Every organization in the process of doing business generates data. This data has to be entered into the system so that it can be processed and stored for future use. This process of entering data into a computerized database or spreadsheet is defined as data entry. The data entry process can be performed by an individual by typing on a keyboard or by a machine entering data electronically.
As businesses grow, the requirement for data entry and processing increases exponentially. In order to ensure that the quality of data is good and reliable and that the data entry process is efficient, it is essential to follow certain basic ways that optimize the process.
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.
Data profiling or data archeology is 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 invalid 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.
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:
approach, which tries to narrow down the sources of errors. Here, the inaccurate data set is analyzed to arrive at the source error.
approach, where the events where data is created and changed are studied in detail to identify the root causes of problems.
Defect prevention involves taking steps that reduce 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 the operator for re-entry, should be taken.
Standardization of the data entry process helps to improve the accuracy, consistency, and compliance of data along with reducing the time taken for the process. Further, the process of standardization is a prerequisite to the process of 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 the use of better technologies in form of OCR, IMR, or the use of complete data entry automation packages. Automation of data processing reduces errors and decreases costs and corporate risks in long term.
Continuous monitoring of the results provides help in multiple ways. Firstly, it validates that the improvement had a positive impact. Secondly, it prevents the 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 checking the wrong data, mining comments by operators, and listening 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.