More CIOs are turning to an emerging technology practice called robotic process automation (RPA) to streamline enterprise operations and reduce costs. With RPA, businesses can automate mundane rules-based business processes, enabling business users to devote more time to higher-value tasks. Others see RPA fitting into a larger context, as they take a more deliberate path to adoption, seeking to understand RPA's potential to work alongside machine learning (ML) and artificial intelligence (AI) tools.
Here CIO.com takes a look at what robotic process automation really is, and how CIOs can make the most of RPA in alignment with business goals.
What is robotic process automation?
RPA is an application of technology aimed at automating business processes. Using RPA tools, a company can configure software, or a “robot,” to capture and interpret applications for processing a transaction, manipulating data, triggering responses and communicating with other digital systems, according to the Institute for Robotic Process Automation and Artificial Intelligence.
Inclusion of the term "automation" may cause some to confuse RPA with ML and AI. RPA can include ML or AI, but it is governed by set business logic and structured inputs, and its rules don't deviate, whereas ML and AI technologies can be trained to make judgments about unstructured inputs.
RPA scenarios span a wide spectrum, ranging from something as simple as generating an automatic response to an email to deploying thousands of bots, each programmed to complete a specific task, to automate jobs in an ERP system. Insurers use RPA to pipe policy management data into a claims processing application, rather than having humans type them in from their computers.
Enterprises are looking to RPA to automate legacy business processes because their talent, technology and time resources are constrained, Dave Kuder, a principal with Deloitte Consulting LLP, tells CIO.com. With RPA, CIOs can complete in days or weeks manual processes that previously took months or years, and at a fraction of the cost. "You can imagine why this is gaining a ton of traction right now," Kuder says.
The RPA market is small but growing. Spending on RPA software will reach $1 billion by 2020, Gartner says, growing at a compound annual growth rate of 41 percent from 2015 through 2020. By that time, 40 percent of large enterprises will have adopted an RPA software tool, up from less than 10 percent today. For many organizations, RPA may prove to be a stop-gap on their way to AI.
Either way, the consensus is that RPA remains a vital tool worth exploring. CIO.com asked some technologists and consultants how IT leaders can tackle RPA.
9 tips for effective robotic process automation
1. Set and manage expectations
Quick wins are possible with RPA, but propelling RPA to run at scale is a different animal. Deloitte’s Kuder says many RPA hiccups stem from poor expectations management from the outset. Bold claims about RPA from vendors and implementation consultants haven't helped. That's why it's crucial for CIOs to go in with a cautiously optimistic mindset. "If you go in with open eyes you'll be a lot happier with the result," Kuder says.
2. Consider business impact
RPA is often propped up as a mechanism to bolster return on investment or reduce costs. But Kris Fitzgerald, CTO of NTT Data Services, says more CIOs should use it to improve customer experience. For example, enterprises such as airlines employ thousands of customer service agents, yet customers are still waiting in the queue to have their call fielded. A chatbot, could help alleviate some of that wait. “You put that virtual agent in there and there is no downtime, no out sick and no bad attitude,” Fitzgerald says. “The client experience is the flag to hit.”
3. Involve IT early and often
Thanks to the emergence of cloud computing in the digital era, "citizen developers" without technical expertise are implementing RPA right from their business units, Kuder says. Often, the CIO tends to step in and block them. Kuder says that business heads must involve IT from the outset to ensure they get the resources they require.
4. Poor design, change management can wreak havoc
Many implementations fail because design and change are poorly managed, says Sanjay Srivastava, chief digital officer of Genpact. In the rush to get something deployed, some companies will overlook communication exchanges, or "handshakes" between the various bots, which can break a business process. "Before you implement, you must think about the operating model design," Srivastava says. "You need to map out how you expect the various bots to work together." Alternatively, some CIOs will neglect to negotiate the changes new operations will have on an organization's business processes. CIOs must plan for this well in advance to avoid business disruption.
5. Don't fall down the data rabbit hole
A bank deploying thousands of bots to automate manual data entry or to monitor software operations generates a ton of data. This can lure CIOs and their business peers into an unfortunate scenario where they are looking to leverage the data. Srivastava says it's not uncommon for companies to run ML on the data their bots generate, then throw a chatbot on the front to enable users to more easily query the data. Suddenly, the RPA project has become an ML project that hasn't been properly scoped as an ML project. "The puck keeps moving," and CIOs struggle to catch up to it, Srivastava says. He recommends CIOs consider RPA as a long-term arc, rather than as piecemeal projects that evolve into something unwieldy.
6. Project governance is paramount
Another problem that pops up in RPA is the failure to plan for certain roadblocks, Srivastava says. An employee at a Genpact client changed the company’s password policy but no one programmed the bots to adjust, resulting in lost data. CIOs must constantly check for chokepoints where their RPA solution can bog down, or at least, install a monitoring and alert system to watch for hiccups impacting performance. "You can't just set them free and let them run around; you need command and control," Srivastava says.
7. Control maintains compliance
There are lot of governance challenges related to instantiating a single bot in environment let alone thousands. One Deloitte client spent several meetings trying to determine whether their bot was male or female, a valid gender question but one that must take into account human resources, ethics and other areas of compliance for the business, Kuder says.
8. Don’t forget the impact on people
Wooed by shiny new solutions, some organizations are so focused on implementation that they neglect to loop in HR, which can create some nightmare scenarios for employees who find their daily processes and workflows disrupted. “We forget that it’s people first,” Fitzgerald says.
9. Put RPA into your whole development lifecycle
CIOs must automate the entire development lifecycle or they may kill their bots during a big launch. “It sounds easy to remember but people don’t make it a part of their process.”
Ultimately, there is no magic bullet for implementing RPA, but Srivastava says that it requires an intelligent automation ethos that must be part of the long-term journey for enterprises. "Automation needs to get to an answer — all of the ifs, thens and whats — to complete business processes faster, with better quality and at scale," Srivastava says.