The rise and rise of robotic process automation

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Because robots don’t require breaks, don’t get tired, don’t get distracted and work around the clock, a robot can significantly increase the amount of processed data, which can be good or bad, depending on the quality of that data

Gartner says robotic process automation (RPA) software revenue grew 63.1 per cent in 2018 to $846 million, making it the fastest-growing segment of the global enterprise software market.

The analyst firm says it expects RPA software revenue to reach US$1.3 billion in 2019.

“The RPA market has grown since our last forecast, driven by digital business demands as organisations look for ‘straight-through’ processing,” says Fabrizio Biscotti, research vice president at Gartner. “Competition is intense, with nine of the top 10 vendors changing market share position in 2018.”

The top-five RPA vendors controlled 47 per cent of the market in 2018. The vendors ranked sixth and seventh achieved triple-digit revenue growth. “This makes the top-five ranking appear largely unsettled,” says Biscotti.

Table 1: RPA Software Market Share by Revenue, Worldwide (Millions of Dollars)

2017 Rank	2018 Rank	Company	2017 Revenue	2018 Revenue	2017-2018 Growth (%)	2018 Market Share (%)
5	1	UiPath	15.7	114.8	629.5	13.6
1	2	Automation Anywhere	74.0	108.4	46.5	12.8
3	3	Blue Prism	34.6	71.0	105.0	8.4
2	4	NICE	36.0	61.5	70.6	7.3
4	5	Pegasystems	28.9	41.0	41.9	4.8
8	6	Kofax	10.4	37.0	256.6	4.4
11	7	NTT-AT	4.9	28.5	480.9	3.4
6	8	EdgeVerve Systems	15.7	20.5	30.1	2.4
7	9	OpenConnect	15.2	16.0	5.3	1.9
9	10	HelpSystems	10.2	13.7	34.3	1.6
		Others	273.0	333.8	22.2	39.4
		Total	518.8	846.2	63.1	100.0

Due to rounding, numbers may not add up precisely to the totals shown (Source: Gartner, June 2019)

North America continues to dominate the RPA software market, with a 51 per cent share in 2018, but its share dropped by 2 percentage points year over year.

Western Europe held the number two position, with a 23 per cent share. Japan came third, with adoption growth of 124 per cent in 2018.

“This shows that RPA software is appealing to organisations across the world, due to its quicker deployment cycle times, compared with other options such as business process management platforms and business process outsourcing,” says Biscotti.

DX programmes boost RPA adoption

Although RPA software can be found in all industries, the biggest adopters are banks, insurance companies, telcos and utility companies. These organisations traditionally have many legacy systems and choose RPA solutions to ensure integration functionality.

“The ability to integrate legacy systems is the key driver for RPA projects. By using this technology, organisations can quickly accelerate their digital transformation initiatives, while unlocking the value associated with past technology investments,” says Biscotti.

Gartner expects the RPA software market to look very different three years from now. Large software companies, such as IBM, Microsoft and SAP, are partnering with or acquiring RPA software providers, which means they are increasing the awareness and traction of RPA software in their sizable customer bases.

At the same time, new vendors are seizing the opportunity to adapt traditional RPA capabilities for digital business demands, such as event stream processing and real-time analytics.

“This is an exciting time for RPA vendors,” says Biscotti. “However, the current top players will face increasing competition, as new entrants will continue to enter a market whose fast evolution is blurring the lines distinguishing RPA from other automation technologies, such as optical character recognition and artificial intelligence.”

Best practices

RPA emulates human activity — keyboard and mouse input — in addition to purely programmatic operations, explains Gartner.

This allows RPA to automate systems and operations that have always required humans and, when done well, automate with greater efficiency, availability and accuracy, writes Gartner analyst Gregory Murray in a report on best practices for RPA success.

“Because robots don’t require breaks, don’t get tired, don’t get distracted and work around the clock, a robot can significantly increase the amount of processed data, which can be good or bad, depending on the quality of that data,” he writes.

“Where data quality is good, there is potential for RPA to maintain that level of data quality.

“By eliminating transposition or mechanical errors, RPA helps ensure that data input by the robot doesn’t introduce errors and preserves upstream data cleansing. RPA script developers create automation scripts either through a recorder or through a simplified, low-code development interface. The developers will define triggers for these scripts that will invoke the automations through a variety of system or datacentre events.”

Murray notes that a governance framework for selecting and validating RPA use cases, often managed by a centre of excellence, is a critical part of any enterprise RPA rollout.

“Establish a governing body to provide the guidance necessary to ensure that RPA is used only when it is the right tool and that RPA applications comply with all corporate and regulatory requirements,” he further advises.