If you’ve been following our blog for a while, we don’t need to convince you that Robotic Process Automation is rising. But in case you’re new here, here are a couple of RPA stats to help you understand its impact:

• By 2025, 4 million RPA bots will perform various office, administrative, and sales tasks.
• The RPA market value is expected to reach over $13 billion by 2030.
• Companies that adopted RPA report an average of 40% time savings in the first year.

But no matter if you’re an automation aficionado or an RPA rookie, one thing can’t be stressed enough: all that advancement wouldn’t be possible without RPA testing.

Proper testing reduces the overall cost and effort needed for a successful RPA implementation. Regardless, RPA testing is often neglected by RPA specialists and companies seeking to implement workflow automation. In this article, we’ll challenge that false notion by defining various types of RPA testing, explaining its role, and listing tools used in the process.

Let’s be honest: complex RPA implementation requires an investment like any other software project. While small, single-process deployments are mostly affordable, license and implementation costs of large automation projects spanning multiple departments and applications may quickly add up. Still, companies agree to pay the price because the productivity boost far outweighs the initial expenditure. Provided RPA is working as intended.

If it’s not, the costs will continue to stack up. An RPA bot performs up to thousands of daily instances of the same task. Given this scope, even a single mistake can affect every single execution, generating severe losses before the error is detected. Then, the bot must be fixed, which takes even more precious time.

Luckily, there’s an easy way to increase the odds of a fast ROI and prevent costly errors and downtime. Yes, you guessed it: devoting some time before the launch to thoroughly test the bot.

What are the benefits of thorough RPA testing that make it a crucial stage of the implementation process? Let’s see.

Testing RPA for cyber attacks, tampering, unauthorized access, and other dangers warrants that the automated process is secure and doesn’t put the organization and its members at risk. Identifying weak spots is one thing; another is checking the existing safety measures. Here, RPA testing helps verify if protection features, like logging, monitoring, user authentication, and access control, function correctly and can nullify the threats.

One of the main advantages of RPA is reducing the margin of error for manual processes. However, this is only attainable if the bot doesn’t replicate or commit its own mistakes. RPA testing allows developers to identify errors early in the development cycle and ensure that the bots run the process consistently. This way, errors can be addressed before the launch, when fixing them becomes more challenging and expensive.

Besides bug wrangling, RPA tests are essential to ensure that the RPA solution meets the desired performance standards. By running performance tests, RPA developers can spot inefficiencies before the launch so that the automated process is executed correctly. In some cases, testing the solution can even lead to new discoveries and guide developers toward tweaks that further enhance it.

Sometimes, particularly during more complex implementations, it’s easy to lose sight of how the final solution will be used daily. RPA tests are the perfect opportunity to see how end-users interact with it and ensure that the automated processes are user-friendly. It’s essential in the case of bots that will assist non-technical staff in everyday tasks like document retrieval or data entry.

Effectively, RPA testing leads to a better outcome for everyone: 

• developers, who deliver a more reliable solution that they will require less of their time to maintain;
• end-users who enjoy a bug-free and more intuitive tool that expedites cumbersome work;
• business owners who see substantial growth in productivity and faster ROI on RPA implementations.

There are 5 main methods of RPA testing, each with its defined purpose.

• Unit testing — In unit testing, the performance of all RPA components and workflows is verified individually in both standard and edge cases. Breaking down the entire solution into smaller units and testing them individually allows automation developers to focus on one functionality or bot action, e.g., clicking a button or filling data fields. Thus, they can easily spot defects in specific areas.
• Integration testing — RPA workflows often rely on integrations between the automation platform and one or more business apps. The role of integration testing is to make sure that all third-party systems, APIs, and RPA components involved in the automated process are well-coordinated and can cooperate seamlessly, e.g., when moving data. Integration testing usually takes place once all relevant components have been unit-tested.
• Regression testing — RPA development is a gradual process. Constant modifications are necessary, but with each round of changes, there’s a chance that previously working code will crash, produce errors, or otherwise stop functioning. Regression tests focus strictly on these defects. Regression testing can involve other testing methods to pinpoint the change that causes the defect.
• Security testing — A separate risk assessment phase that verifies if necessary safety measures (governance, authentication, access control, traceability, etc.) are present and whether automation makes the organization vulnerable to any threats.
• User acceptance testing (UAT) — A user-oriented testing method that aims to confirm if the bot is executing the task as intended in terms of performance, usability, and functionality. In the case of attended RPA bots triggered by human employees, UAT also determines how intuitive and practical the automation is to its users.

It’s worth noting that since all testing methodologies have a distinct purpose, it’s not a matter of choosing one over another. Each of them has its use at different stages of development, and combining them is the best way to guarantee a secure, stable, and highly-performing RPA automation.

Invaluable as it is, RPA testing isn’t free from its challenges. Here are the main obstacles you must consider and how to overcome them.

• RPA complexity — Sophisticated, enterprise-wide RPA deployments require significantly more test rounds, scenarios, tools, and methods. You can also work with subject matter experts, RPA consultants, and business analysts to simplify the process, e.g., by double-checking it for unnecessary steps or reducing the number of exceptions.
• Costs and scheduling — Though RPA testing is fundamental for effective implementation, thorough checks take time, affecting the project timeline and end budget. Advocate for allocating time and resources for RPA testing right from the start and make sure that all stakeholders are on the same page about its importance.
• Improperly defined scenarios — Rather than using generic testing scenarios, select or create cases that are relevant to specific bots. Aim to cover distinct use cases, exceptions, input variations, etc.
• Lack of test data — RPA teams often work under strict deadlines imposed by the business teams, which can lead to missing data for some scenarios. Convince your business team that providing test data for all scenarios will go a long way and result in a more stable deployment.
• Insufficient business expertise — Misalignment with business objectives is a common pitfall that can be easily avoided by collaborating with a business analyst throughout the testing process. Understanding the business requirements is necessary for verifying if they were met during the development phase.
• Using unrealistic data — To check if bots will perform well in real-life scenarios, use datasets that will be relevant to these tasks. Include incomplete and incorrect records to test if the bot can identify missing fields, typos, etc.
• Lack of a dedicated test environment — RPA bots usually automate other applications, and often, the client doesn’t have a separate test/sandbox environment to test. Create a dedicated testing environment that matches the production setup to easily isolate issues without affecting the actual automation.
• Fragmented testing — While unit testing is vital, don’t forget to ensure the process runs correctly from start to finish through end-to-end testing. Running holistic tests will also help you validate the automation’s business logic, data flow, and usability.
• Single testing environment — Unless you’re absolutely sure that your bots will only be used on one platform, verify that they can work on desktop, web, and mobile. Account for version changes and software updates by equipping bots with self-diagnose, reporting, and recovery functionalities.

Now that you know the basics of RPA testing with its benefits and challenges, it’s time to implement your own testing process. But before you start, here’s a bunch of useful beginner tips:

• Build RPA bots with testing in mind — You can (and should) prepare your automation for testing as early as in the planning phase. Assign separate, dedicated workflows to each task, break down processes into small, well-defined blocks, and include logging and reporting functionalities.
• List all scenarios — Taking the time to create a simple document or spreadsheet containing all the scenarios will allow you to define the expected behavior of the automation and precisely assess the scope of testing.
• Focus on readability — A simple but often overlooked method that facilitates testing, particularly in larger teams. Established naming conventions, adding comments explaining complex workflows, and creating a detailed process definition document will all contribute to easier RPA testing.
• Create effective test cases — Test cases should reflect real-life scenarios and cover all outcomes for a given step. Keep test cases independent of each other to prevent incompatibilities and assign one purpose to every test case.
• Run and update tests regularly — Once you’re done implementing an RPA testing solution, remember to use it whenever you make a change to a given step (here’s when having small, dedicated workflows comes in handy). Test cases themselves should also be kept up-to-date with all relevant changes.

Between extra post-launch fixes, slower ROI, more downtimes, and defects, cutting corners on proper RPA testing is a minuscule saving that’s not worth it in the long run. Instead of learning it the hard way, use our short guide during your next automation project: test your process multiple times before it goes live with different methods and tools to build an RPA that’s a boost, not a burden.

At Flobotics, testing is a mainstay of our RPA development process. Want to talk about that or anything RPA-related? Give us a call.