Cliff Saran’s Enterprise blog

Aug 23 2019   1:01PM GMT

Gigging for robots

Cliff Saran Profile: Cliff Saran

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A few months ago Automation Anywhere began collaborating with freelance software developer recruitment platform, Toptal, on robotic process automation in the human workforce. The concept is called the “digital worker”.

There appears to be a number of forces coming together. The so-called gig-economy is showing that there are people happy to make themselves available for work on a zero hours style of work contract. And this trend is not limited to the likes of Uber and Deliveroo drivers. The nature of IT contracting is also changing . “People don’t want to work on a year long contract. They may only want to use their technical skills for work one day a month,” says Nick Woodward, CEO of ETZ Payments, a company that aims to simplify payments for freelance workers.

Bola Rotibi, research director, software development, at CCS Insight believes demand for IT services offered through the gig economy may increase as a result of tech skills shortages. “They work well when the work needed is very standardardised and well-scoped so that there is no ambiguity and you don’t have to open the company so that information flows out,” she said.

Robotise work, backfill with humans

Automation Anywhere provides a way to automate manual processes. But if this work cannot be accomplished through automation, it needs to be handed over to a real person. Today, RPA and hiring new talent are not directly connected. But imagine if the platform was smart enough to understand what IT work could be automated and where an IT job  needed handing over to real people. The algorithm could then find a suitable IT contractor that met a predetermined set of requirements, similar to how Uber’s platform identifies the closest driver who is free to pick up a customer.

Such a scenario does not put much value on the human workforce. Neither does the terms “human capital management”, headcount or man-hours.  However, if an RPA cannot perform a task, but can identify a real person free to complete the job, then that has to be a good thing?

The algorithm only really has to do the job of an applicant tracking system in reverse – to identify contractors with availability who have the right skillset. Perhaps add in weightings based on the sentiment of Checkatrade style reviews from previous employers and some smarts around recommendations. How hard can it be? The sad truth is that automated systems for identifying talent are often woefully inadequate.

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