The big picture: Companies implementing robotic process automation (RPA) often underestimate the importance of a proper support function for their program.
Why it matters: Without considering the importance of support and the associated costs, organizations put at risk anticipated efficiency gains, business partners’ confidence in the automation and overall investment in automation technology.
The bottom line: Prioritizing the support function at the start of the company’s automation journey will help jump-start the RPA program by setting realistic expectations for management and business subject matter experts and help minimize disruptions and increase efficiencies.
Go deeper: Organizations that are innovating to increase efficiency, productivity and growth have propelled RPA into one of the fastest-growing software segments among global enterprises. End user spending on RPA is expected to exceed $3.5 billion in 2023, an increase of 40% over 2021. In a recent Gartner study, 80% of finance leaders state they must accelerate the implementation of digital technologies, including RPA, and Gartner predicts that by 2024, organizations will lower operational costs by 30%.
Depending on the number of automations deployed, as well as the amount and complexity of tasks, the cost of implementing and supporting RPA can range significantly. If organizations do not build support into their automation strategy and business case, implementation can lead to unwelcome surprises and costs. As many as 50% of initial RPA projects fail to meet their objectives, often because of an inability to scale and teams not accounting for what it takes to run a successful program.
Many organizations see RPA as a set-it-and-forget-it program, believing that their automation tool will repeatedly produce the same results without fail. Then, months later, many organizations are shocked to discover that their once-stable RPA program has gone awry.
While an automation can provide some of the lowest level of support by monitoring operations and alerting organizations to errors, most RPA solutions do not provide the all-encompassing reporting needed to identify and resolve more complex irregularities.
These irregularities include upstream process events or latent infrastructure problems that can create pain points and negatively impact business operations. This could include a user-interface update where a bot interacts, a vendor providing data to an automation that has changed its communications procedures, staffing changes, a bug in the bot or a host of other reasons.
Plan Early
Whatever the cause, potential errors threaten to eat into operational cost savings and return on investment. Therefore, it is critical that organizations begin thinking about RPA support at the earliest stages of program design. Importantly, proven RPA support frameworks can help organizations not only troubleshoot problems more effectively but also reduce the number of process issues and, in turn, the support team’s workload.
Organizations should consider taking the following steps and metrics to track as they embark on their journey to build a best-in-class RPA program:
Identify opportunities to drive efficiency: There are several areas where an organization can limit the amount of support needed. This could be through consistent coding practices or enriched exception reporting to drive greater efficiency in addressing errors.
Service-level agreements (SLAs): SLAs are based on process criticality and the ability for work to continue without automation. If SLAs are tight, support must be automated or almost instant so that the business doesn’t exceed its promised SLA.
Monitoring and alerts: Machines and processes automatically restart on failure, while processes that require a business action before running send alerts when the action does not occur. Support teams and business owners receive detailed and unique alerts highlighting technical failures.
Reporting: Mobile and online dashboards updated hourly provide major stakeholders with platform and process health insights, as well as other performance indicators in real time. Weekly dashboard reports also provide value-added performance analysis and a recap of notable events.
Quality Over Quantity
Organizations need to recognize that support for RPA requires consistency. Ultimately, how much of the function is automated versus manual will help determine how much time organizations need to dedicate to maintenance: Every annual hour of RPA support that is automated will pay off exponentially each year.
The support function does not usually require the type of full-time effort that more traditional applications often need. But it does demand a human-in-the-loop approach in cases where more difficult problems related to coding or other RPA complexities arise. Weaknesses in a bot’s construction or documentation during the development phase can increase the challenges facing support.
Establishing business ownership for a proper support function depends on the centralized or decentralized nature of the company. As a rule of thumb, the closer it is to the end user, the better. More importantly, support should be distinct and separate from the organization’s development arm to ensure that each team can focus on its area of expertise, or progress in both fields may suffer.
Final thought: Ideally, RPA support is an element that needs to be accounted for during program design, not postlaunch. By utilizing proven RPA support frameworks, companies will help ensure that their automation programs run efficiently and fulfill ROI expectations.
Additional contributor:
Bob Kiser, Senior Manager, Digital Engagement & Automation
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