Men were found to be more accepting of insurance advice given by robots.
Be it car, pet, home or life insurance, one in four UK adults would trust an automated robotic service to provide insurance advice.
The CenturyLink EMEA survey of over 1,200 adults in the UK also revealed what type of advice consumers would feel comfortable in taking from a robot. Nearly one in five (19%) would trust robotic guidance on how to claim for something, for example a car accident or contents theft.
A further 18% would seek robotic advice as to which insurance provider would give them the best offer for their needs, but only 15% would trust robotic technology to manage and send relevant documents required to set up a policy, such as passports and proof of identification documents.
Car insurance came out top as the insurance policy that consumers most trusted to be led by robotic services (19%), beating pet insurance (12%), holiday insurance (13%) and phone insurance (9%). This could point towards the frequency that people renew insurance policies for certain products, or could expose consumers views on how often they might need to interact with, or claim for something, with a specific type of policy.
“It is interesting to see the growing trust that consumers have in robotic advice for insurance matters, particularly that almost a fifth (19%) would trust automated advice just as much as they would from a human. Businesses must take note of the views of the consumers and adapt their strategies to reflect this shift in the way buyers like to receive their services,” said Jay Hibbin, director of insurance and financial services CenturyLink EMEA.
Interestingly, the research findings also revealed a generational split in views towards robotic advice. Those between the ages of 16 and 34 placed most trust in automated services (33%), whilst only 21% of those between the ages of 45 and 55+ would be happy with this form of interaction. Men are also more accepting of this kind of advice, with almost a third (30%) placing trust in insurance robots, as opposed to only 23% of women.
“The insurance industry is going through a rapid period of change and businesses are having to think about how they streamline services in order to survive and thrive. Time-poor IT teams at insurance enterprises have been, perhaps unfairly, described as “anti-innovation” and “risk averse” but now is the time to shake off these stereotypes,” said Mr Hibbin.
“By working on, and investing, in digital transformation strategies, IT leaders that can meet the new demands, and expectations, of consumers. If insurers are to stay competitive and keep up with the challengers that are nipping at their heels, they must look to how they implement and maintain technologies such as these to provide services fit for the future”.
As part of techUK’s AI Week, Alastair Bathgate, Group CEO at Blue Prism has provided a blog on ‘Friend not Foe: Robotic workforces could boost – not break – our working world’
Pressure is mounting on us, wherever we work to outperform peers, fend off threats from new challengers and remain competitive. That’s modern life – but each of us is only human. We can’t do everything at once. Some things we just don’t want to do, maybe even ought not to do. In any event, every now and then something’s got to give.
In the past 20 years, Business Process Outsourcing cast itself as the saviour of productivity – sometimes even of corporate sanity. Companies large and small took a long hard look at themselves, at the places where they added value (and where they leaked it) and looked to outside talent to work harder, smarter, faster.
Today, that outside talent alone isn’t enough. The future of work is changing at a faster pace than any of us have ever known. Virtually every company on earth is now looking at ‘what’s next’ – and increasingly that’s software robots.
Robots attract a great deal of emotion. We imagine sci-fi figures from TV and film. We fear replacement, not emancipation, from machines much better at work than we are. But, just like the fears that accompanied BPO in its infancy, the truth and potential around software robotics is far more exciting than this imagery allows.
Robotic Process Automation (RPA) is the game-changer. We’ve all seen industrial robots make waves in manufacturing, deliver efficiency in supply chains and improve product quality. We are now seeing software robots do the same elsewhere.
Software robots put process where process belongs, inside smart systems. They free each of us up to apply our human brains to tasks far more valuable. Let’s face it: traditional IT systems can often creak under the simplest of pressures. There are gaps, flaws, missing links – and all too often human intervention isn’t the best way to mitigate for those failings.
Smart software robots are far better suited to the task. Rather than have employees stretch time and resource to marginally improve an already broken system, what if you could simply add extra robotic capacity to do all that for you? Robots that feed on process, scalability and compliance.
But that’s just the beginning. Imagine a robotic ecosystem where users can leverage best-of-breed solutions for AI, cognitive and cloud technology. Consider the benefits to an a la carte menu of services and capabilities that would let you free up the creativity of people to do more valuable tasks: seek out that new market, revitalize sales, spot new opportunity and double output with virtually zero cost.
Doesn’t this sound like good news for business, not bad? Couldn’t it be good news for productivity, for people and for process? We think so. Increasingly the biggest players in business think so too. Perhaps it’s time we put sci-fi to one side and gave robotics a fresh look…?
In the popular media, we talk a lot about robots stealing jobs. But when we stop speculating and actually look at the real world of work, the impact of advanced robotics is far more nuanced and complicated. Issues of jobs and income inequality fade away, for example — there aren’t remotely enough robots to affect more than a handful of us in the practical sense.
Yet robots usually spell massive changes in the way that skilled work gets done: The work required to fly an F-16 in a combat zone is radically different from the work required to fly a Reaper, a semi-autonomous unmanned aerial vehicle, in that same zone.
Because they change the work so radically, robot-linked upheavals like this create a challenge: How do you train the next generation of professionals who will be working with robots?
My research into the increasing use of robotics in surgery offers a partial answer. But it has also uncovered trends that — if they continue — could have a major impact on surgical training and, as a result, the quality of future surgeries.
How do you train the next generation of professionals who will be working with robots?
As I have previously explained, robotic surgical systems allow for one (liable) senior surgeon to take near-complete control of the surgical act. This means trainees are involved less — far less — in performing surgical work, which spells trouble for the profession’s competence and legitimacy. Who wants to be operated on by a surgeon who has watched a lot of surgery, but done very little?
If we are at the cusp of a robotic era, I think there are some crucial lessons to be learned here for the world of skilled work in general.
A few points set the stage for these lessons. Many fiercely debate whether robotsare the equivalent of the canary in the coal mine or a red herring. Partially this is because we don’t agree on how to count them — are robots only mechanical devices guided by AI and fed data by sensors, or are they also things like software and process automation? The second of those groups is far, far bigger and has had far, far greater impact on jobs and the economy than the other.
Even if we count conservatively, there is reason to think that robots are about to have their “PC” moment. Robot development and investment are accelerating rapidly, and every year robots get dramatically more capable and less expensive — the Internet means that what one robot learns, many can learn instantly, for example.
If we’re about to see explosive growth in robotics, it is important to keep in mind that, in principle and in practice, robots add real value when they enhance human capability rather than replace humans. But what counts as enhancement or replacement changes when you look up close.
Paradoxically, for example, it looks like the Da Vinci Surgical System is reducing surgical capacity in practice. Traditionally, surgical residents learned the craft by assisting senior surgeons. This is partly due to a happy accident — surgeons needed more skilled arms and thus relied on residents for assistance. Residents could observe and, under the watchful eye and hands of senior surgeons, perform procedures or even take over. Senior surgeons typically retract tissue so the resident can cut or suture, for example.
Traditional surgical practice basically demanded that residents play every minute of the game, literally shoulder to shoulder with their mentor. That’s how surgical training has been done since the early 20th century.
Robotics upsets this dynamic.
In many Da Vinci procedures, residents find themselves on the edges of the playing field. When once they might get four hours of practice during a traditional operation, now they get 10-15 minutes during a Da Vinci procedure — if they get a chance to participate at all. It’s not that the robotics technology itself prevents residents from learning; the technology just makes it iPhone-easy for liability-saddled attending surgeons to assume complete control. The expert does the work, which is good for patients in the short run, but the profession itself is in a new kind of trouble.
So what’s the broader lesson here for the future of skilled work? Surgeons are one of the first professional groups to deeply integrate sophisticated robotics systems into their methods, and the result is that surgery itself is radically reconfigured. But as with others that have already crossed this threshold — like pilots — the rush to integrate the latest robotic system may obscure the need for wholesale revisions to training methods so that humans can learn to perform even better in collaboration with robotic systems.
With robotics making great strides and more companies welcoming robots into the workforce, IT managers need to start prepping for the changes coming their way.
“Robotics will probably touch every business over the next decade,” said Dan Olds, an analyst with OrionX. “I think we’re nearing a tipping point where more businesses will be adding robots and robotics to their operations. They’ll be doing everything from manufacturing, to delivering food to restaurant tables to cleaning chores and farming — and lots of stuff in between.”
While robots have been working on assembly lines and in giant warehouses for some time, they’ve become much more than giant hulking arms moving car doors and stacking boxes. With advances in technologies like artificial intelligence, computer vision and mobility, robots are taking on a host of new roles.
Late last summer, for instance, Lowe’s, the home improvement chain, announced plans to use customer-service robots in 11 stores in the San Francisco Bay area.
The Aloft hotel in Cupertino, Calif. is already using a robot butler to autonomously deliver snacks and small items to guests in their rooms.
And two delivery companies — Postmates and DoorDash — will use fleets of autonomous robots to bring orders directly to customers’ front doors. That means the robots will navigate through cities and on crowded sidewalks in Washington, D.C. and Silicon Valley.
“Over the last decade, robotics has started in industry after industry and that will continue to advance during the next 10 years,” said Jeff Kagan, an independent industry analyst. “Robotics will play a growing role in a number of businesses, from making cars to taking orders at McDonalds. Not only will more companies move into robotics, but robotics will do more as it gets more intelligent with A.I., the internet of things and the cloud.”
The trend means that CIOs and IT managers need to be prepared for an influx of robotics because introducing this technology isn’t as simple as firing up a fleet of humanoid robots and letting them loose in an office building. It’s going to take planning, new skills and thought about how robots will affect employees and require new infrastructure.
This is not going to be IT as usual.
“It’s very much a different mindset than traditional IT,” said Mike Gennert, a professor and director of the Robotics Engineering Program at Worcester Polytechnic Institute, in Worcester, Mass. “IT managers worry about how they manage information, how it’s used, how it’s stored and secured. But none of that has the ability to directly affect the physical world. Robots affect the real world. That brings issues IT managers have not had to confront.”
For instance, It’s bad enough if a company computer is hacked and it becomes part of a zombie botnet. But what if someone hijacks a company robot and makes it do things, harmful things, in the real world?
Here are a few things CIOs and IT managers should start to think about and prepare for:
It’s time to bring in new skills
Some large companies will need to consider hiring a CRO — a Chief Robotics Officer — to go along with their CIO and CTO. A CRO would be responsible for the company’s robotics strategy and how it’s integrated into the processes already in place.
“I think the need is already starting to show up,” said Gennert. “For somebody who’s in the fast food industry, you’ll want to know how robotics can be used in your plants [for] packaging foods and moving foods, and on-site in point-of-sales and logistically and cleaning up afterwards.”
However, hiring a CRO isn’t the only position IT managers will need to fill. They’ll also need to bring in IT workers with a background in robotics — people who understand computer vision, sensors, programming models and security models, and who can do more than basic repairs and maintain robotic code.
Companies will also need someone experienced in A.I., since it will be the smarts in autonomous machines.
“Applications of machine learning in robotics is on the rise,” said Taskin Padir, an associate professor of Electrical and Computer Engineering at Northeastern University, in Boston. “Each practical robot system will rely on some level of A.I. to become more adaptable to situations that cannot be foreseen by the robot’s programmers.”
And time to upgrade your own skills
While IT managers are looking to hire new employees, they should consider bolstering their own skill set so they understand enough about robotics to get them up and running.
“IT managers will need to become intimately familiar with their new robot charges,” said Olds. “I think the robot vendors will provide a lot of this training, which will make it easier for IT personnel to quickly come up to speed.”
However, Gennert thinks IT managers will need a deeper knowledge than they can get from a few tutorials.
“I think IT managers need enough of an understanding to get what the changes will be and what the new needs will be,” he said. “They’ll surely want to have more expertise on some bigger skills, like manipulation, perception and vision, navigation and locomotion. You’ll need more expertise than you’d get from a few webinars or short courses.”
One robot will not replace one human
While there are a variety of estimates and a lot of fears floating around about how many jobs robots might take in the next five to 10 years, it’s hard to calculate how bringing robots into the workplace will affect employee numbers.
“Don’t think of robots as a one-to-one replacement for employees,” said Olds. “Trying to ‘roboticize’ all the tasks an employee does is extremely difficult. I don’t think robots will be taking over everyone’s job.”
While some workers will be displaced, the majority will carry on as before. Some employees may have more mundane, physically demanding or dangerous tasks taken over by robotic counterparts.
Artur Dubrawski, director of the Auton Lab and senior faculty in the Robotics Institute at Carnegie Mellon University, used to be the CTO at Aethon, a Pittsburgh-based robotics company. Aethon makes the Tug robot, which is often used to make deliveries in hospitals, pulling carts carrying everything from linens to medicines and food.
Through the deployments he worked on while at Aethon, he did not see robots replacing human workers, but helping them.
“There’s concern about robotics eliminating jobs, but in my practice that wasn’t the case,” Dubrawski said. “In the hospitals I watched through our deployments, nobody who worked in delivery lost their jobs. The efficiency increased. The quality of those employees’ lives picked up.”
At one hospital that was using a Tug robot, an employee told Dubrawski that his knees had always hurt him when he was pushing the cart to make deliveries. With the robot, however, he began focusing on making sure the carts had the right supplies and then pushing a button on a touch-screen to have the robot take it to make the delivery.
The worker’s knees didn’t hurt anymore.
Think about human/robot interactions
While working with a robot helped that hospital employee, other people may be anxious about working with a robot — particularly an autonomous one. The image that often comes to mind: Out-of-control, malevolent robots like the ones on Battlestar Galactica or The Terminator.
Add to that the fear of a robot accidentally hurting someone or taking their job, and employee concerns about their new, non-human co-workers could quickly arise.
It’s going to be up to the company, and likely the IT department, to work with employees, train them and put them at ease with robots.
“Having people who are willing to work with the robots is important,” said Gennert. “The fact that so many young employees today are already digital natives and feel very comfortable with computers means those folks will be pretty eager adopters of technology. And if people see how it helps them in their jobs, they’ll be more happy to have the robots come along.”
Olds noted that part of the job for IT — and anyone introducing robots into the enterprise — will be to make it clear to employees what’s happening. Are the robots replacing workers? Are the robots aimed at making some jobs easier?
“It’s important that employees get comfortable with the new tools and management needs to foster that sort of cooperation,” said Olds. “There will certainly be some people displaced by robots, which will cause them to resent them. But this won’t be the majority of workers. The majority of workers will carry on as before, but will probably find their jobs become more interesting and less wearing on them with the addition of their robot helpmates.”
IT managers will need to assess their infrastructure to figure out what they need to not only run robots but to have them safely and efficiently connect with other aspects of the corporate network, take orders from people in different departments, have them download information, track them throughout the property and even help robots deal with things like automatic doors and elevators.
“We are still in the early stage of utilizing robotics and A.I. in enterprise IT,” said Andy Chang, a spokesman for KUKA, a German-based robot manufacturer. “It is extremely important to make sure that you have a good infrastructure foundation to scale for the next 10 years.”
According to Chang, companies tend to utilize proprietary communication protocols, which can make extracting machine information difficult. “Existing networks can scale in the short term, but be ready to invest in new technologies such as 5G or Li-Fi as they become commercially available,” he added. “It will be critically important.”
Dubrawski added that it’s also a matter of thinking about how robots will need to communicate with the physical world, as well as with other company computers.
“As an IT manager, you need to have the robot access the networking system in your [company]…and communicate with each other and be able to convey their whereabouts to whoever sends them on a delivery trip, as well as to those who are waiting for them. We want to know where they are and if they get into trouble, and how to deal with them remotely if they get stuck. You need to be able to resolve navigational challenges, or if it might be cornered by a bunch of kids.”
As the hype continues around Robotic Process Automation (RPA) and Artificial Intelligence (AI), organizations are looking to invest additional efforts to better understand potential benefits and risks associated with these.
The fact of the matter: RPA and AI are already a reality and many service providers are taking an active role in the lookout for opportunities to maximize their service delivery models, profits and increased client satisfaction.
Below are some ideas and considerations for organizations prior to determine a course of action:
Understand the benefits beyond the hype: Organizations should have a realistic perspective on the potential benefits RPA/AI can bring to their environment. Obviously the excitement to bring those to life and all the value add innovation that can be achieved are phenomenal. Prior to executing, just make sure investments are made towards a sound business case – in which a realistic perspective of benefits and risks is presented, not the hype effect.
Determine demarcation points in order to maximize benefits: If service providers are already deploying RPA and AI to some of the services offered to an organization, there is a good leverage case to be used. These should translate in both financial/non-financial benefits to the services provided. In order to achieve this, it is important to determine what the opportunities are and activities that can be automated through the service provider’s capabilities. By doing so, organizations can potentially minimize capital investments, and at the same time allow RPA and AI related risks to be managed by such service providers.
Review your service provider’s agreements prior to adopting RPA and AI: Like other disruptors such as Cyber and Cloud, it is important for organizations to have appropriate commercial terms in place prior to entertain RPA/AI services so that the organization’s interests and risks are aligned with the organization’s procurement, outsourcing, privacy and supplier risk policies. The hype effect shall not create unnecessary exposure or challenges for the organizations that otherwise could have been prevented.
Determine overlap between initiatives across the organization: It is common for different areas within an organization to work independently on their respective challenges and opportunities. In order to determine the organizations best course of action, a holistic approach aligned with the organization’s strategy should exist. This will enable the organization to identify overlaps and also promote collaboration within the organization. Another important point goes back to basic strategic sourcing principles around effective governance and economies of scale – as financial benefits and costs should be clearly stated and understood.
The importance of Governance and Risk Management should not be understated: I know I have written this topic before but I felt the need to reemphasize the importance to having “all ducks in place”. This is particularly important for organizations in highly regulated sectors (e.g., Financial Services, Insurance and Healthcare), for which this should be considered a top priority. Remember that organizations should not compromise their ability to comply with their respective regulatory requirements, as this can have a significant impact to the organization’s reputation and bottom line.
Enjoy the excitement and discovery process but do not underestimate change management: There are a lot of “pluses” bringing disruptive technologies to an organization. Take the time to enjoy and generate the required momentum – so that change management activities are positively perceived across the different organization levels and generations. Usually organizations that pursue these through business transformation exercises tend to dig deeper on the potential additional values the organization can achieve beyond the hype. For example, the need to change processes that, although efficient, will require significant changes to support the organization’s desired future state RPA and AI. That also help the organization’s internal staff to gain valuable knowledge and experience through hands on experiences as the business transformation is being executed. In other words, the excitement and hype may help foster employee’s engagement.
Understand where the market is going beyond the hype: There are talks of RPA/AI organizations going public or being a target to large service providers such as IBM and CapGemini. Before entertaining a direct relationship with a specific RPA/AI service provider, it is very important to understand the potential issues of a fourth party and the implications to the organization service delivery model. For example, the Bank of New York Mellon faced significant challenges due to an acquisition of one of its main service providers by another institution back in August 2015 – The Wall St. Journal has an interesting article on it.
The conclusion: Go ahead and have fun! At the same time, do not lose sight of potential exposures for the organization. In today’s world, organizations cannot afford reputational risks / impacts to their brand and clients. Remember that the higher the benefits, the higher the risks. At the same time, organizations cannot afford to stay put, as our worlds breathes change.
A final and important update: the Wall Street Technology Conference is taking place in New York City on May 24. Further details can be found here. I look forward to seeing you there!!!
About This Year’s Wall St Technology Conference: Managing Risk & Reward in a Digital World
2016 will be the year that companies go beyond the hype, get to reality and actually invest in digital innovations that produce results and deliver ROI. It is the year that providers will go from selling buzz-ware to offering real industry-driven solutions.
Digital value chains will become a reality and organizations will reap the true power of data and insights. But along with new opportunities, there are increased risk of cyber-security hacks, data privacy breaches and regulatory issues. Financial services and insurance companies have to balance their strategic priorities with the risks, regulatory and cost objectives. The advent of Digital banking and mobile payment systems coupled with consumerization of IT, automation and real-time analytics is changing how CXOs procure and implement new solutions.
Robotic Process Automation (RPA) is an increasingly hot topic in the digital enterprise. Implementing software robots to perform routine business processes and eliminate inefficiencies is an attractive proposition for IT and business leaders. And providers of traditional IT and business process outsourcing facing potential loss of business to bots are themselves investing in these automation capabilities as well.
While the basic benefits of RPA are relatively straightforward, however, these emerging business process automation tools could also serve as en entry point for incorporating cognitive computing capabilities into the enterprise, says David Schatzky managing director with Deloitte.
By injecting RPA with cognitive computing power, companies can supercharge their automation efforts, says Schatzky, who analyzes the implications of emerging technology and other business trends. By combining RPA with cognitive technologies such as machine learning, speech recognition, and natural language processing, companies can automate higher-order tasks that in the past required the perceptual and judgment capabilities of humans.
Some leading RPA vendors are already combining forces with cognitive computing vendors. Blue Prism, for example, is working with IBM’s Watson team to bring cognitive capabilities to clients. And a recent Forrester report on RPA best practices advised companies to design their software robot systems to integrate with cognitive platforms.
CIO.com talked to Schatzky about RPA adoption rates, the budding relationship between software robots and cognitive systems, the likelihood that the combination of the two will replace traditional outsourcing, and the three steps companies should take before implementing RPA on a wider scale.
CIO.com: Where are most companies in terms of their adoption of RPA?
David Schatzky, managing director, Deloitte: RPA is a new topic to some and a well understood one to others. More and more IT leaders have heard of the term and at least know what it is in principle. Adoption thus far is pretty modest. RPA has been more widely adopted in Europe and Asia than it has been in the U.S. And even those companies in the U.S. that have adopted RPA are typically just piloting it.
CIO.com: Why did RPA catch on more rapidly in Asia and Europe?
Schatzky:That’s due to the level of business process outsourcing that has taken place there. Asia is the hope of business process outsourcing and European companies have been eager to cut the costs of onshore operation using RPA. Also, one of the leading RPA companies, Blue Prism, is based in Europe.
CIO.com: Why are you focusing on the potential combination of RPA and cognitive computing systems in particular?
Schatzky: I think it will help to broaden the application of RPA and increase the value it delivers to the companies that adopt it. Cognitive technology is progressing rapidly, but many companies don’t have a clear path to taking advantage of these technologies. They’re not sure how and where to put them to use.
RPA is a platform that can provide clear use cases for applying cognitive capabilities. Companies can install it to automate processes and it provides a framework or platform to integrate with cognitive systems to take automation to the next level. It’s almost the ‘killer app’ for cognitive computing.
RPA is very useful technology, but it’s not terribly intelligent technology. It only performs tasks with clear-cut rules. You can’t substitute RPA for human judgment. It can’t perform rudimentary tasks that require perceptual skills, like locating a price or purchase order number in a document. It can identify a happy customer versus an unhappy customer. Cognitive takes the sphere of automation that RPA can handle and broadens it.
CIO.com: Where will be the most beneficial use cases for using RPA in conjunction with cognitive technology?
Schatzky: A lot of them are in the front office: classifying customer issues and routing them to the right person, deciding what issues need to be escalated, extracting information from written communication.
CIO.com: Who tends to lead these RPA efforts—an IT leader or a business process owner?
Schatzky: It’s mixed. Sometimes it’s led by the process owner in the business. They learn about RPA and identify an opportunity to deploy it and improve efficiency. In other cases, IT has been leading the effort. It’s indicative of the broader trend of tech-centric decision being made increasingly in the business and not just IT.
One of the main tenets of advancing technology is to free up the time and effort workers are often required to put into relatively mundane tasks. Automating processes that once took hours for a person to complete has been a boon to a business’ bottom line while allowing IT workers to focus on tasks more central to advancing a company’s strategic initiatives. When it comes to Robotic Process Automation (RPA), Rod Dunlap, a director at Alsbridge, a global sourcing advisory and consulting firm, understands how RPA tools can positively impact workflow in industries such as health care and insurance. In this interview with CIO Insight, Dunlap expands on the RPA ecosystem, when it makes sense to employ RPA tools—and when it doesn’t.
For those unfamiliar, please describe Robotic Process Automation and explain a basic example of it in use.
RPA tools are software “robots” that use business rules logic to execute specifically defined and repeatable functions and work processes in the same way that person would. These include applying various criteria to determine whether, for example, a healthcare claim should be accepted or rejected, whether an invoice should be paid or whether a loan application should be approved.
What makes RPA attractive to businesses?
For one thing RPA tools are low in cost – a robot that takes on the mundane work of a human healthcare claims administrator, for example, costs between $5K and $15K a year to implement and administer. Another advantage is ease of implementation. Unlike traditional automation tools, RPA systems don’t require extensive coding or programming. In fact, it’s more accurate to say that the tools are “taught” rather than “programmed.” Relatedly, the tools can be quickly and easily adapted to new conditions and requirements. This is critical in, for example, the healthcare space, where insurance regulations are constantly changing. And while the tools require some level of IT support, they don’t have a significant impact on IT infrastructure or resources or require changes to any of the client’s existing applications.
What are the drawbacks of RPA?
RPA tools are limited in terms of their learning capabilities. They can do only what they have been taught to do, and can’t reason or draw conclusions based on what they encounter. RPA tools typically cannot read paper documents, free form text or make phone calls. The data for the Robots must be structured.
In what industries does RPA make the most sense?
They make sense in any situation that has a high volume of repeatable or predictable outcomes, on other words, where the same task is repeated over and over. We’ve seen a lot of adoption in the Insurance, Financial, Healthcare, Media, Services and Distribution industries.
Where does it make the least sense?
They don’t make sense in situations that have a high volume of one-off or unusual situations. To take the healthcare claims processing example, RPA is ideal for processing up to 90 percent of claims that an insurer receives. The remaining 10 percent of claims are for unusual situations. In these cases, while you could teach the robots the rules to process these claims, it’s more cost-effective to have a human administrator do the review.
If you automate a process once done by humans, and have it perfected by a robot, is it possible for the robot to determine a better way to accomplish the task?
Not with RPA. As mentioned, these tools will execute tasks only in the way in which they were taught. They can’t observe and suggest a different way to do things based on their experience, but what you are suggesting is indeed where the industry is heading.
What sort of data can be learned from RPA?
RPA tools can’t really provide insight from data on their own. They can log detailed data about every transaction they process. This can then be fed into a number of tools that will provide operation statistics. Also, they can work in tandem with more sophisticated cognitive tools that use pattern recognition capabilities to process unstructured data. For example, insurance companies have huge volumes of data sitting on legacy systems in a wide range of formats. Insurers are looking at ways to apply the cognitive tools to process and categorize this data and then use RPA tools to feed the data into new systems. Retailers are looking to apply the tools in similar ways to gain insight from customer data.
How much human oversight is needed to ensure mistakes are avoided?
The robots won’t make “mistakes” per se, but oversight is necessary to make sure that the robots are updated to reflect changes in business conditions and rules. An operator, similar to a human supervisor, can start and stop robots, change the tasks they perform and increase throughput all without worrying about who gets the window office.
The use of Robotic Process Automation, using concepts such as software bots, is emerging, but its use can’t succeed in isolation. The CIO needs to get involved to implement an enterprise strategy.
In recent years, Robotic Process Automation (RPA) has emerged as an effective enabling technology to gain efficiencies by automating repetitive, rule-based, manual tasks and mitigating human error risks.
For example, AT&T has established and grown a footprint of 200 software bots across its customer service organization, a capability that emerged out of an innovation center. Now, launched as a simple-to-use, cloud based enterprise technology, these software bots can be used by any AT&T employee to automate manual work.
The growth projections for RPA have created a fair amount of excitement. Spend on RPA tools and services is expected to grow at 60% annually over the next five years according to a new market report published by Transparency Market Research. However, the RPA growth story has its challenges. While we continue to see initial interest and pilot initiatives amongst buyers to test automation technologies, some struggle to grow initial success into an enterprise level capability.
Even for buyers that have successfully executed automation initiatives, growth may be difficult to sustain with sporadic, stand-alone deployments across multiple business functions.
Proactive IT involvement is essential to RPA’s emergence as a strategic capability. Many business teams have eagerly adopted RPA due to its non-intrusive automation approach and minimal impact to current IT systems. However this move often results in marginalizing the IT team’s involvement in such initiatives. Further, CIOs across industries have been largely dismissive of RPA as a tactical short-term fix, ultimately to be usurped by traditional IT transformation or Business Process Management Suite (BPMS) projects.
There is a clear need for change, as IT has a pivotal role to play in growth of RPA as a strategic enterprise competency. CIOs must define the automation strategy for their organizations by developing a better understanding of the business requirements and driving RPA as an enterprise level capability—not dissimilar from the way cloud technologies have evolved in the last few years. Here are three steps for CIOs to consider:
1. Partner with business to be a trusted solution advisor. Business users can clearly define their automation needs, but RPA may not be the right answer in all situations. Some requirements can be better addressed with IT transformation or BPMS, and only IT can help make these crucial decisions. Also, regardless of the “light automation” offered by RPA solutions, a host of other IT considerations need to be factored in. Impact to existing security protocols and any possible risks to business and data due to automated processing need to be assessed carefully. Use of RPA software can increase transaction load on existing applications (robots work relentlessly, often drastically increasing productivity and system workload), posing the risk of unplanned downtime and wasteful use of support resources to recover crashed applications. As RPA solutions scale up from tens to hundreds of robots across the organization, adequate infrastructure and network capabilities need to be provisioned with well-defined contingency plans. Such issues can be addressed effectively only if the CIO’s organization gets involved upfront, develops a clear understanding of the business requirements, and proposes the right solution and implementation approach.
2. Select an enterprise-level platform to build RPA capability. As multiple individual functional owners experiment with automation, technology choices are seldom made cross-functionally. This could result in multiple RPA platform deployments across the organization, making it difficult to manage and scale automation and deliver a real enterprise capability to the overall business.
Organizations need to make the platform choice at an enterprise level, and no function is better positioned than IT to drive that decision. IT can conduct a thorough evaluation of technical capabilities and architectural considerations, including performance and reliability of the software, change control, access management, maintenance requirements and integration capabilities. For example, the platform should be able to easily setup a library of services that can be used to integrate with the existing application portfolio. By gaining a deeper understanding of business requirements, IT can make an informed choice of a platform that’s easy to manage and control. There are financial benefits from an enterprise level decision too, better pricing and contractual terms as compared to function-level deployments.
3. Establish an RPA Center Of Excellence (COE). The COE approach is fast emerging as the recommended operating model to grow an RPA footprint in medium and large enterprises. In one example, a financial services organization successfully launched a pilot project in 2008 to automate their claims receipt and adjudication processes, long before RPA became an industry buzzword. By launching an automation COE thereafter, this organization has successfully expanded RPA capabilities to several hundred bots operating across its domestic and international delivery centers.
Investment in a COE can help organizations to better manage requirements and deliver efficient automation solutions by:
Leveraging best practices and implementation experience to deploy RPA where it is the most effective choice for automation
Establishing a sustainable governance model to identify and qualify RPA opportunities, and to deploy and stabilize RPA solutions
Instituting an “asset management” approach to manage RPA deployments — For example, if RPA solutions become redundant to a particular function due to an IT project, the COE can re-use the technology for future initiatives elsewhere
Tracking, monitoring and reporting process improvements and financial benefits across the enterprise.
Such a COE should be staffed with both technical and functional resources, including RPA solution developers, project managers, process SMEs and business analysts, along with cross functional representation from human resources and procurement. Careful consideration should be given to whether the COE should be aligned to the CIO, even though conventional thinking suggests automation efforts have better likelihood of success while reporting to the business.
Ultimately, RPA’s light automation approach is here to stay, but its emergence as a strategic capability is contingent to the CIO’s office coming on board. Functional owners can take the initial baby steps, but IT can help take it to the next level with enterprise-grade results.
What is the key to making Robotic Process Automation a success? HCL Technologies’ Kalyan Kumar looks at how business can benefit from leveraging the power of AI and automation.
It’s an age-old problem for the C-suite to solve: how do you do better and do more with less? Having invested in technological advances such as cloud and digitalisation over the last few years, many businesses are now at the part of the roadmap where they have budgeted for spend to level-out, and the forecasted benefits to roll in. However, investment is still needed in most cases, so how can enterprises continue to build when the resources available to them have ceased to grow? The answer is getting technology to lend even more of a helping hand than it is currently doing, in the form of analytics and Artificial Intelligence (AI) integrated Robotic Process Automation.
What form will Robotic Process Automation with AI take in the business arena?
On a practical level, Gartner says AI will manifest itself in the continued rise of the ‘smart machine,’ something it predicts to be one of the biggest technology trends over the coming decade. It says enterprises will increasingly draw on growing computing power and ever-increasing sources of data to adapt to new situations, solve problems and ultimately get ahead of the competition. One of the key ways that they can do this is by automating routine processes and using AI, so that the efforts of skilled employees can be redirected to areas that will be more beneficial to the business than ever before.
This is where Robotic Process Automation (RPA) with AI comes in, enabling business and IT teams in an enterprise to automate processes using a virtual software robot. This robot interprets activities and stimuli within the business and then responds with an appropriate action, based on the parameters defined by the business. In effect, RPA with AI emulates a human operator, or acts as a tool to carry out repeatable processes or tasks. For example, it could be used by a bank to auto-complete registration forms when processing a higher than expected number of applications for a recently-launched type of account. Firms in a range of other sectors could also enjoy the benefits of being able to handle a sudden peak in inbound calls using of a virtual service desk employee to route inquiries more efficiently.
Reaping the benefits
Businesses will benefit greatly from having functions and processes automated at scale, and with repeatability. In addition to bringing potential cost reductions, RPA can also streamline processes and enhance the overall end-user experience. There are four big benefits enterprises should be able to draw from this:
A more consistent experience than ever before. With robots following specific formulae and layouts, and performing at a uniform speed, a standard level of output should be more achievable than ever before.
Deeper insights into business / IT performance and customer experience.
A reduction in the level of human error. We all become fatigued and make mistakes on occasion; this potential for error is limited by the use of RPA.
More speedy execution than ever before, with some areas of the business able to run 24/7. This means enterprises will be in a much better position to keep things moving even when it’s the end of the working day for its human employees.
Is it for everyone?
As with the adoption of any new kind of technology, enterprises must build a realistic business case for Robotic Process Automation before taking the plunge, or it could just be a wasted effort. This means taking the time to map out costs and expected benefits before budgets can be assigned and work can get underway. The key to making this work is thinking about RPA with analytics and AI from a wider strategic perspective: it’s no good just making vague statements about the potential benefits it can bring. Be clear on exactly what the end goal is, and how it will bring improvements to different existing processes within the business.
Once funds have been secured, businesses must develop a clear idea of the internal processes that are already running: what duty does everything perform, and what does it connect with? As the wires can become increasingly tangled here, it goes without saying that processes that have not previously been integrated and automated in the past will be much easier to improve through the use of RPA. Businesses will also need to consider how processes that are supported by their legacy IT systems will be impacted, as it will be much more difficult to integrate Robotic Process Automation with older technologies. The good news is that it is relatively simple to integrate RPA with existing automation and orchestration platforms, so those that have already invested in machine learning technologies may have much of the groundwork already in place.
Success as part of the wider picture
It’s also important to realise that the benefits won’t be so great if you’re automating a
single or standalone process. To be truly effective, RPA must be integrated with a complete service delivery chain to streamline the entire process, rather than just one small part of it. Furthermore, when Robotic Process Automation is integrated with Cognitive/Machine Learning capabilities, it will be able to learn to complete new processes and functions by itself, which is where it will really start to have a positive impact for the workforce.
The key to making RPA a success is taking the time to ensure it is embedded deep within existing systems and business operations. By skipping that stage, there is the risk that RPA will be tacked on simply for its own sake and is unlikely to deliver the benefits it can provide. If they get it right however, enterprises will be perfectly placed to leverage the power of AI and automation to accelerate the adoption and dynamic adjustment of process change in the digital world, proving a real springboard to success for the 21st Century enterprise.
Automating manual or inefficient processes is the bread and butter of any technology organization. Here are nine considerations for approaching process automation tasks the right way, and ultimately delivering successfully.
1. Avoid ‘automated crap’
A colleague of mine once quipped that automating a ‘crap’ process just results in ‘automated crap,’ and while the language might be a bit uncouth, the sentiment is absolutely correct. It can be tempting when tasked with automating a process to immediately start considering the systems and software to deploy; however, it’s worth determining whether the process is currently valid, effective, and necessary before diving into automating it. Furthermore, some processes simply should not be automated.
2. Check your options
Sometimes pure technology is not the right answer for process automation, as the whole offshore process outsourcing business can attest to. While there are myriad risks and considerations to process outsourcing, considering non-technology options for process ‘automation’ should be part of your evaluation and due diligence process.
3. Look for cheap fixes
Similar to avoiding ‘automated crap,’ before digging into the technical aspects of automation, consider whether there are low- or zero-cost changes that can make the process more efficient. In particular, look for areas where data are painstakingly gathered but no one knows why they’re needed, or complex workflows ‘ping-pong’ a process between multiple operators when one person could perform several steps. Automation should be icing on the cake of a well-designed process; if you don’t have the cake, all the icing in the world won’t prepare you for the birthday party.
4. Size the solution to the problem
I was once tasked with building a complex automated order management process for ‘selling’ scrap paper that had dozens of unique tracking and invoicing requirements. As we contemplated solutions, I asked how much revenue was generated by this process, and was solemnly told it was “as much as $500 annually.” While the goal of integrating all sales processes in one system was laudable, a $50,000 solution to a $500 problem was laughable. Simply disposing of the scrap paper was a far more cost-effective solution than expensive automation.
5. Consider the KPIs
When we automate, we usually consider increased speed or reduced cost as the ultimate successful outcome of the automation effort. However, these may not be the right KPIs in some cases. Shortening the time to handle a customer sales call might increase the number of calls you can process, but will reduce sales revenue since reps no longer have time to cross sell, just as a confusing automated system can actually increase customer service calls, producing the exact opposite of the intended outcome. Before reflexively considering cost and speed as your key KPIs, think a level deeper and add KPIs that will mitigate unintended outcomes.
6. Consider the user experience (UX)
Along with well-defined KPIs, User Experience (UX) should also factor into your automation concerns, both from the perspective of the process operator(s) as well as the consumer of the process. Automation that’s targeted toward an employee with minimal training will require more robust error handling than one that’s in the hands of a skilled operator. Similarly, extra time spent ensuring the process is clearly articulated and displayed toward the operator and end customer will ultimately make the process more efficient by reducing errors and confusion. For example, self-checkout systems at the grocery store were supposed to be a superior option to human-assisted checkout. However, users quickly learned that manually finding and keying codes for produce and bagging their own groceries was inferior and slower than checkouts staffed by humans, resulting in low adoption rates of self-checkout. Obviously, these systems save the store staffing costs, but ultimately they increase customer frustration.
7. Test the edge cases
A key failure point for many automated systems is poor testing. The automation is great ‘most of the time’ but completely breaks down during an edge case or error condition. While there’s a risk of ‘over-testing’ and becoming obsessively focused on convoluted and unlikely use cases, it’s imperative that the automation recover gracefully from predictable errors. What happens if unexpected data are entered? How does the automation respond to a system that’s down? How does the automation recover and guide a user when failures occur?
8. Avoid ‘orphaned’ automation
Like any IT project, once automation is successfully deployed it’s tempting to cross the item off the organizational to-do list, and not revisit the automation until it’s obsolete or fails. As part of your regular maintenance activities, check the performance of key automated processes. Perhaps there’s a new tool or technique that could quickly be adopted for significant benefit, or a minor technology upgrade could provide dramatic returns. Applying continuous improvement practices to your process automation efforts can reap additional benefits from your automation at lower costs than new efforts.
It can be easy to apply the same solutions and techniques to your ongoing automation efforts, but take a moment to consider if there are new technologies or services that might be more effective at accomplishing your automation goals. Emerging technologies like Robotic Process Automation (RPA) or Artificial Intelligence (AI) technologies could be relevant to the automation problem at hand, or perhaps you’re tasked with automating a low-risk process that could serve as a test case for advanced tools and techniques.
While process automation is old hat to many IT organizations, to the point that it’s seen as a low-level activity that can be given limited attention, there are very real considerations, concerns, and benefits to effective process automation. Executing a difficult technical task often has less visible impact, and associated financial benefit, to shaving some time or improving the quality of a process that’s performed thousands of times each day.