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Software robots: The employees that never sleep

Dmitry Shushkin

May 31, 2018

Intelligent technologies broaden every sphere of business opportunities, including the office work. The never-tiring digital employees - software robots – are entering into marketing, sales, accounting and HR. One reason for this is that the cost of human labor is rising in both developed and developing countries. Meanwhile, the human workers go on vacation, sometimes get sick, and they make an average of 10 errors while performing 100 monotonous actions, and even though a small oversight can result in huge losses. In April, a Samsung employee accidentally transferred dividends worth $105 billion to colleagues. Pushing the wrong button led to a drop of 12% in the exchange value of Samsung. On the contrary, well-trained robots are not prone to mistakes; they need no lunch, tea or smoke break. Yet they can handle from 30% to 70% of a company’s routine work, depending on the industry.

In 2017, the market for Robotic Process Automation (RPA) reached $443 million, according to Horses for Sources . This is not a lot when compared to the multibillion-dollar investments in unmanned vehicles or blockchain. Nevertheless, this represents 36% in annual growth, and could exceed $1 billion in total by 2020. The capitalization of software robot developers, such as UiPath, increased tenfold over the past year, while the demand for Workfusion’s RPA solutions spiraled up 850% in the same period. Google has also reported a tenfold growth in search queries about RPA related topics in recent years.

Working around the clock, without a break

When thinking about robots, most people envision awkward machines on wheels, or iron dogs from Boston Dynamics. What many fail to realize, however, is that robots come in both hardware and software forms. Software robot resides on the server, but we can see when it launches a program, moves the mouse around the screen, or checks cells in a document. Software robots mimic human actions via enterprise RPA. They perform routine and repetitive tasks like logging into the system, reprinting data from one system to another, generating a report or adding meetings and other events to the calendar.

One of the main advantages of RPA is the relative ease of its implementation. It does not require a tight integration into systems. The solution can also be scaled up to different divisions of the company, since humans essentially repeat almost the same operations on their computers using different information inputs. Moreover, the payback period is, according to Ernst & Young, from 6-9 months.

A good example is Siemens medical unit - Siemens Healthcare – which recently implemented the RPA system, which collects genetic data of clients for diagnosis of diseases. The solution automatically sets parameters for analysis using more than 90 different settings. The robot extracts the necessary data in 15 mouse clicks, after which the results are entered into Excel to compile various reports. In 2017 Ernst & Young introduced 700 robots that search for information in the knowledge base on personnel issues, collect data from resumes, and even remind employees about meetings and hotel reservations. The company plans to save more than 2 million hours on routine actions within a year and a half.

Important considerations before implementing RPA

Despite companies’ interest in RPA, almost 30% of such projects end in failure. Most of the problems are in scaling the solution, managing and controlling the robots. Here are a few factors to consider for successful implementation of RPA projects.

1. Not every process in a company’s workflow is suitable for RPA implementation. Generally, software robots work well when there is a well-defined business process in place. The software operation is strictly rule-based, therefore RPA should not be used in processes where there are more exceptions than rules.
2. Using RPA exclusively to process unstructured information will not produce the desired results. Standalone software robots cannot extract data from contracts, applications or resumes. When combined with natural language processing (NLP) technologies however, over 70% improvement in performance can be achieved. Cognitive RPA solution are perfect for key processes like customer onboarding in banks, insurance, retail, healthcare and other spheres.
3. There is a need to monitor software robots. Like any IT solution, RPA requires regular updates and checks. Security patches, different versions of the programs with which robots interact, data entry formats, types of documents, even passwords change with time. It is more like a clockwork mechanism that works only if all the gears are in place.

Healthcare Artificial Intelligence (AI) Robotic Process Automation (RPA)

Dmitry Shushkin

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