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Research Outline
Prepared for Tomoe I. | Delivered April 3, 2020
Robotic Process Automation: Case Studies
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Goals
To identify use cases of companies that have automated the PO data entry process (sent via fax) using RPA software or AI.
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Early Findings
Cisco
The issue: Manual processing of orders was found to be
costly and stressful
. Employees had to validate
S
K
U
s
, configurations, discounts, billing addresses, etc. Manually entering a single order took hours- or several days for large purchase orders of 100 pages or more.
Solution: In May 2019, Cisco rolled out a
fax order entry automation
process. The technology used was robotic process automation with deep learning.
Process:
-
To automate fax orders, Cisco was faced with
three challenges
: extracting data from unstructured document images, validating the accuracy of the data, and entering the data into the e-commerce system.
-
Combining machine learning
(Naïve Bayes and
s
p
a
C
y
) with a deep learning (Faster R-CNN) algorithm proved to be a success.
-
For graphics processing, the company used the Cisco UCS C480 ML server, which is optimized for machine learning and has eight NVIDIA V100 GPUs. In addition, an
internal solution
was built through their private cloud that could offer ‘GPU as a service,’ billing different departments according to their usage.
-
The accuracy of PO data is validated through
human agents
and the machine learning algorithms are readjusted for continuous improvement.
Results:
-
Productivity increased by
50%
(
65%
of
P
O
s
were automated, reducing annual support costs by
50%
)
-
More than
90%
accuracy.
-
Increased customer satisfaction as a result of
50%
faster order cycles and automatic acknowledgment of order receipt.
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