What is a good approach to reduce the time in processing the data?
Answers
Answer:
1.Reduce Data Redundancy:
Data entry of information is time- consuming. Hence, it becomes essential that only useful data is entered and processed. There has to be a periodic review of forms, applications and other data documents to check for the relevant data content. Forms that bring up obsolete data should be redesigned so as to involve only relevant data. Redundant data must be removed.
2.Carry Out Data Profiling:
Data profiling or data archeologyis the process of analysis of data for completeness, correctness, uniqueness, reasonability and consistency. It is the process of identification of defects in the data.
Sometimes, even in valid accepted data, there can be instances where data is wrongly entered. This incorrect information has to be restricted from flowing downstream as it would result in rework and extra costs owing to wrong predictions and analyses.
3.Perform Causal Analysis:
The process of detection of defects is just the first step towards the process of improvement. Data profiling should be followed by in-depth error analysis.
Two basic methodologies followed for error analysis are:
4.Error cluster analysis:
approach, which tries to narrow down the sources of errors. Here, the inaccurate data set is analyzed to arrive at the source error.
5.Data event analysis:
approach, where the events where data is created and changed are studied in detail to identify the root causes of problems.
6.Prevent Data Defects:
Defect prevention involves taking steps that reduces the entry of wrong data. It is a continuous process, critical to improvement in data entry.Steps like creating intelligent forms which can validate entered data, identify wrong data and ask operator for re-entry, should be taken.
7.Standardize the process:
Standardization of data entry process helps to improve the accuracy, consistence and compliance of data along with reducing the time taken for the process. Further, the process of standardization is prerequisite to the process of automation.
8.Enable Automation:
Manual data entry is a cost-intensive, time-consuming and monotonous process. It can also lead to the information being incomplete, inconsistent and non-compliant. To weed out such shortcomings, it is recommended to automate the process of data entry. Automation data entry process can be done with use of better technologies in form of OCR, IMR or use of complete data entry automation packages. Automation of data processing reduces errors and decreases costs and corporate risks in long term.
9.Monitor The Process & Use Feedbacks:
Continuous monitoring of the results provides help in multiple ways.Firstly, it validates that the improvement had a positive impact. Secondly, it prevents repetition of similar mistakes. Further, the process of improvement can never be complete without making allowance for a feedback system and building up a mechanism for using this feedback in a constructive manner. Hence, the organization should make an effort for profiling and checkingthe wrong data, mining comments by operators andlistening to field staff. Taking into accounts this feedback, re-engineering of forms & interfaces should be undertaken to further improve the process.
The process of data entry, though a non-core activity, is an indispensable part of any business activity.
However, it utilizes significant time and resources of the organization and hence, every step has to be taken for its optimization.Enlisting the services of high quality and efficient data entry outsourcing service providers would help to enhance the productivity of your organization, helping growth.
Explanation:
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Answer:
Explanation:
Good approach to reduce the time in processing of date are:
1) Electronic data processing: This approach helps in processing of data with the help of modern technologies. This method of data processing is most expensive but provides the fastest processing speed with the hight rate of accuracy.
2) Reduction of errors: Errors can increase the data processing time and time will be used in rectifying the errors. Less error will help in decreasing the data processing time.
3) Validation of data: Apart from speed and accuracy, it is important to notice the output quality is unique, complete, consistent and relevant.