8 Effective ways to improve bot stability
Stability is the ability to adapt the changes.
A bot that adapts to the
changes to a certain extent can be called “stable”.
Stability is an important factor
to consider while building resilient bots.
Since the past few years, there has been a surge in Robotic Process Automation. Healthcare, Telecom, Insurance, Banking, and Financial Institutions are driving new efficiencies by creating a digital workforce. Initially, RPA could automate mundane tasks. However, today it is a different story. Intelligent Automation is extending the horizons of automation by accelerating this digital transformation.
To ensure the bot provides good ROI in the long run, one should focus on one of the most important aspects of bot development
How do you define stability?
Stability is the ability to adapt to changes. A bot that adapts to the changes to a certain extent can be called “stable.” It is an important factor to consider while building resilient bots.
To understand how to improve the stability, let’s first understand which factors affect the stability of a bot.
What are factors that lead to losing stability?
On a high level, any change in the bot environment, unhealthy coding practices, or automating processes that are not best suited for RPA affects the stability of the bot.
Let’s dive deeper to understand which changes can affect the bot’s stability.
- Environmental: Environment is the server/machine on which the bot is deployed. Resolution, language, culture, keyboard type, date format, etc. are often overlooked but are very important to ensure bot stability.
- Business: It includes business applications such as webpages, desktop applications, etc. This is the key focus area for most of the RPA developers. These changes are often anticipated in the initial stages of development. So, the risk of them affecting the bot stability is low.
- Technical: Variable parameters like folder/file paths, URLs, Username and Passwords, etc. changes in any of these cannot be automatically adapted by the bot. It needs reconfiguration. In this case, a stable bot is the one that allows the end-user or the developer to reconfigure these parameters easily without leading to bot failure.
Even without any of the above changes, the bot might fail due to the use of unhealthy coding practices. I have listed some of the best practices in the next section which help you minimize the bot failure and increase its stability.
Sometimes it’s not the code, it’s the process. Not all tasks that are redundant and done manually can be automated. One should perform a good feasibility analysis of the process before considering it for automation.
With that being said, let’s move on to the best practices to improve bot stability.
Best practices to create stable bots
Now that we have seen what stability is and how it is affected by different factors, let’s see how to create stable bots. Below are some best practices that you can follow to make the bots stable.
- Recovery from bot failure: A bot tends to fail if there is even a minor change in the process. Anticipating all such changes while developing the bot is practically impossible. Hence to avoid bot failure it’s always a good practice to add a recovery logic to the bot to handle such changes. For instance, while automating a website, the bot logins with the provided credentials and performs certain actions. After some time, the session might terminate, and the user is logged out. As a result, the bot fails to find the required elements on the webpage resulting in the abrupt termination of the process. So instead of stopping the bot without finishing the process, it is always a good practice to add a recovery logic that closes the browser and reinitiates the session to continue the process.
- Use of background processing: There are some scenarios where we cannot recover the bot from failure. In case there is a new pop-up on a webpage that was not present at the time of development, closing the browser and reinitiating the process won’t help. The pop-up might still appear. To avoid such issues, one must use background processing wherever possible. This can be achieved by using APIs instead of direct interaction with the websites, using the database instead of Excel application to read data from excel files, etc.
- Configurable parameters: Some changes like change of folder path, URL, Email id, etc cannot be adapted automatically. Hence while developing a bot, one should try to keep most of the parameters configurable to ensure easy reconfiguration without causing bot failure.
- On the go setup: Bot setup is usually considered as a one-time activity. But in some cases, the required files might get deleted or moved, causing the bot to fail. It is a good practice to check and create these bot dependencies on the go. This can be achieved by maintaining them in a shared folder and using them whenever required.
- Clean-Up: Despite handling errors and adding recovery logic there are scenarios where the bot may fail due to an unprecedented error/exception. The applications which the bot used might remain open and cause issues for other bots running on the same machine. Hence to avoid this, cleaning up the machine by closing open applications is always a best practice.
- Environment Setup: Bot might fail due to differences in resolution, date format, keyboard, culture, etc in different environments. To ensure there are no differences in development, testing, and production environments one can replicate the machines and minimize the chances of bot failure.
- Avoid Image-based automation: Image-based automation is used in case a particular element is not identified on a webpage/application. Using Image-based automation the bot searches for images the same as the one that was provided at the time of development. If the bot fails to find the exact image due to a slight change in size or colour, it will result in bot failure. This should be your last resort in case you have exhausted all the tricks to find the exact element in your RPA playbook.
- Maintaining the equilibrium: A process might need a change of few parameters in the bot environment (Ex. Language). One should not forget to add the logic to revert these changes after successful completion and especially in the event of bot failure. It is important to make sure such changes don’t affect other bots running in the same environment.
“The only constant in life is change” – Heraclitus
As Heraclitus rightly quoted it is impossible to evade the changes, but you can apply the best practices discussed in this article to ensure the bot adapts them. These ticks are tool independent and will help you reduce the maintenance efforts resulting in a good ROI in the long run.