Enabling Technology

The NelsonHall Report: Seeking Digital Transformation

Organizations are looking to leverage intelligent technologies in order to increase efficiency in HR delivery models.

By Pete Tiliakos

With digitalization at the forefront for most business leaders today, the demand for advancing technology capability continues to intensify. Many organizations are diligently executing on digital strategies with the goal of transforming and advancing their operations, both client facing and back office, toward a more future-proof model. In HR, the need for transformation is long overdue and more critical than ever.

As a result, organizations of all sizes are seeking digital HR transformation to enable a high-performance delivery model. It needs to support competing for, attracting, developing, and retaining top talent by providing next generation HR capabilities. Now more than ever, HR is playing a critical role in enabling businesses to remain competitive in what is arguably the most challenging labor market in decades.

However, there is still a great deal of opportunity in process optimization within HR and payroll delivery models where historically, teams have operated in a highly manual, labor-intensive, and often imperfect environment. So it’s no surprise that intelligent technologies like robotic process automation (RPA), artificial intelligence (AI), and machine learning (ML) are steadily increasing in demand as organizations seek to leverage the advancing capabilities to drive HR delivery model efficiency and effectiveness, support scalability, and lower costs.

While HR leaders’ curiosity and demand for advancing technology is steadily increasing across all industries, most do not know what is possible or where to begin. Investments in RPA initiatives for HR are primarily being taken on by enterprise-sized organizations since automation programs can handle high volumes of employees and transactions, high HR operating costs, and deep pools of HR data. Therefore, unless an organization has a sizable population and the means to support internal RPA programs, achieving a case for investing in automation for HR’s unique needs is more challenging.

HR Service Partners’ Role in RPA and AI Progression

The breadth of current investments and the advancement of automation capabilities in HR is primarily coming from HR service partners. Those in the space are fundamentally pioneering the advancement of RPA and AI, and directly impacting the digitalization of HR, enabling organizations of all sizes to access turnkey HR automation programs without the need for major investments.

HR TechNelsonHall’s research finds that RPA and AI capability in HR is in the early stages of maturity but progressing quickly as early adopters work to solve the most common and impactful use cases first. While cost reduction is a key consideration, it is not currently the primary driver. Organizations are focused on delivering enhanced HR outcomes and user experiences across the HR delivery model.

HR service partners have only begun to impact their full suite of HR processes through automation, with most automating less than 10 percent of processes to date. At this stage, talent management leads the way for RPA and AI advancement, with recruiting currently leading all other HR towers in the maturity of RPA and AI adoption due to high demand for enhanced candidate experiences to attract top talent. The highly complex nature of payroll and benefits administration has led to slower RPA adoption. However, HR service partners are rapidly developing automation that reduces the risks of these critical processes, with multiple major players in the payroll space actively investing in and progressing toward a fully autonomous payroll processing solution.

Organizational adoption of RPA and AI vary widely, with the highest levels achieved by more mature HR service lines, like recruiting, compared to less mature HR service lines like payroll. HR service partners expect to increase the use of automation by client organizations in the coming year. Nearly 40 percent that have yet to reach their entire client base expect to achieve this over the next 12 to 18 months.

The Outlook for RPA and AI in HR

Over the coming 12 to 18 months, HR service partners expect to expand their RPA and AI capabilities in the following ways:

  • adding new bots and expanding the capability of existing bots to manage and handle a wider scope of HR processes;
  • introducing ML, AI, and natural language processing (NLP) to enhance cognitive capabilities;
  • leveraging NLP to support “conversational HR” capability through virtual assistants;
  • infusing more predictive and prescriptive analytic capabilities to improve candidate experience through personalized, prescriptive guidance and insights;
  • developing additional capabilities such as optical cognitive recognition for unstructured document processing and facial recognition capabilities (for use in time and attendance clocking, interviewing, security, etc.); and
  • exploring the use of blockchain capabilities in HR processes.

NelsonHall expects that organizational adoption of RPA and AI in HRO will escalate steadily, with solutions addressing the full spectrum of HR processes. Currently, nearly 80 percent of HR service partners indicate an increase in demand for their primary HR services as a result of organizations seeking to incorporate more intelligent technology capabilities in their HR delivery models. Service partners in the recruitment process outsourcing (RPO) space are seeing as much as five times the number RFPs and cite a significant increase in wins for RPO services as a result.

Stand-alone “HR automation as a service” offerings will likely become common in the marketplace, offering clients the ability to license the capability and operate independently or a mix of point solutions and offerings. In fact, in October, the market saw the introduction of the first HR specific RPA-as-a-Service offering targeted to the middle market buyer.


Pete Tiliakos is principal analyst of HRO for NelsonHall.

Tags: Enabling Technology

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