General

Fundamentals of Workplace Automation

Robotic process automation (RPA) is the next big thing in managing endless

What are the Fundamentals of Workplace Automation?

Shifting human work to the machine is nothing new nor is it something so massively complex that it’s reserved only for the likes of multi-billion-dollar operations. One needs only to take notice of the interactions of their everyday life to realize how much artificial intelligence has become an integral part of our society. In fact, if one has ever used the self-checkout at your local grocery store or deposited a check at the ATM, you’ve leveraged automation technology.

Robotic process automation (RPA) is the next big thing in managing endless, dull workplace routine while cutting costs significantly. It encompasses software with machine-learning capabilities, not a sci-fi-style metal robot, to input or manipulates data & perform repetitive, rules-based tasks previously performed by employees.  Which can manage anything from data gathering to sophisticated analysis using artificial intelligence to understand meaning & context from unstructured data? It is the use of electronics & computer-controlled devices to undertake regulator of processes. The aim of automation is to boost efficiency & reliability. In most cases, however, automation replaces labour. In fact, economist’s today fear that new technology will eventually push up unemployment rates significantly. In most of the manufacturing units, robotic assembly lines are progressively carrying out functions that humans used to do. Automation^[1] encompasses many key elements, systems, & job functions in virtually all industries. It is especially prevalent in manufacturing, transportation, facility operations, & utilities. Additionally, national defence systems are becoming increasingly automated. Automation today exists in all functions within the industry including integration, installation, procurement, maintenance, & even marketing & sales. Replacing manual operations with electronics & computer-controlled devices. For example, office automation replaced manual typewriters, filing cabinets & paper appointment books with computer applications.

Main Content

The potential of AI & advanced robotics to achieve tasks once reserved for humans is no longer reserved for spectacular demonstrations.

• The Automation of Activities
  

Almost half of the activities individuals are paid to perform could be automated using currently available technologies & that’s not just routine, systematic tasks. One of the examples is narrative science’s AI (artificial intelligence) system, Quill, for instance, can analyse raw data & write reports in natural language. If the technologies that process & understand natural language were to reach the median level of human performance, an additional 13% of work activities in the US economy could be automated. The scope of automation potential which reflects the speed with which advances in artificial intelligence & its variants, such as machine learning, are challenging our assumptions about what is automatable & where the condition is not that only monotonous, codifiable events are applicants for automation & that activities requiring tacit knowledge or experience that is difficult to translate into task specifications are immune to automation. Mostly the automation technology can already match, or even exceed, the median level of human performance required. Some of the companies are equipped with automation technologies that plan, navigate, & coordinate among individual robots to fulfil warehouse orders roughly four times faster than the company’s previous system.

• The redefinition of jobs & business processes
  

Actually, very few occupations could be completely automated & on another side which could possibly realize a vital portion of the day to day activities & duties are automated. What this means is that although artificial intelligence is not yet capable of replacing humans entirely, automation will most certainly begin to – at least to some degree – change the vast majority of occupations. To accommodate these changes, a redefinition of roles & subsequent adaptation of businesses process will be necessary.

Thus, automation may eliminate some of a human worker’s task load, it will simultaneously free them up to focus their skills & intellect elsewhere. In other words, job descriptions^[2] & their duties will inevitably evolve. At the same time, however, new & innovative job opportunities as they relate to managing AI will begin to emerge & it is expected to vary the huge majority of occupations at least to a certain degree which will require significant job redefinition & a transformation of business processes. Mortgage-loan officers, for instance, will spend much less time inspecting & processing rote paperwork & more time reviewing exceptions, which will allow them to process more loans & spend more time advising clients. Likewise, in a world where the diagnosis of many health issues could be efficiently automated, an emergency room could combine triage & diagnosis & leave doctors to focus on the cutest or unusual cases while improving accuracy for the most common issues. As roles & processes get redefined, the economic benefits of automation will extend far beyond labour savings. Mainly in the highest-paid occupations, machines can enhance human capabilities to a high degree, & magnify the value of expertise by increasing an individual’s work volume & freeing the employee to focus on work of higher value. Lawyers are already using text-mining techniques to read through the thousands of documents collected during discovery, & to identify the most relevant ones for deeper review by legal staff. Likewise, sales organizations could use automation to produce leads & recognize more likely opportunities for cross-selling & up-selling, increasing the time front-line salespeople have for interacting with customers & improving the quality of offers.

• The impact on high-wage occupations
  

Most of the low-skill, low-wage activities on the front line are the ones most susceptible to automation & one is now able to scrutinize this view using the comprehensive database of occupations one has created. It encompasses not only occupations, work activities, capabilities, & their auto-matability, but also the wages paid for each occupation. An important percentage of the activities performed by even those in the highest-paid occupations (for example, financial planners, physicians, & senior executives) can be automated by adapting current technology. For instance, one of the estimations is that activities consuming more than 20 per cent of a CEO’s working time could be automated using current technologies. These include analysing reports & data to inform operational decisions, preparing staff assignments, & reviewing status reports. Conversely, there are many lower-wage occupations such as home health aides, landscapers, & maintenance workers, where only a very small percentage of activities could be automated with the technology available today

• The future of creativity
  

Capabilities such as creativeness & identifying emotions are main to the human experience & also difficult to automate. The amount of time that workers spend on activities requiring these capabilities, though, appears to be surprisingly low. While some of the findings might be lamented as reflecting the impoverished nature of our work lives, they also suggest the potential to generate a greater amount of meaningful work. This could happen as automation substitutes more routine or repetitive tasks, allowing employees to focus more on tasks that utilize creativity & emotion. Financial advisers, for example, might spend less time analyzing clients’ financial situations, & more time understanding their needs & explaining creative options. Interior designers could spend less time taking measurements, developing illustrations, & ordering materials, & more time developing innovative design concepts based on clients’ desires.

These interim findings, emphasizing the clarity brought by looking at automation through the lens of work activities as opposed to jobs, are in no way intended to diminish the pressing challenges & risks that must be understood & managed. Clearly, organizations & governments will need new ways of mitigating the human costs, including job losses & economic inequality, associated with the dislocation that takes place as companies separate activities that can be automated from the individuals who currently perform them. Other concerns centre on privacy, as automation increases the amount of data collected & dispersed. The quality & safety risks arising from automated processes & offerings also are largely undefined, while the legal & regulatory implications could be enormous.

Critical factors include the speed with which automation technologies are developed, adopted, & adapted, as well as the speed with which organization leader’s grapple with the tricky business of redefining processes & roles. These factors may play out differently across industries. Those where automation is mostly software-based can expect to capture value much faster & at a far lower cost. (The financial-services sector, where technology can readily manage straight-through transactions & trade processing, is a prime example.) On the other h&, businesses that are capital or hardware intensive, or constrained by heavy safety regulation, will likely see longer lags between initial investment & eventual benefits, & their pace of automation may be slower as a result.

Conclusion

For the new top-management imperatives, keeping an eye on the speed & direction of automation, for starters, & then determine where, when, & how much to invest in automation. Building such kind of determinations will require executives to build their understanding of the economics of automation, the trade-offs between augmenting versus replacing different types of activities with intelligent machines, & the implications for human skill development in their organizations. The grade to which executives embrace these priorities will influence not only the pace of change within their companies but also to what extent those organizations sharpen or lose their competitive edge. Whatever the precise scale of automation, its impact is clear. Management teams will need to adapt to increasingly automated organisations.

Ultimately, time will tell just how much of an impact advanced automation, machine learning & artificial intelligence technology will have on the future of work. One thing is for certain, though. Its adoption is inevitable. The best way to prepare your organization is to stay a step ahead by embracing the tools that are currently available to one.