How a Robotic Operations Center’s rigorous standards help strengthen and stabilize automations

With nearly any automation project, an organization is expected to face common challenges such as errors and exceptions. The role of a Robotic Operations Center (ROC) is to strengthen and stabilize an organization’s automations so that they can overcome those challenges with less downtime and mitigated business impact. One of the main ways a ROC does this is through the establishment of a rigorous set of standards for automation documentation, testing, and logging.

The market for RPA services is seeing rapid growth, with Forrester estimating it to reach $12 billion in 2023. Yet many firms still lack standardized criteria for automation design and documentation. This not only makes it more difficult to isolate and address automation issues; it makes it more challenging for an organization to scale their automation deployments and see long term value. By adhering to an exceptional set of standards, the ROC bolsters an RPA program to be more robust and scalable.

We’ve outlined a few of our ROC standards and best practices that help clients see the full value of their automations.

Detailed Logs for Faster Issue Identification – Logs allow us to keep track of critical pieces of information to help the business understand what’s happening with their bots and the systems they interact with. Log messages are vital to an automation practice as they show what the bot does at each point in the process, the data being processed, and if the bot followed all required process steps correctly before encountering any errors. In order to be most effective, they must be descriptive and easy to read – logs should contain a detailed problem description and include the name of the step or module that failed.

Detailed Logs for Faster Issue Identification

Detailed and specific log messages allow the ROC analysts to identify where an error occurred within a process and understand the cause of the error. ROC teams will interactively follow these logs to gather and analyze metrics on bot run times, daily transactions, exceptions, and how frequently errors are thrown. By reviewing this information whenever a process fails to perform as expected, the ROC team can quickly identify and resolve the issue to prevent downtime.

Exceptional Documentation Practices – A ROC is responsible for creating accurate and up-to-date documentation. In addition to the Process Design Document (PDD), Solution Design Document (SDD) that our automation teams provide the business when they begin their RPA project, the ROC provides further documentation in the form of runbooks and a detailed operational handbook. These map out any errors and exceptions, bot runtimes, and points of contact if the business encounters an issue requiring escalation. Having centralized and up-to-date documentation ensures knowledge continuity and process clarity if new developers join the project or if the process undergoes any changes, corrections, or application updates.

Rigorous Testing Before Automations Go into Production – ROC developers perform a series of tests before automations are pushed into production to ensure the client’s processes are as resilient and effective as possible. This rigorous UAT testing includes testing for positive and negative cases for every exception. While positive test cases are useful in validating that the process results are as the business would expect in production, negative test cases help our analysts understand which inputs may cause a bot to fail. By negative testing, the ROC can proactively detect these situations to prevent bots from crashing.

Robotic Enterprise Framework for Enhanced Reporting and Issue Resolution – Robotic Enterprise Framework (REFramework) is a UiPath project template used by the ROC teams to build robust, large-scale solutions. Its well-written structure works best for queue-based transaction processing, ideal for functions like invoice processing and customer onboarding. REFramework provides the ability to read and store the config data, get an individual transaction and process it, and retry failed transactions when required; it also logs the status of all processed, failed, and successful transactions. This makes lengthy processes more reliable, efficient, and easier to maintain in the future. It also gives ROC teams the ability to produce transaction-based data that can be analyzed, interpreted, and visualized to discover valuable insights about the business process.

Case Study: ROC Implements REFramework to Improve Transactions Processing

One client, a Global Insurance Company, was facing challenges with its Premium Funds Allocation process. The process involves allocating the necessary cash for policies in the company’s ERP system and extracting the generated Journal and Allocation numbers for auditing purposes. When transactions are submitted for processing, they are grouped into an Excel spreadsheet, which is then used for batch processing in the ERP system.

The process did not incorporate any queue mechanism for processing transactions individually, which presented a major problem. If the Bot were to encounter an issue with the input file format or any individual transactions, it would not be able to skip the unsuccessful transaction and move on to the others. Instead, it would require a new input file submitted, causing significant disruptions for business users who need their transactions to be processed on time.

Accelirate’s ROC team solved for this problem by implementing REFramework and breaking the process down into two parts – a dispatcher process and a performer process. The dispatcher looks for High Radius input files in all available input file locations and adds each transaction – with the required transaction details in the Genius System – to a queue in Orchestrator. The performer process then grabs each transaction and processes them in the Genius System. The workflows are separated into an initialization stage, where all preliminary initializations are performed; a transaction stage, where the transaction will be pulled from the Orchestrator queue; a process transaction state, where the transaction is be processed in the Genius System; and a close state, where after all transactions have been processed, the Bot finalizes the transaction report with the journal and allocation numbers.

Using REFramework allowed the ROC to transform this complex and error-prone process into a reliable and effective one. The queue mechanism and individual transaction processing and tracking provided far greater control over the process, with teams able to retry failed transactions at an appropriate time without delaying the rest of the batch from processing. This, combined with the ROC’s exceptional logging practices, made the Premium Funds Allocation process more structured and scalable.

Case Study: ROC Instills Best Practices to Transform Credit Union’s RPA Program

For another one of our clients, a North American Credit Union, ROC support was instrumental in getting their program back up and running after a failed RPA project with a previous development vendor.

The client’s automations were yielding little value due to a number of issues, particularly with business and system exceptions. Processes were regularly failing or not completing, and the client had no exception handling in place, making it difficult to resolve issues quickly and precisely. Since the bots had not been programmed to notify the business of errors and exceptions, the business had virtually no visibility into which transactions had processed completely and which had only partially completed. Adding to the problem were the client’s vague logging practices, which made it especially challenging for the team to determine where incidents occurred in the process.

Accelirate’s ROC team saw this opportunity to make improvements in the client’s incident management practices and began by updating the log messages to be more detailed and specific to each process module. This would help the team identify where errors were encountered, and the log data could now be used to visualize critical metrics such as error rates and common exceptions. Since the client was already using the UiPath platform, we added UiPath Insights as well as Kibana dashboards to their program to provide continuous insights into their processes.

Next, our rigorous testing practices were implemented to improve automation performance. The client’s automations were encountering frequent errors that had never occurred during their internal test phase. They had previously only been testing their automations in debug mode, and were constantly running into unexpected issues. To address this, Accelirate’s ROC team first performed positive and negative case testing. Then the team tested the client’s bots in a production simulated environment to get a realistic inventory of the issues the bot would encounter while running on a daily basis. Doing so allowed our team to uncover a number of bugs and selector issues that the client otherwise wouldn’t have been prepared to encounter.

By instilling ROC best practices, we transformed the client’s entire RPA program to be more stable and better equipped to generate long term value, giving the client a renewed trust in automation after their previous unsuccessful initiative. The client is currently being supported by the ROC team’s 24-hour bot monitoring 5 days a week, along with break fixes and enhancements. Since the client was previously relying heavily on its small team of in-house developers to make changes and updates to processes, the ROC also enabled these developers to dedicate more of their time to discovering and creating new automations.

With automation becoming a necessary component of nearly every industry and leaders’ continuous improvement efforts towards daily operations, Robotic Operations Centers grow increasingly important to manage and support the digital workforce. The rigorous set of standards put in place by a ROC ensure that an RPA program is following best practices with automation documentation, testing, and logging. Through these practices, the ROC enables scale and helps the business realize greater ROI from automation.

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