The Robotic Process Automation market will reach $443 million this year

Have we ever got so excited about a market that isn’t even yet past the half-billion dollar spend level? Are we getting over excited about solutions because of their potential before they are fully tried and tested in reality? Let’s get to the realities of RPA by examining the size and five-year forecast for software and related services expenditure:

The global market for RPA Software and Services reached $271 million in 2016 and is expected to grow to $1.2 billion by 2021 at a compound annual growth rate of 36%. The direct services market includes implementation and consulting services focused on building RPA capabilities within an organization. It does not include wider operational services like BPO, which may include RPA becoming increasingly embedded in its delivery.

RPA describes a software development toolkit that allows non-engineers to quickly create software robots (known commonly as “bots”) to automate rules-driven business processes. At the core, an RPA system imitates human interventions that interact with internal IT systems. It is a non-invasive application that requires minimum integration with the existing IT setup; delivering productivity by replacing human effort to complete the task. Any company which has labor-intensive processes, where people are performing high-volume, highly transactional process functions, will boost their capabilities and save money and time with robotic process automation. Similarly, RPA offers enough advantage to companies which operate with very few people or shortage of labor. Both situations offer a welcome opportunity to save on cost as well as streamline the resource allocation by deploying automation.

The bottom-line: RPA provides the building blocks for digitizing rudimentary processes in the digital underbelly, but the broader market for intelligent process automation is more than 10x the size

Stay tuned for our broader forecast for the global Intelligent Process Automation market, which is in the final stages of its fine-tuning, as the expenditure enterprises and service providers are making their internal teams to learn how to automate business processes intelligently, the internal training and development, pilot projects and trial implementations, is so much larger than simply software licences and third party professional services to work the software effectively.

Net-net, we have to be realistic about the value RPA brings to enterprises today, versus its potential for the future. RPA’s value for most of today’s early adopters lies in the digitizing of rudimentary manual processes. It’s a starting point for designing the underbelly that enables a digital OneOffice environment:

Digital effectiveness is all about organizations enjoying real-time process flows forged through the elimination of manual process break-points and intelligent linking of data patterns across the front and back offices. RPA is a critical building block in facilitating this journey, but ultimately it’s the whole OneOffice, not the sum of the parts, that matters for true real-time effectiveness. This is about one integrated organization unit, where teams function autonomously across front, middle and back office functions and processes to promote real-time data flows and rapid decision making, based on meeting defined outcomes. In the future… front, middle and back offices will cease to exist, as they will be, simply, OneOffice, and RPA has a critical role to play supporting the building blocks. However, the market is still very young and we’re only at the start for so many organizations, so let’s not get too carried away until we see really robust solutions with proven ROI and long-term business value.

In short, every siloed dataset restricts the analytical insight that makes process owners strategic contributors to the business. You can’t create value – or transform a business operation – without converged, real-time data. Digitally-driven organizations must create a Digital Underbelly to support the front office by automating manual processes, digitizing manual documents to create converged datasets, and embracing the cloud in a way that enables genuine scalability and security for a digital organization. Organizations simply cannot be effective with a digital strategy without automating processes intelligently – forget all the hype around robotics and jobs going away, this is about making processes run digitally so smart organizations can grow their digital businesses and create new work and opportunities. This is where RPA adds most value today… however, as more processes become digitized, the more value we can glean from cognitive applications that feed off data patterns to help orchestrate more intelligent, broader process chains that link the front to the back office. In our view, as these solutions mature, we’ll see a real convergence of analytics, RPA and cognitive solutions as intelligent data orchestration becomes the true lifeblood – and currency – for organizations.

Source: HFS-The Robotic Process Automation market will reach $443 million this year

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How to make your legacy systems perform like new with intelligent automation

How to make your legacy systems perform like new with intelligent automation

Unless you’re a techie, most people haven’t – or wouldn’t want to– work with a “green screen” system.
Whilst your legacy systems and applications were once cutting edge, they are likely now considered unintuitive and slow in comparison to their modern-day counterparts. The problem is, while legacy systems and applications still perform their job and are highly critical to the success of your business, employees and customers alike do not wish to interact via these channels.

Chances are, if you’re like many finance or insurance companies, you’ve stored important information about all of your customers’ in these legacy systems, so your staff must regularly use them to deliver your products and services. While they may have to use them, you already know that this situation isn’t conducive to high levels of productivity or customer service.
So, with that in mind, what are your option for creating a digital service and moving away from “green screens” and legacy systems into the new digital economy?

“Rip and Replace”
You could “rip and replace” your current systems and embark upon a digital change program to implement a new system, using modern interfaces and streamlining your business process. But, while it’ll work, implementing a new system or application into your organization often requires significant investment and comes with a high degree of risk.
For most organizations, digital change programs take years of commitment to complete, as you are required to perform an array of large tasks such as safely managing data transfer, the creation of new software applications, replacement of business logic and retraining of staff. And while this could run smoothly, we’ve all seen high profile digital change programs and projects fail.

Modernise with Intelligent Automation
Rather than go down the expensive and risky route of a digital change program, you can modernise using intelligent automation. This approach combines the use of virtual workers and web based input channels to manipulate your current applications, giving you many of the benefits of a new system –without having to disrupt your business.
By taking this approach, your customers and employees enjoy a modern intuitive user interface and all interactions with legacy systems and applications are handled by virtual workers.
As a result, tasks such as data query and capture which would be error-prone and time-consuming, are performed in an instant and without error by virtual workers. So, you can deliver a digital service to your customers and improve the job satisfaction of your staff – while cutting your costs and reducing your time to market.

Given the time and cost it takes to implement a new system, we would recommend you take advantage of the power of intelligent automation to make your old systems new and leave the “green screens” behind.

Source: thoughtonomy.com-How to make your legacy systems perform like new with intelligent automation

RPA and AI – the same but different

For a conference run by the Institute of Robotic Process Automation (IRPA), there sure was a lot of talk about Artificial Intelligence (AI). Unfortunately, most of that talk only seemed to confuse people about this latest, and most-hyped of, technologies. There were frameworks presented which showed RPA and AI as a ‘continuum’, there were models that seemed to suggest that there was a natural ‘journey’ from RPA to AI, whilst others talked about AI being a ‘must have’ if RPA was to realise its full value. Some presenters talked about a ‘choice’ between RPA or AI. None of which really helped educate the conference attendees on the benefits of either technology. Let’s unravel each of these points so that everyone can be clear on the relationship between RPA and AI.

The RPA/AI Continuum – whilst it can be argued that RPA is the relatively simpler of the two types of technologies, they are very different beasts indeed. The key difference is that the robots of RPA are ‘dumb’ whilst the AI is ‘self—learning’. The robots will do exactly what you tell them to do, and they will do it exactly the same way again and again and again. Which is perfect when you have rules-based processes where compliance and accuracy are critical. However, where there is any ambiguity, usually when the inputs into a process are unstructured (such as customer emails) or where there are very large amounts of data, then AI is the appropriate technology to use because it can manage that variability and, most importantly, get better at it over time through its own experiences. So, if you do want think of a technology continuum, make sure you put a large gap between RPA and AI.

The RPA to AI Journey – there are a number of case studies where companies have implemented RPA and then implemented AI, but only because RPA is a more mature technology than AI. There are far more examples of companies implementing RPA and not implementing AI at all because they actually don’t need the AI. RPA does a fantastic job of delivering labour arbitrage, accuracy and compliance without AI coming anywhere near it. And, of course, some companies implement AI without RPA. It’s not a journey, just a set of choices based on specific demands.

The RPA Dependency on AI – another view that was put forward was that RPA is only valuable when it has AI in support. This is clearly a self-fulfilling view put forward by the vendors that are able to offer both technologies, but it is simply not correct. As mentioned above, many (in fact, most) companies implement RPA without any consideration or need for AI. If you want compliant, repeatable processes, and can feed the robots with structured data, then why complicate and confuse matters by introducing AI?

The RPA/AI Choice – There was yet another the view put forward (which actually conflicts with much of the above) that companies need to make a choice between RPA and AI – in other words which is the best one for them to implement that will deliver their objectives? As should be clear by now, the two technologies actually complement each other very well, for example by using AI to structure unstructured data at the beginning of the process, by using the robots to process the transactions, and then potentially using AI for decision making and/or data analytics at the end.

So, why all this confusion and mis-information? Part of it is obviously self-interest from vendors and providers to create frameworks and models that align with their own capabilities and marketing messages. And, although RPA is now pretty well defined (with that badge of maturity: its own acronym) some of the confusion surely arises from the multiple terms used to describe artificial intelligence; AI, cognitive computing, machine learning, NLP, etc. For now, it is much the best approach to think of AI in terms of how it can help your business, without worrying about what to call it. As the technology develops though a more robust approach is required, which is why at Symphony Ventures we are working on an ‘AI taxonomy’ that will clarify the different types of AI, and therefore help to explain the practical opportunities and uses for AI in our clients. We look forward to sharing this with you and de-bunking much of the confusion around RPA and AI that we have seen over the past few months.

Source: Symphony-RPA and AI – the same but different

Why Robotic Process Automation can be more than quick wins

Every CFO wants robotic process automation (RPA), and they want it now. That puts a lot of pressure on finance departments to not only learn about a relatively new technology (or, at least, a new buzzword), but also figure out how RPA will impact their company. Ann Furlong explains.

With CFOs shining the spotlight on RPA, the investigation and adoption of the technology are in full swing.

According to Deloitte’s 2016 Report, “The Robots Are Here”, only 13 per cent of the shared services and global business services leaders that Deloitte surveyed are unfamiliar with RPA. Almost a quarter of the people surveyed have investigated it as an opportunity for their company, and 22 per cent of those respondents are either in a pilot phase or have already implemented it. And everyone, regardless of what stage they’re in, wants to know how their company can quickly implement robotic process automation and see fast return on investment (ROI).

There are also a lot of myths about RPA that have caused some confusion. While no company wants to miss out on the many benefits or RPA, it’s important to follow a well-thought out strategy when adopting this new technology. This includes both processes to be robotised as well as expectations for short-term and long-term ROI.

Many companies that are adopting robotic process automation are too focused on the short-term ROI. While everyone wants quick wins like automating the reconciliation of zero-balance accounts, focusing only on the low hanging fruit will deliver your time to value (TtV), but can cap your long-term ROI.

Whether this focus on the short-term is a consequence of acting hastily to please the CFO, or if it’s just short-sightedness, only picking the low hanging fruit for automation will minimise the automation levels you could otherwise achieve.

RPA’s quick wins, such as automatically matching and reconciling bank account transactions, are very tempting. However, these quick wins alone aren’t bringing companies the return on investment for which they had budgeted.

According to McKinsey, robotic process automation can offer automation levels of 50 to 70 per cent and a reduction in straight-through process time of 50 to 60 per cent, but in order to achieve these levels of automation, you need to take a more holistic look at your financial close processes.

As Leslie Willcocks, an international authority on RPA, states in an interview with McKinsey, “[I]t’s wrong to look just at the short-term financial gains […].” If you’re only focused on the quick wins, your implementation won’t see long-term returns and may even fall short on achieving initial RPA goals, resulting in your project being considered a failure.

So how can you and your company avoid getting caught up in the “quick win” mindset?

Don’t just focus on what you can achieve in the first six months, or year, even. Make sure that you’re using robotic process automation to the full extent of its ability by having a three-year roadmap.

While that roadmap may evolve as your RPA transformation advances, it will keep the project moving forward and encourage a continuous improvement mindset. Applying continuous improvement is essential for a successful RPA transformation.

Finally and perhaps most importantly, don’t forget that RPA isn’t the end goal, but only a part of a finance department’s strategy.

Source: insidesap.com.au-Why Robotic Process Automation can be more than quick wins

3 reasons adoption of robotic process automation is on the rise

The average knowledge worker has a lot of repetitive and mundane tasks that are manual, dreary, uninteresting and take up a lot of time. Robotic process automation (RPA) software robots help to perform such time-consuming tasks by mimicking the way humans interact with applications through a user interface.

RPA removes the robot from the human, freeing them to focus on more important strategic tasks that require emotional intelligence, reasoning and judgment.

Most cost optimization and efficiency improvement initiatives have reduced costs through standardization and centralization. However, that prevents the business from being nimble and agile when reacting to business opportunities and changes in the ecosystem.

On the other hand, RPA can have a wide-ranging impact on a company’s operations and competitive positioning such as economic value, workforce advantages, quality and control improvements, and flexible execution.

Hence, demand for RPA tools is growing quickly, at 20-30% each quarter, according to Gartner, which refers to RPA tools as “gateway technologies” or “surface tools” because they just begin to skim the surface of the larger intelligent automation services market.

RPA is used extensively in banking, finance and accounting, insurance, retail, manufacturing and telecom sectors. Some noteworthy vendors include Automation Anywhere, Blue Prism, EnableSoft, Kryon Systems, NICE, Openspan (a unit of Pegasystems), Redwood Software and UIPath.

Here are the top three reasons why RPA use is on the rise:

Allows more control, accuracy

One of the biggest advantages of using RPA tools is that they are relatively low-cost, quick to implement and unobtrusive. The user who is looking to automate a particular task need not have programming expertise.

With a few weeks of training, people with business operations experience and subject matter expertise can start automating processes with RPA tools.

It is also a relatively lightweight IT operation and does not disturb underlying computer systems. This leads to adoption of RPA within business operations rather than something brought by the IT to the business, leading to lower costs of deployment.

The best part is that a proof-of-concept RPA project may take as little as two weeks. It could be up and running within four to eight weeks, depending on its scope and complexity.

Since it minimizes manual processes and reduces errors while filing paperwork, RPA robots are more accurate than humans. Cognitive RPA will help in business continuity as automation will lead to enhanced disaster recovery processes. As compliance requirements can be embedded into RPA’s automated rules, it will reduce internal risks to data and processes.

Reduces people costs

According to EY, 65% of HR rules-based processes can be automated and 93% of HR employees’ time is spent on repetitive tasks. The big advantage of RPA is that robots are able to use the existing HR processes and systems.

Robots can easily take care of repetitive tasks and compared to humans, they cost less as well. The cost of an RPA robot will range from $5,000 to $10,000annually.

Most often, a robot can easily do the job of three to five workers, thus helping to save on employee costs. PwC estimates that 45% of work activities can be automated, and this automation would save $2 trillion in global workforce costs.

Cognitive RPA will also present opportunities to redesign jobs and reassign people to higher-value roles. Most companies who have to deal with seasonal/transactional demand for workforce rely on RPA robots as they can execute a process that can easily be scaled up or down.

Also given that a software robot can cost as little as one-third the price of an offshore FTE, RPA offers an alternative to some BPO relationships.

Uses data to improve service

Intelligent technologies can learn and make decisions beyond their initial programming. As RPA can quickly generate and gather data, combining it with intelligent technologies makes the learning process a lot faster.

RPA can be used across industries and will also help in auditing as the robots record and monitor their own steps as they execute automated workflows. More importantly, RPA can contribute to Big Data and uncover valuable business insights and trends.

For example, in the case of a financial company, RPA can reveal transaction process times, the number of automation activities processed and the outstanding. This will reveal bottlenecks in business operations and help in creating financial forecasts and budgets.

RPA is already disrupting industries and is delivering significant benefits that the businesses will find hard to ignore. The technology is gaining traction as a cost-effective alternative to traditional systems integration and is projected to become a $5 billion market globally by 2020, with a CAGR of over 60%, according to Deloitte.

The key to delivering rapid success in the deployment of RPA solutions is finding the right balance between technology and skilled staff. Businesses must be prepared to manage the significant technological and cultural challenges that will follow large-scale deployment of RPA.

Source: CIOdive-3 reasons adoption of robotic process automation is on the rise

Digital Finance: Why (and How) Robots Are Joining the Team

What comes to mind when you hear the word “robot?” Maybe an image from pop culture, such as R2-D2 or, at the other end of the spectrum, Arnold Schwarzenegger in The Terminator? Perhaps giant yellow arms pivoting on an auto assembly line? Or even one of those package-delivery robots currently cruising the streets of San Francisco? In any event, you probably associate “robot” with some sort of physical entity, a substitute human made of metal, plastic, and plenty of electronic componentry: mobile, task-oriented, still somewhat exotic—and certainly expensive.

It may be time for CFOs to put aside such misperceptions, because the robots that are quickly and quietly becoming an integral part of the finance function bear no resemblance to those just described. Rather, they are arriving in the form of a technology termed “robotic process automation,” aka “RPA,” with the emphasis squarely on the “PA.”

These robots exist as software and are designed to automate a wide range of processes that tend to be repetitive, labor-intensive and rule-based. RPA has been described as “a spreadsheet macro on steroids,”but that’s like comparing the cruise control function in cars to fully automated, driverless vehicles. Put simply, RPA replicates any mouse and/or keyboard actions a human would perform across multiple applications on their PC. RPA can do everything from open email and attachments to collect social media statistics to follow if/then decisions and rules (see Figure 1, “What RPA can do”). In finance, that translates into everything from recording journal entries to reconciling general ledger accounts to auditing expense reports, to cite just a few common applications.

While RPA is simply software code—and fairly simple, inexpensive code at that—it is, in one sense, analogous to those giant yellow-armed robots deployed across factory floors in that it changes the calculus of outsourcing/insourcing decisions by automating labor-intensive tasks. Companies that have turned to business process outsourcing as a way to economically tackle a variety of finance needs may find that an increasing number of them can be handled by RPA.

Many, in fact, already are. This year the market for RPA products and services will reach $433 million, according to HFS Research, and may climb to $1.2 billion by 2021, a compound annual growth rate of 36%.¹

Demystifying RPA

As mentioned, RPA is a relatively simple and inexpensive software-based technology (a “fully loaded” robot may cost about one-third of what a globally sourced employee might cost²) that sits on top of other applications (at the user-interface level), requires no special hardware, and plays well in almost any IT environment. It is robotic in the sense that it does what people sitting at desks often do: enter keystrokes, mouse over certain fields within an application, cut and paste, move data from one place to another, make queries and calculations, hit “send,” etc.

Source: “Robotics & cognitive automation: General overview,” Deloitte Development LLC, 2017

To get a robot up and running, a “robot configurator” specifies in detail the instructions the robots will follow and publishes that script to a robot controller, a centralized repository that will assign the jobs to various robots and monitor their activities. The robots can reside on desktop computers or be virtualized, but either way they will interact directly with whatever business applications are needed to do their jobs. Business users typically resolve any exceptions or escalations that might occur as robots do the lion’s share of the work.

Many vendors offer RPA software, and over time its capabilities are likely to become embedded in core systems as relevant applications evolve, facilitating interoperability. But CFOs don’t need to wait; even in its current form RPA is already saving companies substantial amounts of time and money. In some instances, RPA is 15 times more efficient than humans and offers a 15% to 90% cost-reduction opportunity,³ depending on the characteristics of the function to which it’s being applied.

Not only can RPA save on full-time equivalents (FTEs), but it can also provide several other advantages. Because it can run 24/7, it can grind through time-sensitive reporting tasks that often require finance staff to log night and weekend hours in order to meet deadlines. And it is often more accurate, with some companies reporting the complete elimination of data re-entry and rekeying errors.⁴ That reliability is bolstered by the creation of an audit trail that identifies any potential glitches. In fact, many organizations create a monitoring system that allows a finance staffer to “supervise” a team of robots in real time.

That may sound fanciful, but RPA differs from many other technology implementations in that it is not really about technology, but about redeploying human talent: let the robots do what they do so well, which can free up finance talent to address activities that are less rote and add more value. Within a shared services center, for example, using RPA to automate some tasks can enable staff to focus on delivering customer and market insights or develop new levels of service altogether.⁵

Making RPA Happen

When it comes to leveraging RPA, companies generally fall into one of two camps: those that have launched pilots and are now trying to scale the technology, and those that are at the early stages of exploring its possibilities.

If your organization falls into that latter camp, one viable way to begin is with a prototype or pilot that will allow you to become familiar with RPA at a basic level. Begin by identifying tasks that lend themselves well to RPA. Often, this low-hanging fruit exists in a Center of Excellence or in an outsourcing arrangement and may include the following:

—Tasks that may have been outsourced, such as reconciliations, claims processing, returns management, inventory processing, desktop support and network monitoring;

—Process automation tasks in the front office (sales order management, competitor price monitoring, customer engagement), middle office (trend tracking, report generation) and back office (data reconciliation, applications integration);

—Shared services tasks that typically entail multiple interactions with different systems, such as payroll, onboarding and benefits management in HR, and folder and file management, infrastructure/application monitoring, and user/directory and release management in IT.

To be manageable, an agile pilot program would begin with selecting three to five processes. As with most pilot efforts, it is advisable to make reasonably fast decisions regarding team composition, product selection and the pilot process. With RPA, though, it’s also important to invest time in understanding the value and limitations of whatever tools you decide to deploy, in order to ensure they are right for today’s needs and, if applicable, have the ability to scale. Another key consideration: determine how to engage the owners of a given process to give an RPA pilot a try, because they have the process knowledge that will be a key component in programming the robot, not to mention the business need that can prove the value of RPA.

Assuming a successful pilot, many organizations may want to determine how to scale the technology to meet additional needs and opportunities. In this regard, organizations can adopt something of a pay-as-you-go strategy, using the money saved from a first round of RPA to finance the next round, and so on. Aside from that, several core decisions need to be made.

For example, to build a business case, companies should determine what pain points can be alleviated by RPA, what metrics will be useful in assessing RPA’s effectiveness and what strategy will be used for redeploying existing resources once RPA is up and running. In addition, companies should also decide which operating and governance models most suit their needs: Should they own RPA capability long-term, or continue to partner with a third party? Is the right team in place to support the solution, and who will manage and monitor the robots as they carry out their duties? With so many vendors in this space, organizations should also determine which ones are best suited to their business needs, which sourcing options work best and how various pricing models compare. Finally, it’s also important that the people driving RPA efforts ensure that all stakeholders affected understand what RPA is, why it’s being deployed and how it will be rolled out.

The Promise and the Pitfalls

Regardless of whether a company is piloting RPA or beginning to scale it, odds are good that the tasks it’s being applied to today are highly transactional, rules-based, and labor-intensive. But already some companies are combining RPA with other technologies to automate not only human actions but human judgment, and, eventually, intelligence.

By combining RPA with cognitive and artificial intelligence capabilities, natural language processing/generation, and other emerging technologies, companies can create toolsets that can tackle judgment-based processes, predictive decision-making, and more, to produce virtual customer assistants, conversational user interfaces, and many other advances.⁶ Seen through that lens, RPA becomes a foundational technology for a digitally transformed enterprise that can evolve in lockstep with these quickly advancing technologies.

That’s not to say that robots will do everything, of course. But as RPA and other technologies usher in an era of digital transformation, CFOs will have to think carefully about what (human) skills they will need to hire or train for. One advantage of RPA is that it can be configured by non-technical staff: any finance team member comfortable creating spreadsheet macros should be able to play a key role in making RPA happen.

As RPA proliferates and acquires additional capabilities, however, there will likely be a growing need to have finance staff focused on how to apply an expanding arsenal of digital capabilities to finance and broader business needs. Put another way, RPA is not a “one-and-done” technology implementation, but a capability that needs to be continuously managed. CFOs are already well aware that in an ever more dynamic business environment, success depends on continuously training, retraining and redeploying their human talent. The same holds true for the robots that can increasingly augment the work of the finance team: As companies acquire and divest businesses, move to new ERP or other large-scale IT systems, change their processes, or evolve in any number of ways, robots will likely require frequent reprogramming in order to deliver as much value as possible. They may never match the wit of C-3PO, but they seem bound to become indispensable members of the finance department.

–Produced by Anthony Abbattista, principal, co-leader RPA/RCA, Deloitte Consulting LLP; Matt Soderberg, principal, Deloitte Consulting LLP; Tadd Morganti, managing director, Deloitte Consulting LLP; and Jan Hejtmanek, manager, Deloitte Central Europe.

Endnotes

Source: dtte.wsj.com-Digital Finance: Why (and How) Robots Are Joining the Team

Path of progress in Robotic Process Automation: Three stages to RPA success

This blog post will focus particularly on improving productivity through Robotic Process Automation (RPA). We will look at three development stages that companies and organizations can use to increase their productivity through RPA.

This new technology of business process automation has evolved to the point where it can be utilized extensively at a very low cost compared to traditional ERP (Enterprise Resource Planning) and EAI (Enterprise Application Integration) integration methods. With software robots getting down to work around the world to eliminate dull, repetitive and routine tasks, it is time to think about how people and organizations could best make use of their digital assistants.

Continuous, rapid change as a driving force for RPA

Why are organizations and companies using more and more time and energy on automation?

Growing business organizations have traditionally utilized ERP systems to produce automated processes. However, the rapid growth of companies has made their earlier ERP investments prematurely outdated, as their ERP technologies have been too stiff and massive to scale according to organizational growth and process changes.

This has resulted in multiple manual process steps (humans transferring data between systems), inconsistencies in data processing (entering the same data separately in several systems) and uneven quality in intermediate process steps and final outcomes. In other words, the agility and capabilities of traditional automation do not meet the pace of development in organizations. RPA is a potential answer to these growing pains!

RPA has the following implications for organizations:

1. Reduced process turnaround times;
2. Higher outcome quality;
3. Scalability and agility;
4. Improved measurability (manual process steps are digitized).

Here are just a few examples of operations that can easily be performed by current software robots:

  • Opening emails and attachment files and saving them or extracting data from them
  • Filling out web forms based on rules
  • Extracting data from several information systems and re-editing data to create dashboard reports
  • Integrating and pruning data and comparing data between different information systems
  • Performing calculations and copying and pasting the result forward
  • Visually identifying a certain character string in a document (pattern recognition) and extracting data on this basis

Means of increasing RPA utilization rate in organizations

Robotic Process Automation offers a variety of ways to increase the degree of automation. For organizations, however, robotics is a new phenomenon and its implementation may arouse suspicion and resistance to change. Therefore, business management should quickly increase knowledge about RPA among management and employees in order to ensure that the potential benefit is realizable.

RPA software, just like any other business software, is used and steered by people. While the degree of automation is being increased in, say, payroll computation and financial administration processes through RPA, robotics should shift towards people’s work and be integrated into it. RPA is based on well-defined processes and logical rules related to them. These allow the robot to work either a) automatically in the background or b) initiated by a human. When changes are made to a process or to the business software used in the process, the robot has to be retrained for its task as well. This training will be a new special skill that companies must be able to obtain.

Three stages on the path of progress in Robotic Process Automation

We have defined three stages for the path of progress in robotics. Each of these contains different requirements for the organization’s ability to develop and learn.

Stage 1

In the first stage, the organization sets out to test and pilot RPA in its processes. In this stage, it is usually a good idea to use a consultant and an expert with special know-how in the field of RPA as well as a vision about how Robotic Process Automation could benefit your company. It is typical to select one function and a few processes as starting points for piloting. With the help of the consultant, the benefits of RPA can be estimated quickly and an action plan can be prepared for the development of RPA automation.

The key is to increase your organization’s understanding of RPA and gather experiences.

Stage 2

In the second stage, the organization expands the utilization of RPA to several functions and processes. The consultant can help to define complex sets of rules and assume part of the workload in training the robots. In this stage, the key is to share the information and know-how obtained in the pilot with the organization and to increase internal RPA capabilities in a determined manner.

Stage 3

In the third stage, RPA has become the standard procedure for increasing the organization’s productivity, and it is managed through a centralized center of excellence or function-specific RPA teams. The organization possesses plenty of internal intellectual and knowledge capital on robotics and is able to maintain and develop these self-sufficiently. The key is to standardize RPA and to measure and manage competence and capabilities.

Source: Arcusys-Path of progress in Robotic Process Automation: Three stages to RPA success

10 Success Factors for Deploying Software Robots in the Enterprise

The implementation of software robotics and smart technologies frees a workforce from routine tasks while improving efficiencies, data accuracy and compliance.

Make Sure IT Is Involved from the Start

There often is tension between what IT resources a company’s lines of business need to operate most effectively and the allocation of said resources. While the overarching mandates are to improve service and reduce costs, the resources and priorities of the two groups often are misaligned, constraining business growth and performance. Many RPA implementations emanate from business operations teams, leaving IT on the sidelines in favor of speed and creating shadow RPA projects outside of IT’s oversight. This is a mistake. The most successful, scalable deployments of RPA are implemented in full collaboration with IT leadership.

IT Must Demonstrate its Willingness to Collaborate

It also is important for IT and the business teams to work on the same page. IT must recognize the urgent need for RPA in the business in terms of mandates to improve efficiencies, improve customer satisfaction and other drivers and offer appropriate levels of support and partnership to avoid shadow deployments. Collaborating and agreeing on priority deployments upfront will alleviate alignment issues later.

Begin with an Automation Strategy that Sets Direction

One way to align priorities for the business is to work together on setting and aligning expectations with a common vision. Beginning this process with a documented automation strategy is important. What is the target state of RPA within the operations team? What does the roadmap look like? Establish executive sponsorship upfront, agree to the scale of investment and quantify the expected benefits of that investment so it can be measured. Also consider including a proof of concept or pilot project that supports the defined strategy and vision.

Identify Ideal Process Candidates for Automation

For most businesses, the best candidates for automation often are back-office processes wherein the goal is to provide faster, easier service to customers—such as activating a new SIM card in five minutes rather than 24 hours. These processes are mundane and require entering repetitive data into multiple systems that don’t talk to each another. The goal is not to reduce jobs, but to minimize mundane tasks so people can focus on more value-added and fulfilling work.

Don’t Stop with Quick Tactical Wins

You’ve likely identified a large number of existing processes that can be improved with automation. You can move to automate those quickly, secure wins and demonstrate the success of RPA. But RPA presents an opportunity to drive transformational change in your business. Now is the time to take a step back and allow teams to imagine what is possible. Brainstorm with different groups within the business and allow them to be creative in identifying game-changing and high-impact opportunities to create competitive advantage. What would your business do if time, people and resources were unconstrained?

Choose the Right RPA Technology To Enable Process Automation

As business-line and IT leaders work together to choose the right RPA solution, it’s important to understand the difference between simple desktop scripting, software development kits (SDKs) and enterprise RPA. A desktop automation solution offers a quick solution for a team with short, recorded and replay tactical automations aimed at navigating systems on the desktop. Automated tasks, often manually triggered, are coded or recorded individual keystrokes of a user. They are not connected to enterprise systems and are often deployed without the knowledge of IT. SDKs give IT a better, faster way to deliver on business teams’ expectations, but often don’t involve the operations teams in the process.

Make Security a Key Requirement for Vendor Selection

Business and operations leaders should engage IT early on in the process to ensure proper security, infrastructure and support. Enterprise-class RPA should be deployed in the data center or in the cloud, but never on the desktop. If there is a record button on the desktop, IT can’t monitor or provide security or meet regulatory requirements. Desktop deployments should scream “shadow RPA” to the IT organization. It’s important to ensure RPA software meets required compliance requirements such as PCI-DSS, HIPAA and SOX to provide the necessary security and governance.

Find a Strong Implementation Methodology

There are well-defined methodologies that already have been tried and tested for implementing software robots in the enterprise. Make use of these in your environments: 1) Identify the processes that are best-suited to robotic process automation; 2) Establish the benefits case for robotic process automation, encouraging organization wide recognition and adoption; 3) Implement the required infrastructure, governance and support framework to enable a robotic process automation capability to run efficiently and effectively; 4) Define a best-practice approach for process configuration, which increases the potential for automation and accelerates the development life cycle; and 5) Provide the necessary skills to operational resources via a role-based training and mentoring accreditation program.

Welcome ‘Bots’ to Workforce with Change-Management Best Practices

Both IT and business operations should incorporate change management best practices when introducing software robots as part of the workforce to bring teams along with the vision. Introducing bots into the workforce is new and different, and it requires careful concept selling and implementation. Sharing the company’s vision for how the software robots will add value and improve the business is important, but it’s equally important to help employees understand what’s in it for them: How will these robots help them do their jobs better and more efficiently?

Measure Impact to Demonstrate Value

When helping teams understand the total value of RPA, calculate expected benefits across shareholders, customers and employees. Focusing on one area only will sell the initiative short and miss an opportunity for driving broader enterprise value and scale. Use your RPA software to collect meaningful business intelligence data and real-time operational analytics to report on decisions and actions taken by each software robot. Use this data to see how the organization is performing, where process improvements can be made and what new opportunities for revenue and customer satisfaction can be identified.

 

Source: eweek.com-10 Success Factors for Deploying Software Robots in the Enterprise

RPA: Mapping out a plan for enterprise automation

Robotic process automation technology has the potential to make business processes more efficient, boost productivity and save lots of money by enabling “virtual workers” to take on tedious tasks — without the odious work typical of big enterprise-level applications. But this type of enterprise automation is an emerging technology, tools are still taking shape, and matching robotic process automation (RPA) to the right process is “still an art form,” says Forrester analyst Craig Le Clair.

Because the technology is so new, he says, businesses risk implementing systems without the safety net that underlies mature technology.

Read on for advice around establishing IT’s role in RPA projects and hear from two execs who have implemented RPA. Elsewhere in this issue, we examine how Lucas Metropolitan Housing Authority upgraded its obsolete on-premises infrastructure. And Nationwide Mutual Insurance’s Guru Vasudeva explains his IT department’s lean management system.

Download: Here comes the bots

Source: Techtarget-RPA: Mapping out a plan for enterprise automation