Intelligent Information Management is the merger of Content Analysis and Document Management. Combining these two separate disciplines for more streamlined access and representations of your data enhances the power and accuracy of Business Intelligence. Document Management Systems typically manage unstructured data such as text. Content Analysis focuses on structured data such as numbers in databases.  Merging these two systems into Intelligent Information Management provides a powerful decision-making tool kit.

The benefits of Intelligent Information Management cross all aspects of your business. As an example, customer relevant data can often be stored in content form. Transaction receipts contain content describing the reason an item is returned for credit. Capturing item return reasons along with quantities provides the information needed to optimize order sizes, suggest alternate products, or correct product flaws to decrease returns. Intelligent Information Management utilizes the unstructured content, the return reason, to provide additional data points to Business Intelligence to enable more informed decisions.

At the heart of all the data is the question of trust. To address this one must ask, “How accurate and hence reliable is the data being entered? What error rates can the business tolerate and still have the ability to see the health of the organization and make forecasts?”  

Underlining Data Integrity Issues… Question, “Can manual entry affect data integrity?”

Intelligent Information Management’s benefits can only be achieved with accurate data; you must trust the data used for analysis. To address this one must ask, “How accurate and hence reliable is the data being entered? What error rates can the business tolerate and still have the ability to see the health of the organization and make forecasts?”  

The accuracy rate of single keyed data is on average 96 percent. That works out to an error rate of 400 per 10,000 entries significantly affecting even small amounts of data.  Double keyed verification can help; the accuracy rates for double keyed data vary from 99.963 to 99.995 percent but this adds significant costs.

A Google search will reveal over 1.7 Million results related to the downside of manual entry. More compelling, a search for manual data entry benefits returns 8.3 Million articles about its drawbacks rather than its benefits.

Let’s look at some of the drawbacks (From the article):

1. High Error Rate: The reasons for a high error rate could vary – from inadequate training of data entry professionals to human error, illegible handwritten forms, misinterpretation of comments, and so on. Whatever the reason, the net impact could be one that is debilitating for the business, whether it has a negative effect on internal operations, customer satisfaction or external supplier relationships. The average benchmark for data entry error rate is generally acknowledged to be 4%. Thus, any higher error rate could be a matter of grave concern for the business.
2. Slow Turnaround Time: It is generally held that a good speed of data entry from paper documents varies between 10,000 and 15,000 keystrokes per hour. Capturing data from images is believed to be slightly faster. The number of keystrokes per hour can be higher for data entry tasks that are text heavy or require understanding of the text
3. Unclear Fields and Formatting: As per the publication ‘Data Quality Assessment’ by Arkady Maydanchik, a typical data entry challenge that operators run into is missing values. Assigning blank values, meaningless substitutes, default values or the first entry that appears in a box can create discrepancies in the desired output.
4. Quality Check: The application of the 1-10-100 rule to data entry translates into the following: it costs $1 to verify data accuracy at the point of entry; it costs $10 to clean up or correct data when it is in batch form; and it costs $100 or more for each record if no action is taken. From this principle, it is evident that quality check is an integral part of the manual data process.
5. Spike in Volume of Data Entry: An eCommerce business that announces a big sale may require large volume of data entry from paper catalogs to their website in time for the marketing initiative. Similarly, a manufacturing company that opens a new office in another location may have a sudden influx of purchase orders from new customers. Managing an unexpected spike in manual data entry work will put tremendous pressure on in-house manual data entry professionals, and may cause an increase in errors as well.
6. Loss of Focus from Other Core Tasks: If manual data entry is not one of the core tasks of the business, it can divert employees from completing other important activities. This itself can have a detrimental effect on the organization in the long run, as a targeted effort to achieve strategic objectives might get diluted.

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