the team members thus the quality of the data collected and the decisions made from this data is free from bias.
Bias affects the quality of data collected by a researcher and subsequently the quality of the decisions made by the researcher. Using templates, understanding the instruments, the use of decision trees and conducting research in an open information environment are some of the steps taken to improve the quality of research by eliminating bias.
