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Post-Covid Reskilling Strategy: Developing Niche Talent for Hyper Intelligent Automation

Reskilling September 7, 2021

Post-Covid Reskilling Strategy: Developing Niche Talent for Hyper Intelligent Automation

The global robotic process automation market size was valued at USD 1.4 Bn in 2019 and is expected to reach USD 11 Bn by 2027 at a CAGR of 34%.

With the incremental growth of RPA across industries, demand for skilled RPA talent is expected to rise drastically in upcoming years. However, during the pandemic, Hyper intelligent automation(HIA), an advanced version of RPA, has gained a lot of attention from enterprises that are looking to efficiently and effectively automate their process workflows.

The global HIA market stood at USD 4.7 Bn in 2020 and is expected to be at USD 7.5 Bn by the end of 2021, showcasing a growth of 60% in a year.

The implementation of HIA yields several benefits for organizations, including:

  • Greater resilience
  • Seamless integration with other technologies
  • Cost-effectiveness in all areas of operations
  • Remote deployment
  • Higher accuracy in general and specialized processes
  • Scalability
  • Agile implementation
  • Accelerated transformation

It is evident that much work has to take place to deliver such critical features, and it requires skilled talent. Hence, the demand for RPA talent will experience a boost in the coming decade.

HIA/RPA Industry overview:

Enterprises across Technology, as well as traditional Industries, are aggressively adopting and deploying HIA/RPA solutions to automate their critical processes.

BFSI organizations account for a majority of the HIA market share due to the increased adoption of HIA solutions to automate repetitive processes such as customer service, reconciliation, transaction verification, and more.

A 360-degree overview of HIA/RPA market share would look like this:

  • Banking, Finance, and Insurance: 30-35%
  • IT & Software : 15-20%
  • Retail & CPG : 10-15%
  • Healthcare: 7-12%
  • Travel: 6-11%
  • Telecom : 5-10%
  • Public Sector: 5-10%

HIA is helping Industries unlock the full potential of RPA by expanding the use cases in new areas with potential end-to-end process automation. There are over 150 emerging use cases of HIA, from software bots to tax reconciliation and product inspection to document validation. With the diverse use cases and features that HIA comes with, it is natural that the demand for RPA talent will see a surge.

RPA Job Market: An Overview

Since HIA is already finding space in organizational operations and is increasingly being implemented, specific job roles have already become critical for enterprises to consider.

These in-demand job roles include:

  • RPA developer
  • RPA solutions architect
  • RPA consultant
  • RPA project manager
  • RPA product manager
  • RPA support engineer

Out of these six emerging job roles, RPA developer is the most in-demand talent for today.

However, due to a relatively small talent size and a fledgling RPA talent ecosystem, HR leaders are struggling to meet the demand surge for their organizations.

To overcome the hiring challenges and meet the increasing talent demand, HR leaders are concerned about the following parameters:

  • Understanding specific skills/qualifications for these emerging job roles
  • Location intelligence of relevant talent pool across hiring locations
  • Talent ecosystem, cost and peer analysis in target locations
  • Reskilling/upskilling or alternative talent development strategies to meet the unmet hiring demands.

RPA Developer: Job role overview

The job of an RPA developer involves designing, developing, and implementing software bots and work alongside humans to enhance business process efficiency.

The role requires understanding the process that needs to be automated, checking the feasibility of automating that particular process, and designing and developing the automated state of that process.

Job role overview

Bridging the RPA skills gap

The global talent size of an RPA developer is only 27,250, with Asia being the hub for the largest RPA talent pool. However, the demand for RPA talent far exceeds the available supply. With the high demand for such talent across Industries, Reskilling is imperative to compensate for the limited talent pool and meet the increasing RPA talent demand.

There has been a 40% increase in job postings for RPA engineers in 2020, representing an emerging market for this talent.

The significant reasons discovered for reskilling the RPA talent include:

  • Supply is significantly lower than demand
  • Increase in job postings in the last one year
  • RPA is the fastest-growing enterprise software in the world
  • Around 72% of RPA talent is outsourced and cannot be relied upon
  • RPA is relatively new and is not included in the curriculum.

HR leaders are effectively utilizing reskilling strategies to train adjacent IT job roles to RPA roles. The process of reskilling for RPA is spread across four steps and requires an understanding of the RPA talent ecosystem to get the job done.

Step 1: Identify disrupted job families

Step 2: Look for overlapping skills in disrupted talent that can be reskilled to RPA roles

Step 3: Analyse feasible transitions based on relevant reskilling parameters

Step 4: Reskill with suitable learning modules to bridge the skills gap

An effective Reskilling strategy can help companies estimate the Reskilling propensity in advance by analyzing the skills gap between desired job roles and disrupted IT roles. With programming and database skills being a part of RPA job roles, some of the disrupted IT professionals can be easily reskilled to desired roles due to overlapping skillsets.

Case Study: Reskilling a Systems engineer to transition into an RPA developer

The commercialization of HIA/RPA will cause an unprecedented disruption in the existing IT talent and massive demand for RPA skills. Reskilling current talent with emerging skills will become inevitable for enterprises to meet the sudden demand surge for RPA job roles.

For instance, to develop an RPA developer in-house, the transition has to take place from a systems engineer to an RPA developer.

This transition has to go through a reskilling process that includes identifying:

  • Skills needed for the new role
  • The skills gap between the new and previous role
  • Feasibility of transitions based on relevant reskilling parameters
  • Suitable learning module to facilitate reskilling and bridge the skills gap.

It is essential to identify each element in the list given above and prepare a reskilling path to facilitate this transition. Let us try preparing a reskilling path from a Systems engineer to a new-age RPA developer.

Reskilling a Systems engineer

In a duration of 5-6 months, a Systems engineer would be transformed into an RPA developer with the help of the reskilling path discussed above. With further commercialization and market penetration, HIA/RPA is expected to heavily disrupt the existing skills of the IT workforce across all experience levels very shortly.

Reskilling is the need of the hour, considering the global skills gap and shortage of RPA talent. Enterprises that choose to move with reskilling would be less likely to face a talent shortage in the coming future as they will be developing such talent in-house with custom reskilling strategies.

Draup is an AI-powered talent intelligence platform that delivers HR leaders with data-backed insights into the global talent pool, cost modeling, and reskilling pathways suitable to manage talent faster and drive company-wide reskilling initiatives or hire quality talent.

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