Robotic automation software
The term robotic automation or robotization refer to the automation of industrial and business processes using robots, of various guises. Robotic automation software refers to a class of software products used in that latter, clerical, context.
Examples of robotic automation include the use of industrial robots in manufacturing and the use of software robots in automating business processes in services industries. In the latter case, the use of the term robot is metaphorical, conveying the similarity of those software products – which are produced to provide a generic automation capability and then configured within the end user environment to execute manual and repetitive tasks – to their industrial robot counterparts. The metaphor is apt in the sense that the software "robot" is now mimicking or replacing a function classically associated with a person, for example in IVR voice recognition and chatbot technology as a means of data collection and distribution, in place of a person conducting a telephone conversation, for example.
In general terms, robotic automation corresponds to an emerging trend for technology to replace the functions performed by humans, particularly in the service sector, where the adoption of – and the concept of – robotics falls significantly behind the rate and incidence of adoption of automation within manufacturing.
Drivers of automation
Typically, the motive for deploying robots is to either improve quality, cut cost of production or to achieve both of these things. The typical characteristic benefits of robotic automation are reduced cost, increased speed, increased accuracy and consistency, improved quality and improved scalability of production. These characteristics carry differing importance across differing applications: a notable difference in impact can be observed between the manufacturing and service sectors where the benefits conferred by these characteristics can differ greatly in significance.
For example, as far as any increased speed of production is concerned, this produces an increase in productivity for the manufacturing sector whereas it typically implies a customer service benefit in the service sector. Scalability is another area where the impact on the service sector is dramatically different from manufacturing. The marginal cost of additional robots in manufacturing may be significant whereas additional software robots can be deployed with minimal (if not zero) marginal investment. Hence for products and services with varying or seasonal demand (be it financial applications pegged to the tax year or one-off spikes in orders for telecommunications services associated with the release of new cell phone handsets), robotic automation can be an effective means of scaling throughput, at a fixed and known level of service and quality, without the overhead of recruiting and training new staff to perform the same tasks.
Where robots replace human labor in high volume repetitive tasks at a lower price point, the reduced cost justifies the capital investment in its own right. Equally, where an increased rate of production is gained through automation the productivity gain justifies the investment, even at a higher unit price as compared to human labor.
Lastly, the role of robots in increasing security is significant. Unimate, the first industrial robot used in the manufacture of cars was introduced in order to improve health and safety within the manufacturing context. Similarly, software robots have a role to play in the service sector where, even if the cost of automation would not otherwise by economically justified (say for a low volume clerical process), it may be that a particular process is so sensitive (or perhaps that the cost of an error is so high) that it is preferred not to use error prone - and potentially untrustworthy - people to execute them. In this context, robots provide a trustworthy and accurate means of executing processes. For example, a sovereign department administering the personal pensions and administrative affairs of armed forces personnel could be expected to be extremely sensitive about the treatment or abuse of personal data relating to those personnel, who might become targets of terrorist aggressors, spies or anyone who is in any way inclined to pervert the interests of the sovereign entity. Alternatively, in a financial services context, the opportunity for fraud might be greatly increased by providing a single person with access to multiple banking systems. One option is to segment a process between departments, to the detriment of speed and quality associated with that process. Alternatively, a software robot can be trusted to execute a process as directed, without inappropriate data collection, fraudulent intervention or deviation from the prescribed process.
Technological and market drivers
The advent of the internet has enabled a new trend towards self service across many industries. The ostensible merit of the self-service model is that it benefits both the consumer and the provider: the provider enjoys an efficiency gain through the reduced dependence on administrative staff and the consumer benefits from greater flexibility of service (web-based, mobile application or telephone services for example).
A principal barrier to the adoption of self-service is often technological: it may not always be feasible or economically viable to retro-fit new interfaces onto existing systems. Moreover, organisations may wish to layer a variable and configurable set of process rules on top of the system interfaces which may vary according to market offerings and the type of customer. This only adds to the cost and complexity of the technological implementation. Robotic automation software provides a pragmatic means of deploying new services in this situation, where the robots simply mimick the behaviour of humans to perform the back end transcription or processing. The relative affordability of this approach arises from the fact that no IT new transformation or investment is required; instead the software robots simply leverage greater use out of existing IT assets.
Role in the service sector
An apparent contradiction arises from the use of robots to automate clerical processes. Once configured to perform a particular task a software robot essentially constitutes a software program in its own right, executing a sequences of steps according to a prescribed set of rules and procedures. This raises the question why a robot is needed in place of core systems of record that are procured or developed to meet the processing needs at the outset.
However, a software robot is often only deployed in place of a function that a human would otherwise do. Activities might include performing double data entry, copying and pasting data between computer systems, reconciling and cross referencing data between different systems and implementing high level decision making at key points along the business process. Such activities are frequently performed in many large organisations and these disjointed processes tend to arise out of an organic growth of changing system requirements and the fact that the changing needs of the business over time (arising from, for example, changes in consumer demand and regulatory mandates) cannot always be matched by commensurate investment in IT system changes. The high investment cost of time and money to achieve IT transformation often then means that such workarounds and manually intensive clerical activities then persist over long periods of time and are liable to creep back in (post transformation) as the business' needs continue to evolve.
The configurable element in most service-based organisations is the labor force. The intelligence and adaptability of people – whose chief skill and benefit is, arguably, this ability to readily adapt and change function – is the primary means of meeting changing service requirements.
Robotic automation adds a new nuance to this picture: increasingly, the use of robots is expected to automate the mundane and repetitive and functional aspects of clerical processes, replacing humans – in part – in this role of "configurability" within an organisation. However, without the intelligence, judgement and communication skills of a human, robots are unlikely to completely replace humans in this function. Instead, the likely role of humans in the workforce will be in high level roles where humans can add value: in complex and subjective decision making, in communication and orchestration of activities and in complex analysis in skilled and trained functions.
Outsourced business processes can be categorised into two general categories: front office processes with customer facing roles in some interpersonal capacity (either face to face, on the telephone or via written correspondence); and secondly back office processes where, correspondingly, there is no customer interaction required.
Back office clerical processes outsourced by large organisations - particularly those sent offshore - tend to be simple and transactional in nature, requiring little (if any) analysis or subjective judgement. This would seem to make an ideal starting point for organizations beginning to adopt robotic automation for the back office. Whether client organisations implement automations themselves, taking outsourced processes back "in house" from their Business Process Outsourcing (BPO) providers, thus representing a threat to the future of the BPO business, or whether the BPOs implement such automations on their clients' behalf may well depend on a number of factors. The commercial structure of the contract between the BPO provider and the client may well introduce market friction in certain circumstances: where the contract is based on cost-plus pricing, the provider is not incentivized to remove cost. However, as the client organisation comes to learn about emerging technologies and opportunities, pressure may well be brought to bear (if only at the point of contract renewal), so this factor is anticipated only to introduce temporary delay if we may assume the trend towards automation is otherwise inevitable.
Conversely however, a BPO provider may seek to effect some form of client lock-in by means of automation. By removing cost from a business operation, where the BPO provider is considered to be the owner of the intellectual property and physical implementation of a robotic automation solution (perhaps in terms of hardware, ownership of software licences, etc.), the provider can make it very difficult for the client to take a process back "in house" or elect a new BPO provider. This effect occurs as the associated cost savings made through automation would - temporarily at least - have to be reintroduced to the business in order to whilst the technical solution is reimplemented in the new operational context.
The geographically agnostic nature of software means that new business opportunities may arise for those organisations who have a political or regulatory impediment to offshoring or outsourcing. A robotised automation can be hosted in a data centre in any jurisdiction and this has two major consequences for BPO providers. Firstly, for example, a sovereign government may not be willing or legally able to outsource the processing of tax affairs and security administration. On this basis, if robots are compared to a human workforce, this creates a genuinely new opportunity for a "third sourcing" option, after the choices of onshore vs. offshore. Secondly, and conversely, BPO providers have previously relocated outsourced operations to different political and geographic territories in response to changing wage inflation and new labor arbitrage opportunities elsewhere. By contrast, a data centre solution would seem to offer a fixed and predictable cost base that, if sufficiently low in cost on a robot vs. human basis, would seem to eliminate any potential need or desire to continually relocate operational bases.
This anticipated reduction and stabilisation of cost bases (for those mundane and repetitive back office tasks, not requiring human input) may herald a new emphasis for BPO providers. With cost being broadly equal between providers, competition might be expected to carry new emphases over cost and labor arbitrage. We might expect competition to emphasise differences in service and quality, speed of execution, quality of customer service. Ancillary and complementary consultancy services are likely to be emphasised instead in the form of business process improvement, lean six sigma and business transformation.
Impact on labor
The automation of manual repetitive tasks using robots frees up human labor, a key factor of production, to provide additional capacity for other activities within the economy. The logical impact at the macroeconomic level is therefore that of an overall increase in productivity and economic activity.
At a microeconomic level however, the impact can be quite varied. For example, the impact of a particular automation may only be to free up a (possibly small) portion of each individual's time, with the broader benefit being made up in the aggregate time saving across a large pool of people. In this scenario, no particular individual's function has been entirely replaced by a robot; the effect is only an increase in capacity. A business might hope to translate that increased capacity into a productivity benefit in other areas or to direct it towards an anticipated growth in demand. On the other hand, where a person's function is entirely replaced (as for example in the complete automation of a mundane and repetitive, non-subjective, rules-based process previously sent offshore and now migrated to a robot in a data centre), the impact on that individual might be quite disruptive in the event that he or she is made redundant as a result. The specific circumstances and labor laws in the relevant jurisdiction are expected to be a strong factor influencing whether such individuals might be subject to redundancy or else redirected to more productive activities within the same enterprise.
There are geographic implications to the trend in robotic automation. In the example above where an offshored process is "repatriated" under the control of the client organization (or even displaced by a Business Process Outsourcer from an offshore location to a data centre, the impact will be a deficit in economic activity to the offshore location and an economic benefit to the originating economy. On this basis, developed economies – with skills and technological infrastructure to develop and support a robotic automation capability – can be expected to achieve a net benefit from the trend.
A possible benefit may be expected in morale and job satisfaction. With mundane tasks being taken away from people, where it can be argued they are not truly adding value, those individuals are left to concentrate on where their skills and contribution do genuinely add value. By way of example, the nurse who can dictate notes digitally and avoid time otherwise spent on administration is freed up to spend more time on what he or she was first motivated to train for: the caring of patients; the call centre worker who no longer has to double key the same information across multiple systems can concentrate better on serving customers and adding business value through, say, cross-selling additional products; the analyst of a financial and services organisation who is performing due diligence on client investments benefits from no longer having to mechanically prepare an Enhanced Due Diligence document according to a mundane and repetitive pro forma as this is prepared instead by a robot, leaving him/her to concentrate on the requisite high level analysis.
The advent of artificial intelligence has noticeably affected job search and career development. In the AI age, job seekers use special AI models that are trained to make a list of jobs that correlate with the user’s set of skills and expectations. The same AI models list suggestions for open electives, some MOOCs, internship opportunities as well as hobbies. Such software is mostly based on Natural Language Processing (NLP) and especially benefits graduate students. In 2017, Google for Jobs was launched. This job search engine brings together job postings from across the web and speed up the whole job hunting process. To get you documents ready there is an AI resume builder, which propose you a range of relevant skills and abilities to make your resume up-dated. The point is that AI and jobs are closely linked today. 
Scholars presume that AI will bring 2.2 million jobs to the work marketplace and will eliminate 1.8 million positions by 2020. The impact of automation on employment is significant. At the same time, there are warnings that users may get lost in too much data generated. According to the McKinsey Global Institute study concluded that 45% of 750 paid jobs could be automated. Other sources predict that as much as 800 million jobs will be lost due to automation. The recent report, which covered job market, socials policy, military industry, job hunt, and economic development summarizes that higher skilled jobs are much harder to automate thus developing world tends to prefer lower skilled jobs to be automated first. 
- Robotic Process Automation software, performing repetitive, back office data-driven processes
- Voice recognition and digital dictation software linked to join up business processes for straight through processing without manual intervention
- Specialised Remote Infrastructure Management software featuring automated investigation and resolution of problems, using robots for first line IT support
- The use of Chatbots by internet retailers and service providers to service customer requests for information
- The use of Chatbots by enterprise to service employee requests for information from internal databases
- Presentation layer automation software, increasingly used by Business Process Outsourcers to displace human labor
- IVR systems incorporating intelligent interaction with callers
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