Robotics and cognitive automation in HR

What drives organizations to automate HR processes?

​Progressive HR teams are already applying robotic process automation (RPA) to help tasks like data management and validation; running, formatting, and distributing reports; and replacing manual and spreadsheet-based tasks. Some are also exploring more advanced cognitive automation technologies, like machine learning and natural language processing, to enhance a range of HR processes from talent acquisition to benefits administration and beyond.

Organizations looking to get started typically ask, “Where should I start? or “Which vendor should I choose?” To help inform and steer these decisions, we offer the following four insights.

Insight one: This isn’t one decision about one technology or vendor

While robotics and cognitive automation are typically lumped together—R&CA—they are different technologies at different points of maturity. In turn, different vendors have capabilities in different aspects of R&CA, so your vendor evaluation will involve a different set of vendors based on what you want to accomplish in one of three categories:

• Robotic process automation (RPA) uses software “bots” installed on desktop computers or in the cloud that are configured to automate operational tasks—manual, rules-based, and repetitive activities for things like compensation data entry, talent acquisition license verification, and payroll data entry. Think of them as mimicking what a human can do by logging onto and entering data into existing business systems.
• Cognitive automation (CA) can operate in two primary ways:

1. Cognitive engagement leverages natural language processing (such as via chatbots or voice command) to interact with customers to answer questions, manage transactions, resolve inquiries, and triage requests to HR professionals when needed. So, think of an HR virtual assistant that handles things like HR policy and general inquiries, routine transactions like position changes, and leaves of absence and paid time off (PTO) management.
2. Cognitive insights use statistical data analysis and machine learning to mine and analyze data to uncover new relationships and insights to support better decision-making and continuous improvement. So, think of talent analytics and predictive analytics.

Insight two: That said, vendor capabilities across R&CA are similar and evolving quickly, so your decision will likely hinge on other factors

In our experience and research,¹ the market for R&CA solutions is evolving rapidly. There are “open source” or freely shared algorithms and often multiple solutions with similar capabilities in each of the following areas and, increasingly, combinations of these approaches to cognitive computing:

• RPA
• Data extraction/document capture
• Cognitive engagement
• Machine intelligence/machine learning
• Natural language processing
• Data management/data wrangling
• Data science

Furthermore, many of these algorithms and focused solutions are being embedded into new versions of existing enterprise systems. This means your decision to choose one technology over another today can hinge on variables other than the algorithm’s or solution’s ability to do its intended job. Given the unique need to “train” cognitive technologies and provide appropriate contextual and historical data for machine learning, vendor selection may hinge on particular applications or experience in the HR domain; integration capabilities into your existing sources of workforce data; and length of time and experience or partnerships for implementing their solutions for workforce-facing applications and supporting user adoption.

Insight three: Good news! Vendor and tool selection is not a make-or-break decision

Decisions about R&CA technology are not the same as decisions about other forms of technology, such as on-premises human capital management (HCM) suites or HCM in the cloud. Core platform decisions are typically much more involved and daunting because of their scope (touching multiple aspects of HR and supporting compliance), their scale (time, cost, operational impact), and their longevity (locking you onto a particular path for years to come).

In contrast, decisions about R&CA, particularly when you’re just starting to incorporate these capabilities, can be made relatively quickly and, if needed, rethought down the road. Because the capabilities of various solutions may be similar, you can make a decision and experiment, gain experience and familiarity with the technology and capabilities, and redirect toward a different vendor if you are unsatisfied or as your needs evolve. The main thing is not to get caught up in choosing a tool but instead focus on identifying where these technologies can be put to work in your organization and beginning to use them. You may even want to consider what solutions may already be in use in other parts of your organization outside HR, and partnering to apply them for your needs.

Insight four: Think big. Start small. Scale rapidly.

The evolution of cognitive technologies is ongoing and rapid. Right now this evolution is being driven largely by focused, fit-for-purpose, “pure play” vendor solutions targeted at specific use cases. But further disruption is afoot based on how quickly the larger providers of core cloud HCM solutions (e.g., Workday, SAP SuccessFactors, Oracle) and enabling technology providers (e.g., ServiceNow, Salesforce) embed these capabilities into their platforms. We have already seen movement in this direction, such as: SAP Leonard¹, Oracle’s agreement with Chatbox², and Infor’s Coleman AI platform³.

Our Human Capital Platform team is actively following the market for R&CA technologies in HR domains and will be publishing an analysis of early adopters and leading practices in the summer of 2018. It is also tracking the advancements of AI within the existing HR solution provider ecosystems, which promise to accelerate in the next 18 months. However, we don’t see this merging of cloud and R&CA capabilities as a reason to delay or overthink your R&CA decisions. The important thing is to make a decision and GO! If you spend too much time assessing your options, those options could change as new features and functionality are introduced or new solutions hit the market. As a case in point, one company we worked with initially requested a six-week project for RPA vendor selection. We proposed a much-simplified approach: Over a two-hour meeting, our solution architects, who are experienced with multiple vendor solutions, familiarized the company’s decision-makers with the pros, cons, and capabilities of various solutions and helped them make a decision on the spot.

Speed is essential

Digital is here to stay, and in a few years, “being digital” will likely no longer be a competitive advantage for companies, but necessary for survival. With the dropping costs and rising adoption of R&CA, companies could easily be faced with applying these technologies everywhere, regardless of industry, function, or even company size.

Get started right away so your organization can begin to become more digitally mature and position itself to reap the many potential benefits automation can bring. Once you begin to build capabilities in digital and automation, you pave the way for more advanced adoption. Our research shows that as organizations progress in their adoption of RPA, they tend to become more ambitious with cognitive technologies. More than a quarter (28 percent) of those we surveyed who are implementing and scaling RPA are also implementing cognitive automation, compared to only six percent of those that have not implemented RPA⁵. So build that momentum and keep it going!