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Capitalizing on robotics: How to save with digital labor

How to save with digital labor

This article outlines which form of digital labor to choose based on business need and cost.


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Hand holding coin in white robot machine

What comes to mind when you think of intelligent process automation?

Many businesses understand that to stay competitive, finding a way to make use of digital labor isn’t optional. At the same time, however, the rise of the robots has happened so quickly that few organizations know where to begin, what the cost savings could be and how much of an investment it will take.

In this piece, KPMG professionals Mike Gough and David B. Kirk lay out a few of the foundational ways to think about digital labor, including the drivers that will lead to the best cost savings. No two automation opportunities are the same.

With that in mind, the authors look to find the commonalities that can help businesses answer their questions and take the next step into the automated future.

Capitalizing on robotics infographic

KPMG LLP, "Capitalizing on robotics", 2017 (p4)

To begin with, KPMG classifies digital labor into three classes. Each of these comes with its own set of savings drivers, and they should be explored in full to make decisions on a business’s need.

Basic robotic process automation

These encompass the 'tried and true' technologies that can be brought online quickly and easily. The authors define their use for tasks that: are repetitive, are easily organized and sequenced, require little in the way of decision-making, and use consistent data.

Enhanced process automation

These solutions are less structured and often more specialized than the basic technologies. They still offer out-of-the-box uses, but they also bring capabilities for: understanding natural language, using multiple forms of unstructured data, and even learning. They often require human input or decisions to guide them.

Cognitive automation

The most robust form of digital labor, these systems can include artificial intelligence, machine learning and data analysis to mimic a human’s ability to make decisions. These don’t work out-of-the-box, and instead require months to years of training, but can also replace labor in complex and integral situations.

Read the full story for more information on ways digital labor can drive cost savings and tips on how to implement them (PDF 857 KB).

Also visit our Intelligent Automation hub for more information about our services.

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