The new world of digital labour and its effects

The new world of digital labour and its effects

Different forms of digital labour are affecting businesses. The question is, how can you make use of these changes? According to the research firm Forrester, by 2019 at least 25% of all tasks within any occupation will be automated in some form.

Although digital labour isn't new, recent technological advances have conferred a much greater impact than before. Digital labour doesn't relate to physical robots; rather, it refers to software and can be classified into three different types.

The simplest and most adopted so far is robotic process automation (RPA), or software robots that can carry out applications and transactions on a screen. RPA is most effective for manual tasks and where the business operates in a rules-driven environment. In this form of digital workforce the robots are supplementary to the humans, and humans are still required for decisions and to deal with exceptions. RPA can deliver cost savings of up to 40%, with error rates as low as 0.1%.

Intelligent process automation (IPA) is the next level of automation. These bots are intelligent and able to do simple analyses and correlate data to reach a conclusion. But humans make the final decisions and handle exceptions. In this form of automation, the humans control the bots within the process and the bots help the humans make decisions. The aim is to reduce turnaround time for decision-driven processes that require some form of data analysis. Turnaround time can be reduced by up to 50%.

Artificial intelligence (AI) is the highest level of automation. It involves bots that are able to learn and improve themselves and make the best decisions within a set of given parameters. The bots drive processes and decisions, while humans oversee the decisions and set the overall parameters. Where this can be used is still to be determined.

Today we are seeing a major adoption of RPA across different industries. Many companies have started with RPA proof of concept or are at the stage of deploying robots. Most of them target manual processes that have previously been targeted for shared services or outsourcing. We expect this wave of RPA projects to subside in the next couple of years when simple situations will be automated.

IPA is at a different stage of maturity. The technology exists to support IPA services that are already deployed, but on a much lower scale than for RPA. We've seen banks fully automate credit card applications so that only exceptions need to be handled. Research by PwC shows that we expect this form of automation to pick up significantly over the next two to three years.

AI is an area that is largely at the proof-of-concept or laboratory stage, though there have been isolated cases of use in low-risk areas, such as chat bots to communicate with customers and handle service requests. This technology is expected to hit its full potential in the next three to five years. Applications are yet to be seen, but once fully developed they will affect knowledge-based jobs and roles that require strategic thinking and decision-making.

While the benefits of the digital workforce are clearly on hand and we see widespread adoption of RPA, many others are struggling to move out of the proof-of-concept stage to real deployment in operations. There are three main reasons for this.

First, companies focus on the wrong processes and areas. Many automation projects are designed as a quick fix for some highly manual processes. But these are the symptoms of a bigger underlying root cause, which is poor architecture and design. While some quick wins can help with short-term returns, companies should look at the broader context and use this as an opportunity to improve their overall operating model.

Second, the risks and rewards aren't clear and there's a lack of understanding between business and IT users in terms of where and how to use these technologies. General distrust of technology, and a lack of sponsorship for automation, as well as an uncoordinated approach across different lines of business, are major barriers to wider adoption.

Lastly, the human part of the change isn't being managed as well as it should be. Automation isn't there to replace humans, but to supplement and support certain types and areas of the business. The digital workforce will change roles and ways of working, but it won't make humans redundant. New roles will emerge while others will disappear. Communicating that message to the workforce and taking people along on the journey are key features of the success of an automation programme.

In order to achieve all of this, PwC recommends taking a holistic approach and creating an automation centre of excellence to address the three problems outlined above. It would coordinate and support the different areas while not taking absolute control. It needs to be coupled with a change management programme to address the people aspects.

The digital workforce will augment our work and let us focus on other important things, in a similar way to how other waves of productivity such as the industrial revolution and the information age did before.


This article was prepared by Dennis Trawnitschek, a director at PwC Consulting Thailand. We welcome your comments at leadingtheway@th.pwc.com

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