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What are the cost of errors and rejects in manual processing?  Costs can quickly mount, as illustrated by the following example.

With recognition, there are two important variables affecting success rates that are specific to a customer: errors and rejects. Errors are issues involved with false data recognition. In this instance, data is passed onto another system that is incorrect. A reject occurs when the confidence rate of a particular recognition process does not meet a specific threshold and requires manual intervention. Both incur a cost, but both costs can be quite different.

How so? Errors involve sending incorrect data to another system. Costs here could be trivial. Let’s say the error is associated with a name used for marketing correspondence. The result is that the person receives correspondence but with an inaccurate name. Or it could be large: the error could be associated with a SSN which is used for some financial deal.

For rejects, the cost is typically associated with the effort required to review the data and correct it manually. If the business is outsourcing this effort to a low-cost area, then it might be trivial. The key here is to balance the cost of manual interaction with the cost of bad data going into the system.

A Hypothetical Example – the Cost of Manual Processing

The context around the sample could be as follows (numbers are hypothetical and don’t represent a specific businesses’ actual costs): the company currently does manual processing of claim forms with a manual keying error rate of around 2% of all data entered. The cost of manual data entry is $5 per form and they process 100,000 forms per year. Thus the total manual cost is $500,000 annually. Then add the cost of errors. The cost of 2% errors contributes to additional costs of $200,000 (let’s say if everything was erroneous, it would cost the company $10m). Thus, the total cost of manual processing is $700,000 per year.