With the above five categories for determining success, a company can now make an initial estimate of its ROI based on a certain percentage of automation. Expectations change frequently for organizations not yet experienced in data capture. As organizations become more familiar with the technology and educated in expectations for their area of automation, they increase their ability to estimate accuracy and performance. ROI ranges are highly dependent on document types and quality. Most general business documents of good quality are moderately complex to automate. Examples of complex document types are EOBs and student transcripts, which require a substantial additional fine- tuning effort. On the easier side are packing slips, and survey forms.
Data Capture ROI
Organizations should be mindful of the formula they use to calculate ROI, and repeat that formula during the evaluation of each product at each stage even as expectations change. Usually, data capture ROI is determined by how much money is saved in automation. There are, however, many other areas for organizations to gain ROI from data capture automation that should be considered. For example, automation often frees employee time to be spent on more critical tasks, thus making them more efficient. When an employee is more efficient, less staff is necessary, which decreases staffing costs. Another example is the reduced cost of paper storage. Because of automation, some organizations have a lower need to physically store paper, which reduces monthly storage fees. For some particular industries, ROI is based on a reduction of risk associated with compliance, or even a reduction of legal fees such as worker’s compensation claims due to manual entry.
Assisted Capture ROI
In assisted capture, the calculation of ROI is fairly basic and straight forward. It’s a process of counting the number of user operations that are saved with click-entry versus manual key entry, then calculating what volume of savings is required to replace the work of one operator. As an organization’s paper volume increases, so do the savings. The easiest way would be to calculate how many pages can be entered manually compared to click entered. This gives you a percentage in terms of time savings.
Basic Sample Calculation
Average Operator Hourly Wage: $8.00
Average Document Content: 33 fields of 12 characters
Average Operations Per Operator Per Hour: 11,600 (Data Entry Management Association 1998)
Average Number of working days per month: 22 Average Number of working hours per day: 8 hours
Average Cost of Semi-Automated License: $6,600 one-time, $1,100 annual support
Average Professional Services for Semi-Automated Solution: $10,000
Calculating for 100,000 pages a month data entry:
In an 8 hour day a part time employee will enter approximately
234 (11,600 key- strokes / (33 fields x 12 characters) x 8 hours) pages a day or
5,148 (234 pages * 22 days) pages a month.
It would take 20 (100,000 pages / 5,148 pages) full time employees (FTE) to handle the monthly data entry volume for a total cost of $28,160 (20 employees x 8 hours x 22 days x $8.00).
Total Manual Monthly Cost: $28,160
An operator performs an average of 34 clicks (one per field and one for template selection) and an average of 10 keystrokes (verification of data) a total of 44 operations to enter a page.
The operator can then click-entry 263 (11,600 key- strokes / 44 operations) pages an hour, 2,109 (263 pages x 8 hours) pages a day, or 46,398 (2,109 pages x 22 days) pages a month. It would take 3 (100,000 / 46,400) FTEs to click-entry the entire monthly volume for a total cost of $4,224 (3 x 8 x 22 x $8.00).
Total Semi-Automated Monthly Cost: $4,224
Monthly Savings of using Semi-Automated: $23,936
3 Year Total Cost of Semi-Automated Solution: $36,400 (($6,600 one-time + $1,100 annually x 2) x 3 licenses + $10,000 services)
Return On Investment: 1.5 months ($36,400 cost / $23,936 savings).