Robotic Process Automation (RPA) is a digital technology that automates tasks in business processes.  RPA fits best in high volume, rule-based, and repetitive tasks. Often these tasks come in the form of data entry and migration tasks. RPA is especially useful when the interactions are with older, legacy applications.

Most RPA works at the user interface (UI) level, although leading systems often can be extended to interact at an API level as well. A software “robot” can replay a defined series of UI events at a greater speed, and accuracy than humans. The software interacts by reproducing the mouse clicks/moves, keyboard entry, copy/cut/page actions and other user interface events just as a human would. Software automation characteristics include[i]

• Mimic (replay) keystrokes allowing them to be concatenated together (similar to a macro) to operate any application.
• Interact with multiple systems in a session (systems may include packaged software applications, spreadsheets or other productivity tools, websites).
• Seamlessly integrates with other applications.
• Move data (copy/cut/past) data between systems.
• Perform rules-based tasks based on business rules (examples may include: calculations, queries, or other specific actions).
• Quick to implement, and powerful to scale.

RPA is a more flexible, faster and cheaper solution than traditional process automation solutions. A software “robot” replays a defined series of UI events at a greater speed and accuracy than humans.  Configuring the robot resembles the modeling of processes, instead of detailed programming a piece of software.

A common question is, “what can you automate”. One of the first steps to automation is figuring out where to start. Generally, if you can write the instructions for a process (i.e., rules-based), the process, or some portion, can be automated. If you identify where you’re spending the most person-hours, that’s often where you can start to identify the processes that you should consider for automation.

Note that the return on investment (ROI) for RPA is more than the efficiency of headcount. Data and process quality both see significant improvements and are two of the greatest paybacks a company receives from RPA. ROI is often defined by specific goals such as higher efficiency through data quality (i.e., reducing the cost of errors and rework), processing higher volumes of data (faster cycle time or scaling with growth), and reducing labor cost.

Identifying Opportunities for RPA

Votum’s methodology looks at several key areas to define an RPA strategy and helps identify an organization’s maturity level as they scale to do more automation, and scale with business growth.  We generally consider

Business Opportunity	Discovery activity to identify target opportunities based on business goals or strategy. Define initial evaluation criteria for automation.  This Discovery includes what determines an opportunity, return on investment, and feasibility. Discovery is an ongoing activity that forms the basis of governance. For example: often targeted are internal goals, such as reducing rework; improving the number of invoices paid on time; responding to customer emails, updating customer information across systems; or updates to the master vendor list.
Organization/ People	Discovery activity to identify initial organizational opportunities, awareness of RPA, skills availability, and governance status or readiness. For example: Identifying senior sponsors that are seeking to drive transformation through automation. Preparing or involving people where automation to understand how it impacts them, educating the organization on the value of automation.
Process	Discovery activity to identify initial candidate processes for automation. This Discovery is top-down, bottom-up, or both approaches in several target departments.  Discovery also includes a maintenance strategy as systems and processes change over time. A top-down approach considers major processes and large labor pools. Additionally, identifying processes where rework or quality is a factor is another indicator. A bottom-up approach leverages tools such as process mining or task mining. Collaborative i.e., crowdsourcing, is also an opportunity and requires some level of governance structure in place.
Technology	Discovery activity of the current technology landscape, existing tools, and gaps.  Implementation policies, in terms of standards, security controls, and deployment, are reviewed. This Discovery involves evaluating several areas: technologies in use, ability for automation testing, deployment, versioning, deploying updates, monitoring, auditing, and security.

Performing these activities are essential to successful projects.  Each one of these addresses success factors and mitigate known issues with RPA implementations. Among these, successful companies have a strong vision of automation across the enterprise, a cross-functional strategy, and a plan for maximizing the ROI.

Once organizations move beyond simple examples, there is a critical need for multidisciplinary governance and coordination across business units, IT, security, sourcing, and assurance functions. Without this comprehensive approach, many organizations experience buyer’s remorse due to poor ROI, misaligned resources, siloed usage, and inability to scale. This coming year, we expect to see the beginning of a renaissance as the offerings themselves morph due to high levels of R&D spending and customer feedback.

Key Opportunity Characteristics

One of the more apparent opportunities targets processes based on the number of people performing a specific process. Some of the best opportunities may require introspection into time allocations. For example, some companies leverage RPA for expediting financial month-end close. While there may not be many people involved, it is time-consuming, subject to human error and can take lots of personnel time (i.e., 2 to 4 weeks).  Below are some of the critical characteristics for locating opportunities.

Identifying Opportunities

Note: These can apply to ANY process task in the enterprise where a human interacts with one or more software systems.

• Tasks that require a relatively large number of people performing the same task repeatedly.
• Processes where data entry has an unacceptable human error, creating rework, and lengthening the time to complete.
• Repetitive, low-value people tasks such as data entry, rather solving or reconciling legitimate business issues.
• Rules-based tasks with a higher latency than is necessary, i.e. faster cycle time, often responding to customers to increase satisfaction.

The RPA industry has created new tools to facilitate opportunities identification and ROI analysis. These tools, such as UiPath’s Task Mining and Automation Anywhere’s Discovery Bot, analyze processes to recommend potential projects. In addition, they create documentation and a baseline automation script. While this “discovery” process isn’t fully automated, it does reduce the amount of time to find and develop viable automation solutions. This Discovery can reduce the time typically filled by consultants conducting interviews and process maps. 

Another set of tools, labeled as “process mining”, aid in discovery and process optimization.  Process mining software, such as UiPath Process Mining (previously ProcessGold) or Celonis Process Mining, typically ingest logs of applications, such as ERP or CRM, to map out processes. The process mining correlates steps or tasks in a process showing what users are doing, and where people are bypassing the normal process flow. This process mining can also help identify where people are spending their time, facilitating opportunity identification for RPA.  Also, they can help with process auditing and compliance.

Furthermore, as your RPA journey matures, if it offers more significant opportunity for automation by leveraging artificial intelligence for the decision process, further increasing the level of automation, shorten cycle time, and reducing human-in-the-loop errors or latency.

A recent Gartner report, they noted

“Organizations have paid for an expensive patchwork quilt of applications and systems. Business executives are demanding a path to digital operational excellence. The net result is a tremendous pent-up demand to democratize process automation and data integration. Robotic process automation (RPA) fulfills a need but requires strategy, guardrails and governance.”ⁱ

“Plan your hyperautomation journey by focusing on a wider spectrum of business functions and knowledge work. Strategize and architect across the toolbox of options, including RPA, iBPMS, iPaaS and decision management tools.”ⁱ

Where are you on your Intelligent Automation journey?

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[i] “Predicts 2020: RPA Renaissance Driven by Morphing Offerings and Zeal for Operational Excellence”, Gartner, 10 December 2019