What RPA Really Is

It offers software robots, “bots” for short, that simulate the activity of users operating software manually. They virtually perform keypresses and mouse clicks. They read text from web pages and/or desktop application windows. You can script their behavior, including some conditional branching, and treat that script as a reusable component (a web service, for example).

It’s not new. We did this with mainframes two decades ago. We’ve been doing a basic version of it with recorded macros in applications like Word and Excel.

For specific kinds of activities – the more repetitive, the better  – RPA works great. Do your users have to run two applications side by side and manually re-enter information from one into the other? Get a bot to do that instead.

Why One Should Embrace RPA

RPA is usually talked about in terms of automating repetitive tasks, but this is usually with an eye toward that bot being exposed to other applications, so they can invoke that bot as a remote component, much like a web service or a remote procedure call.

But shouldn’t we be calling those applications’ APIs directly instead? Ideally, yes. But sometimes, what’s ideal isn’t possible.

APIs Aren’t Always Available

Sometimes, an application’s API doesn’t’ exist. Sometimes, the vendor charges extra for it. Sometimes, the API is terrible and arcane. In situations like this, an RPA bot can interact with the application’s user interface but still appear to other applications as if it were an API.

APIs Aren’t Always Allowed

Not every application’s curator is on board with having the system they curate used by someone else. They may block access to APIs. As long as a would-be integrator has access to that application’s UI, they can wrap it in a bot and communicate with the bot instead.

API Approaches Can Take Too Much Time

Given that a lot of bots are initially built by recording interactive sessions, it can take a lot less time to build a bot than it would take to get API credentials, learn how to use it properly, and actually configure the remote requests. Even when API-based access is the eventual goal, RPA bots might be a good fit for an initial prototype.

Why One Should Avoid RPA

RPA sounds attractive, but there are a number of caveats that cannot be ignored.

It’s Resource-Intensive

If you’re simulating user activity, you need to run the same environment a user would run. That means browser sessions, and perhaps even desktop sessions. If you want to do this at scale, the logistical, licensing, and hardware costs can add up.

It’s Fragile

The problem with a bot impersonating a user is that bots – without a lot of foresight – aren’t prepared for unexpected circumstances. If an application displays unexpected error messages if an operating system announced an update is available, if an application crashes, if a page is unavailable, etc., bots won’t always know what to do. If an application’s UI changes without the bot builder being aware of it, bots won’t always know what to do.

It Can Raise Security Issues

If I can write a bot that accesses a service using my credentials and make it available to others, I may be effectively granting them the same access to that service that I have. Not everyone will be comfortable with that. Policies can mitigate this – if bot builders heed them.

The Bigger Issue is One of Scope

RPA is, regrettable, poorly named. It’s not really robotic process automation. It’s robotic task automation. There’s nothing in RPA that addresses actual end-to-end business processes, case logic, overall strategic goals and progress against them, and countless other things that are normally the purview of Business Process Management/Digital Process Automation (BPM/DPA).

For example, solving an IT helpdesk ticket can entail reviewing a ticket, assigning it to a caseworker, searching knowledge archives, conferring with the subject matter experts, verifying with the user whether the ticket can be closed, etc. RPA can help with some of this, but the larger process requires a lot of judgment (assessment and decision making); e.g., the manager decides to whom a ticket should be assigned, IT support decides to loop the manager back in with questions about a particularly difficult ticket, the manager or IT Support decides to cancel or reject a ticket, etc.

Without BPM/DPA, RPA merely speeds up the work and maybe reduces errors in places. But without BPM/DPA, there’s little chance of transforming it.

Divide and Conquer

The answer here isn’t difficult. BPM/DPA processes can make use of any number of RPA bots to accomplish individual tasks as processes progress from start to finish. They already make use of API invocations, so why not bots, too?

Use BPM/DPA to determine what should be done, what its status is, which resources are in play, whether results are addressing goals, and what should happen next depending on what already happened. Use RPA – and APIs, and sometimes manual human task assignments – to execute the tasks that the process needs to have completed.

As long as an application architect is cognizant of the relative – and complementary – roles of RPA and BPM/DPA, RPA becomes a valuable tool to add to an organization’s repertoire.

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Robotic process automation, or RPA, is an increasingly popular technology that helps organizations operate more efficiently. RPA tools such as UiPath’s platform enable companies to create software bots that can perform repetitive, historically manual chores such as copying files between databases. RPA bots enable a company’s employees to focus on more important tasks and in the process reduce human error.

New in the latest release of UiPath’s platform is a tool dubbed UiPath Integration Service. It allows developers to create RPA bots that can interact with a program not only through its user interface but also via the application programming interface.

Usually, RPA bots perform business tasks using the relevant application’s interface. This method is often the most intuitive approach, but it has certain disadvantages. The most significant is that if an application’s interface changes as a result of a software update, the RPA bots that use it must often be modified as well, which can require a great deal of work.

The alternative is to have bots carry out tasks via an application’s API instead of the interface. The API doesn’t necessarily change every time the interface does, which means that RPA bots have to be modified less frequently.

With the newly introduced UiPath Integration Service, developers can create bots that use both an application’s interface and APIs to carry out business tasks. One scenario in which a company may use the tool is when the task that it’s looking to automate involves a mix of modern applications that have APIs and legacy systems that don’t.

Today’s release also introduces a number of other enhancements aimed at developers. Software teams can now use UiPath’s platform to create RPA automation workflows that run on Linux. If the task being automated is so complicated that it requires a specialized machine learning from an external source, developers can now import neural networks using a tool dubbed the ML Ops Solution. The tool makes it possible to import neural networks developed by UiPath partners or a company’s in-house data science teams.

“By bringing adjacent new capabilities together into a single place and providing seamless integration between them, we can blast through existing RPA boundaries, dramatically expanding the playing field for developers, and multiplying and accelerating automation’s overall impact across the enterprise,” said UiPath Chief Product Officer Param Kahlon.

With the new platform release, UiPath is aiming to simplify not only the process of building automation workflows but also the task of running them in production. To that end, the company has added a capability called Robot Auto-healing that can detect and remediate certain technical issues affecting RPA bots without any human input. For cybersecurity teams, an integration with CrowdStrike Inc.’s endpoint protection platform will make it possible to analyze data related to RPA workflows as part of breach investigations.

As companies broaden their adoption of RPA software, business users without coding know-how often join automation projects. Some business users become “citizen developers” and begin actively contributing to bot development. For such users, UiPath is introducing a feature called Object Repository as part of the new platform release. It provides access to software building blocks that can be assembled together into automation workflows with relative ease.

End-users of automation workflows can access RPA bots created by their companies via a desktop application called UiPath Assistant. To improve the user experience, UiPath is updating the application with an integration that will make it easier to access automations from the UiPath Marketplace, its app store for pre-packaged RPA components.

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Robotic process automation (RPA) is a software technology that enables robots to pull data from a variety of sources and follow defined steps to complete tasks. The ultimate goal is to streamline repetitive processes.

“It’s like a time machine that replaces tedious work to create more time for productive work,” said Jim Maholic, Technology Writer and IT Strategist at a recent CanadianCIO Virtual Roundtable. “Automation improves the experience for both employees and customers.”

At first, the technology was mostly used to automate financial processes, said Tom Torlone, Global Vice President of Professional Services with UiPath. “Then, it expanded to IT, HR and manufacturing. Now, it’s being used in call centres and health care,” he said.

“There is no limit to what it can do in as long as it’s applied to repeatable processes,” added one roundtable participant who recently implemented RPA in one use case.

Five reasons to deploy robotic process automation

Maholic said there are five value drivers for implementing RPA:

1. Increase capacity by reducing tedious work for employees.
2. Favourable financial impact. Companies report a significant improvement to their business metrics after implementing RPA.
3. Risk mitigation and risk avoidance. For example, financial institutions use it in their processes to detect fraud.
4. Strengthen audit capability and regulatory compliance
5. Repeatable, dependable error-free accuracy. “The robots never take time off,” said Maholic.

One IT leader described how RPA was deployed in his organization to convert and download video files, which had increased significantly since the pandemic began. The organization’s staff was working overtime to keep up with the volume. Now, the robots complete the task in less than half the time and the implementation has already paid for itself, he said.

Start with an automation operating model

A common starting point for many organizations is to apply automation to replicate existing processes, said Maholic. “Over the course of the journey, companies start to see the benefits and make tweaks or changes to the process down the road.”

As well, organizations can get started before fully standardizing their processes, Torlone said. “Companies can automate variations in their processes and it’s still valuable if it replaces human time,” he said.

As the deployment begins to scale, it’s important to have strong governance procedures, said Torlone. These should include standard criteria to evaluate what processes to automate. If the organization decides to proceed, there should also be defined procedures on how to build it and put it in production. Companies that define the model have greater throughput because all of the questions have been answered in advance,” he said. As automation increases, it’s also vital to ensure that control points are preserved.

Deployments based on the model can be completed in as little as two to three days in a simple case whereas a large deployment might take six to eight weeks, Torlone said.

“We advocate a crawl, walk, run approach,” said Torlone. “Organizations with an automation operating model can become very efficient.”

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The demand for robotic process automation (RPA) is extremely high and for many finance teams already far beyond the stage of pioneers, early adopters, and first movers. According to a Deloitte 2020 survey, demand for RPA is growing: the number of organizations that have implemented more than 50 automations is at double figures. Moreover, just 13% of survey respondents revealed they are now operating automation at scale, while 78% have implemented RPA automations — a clear signal RPA has become the norm for business.

As seen through survey findings, companies that are not focused on investment in automation are in the minority. If you’re a laggard, you now have the opportunity to catch up; if you’re already well on your way, you have an opportunity to deepen capabilities. Consider the following: two‑thirds of survey respondents relied on automation to deal with the impact of COVID‑19, and one‑third accelerated their investment in cloud‑hosted automation as part of their pandemic response. Knowing that RPA is a working technology that many companies are embracing, it’s time to confidently act.

Here’s a breakdown of automation hierarchies and what business leaders should know about them.

Task-oriented RPA

To start, RPA is a software-based form of business process automation that mimics tasks. Task-oriented RPA is a foundational element of building out intelligent automation capabilities.

To enhance automation’s effectiveness, a human employee should have at least one digital worker to support them. This synergy can improve the overall value delivered from the foundational RPA stage up through the most advanced applications. The coexistence of humans, tasks, intelligence, and advanced automation is what the future of finance looks like.

Automation leaders should consider that digital transformation is more than technology adoption; it’s also about engaging, educating, and bringing the workforce through the entire process. Have your colleagues experienced first-hand the impact of automation on their roles?

The adoption of intelligent automation is human‑centered. Involving the workforce from the beginning in identifying, designing, or even developing automations helps onboard new, digital co‑workers.

Intelligent Automation

Organizations that have a well-implemented, task-oriented RPA base can build out their intelligent automation capabilities. To deliver end‑to‑end intelligent automation, organizations need to break down functional and process silos. They  also need to augment business processes through an effective combination of complementary tools and technologies. Our survey respondents reported that 49% of their automations require eliminating, simplifying, or standardizing processes.

To deliver the best outcome for an intelligent automation strategy, it is essential to understand the potential value that can be achieved through a range of process optimization techniques. More than one-half (58%) of organizations we surveyed said that they are using lean automation to change processes, a methodology that increases process efficiency by eliminating non‑value‑adding activities.

When combined with task‑based automation, this methodology offers quick benefits, such as redeploying people away from low‑value activities or creating additional capacity in end-to-end processes.

Cognitive Automation

Finally, organizations ahead of the curve looking to support an advanced finance function can focus on combining human work with artificial intelligence to form “super teams.” These incorporate the use of additional technologies such as cloud automation, artificial intelligence, machine learning, and purpose-built tools, which in turn create an ecosystem that takes automation to the next level.

Super jobs combine the elements of work and responsibilities of multiple traditional jobs, using advanced technology to (1) augment and broaden the scope of value being delivered and (2) engage a more complex set of domains, and technical and human skills.

Over the next three years, survey respondents expected that they will have to retrain 34% of their workforce because their roles have sufficiently changed from automation. The retraining will be worth it: Intelligent and cognitive automation will create competitive advantages for organizations looking to adapt digitally to the post-COVID world.

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