As technologies become indispensable part of our work life, a new form of labor emerges – the digital labor – performed by digital workers. A digital worker is a piece of software capable of performing repetitive, rules-based work that is usually done by humans. To achieve that most commonly RPA is used (Robotic Process Automation) technology, leveraging cognitive tools like machine learning (ML), artificial intelligence (AI) and robotics. Like human workers, digital workers can log in to different systems, navigate between screens and perform rules-based actions, fill in forms, gather data, validate information and so on.
But how did it start?
The history of digitalization can be tracked back to 1703 when the modern binary system was invented by Gottfried Wilhelm Leibniz, but it only started to make sense with the introduction of the first digital computers in the 1940s, followed by a scientific-technical revolution during which personal computers became popular, lasting up to ~1970 and was followed by the digital/information technology revolution (1975-2010) (Larsson, 2019).
The huge technological development throughout the twentieth century has shaped the future of the labor market in the twenty-first century and has set the tone for its further development. With the advancement of technologies industries have begun to generate more and more data. This way data has become a critical factor for the success of the modern business, and the more work is done the more data is generated. As we are moving into the Information age now every worker with a digital device leaves its digital footprint, generating more and more data. Collectively, we’ll be generating 175 zettabytes of data by 2025 (https://mixpanel.com/blog/abc-data/).
How do companies make sense of data?
Data can be any character, number, image, word, or text. Data alone is useless – it is just a random bunch of facts, based on records and observations. But it can be immensely powerful if it is organized. There is a huge need inside corporate departments to gather data and turn it into meaningful information, or in other words to process data, organize it, structure it, and present it in each context to make it useful. The data produced has become central to day-to-day business operations. Companies have been moving their business operations processes online for years – eliminating paper, digitizing workflows, and reducing administrative costs.
Very often, once data is entered into a system it is then used in many ways by various departments and each one is adding more to it or replicating it in different systems. In doing so employees must follow a fixed set of rules for most of the tasks and handle just a few exceptions – cases that do not fit in with the predefined set of rules due to some reason. This way companies wanting to scale their operations engage full teams of experts just to process data. Not only this is intimidating but is also incredibly expensive.
Having the right tools to manage data has become crucial for businesses nowadays. With the advancements of technologies – it is not only anymore about where to store the data. Technologies that can transform data into useful information and perform operations with it are becoming increasingly popular as the amounts of data generated by businesses are continuously growing. While the different corporate systems can handle the data entered in them well integration between different systems is often missing. Because of that, employees often must manually transfer data between systems to enable the performance of transactions within various systems.
Is there a better way to work with digital data?
The constant advancements in digital technologies to enable productivity, reduce errors and minimize costs has made it possible for software to perform actions which are otherwise done by human workers. This does not include only individual tasks, but to gain the best benefit businesses are now looking into automating entire processes end-to-end. The core technology used to make it possible is Robotic Process Automation (RPA). With RPA digital workers (bots) are created to perform the actions a human employee would otherwise do when performing a task. RPA does not replace the software used; it replaces the person that works with that software.
Imagine you need to place an order with a vendor through the vendor website or e-portal. You need to open the portal, get the needed information from your company’s systems, fill the information in the vendor portal and then populate the order details back in your company’s systems. In the best case, this process takes you a few minutes. But digital workers can perform the same task in a matter of seconds. Further, once trained to execute the process correctly, a bot will not make mistakes and can work 24/7/365 without needing even a coffee break, while complying with all company regulations, creating audit trails, and following regulatory rules precisely.
According to CIO Insight RPA has proven to increase business process savings by 25-40% in most markets, and up to 55% in the IT labor market, as the productivity and accuracy of three software robots equal one full-time employee. RPA allows the process automation solutions to be created that benefit not only organizations, their employees, and their customers, but people and society at large. As the popularity of RPA continues to grow the fear of it grows, too. This should not be the case, however, because what robots can do is simply the job everyone hates.
Is RPA going to replace the people at work?
RPA isn’t about cutting off the people out of the loop. RPA is about those vital but mundane tasks and processes that are carried out by humans, freeing them to do more intellectually intensive and creative work. Those tasks that don’t add any value to the employee’s knowledge are the perfect candidates for automation, giving more time and energy to employees to create more value.
Surely, some jobs will change, but they will not disappear – there will be just displacement of labor. According to McKinsey Global Institute 25% of the occupations in America consist of more than 70% of activities that can be automated, but all those jobs include some degree of unpredictable /high precision activities that would always need human interaction. As the technology advancement in the 20th century has shown us – with the change of technology, while some jobs are changing, others that have not been needed until now appear. And while the machines are good at performing routine rules-based cognitive tasks, they cannot replace people in their innovation, creativity and human interaction which is needed in many jobs.
The skills needed will change, giving an opportunity to people to learn more. The new jobs will require more training and a higher understanding of technology, but not all jobs that need low-level of skills will be automated. The dynamics of the job market, including the supply, demand, and cost of human labor, which are also closely related to the demographics of a country and the skills level of the people are a determining factor for how much businesses would need to adopt automation. In areas where there is oversupply of labor companies may not have a good enough incentive to automate what humans can do.
In conclusion, while digital labor fully taking over people’s jobs seems too futuristic, employing digital workers might be beneficial for many businesses. Overall, the technology is advancing rapidly, and the pace of change is increasing. As digital labor reinvents how work gets done, people should be looking at improving the skills that distinguish them from robots, like creativity, emotional intelligence, and some technical skills. On the other side, for those businesses that want to stay competitive on the market – adopting a digital workforce is inevitable.
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