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RPA Resources: The Ultimate Reading List

Each month we publish a list of the top new RPA resources published across business and technical publications. Here's a list of our favorites.

Robotic Process Automation: 5 Key Trends to Watch

By Ericka Chickowski, TechBeacon

A look at 5 trends we’ll see as organizations expand their RPA programs: moving beyond pilots to truly scale RPA, RPA orchestration coming to the forefront,  growing emphasis on process discovery, RPA expanding into a broader enterprise automation strategy, and increasing focus on governance.


Ultimately, the trends unfolding in the next year presage an evolution not just toward a maturing of RPA but toward broader automation across the enterprise. Your organization will need to bring governance and orchestration to the table to keep all of its automation plates spinning, and you'll need to scrutinize how your manual processes work today if you expect to purpose fit automation not just to your current processes but to the underlying business needs. That's ultimately the key to evolving RPA from initial pilot projects into full-scale deployments.

[Read Robotic Process Automation: 5 Key Trends to Watch]


RPA Center of Excellence (CoE): What You Need To Know For Success

By Tom Taulli, Forbes

A deep dive into why an RPA CoE is beneficial, including details on how the CoE is run at Intuit.


The team has a set of guiding principles to help with the decision making. Here are some of them: partner with tech teams to achieve digital transformation; optimize a process before automating it; minimize the technical debt; follow the Software Development Life Cycle methodology; and ensure security and controls are maintained. To help with this, Intuit also uses project management tools.

[Read RPA Center of Excellence (CoE): What You Need To Know For Success]


How to Train Your Bots: 5 RPA Fails to Avoid

By Christopher Surdak, TechBeacon

An analysis of the 5 core reasons for RPA project  failure—financial, governance, operational, design, and technical—including an estimation of the frequency and impact of each type of failure. Bonus: If you like this article, see Surdak’s new book: The Care and Feeding of Bots: An Owner’s Manual for Robotic Process Automation. We’ll take a closer look at this in a future blog.


The 5% of companies that are succeeding with RPA today demonstrate that the technology does work, and these businesses are creating yet another technology arms race that all organizations must join in order to survive, let alone thrive. Yes, achieving full ROI from your RPA investment in one quarter may protect your bonus this year, but successfully deploying bots at scale over the next year or two will protect your job, and perhaps your career.

This may sound like the same hyperbolic rhetoric that the RPA industry has been guilty of all along. It's not. Rather, it is the inevitable result of the technology demonstrating that it can work, when properly applied, and does create game-changing results. In the end, as with the PC, the Internet, and social media, not adopting RPA is not an option. You just have to go about it in the right way. 

Read How to Train Your Bots: 5 RPA Fails to Avoid


Robotic Process Automation is a Big Market, but There Will be Only One Big Winner

By Dave Vellante with Mike Wheatley, SiliconAngle

If you want to take a close look at how the RPA market has shifted over the past few years and how it might evolve in the future, this is the article for you. Be sure to check out the video, which offers a much deeper dive into the analysis.


One of the most important questions to address is whether the RPA market is overvalued, and at first glance that does appear to be the case. Wikibon’s data shows the RPA market is trading at around 15 to 17 times revenue, which is a very high multiple. But Wikibon’s forecasts show that growth in the RPA market is expected to slow to 20% a year by 2025, by which time it will also start throwing off some profits, at least for the leading players…

Wikibon’s forecasts assume a market valuation of around $75 billion a year by 2025, which suggests the RPA market is actually more likely to be undervalued at this time. As for RPA’s total available market, it could easily end up exceeding $30 billion globally, supporting a higher implied valuation multiple.

Read Robotic Process Automation is a Big Market, but There Will be Only One Big Winner


How AI Is Supercharging RPA (Robotic Process Automation)

By Tom Taulli, Forbes

Automation Anywhere’s “Discovery Bot” was the biggest RPA product news to hit the headlines in February. This article investigates what Discovery Bot really does, how it’s different than process mining, and his assessment on whether AI really makes a difference in this context.


Robotic Process Automation (RPA), which allows for the automation of the tasks of workers, has been one of the hottest categories in tech. The reason is actually simple: the ROI (Return on Investment) has generally been fairly high.

Yet there are some nagging issues. And perhaps the biggest is the scaling of the technology. For the most part, companies max out with 20 to 30 bots within the organization.

But AI (Artificial Intelligence) is likely to help out. To see how, consider one of the leaders in the space, Automation Anywhere.

Read How AI Is Supercharging RPA (Robotic Process Automation)

Another bonus: Taulli has an upcoming book: The Robotic Process Automation Handbook: A Guide to Implementing RPA Systems. We’ll take a closer look at this book in a future blog as well.


Barriers and Best Practices for Scaling RPA

By Forrester Research

Last year Forrester reported that the majority of enterprise RPA implementations had 10 or fewer bots in production. This year, they researched why RPA programs aren’t scaling as expected—and what separates the RPA leaders from the RPA “laggards.”


Current approaches to building bots look like a patchwork of workflows and applications sitting on brittle legacy systems, in other words, not taking the right approach to RPA can in turn create brittle bots. When we looked at bot breakage, we found:

    • Firms value RPA resiliency, but can’t seem to master it. While 84% of respondents say that resilient automation is very or extremely important for achieving business objectives, only 16% of firms are very effective at it. Furthermore, about half of RPA programs lack significant resiliency. Firms that struggle with resiliency are also four times more likely to say they are very ineffective at controlling costs associated with RPA.
    • Bots have multiple reliability challenges. The leading cause of bot breakage is infrastructure-related issues, like software reliability issues or crashes, but a third of respondents or more indicated that application UI and data changes are other culprits, along with selecting the wrong tasks to automate.
    • Fixing broken bots is a drain on resources. Forty-five percent of firms deal with bot breakage weekly or more often, and fixing broken bots takes about one day. Meanwhile, firms indicated that broken bots impact customer service and employee experience as well as lower employee productivity. The most common method for addressing the workflow that would otherwise be handled by RPA is to route that work to an internal resource queue — so while bots are broken, impacted employees are overloaded.

Read Barriers and Best Practices for Scaling RPA


Who Should Own RPA?

By Lisa Morgan, Information Week

The short answer to this question is everyone: business and IT leaders as well as process owners. Read this article to understand how the different roles should contribute, and hear some lessons learned from the field.


"There's a lot of, 'I just want a robot.’ The first conversation we have is what are your goals, your vision, your objective?" said Schaefer. "Look at where you can have a strategic impact with this, and then of course labor savings or optimizing the time of precious resources."

That strategy discussion should include business leaders, IT, process owners and applications owners within those processes.

Tom Taulli, author of The Robotic Process Automation Handbook: A Guide to Implementing RPA Systems, also encourages the involvement of multiple stakeholders.

"IT does not necessarily have to lead a project [but] the department should be part of the process from the start," said Taulli. "IT will be essential for compliance, security [and] access to online resources and so on. They will also help to build a foundation to scale the RPA system, which, by the way, can be extremely tough to pull off."

Read Who Should Own RPA?


Robotic Process Automation (RPA) Moves Beyond Finance: 4 Popular Use Cases

By Kevin Casey, The Enterpriser’s Project

How RPA can assist in use cases such as IT user provisioning, integrating core systems (i.e., “poor man’s integration”), HR onboarding, and addressing renewal process complexity.


So RPA hype is growing among finance executives for a reason: These aren’t small-change opportunities. On the flip side, though, this creates a potential misunderstanding that RPA is mainly for finance departments. RPA’s a fit for repetitive, high-volume, computer-based tasks? Cue up the folks in IT, HR, and other information-intensive departments: Yeah, we’ve got those, too.

Here’s a good way of thinking about RPA fits beyond finance: Look anywhere you have processes that span systems that aren’t integrated. If those processes involve moving data between those systems, that very likely involves manual, repetitive effort – and probably intensively boring effort, to boot – on the part of a person.

Read Robotic Process Automation (RPA) Moves Beyond Finance: 4 Popular Use Cases


RPA Investments Could Go Down the Drain without Organization

By Jia Jen Low, TechHQ

New research findings on how to ensure that an investment aimed at boosting efficiency doesn’t end up creating technical debt and sending money down the drain.


Though the research showed that the adoption of RPA is paying off in the long run, maintenance and control issues are burning a hole in the pockets of organizations running it. Even those that are making headway are having to overcome a lot of hurdles — close to half (45 percent) of organizations suffer from poor customer support and engagement due to bot breakage on a weekly basis, or more regularly.

These breakdowns cost business in terms of both staff resource — as workers most revert back to the manual operations the businesses sought to automate — and financially, as business operations lose efficiency.

Read RPA Investments Could Go Down the Drain without Organization


When Robotic Process Automation (RPA) Bots Break: 3 Things to Know

By David F. Carr, The Enterpriser’s Project

Keeping bots up and running has proven to be one of the top challenges to sustainable RPA programs. This article looks at why bots break, how to design bots that break less, and what to do when bots do, inevitably, break.


Teaching software bots to take over repetitive manual tasks is the magical promise of Robotic process automation (RPA). Only it’s not magic.

The problem with RPA is that bots break, and if you start putting them in charge of mission-critical tasks, they could break your business.

“The value is when these bots are up and running, and they keep running,” says Mika Vainio-Mattila, partner and co-founder at Digital Workforce, an RPA services firm. “These solutions require, by nature, more maintenance than traditional IT solutions.”

That is not to say the promise of RPA labor savings and efficiencies is a mirage, but it does mean planning for bot maintenance as well as bot development.

Read When Robotic Process Automation (RPA) Bots Break: 3 Things to Know


Hyperautomation: The Most Significant RPA Trend of 2020

By George Lawton, TechTarget

Explore how RPA is a "gateway drug" to a broader enterprise automation strategy that also includes AI, decision modeling, analytics and machine learning.


Hyperautomation moves automation up a level, adding more intelligence to automation and using a broader set of tools so that previously un-automatable tasks can be automated. Hyperautomation also assumes a broad automation layer across the organization, enabling automation to span organizational boundaries more easily, Perry said.

In addition to RPA, tools that will help enterprises deploy a broad automation strategy include: no-code/low-code application development, integration platform as a service (iPaaS), business process management systems (BPMS) and business rules engines. RPA is not the most efficient option among them for many types of automation, but it is often the easiest for business users to set up -- perhaps the biggest driver of its widespread adoption.

Read: Hyperautomation: The Most Significant RPA Trend of 2020


Robotic Process Automation (RPA) Careers: 4 Hot Job Titles

By David F. Carr, The Enterpriser’s Project

An overview of 4 different RPA career paths—RPA developer, RPA architect, RPA analyst, and RPA champion—and what it takes to break into each area.


RPA opportunities are not limited to technologists. Business analysts and others with the ability to analyze business processes and imagine how they can be automated can learn to produce bots themselves or write up the requirements for an RPA developer to work from. Business leaders whose organizations have not yet taken advantage of RPA have the opportunity to champion the possibilities and carve out a role for themselves leading that initiative (see cautions, below).

Read Robotic Process Automation (RPA) Careers: 4 Hot Job Titles


Getting Real with Today’s Most Hyped Software: An RPA Case Study

By R. Danes, SiliconANGLE

An honest look at what RPA and related technologies such as IT process automation—with examples from Chevron, ServiceNow, and others.


RPA bot: Bringer of a global revolution in work? Or a brittle software tool that agile companies are better off without? Betting it’s the former, providers have updated RPA with some of the same things threatening to outmode it — open source, cloud-native platforming and AI. Will they succeed? It depends largely on whether anyone thinks of anything cool their bots can do at work this year.

[Read Getting Real with Today’s Most Hyped Software: An RPA Case Study]


The GSA RPA Program Playbook

By the US Federal RPA Community of Practice

At 70 pages, this one’s going to require some time and effort—but it’s well worth it.  


This RPA Playbook gives federal agencies a detailed primer for initiating a new RPA program, as well as clear guidance for how to evolve existing RPA programs to achieve increased performance and maturity. Admittedly, this primer does not hold all of the answers for all of the challenges that arise on the RPA journey. To the extent answers can even be foreseen in advance, many of them will be agency-specific and not applicable across government. Instead, this RPA Playbook identifies the major decision points and steps along the journey and provides guidance based on best practices and lessons learned. At 70 pages, this one’s going to require some time and effort—but it’s well worth it.  

The key guidance and themes of the Playbook are:

* Just Get Started

* Ensure Effective Collaboration Between the RPA Program and the CIO

* Establish Aggressive Goals and Deliver

* Invest in Process Assessment and Improvement Capabilities

* Balance the Dual Priorities of Governance and Productivity

* Think Strategically about Technology Options

[Read The GSA RPA Program Playbook]


Robotic Process Automation: Why IT Ops Needs to Lead

By Ericka Chickowski, TechBeacon

Argues that even though RPA was originally pitched as a tool that democratizes automation for the line of business, IT operations  should play a key tole, engaging with the business to help get deployment right.


“Unfortunately, the divide between IT and the business often presents a bit of an RPA deployment paradox for organizations,” Davison explains.

“On the one hand, an IT organization that has achieved a level of maturity in these processes is well-positioned to succeed with robotic process automation,” he says. However, the RPA tools are often used by the business and not IT. And the business is most likely not trained in the software development lifecycle. “There is a need to train the business on the same process, which is called the ‘automation lifecycle,” Davison says.

[Read Robotic Process Automation: Why IT Ops Needs to Lead]


Low-Code Player Grabs RPA for Automation

By Jessica Davis, Information Week

Thoughts on what Appian moving from low-code into RPA (with its acquisition of Jidoka RPA) could mean for the market.


RPA and artificial intelligence are technologies that organizations often will want to put together to automate tedious repetitive tasks. Indeed, analyst firm Gartner named hyperautomation as one of the top 10 strategic technology trends for 2020, saying that the No. 1 use case for artificial intelligence is automation. Putting AI together with RPA can streamline operations and make organizations more efficient. It's another step toward achieving the digital transformation that all organizations are pursuing.

[Read Low-Code Player Grabs RPA for Automation]


RPA Bots Too Brittle? Try Model-Based Low-Code

By Jason Bloomberg, Intellyx

Can a "low-code" approach to RPA relieve all the headaches associated with brittle scripted bots?


The appeal is clear: automate an RPA ‘bot’ in order to mimic the user, simplifying the otherwise onerous task of hand-coding complex automations.
However, automation is not so simple. Most RPA solutions on the market suffer from a common weakness: brittleness. Any change to the application interface, business processes, or data formats breaks the bots, requiring expensive maintenance.
One approach to resolving this brittleness issue is to borrow an approach that spans the worlds of automated testing and low-code development: represent the behavior of bots as models that humans can easily create and maintain to automatically generate working automations without scripting.


Robotic Process Automation (RPA): 5 Lessons to Learn Early

By Kevin Casey, The Enterpriser's Project

Learn from others' mistakes regarding change management, security, and shadow IT so you don't have to make them yourself.


Without documentation, though, IT pros can’t be sure of how their ERP changes will impact the bots that interact with the system.
In fact, if those bots were spun up by business users without IT’s involvement – more on that in a moment – then the IT team responsible for the ERP system might not even be aware they exist in the first place.
“The impact of such an update, especially at the interface level, is oftentimes unpredictable because IT doesn’t know which robots are potentially affected,” Thaler says. “For example, the robots can stop working after the update is complete. If this happens, the company can find itself in a very stressful situation where repairs are required and/or critical processes can’t be executed in the desired way. Unfortunately, this is a very typical situation that many companies are sooner or later faced with.”


14 Rules for Robotic Process Automation (RPA) and Intelligent Automation (IA) Success

By Harrison Goode, LinkedIn

14 solid guidelines to consider as you get started, attempt to scale RPA, or face RPA buyer’s remorse and want a fresh start.


Ensure that your systems integrator is willing to put skin in the game. That way they share both the considerable risks and rewards of your transformation program. Don’t take all of the risks onto yourself, nor be greedy and unwilling to share any financial returns that you never had before. Vendors will complete gain share agreements if you ask. That way they, and you, have skin in your RPA game. Don’t short change your system integrator by not putting 100% into working with them side by side so that they and you succeed together. Set meaningful SLAs and measurable KPIs and hold yourself accountable for delivering real business returns. Count returns as a measure of your success not the number of robots in your business.

[Read 14 Rules for Robotic Process Automation (RPA) and Intelligent Automation (IA) Success]


The Next 7-Steps For RPA Software Robots

By Adrian Bridgwater, Forbes

Gartner predicts that within a year, 40% of enterprises will have “RPA buyer’s remorse. This article highlights 7 things to consider—from no-code to governance to lifecycle management—to lay a proper foundation now...so you avoid regrets later.


Step 1 - Bug free robots
The problem with ‘simple’ instant record-and-deploy automation is that there is no such thing as simple instant record-and-deploy automation for RPA success. These seemingly basic straightforward tools are typically fraught with issues that give the developer/programming team a big debugging task to clean up afterwards. This leads to a high change management overhead and an RPA project that fails to deliver. We need pre-built bug free robots if we’re going to welcome these new electronic critters into our lives.

[Read The Next 7-Steps For RPA Software Robots]


Invisible Robots In the Quiet of the Night: How AI and Automation Will Restructure the Workforce

By Craig Le Clair, Forrester

Get an extremely informed (and insightful) perspective on how the automation projects you’re working on impact the future of work—at both a professional and personal level.

Here’s Craig introducing the book:

[Read Invisible Robots In the Quiet of the Night]


The New RPA Manifesto: Follow HFS’ Ten Laws of Robotic Process Automation to Create a Thriving Industry

By Phil Fersht, Horses for Sources

A renewed vision for RPA—from the experts who were the first to write about RPA over 7 years ago.


Enterprises and the RPA ecosystem must make RPA part of something bigger—part of transformation, strategic initiatives, and broader goals for user experience. Stakeholders must align RPA to other digital enablers: complementary change agent brethren such as process mining, low-code BPM, elements of AI and smart analytics, APIs, and microservices.
The RPA we’ve known for seven years is dead. The fate of RPA for the next seven years is contingent on collaboratively supporting something bigger.

[Read The New RPA Manifesto]


RPA Metrics: How to Measure Success

By Kevin Casey, The Enterprisers Project

What metrics can you use to assess your progress, showcase accomplishments, and build a business case for RPA expansion?


Aaron Bultman, director of product at Nintex, recommends thinking about these six measurement categories, which range from quantifiable to more qualitative – or somewhere in between:

Productivity: “Bots work around the clock at a very high rate of speed,” Bultman says. Are processes running faster and/or more frequently than before?

Accuracy: “Bots [can] complete their tasks perfectly with zero errors.” Have you reduced errors or otherwise improved the accuracy of outcomes (such as in resolving help desk tickets)?

Consistency: “Bots perform the work identically without variation.” Have you brought greater consistency and predictability to a process?

Reliability: “Bots don’t take breaks, never get sick, and are always ready to work.” Have you reduced downtime and/or increased output?


It's All About People: Dispelling the Five Myths of Process Automation

By Jason Bloomberg, SiliconANGLE

Clear up the top 5 misconceptions stemming from the overlap among BPA, RPA , DPA, AI,  and low-code categories. 


Adding cognitive capabilities to RPA doesn’t solve these resilience issues, you simply end up with smarter technology that is still just as brittle as before.  The end result: a surprisingly narrow set of use cases where RPA – or even cognitive RPA – can provide substantial business value.

If we expand our focus beyond RPA, then, can AI help us with process automation generally?

Not so much. The state of the art: several products on the market now that use AI to offer “next best action” advice that essentially acts as an autocomplete for building workflows. As a human assembles a workflow, the AI suggests the next step.

We all like to make fun of autocomplete. Do we really want it telling us how to run our businesses?

[Read It's All About People: Dispelling the Five Myths of Process Automation]


Eaton’s RPA Center of Excellence Pays off at Scale

By Clint Boulton, CIO.com

A real-world example at what an RPA CoE looks like, how it can pay off, and what’s really needed to scale RPA.


Recognizing that emerging technologies require a deeper discovery step to arrive at a set of hypotheses or use cases, Krishnamurthi established a new innovation model that incorporated surveillance, filtering, assessment and adoption. Eaton conducts spurts of rapid experimentation ranging from 4 to 8 weeks to test the viability of technology, followed by a product pilot validation phase of 4 to 8 months, culminating in a business case and large-scale deployment within the enterprise.

This innovation model informs the RPA CoE, which focuses on people, process, technology and governance involving multiple IT, business and operations stakeholders.


RPA: How to Persuade Skeptics

By Kevin Casey, The Enterprisers Project

Four tips for building your RPA business case, plus a 3-step plan for gaining buy-in for your RPA vision.


One way to mitigate the fear factor: Focus less on the technology inspiring that fear and more on the actual day-to-day challenges it can solve. This is also likely a more persuasive approach with people who are simply skeptical.

“Starting with the problem – instead of the solution – prevents the need to convince your audience to believe what you’re speaking about. They will likely have encountered these issues throughout their workdays,” Huff says. “Beginning with the problem gets your audience saying ‘yes, you understand me.’ At this point, you can baby-step into how RPA has been used in similar situations to address exactly these issues, but focus on the outcomes and impact, not on RPA [itself].”


The Dark Side of Robotic Process Automation

By Andy Walter, CIO.com

A shared services leaders’ perspective on why the vast majority of RPA initiatives are failing to scale.


“Breaking bots” has fast emerged as the #1 enemy to RPA success. With easy access to UI-based automation, line of business (LOB) owners create RPA bots to automate processes without having to ask for (and wait for) IT/development assistance. After a little trial and error, they can get basic automation up and running. But, sooner or later, something changes. Interfaces are optimized. Data formats evolve. Or maybe connected/dependent systems are upgraded. Regardless of the cause, the outcome is the same: broken bots. Each time a bot breaks, the LOB requires technical assistance to diagnose and fix the cause…until the next time something breaks. Shared services organizations who are not working closely with IT are often hit the hardest! This is what’s become known as the RPA Death Spiral.

[Read The Dark Side of Robotic Process Automation]


Why RPA Projects Fail: 4 Factors

By Kevin Casey, The Enterprisers Project

How dynamic processes, brittle bots, geopolitical conflict, unrealistic expectations can undermine RPA results.


“The typical problem with RPA is the rigidity of the process and the dependency [and] sensitivity of the applications or systems that are being automated,” says Muddu Sudhakar, CEO at Aisera. “The reason behind that is the fact that RPA is typically leveraging screen-scraping technologies, with the obvious problems [that occur] when the UI screens change.” This tends to be a bigger issue than some people realize when they first deploy RPA.

[Read Why RPA Projects Fail: 4 Factors]


Hot Bots: The Payoffs and Pitfalls of Robotic Process Automation

By Paul Gillin, SiliconANGLE

Continue beyond the introductory “what is RPA” material for a good look at RPA pitfalls and automation advice from the front lines.


Don’t let perfection be the enemy of good enough. Although analysts advise that processes be overhaul before automating, the reality is that there isn’t always time. Some users said they’ll put up with inefficiency for the sake of gaining acceptance.

“If you have to log in to 10 systems and it’s extraordinarily difficult to scale down to three, then leave it at 10 and let the bots at it,” said Polaris’ Brajkovich.

Be aware of costs, however. Prices can range from $1,000 to $16,000 per bot, and some vendors require multiyear licenses, according to Gartner.


AI and RPA in Federal Government: The Time is Right

By Anil Cheriyan, The Enterprisers Project

There's significant opportunity to use AI and RPA to automate processes around antiquated systems without the expense associated with replacing the legacy platforms. 


The benefit of using an RPA approach is that you’re not completely replacing the legacy platform, you’re building a layer on top of it to enable automation across those legacy platforms. That’s what’s attractive about RPA: Rather than spending five plus years replacing a legacy platform, you can build process automation across legacy platforms using RPA techniques in just a few months. 
Another benefit is the cost avoidance of the actual expenses associated with manual fixes around outdated, broken, or legacy systems: There’s automation of controls, automation of reconciliation packages, and a number of other benefits like better accuracy, improving cycle time, and improving the speed of the actual operations.

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