Robotic Process Automation (RPA) is a rapidly growing industry that, according to Forrester, is expected to reach $2.9 billion this year. Five years ago, it had just $200 million worth of a market share.
One of the key buzzwords among enterprises today, RPA captures the imagination of organizations looking to transform into truly digital enterprises. Many business leaders have already seen what RPA can do and are looking to implement it in their teams, departments, and entire companies.
The best way to effectively implement RPA in your organization is to know the RPA software lifecycle.
In this article, we give you a holistic overview of all the different stages RPA software undergoes to help you implement it systematically. Next, we share some best practices for implementing RPA to ensure that your journey to Robotic Process Automation is smooth and successful.
Key stages of RPA lifecycle
Phase 1: Discovery
This is the first and most critical phase of your RPA implementation roadmap, with human expertise and technologies like AI coming together to create something new.
Your first goal is to pick the right process to be automated. This is also when you define the right governance to build the success of the entire procedure.
This phase places more emphasis on your requirements and the decision of whether a process is a good candidate for automation or not. If the decision is positive, the RPA analyst team carries out a detailed analysis of the complexity of the use case. The RPA architect and business team usually collaborate to create a high-level implementation plan that allows making the analysis more accurate and foolproof.
Phase 2: Solution design
During this phase, the team designs all the steps necessary to automate a given task. To develop an RPA effectively, you need to provide developers with several documents, including:
Process Design Document (PDD),
Solution Design Document,
Technical Design Document.
All of these documents include critical information the RPA team needs to process each step accurately. After taking into account all the requirements in the PDD, the team also considers other requirements like budget, timeline, or the current number of people working on the task.
Next, the team creates a flow chart to understand the process flow better and outline all the steps that require automation – together with the particular requirements of each step.
Phase 3: Development
This is the phase when developers finally sit down to write some code. They create automation scripts within the chosen RPA tool or build one from the ground up. The idea is to follow the previously developed PDD to ensure that the bot carries out the task accurately. Once a suitable bot is developed, it's time to test it.
Phase 4: User acceptance testing
During this phase, the team tests the developed bot in the preproduction environments to examine how users are using them via automation of specific tasks. The testing can be carried out by a separate team. Naturally, the testing phase is a process that uses standard QA testing techniques that are part of the regular Software Development Lifecycle flow.
If testing proves to be successful, the team proceeds to the next stage. However, if some tests fail, the bot reverses the development phase for teams to identify errors that led to the failure and fixes them. After that, the testing process is repeated, and after achieving success, the team is ready to transmit into the deployment phase.
Phase 5: Deployment
After developing and testing the bot, it's time to deploy it to the production environment. After that, the bot is ready to be used by its end-users.
However, some issues might resurface again once that happens. There's no need to worry because the bot can go back to the development and testing team at any time to resolve the issues. After that happens, the bot enters the penultimate phase: execution.
Phase 6: Execution
This is a critical phase in the lifecycle of Robotic Process Automation where the execution of bots finally generates meaningful results for the team. Apart from that, the team checks in to make sure that the implementation was carried out in line with the requirements of the end-users.
Phase 7: Support and maintenance
This is the last phase of the RPA lifecycle. Once the bots become available publicly, the team needs to continue offering support and maintenance services to the end-users. That's because users might find a defect or bug - just like in any other application.
The best RPA solutions are the ones that offer excellent support and maintenance, ensuring a smooth resolution of these problems to deliver the best experience to users.
Best practices for RPA implementation
1. Pick processes that will bring the greatest benefits
To maximize the impact of RPA, your first step is identifying the processes that will be most impactful. In most cases, they're usually ones that are:
Influence cost and revenue – They're expensive and impact consumers directly. Quote-to-cash is a good example of that since the speed and effectiveness of this process can really make or break a sale. This is a good candidate for RPA since it can be automated.
High-volume - One of the key advantages of RPA is that it reduces the amount of human effort involved in tasks. It makes sense to start automating the processes of the highest volume first.
Fault-tolerant – If your process can handle errors, then you could prioritize his automation or establish a quality control process to make sure that every automation error is noted. Don't forget that RPAs rely on user interfaces to complete tasks. So, any changes there might result in errors. For example, automating invoice-to-pay processes is a good idea, but payments for a specific value probably need to be approved by a human employee first.
Error-prone - The errors that can creep into your process, the more benefits you will get from automating them. Such mistakes can lead to poor customer experience or even cause regulatory problems, especially for customer-facing processes.
Time-sensitive - Any process that could delay the delivery of services to customers is a good candidate for automation because it makes processes lightning fast.
Once you find a good business case, you need to make sure that automating this process with RPA won't generate another set of challenges.
2. Choose a process that you can easily automate with RPA
Here are the best candidates in terms of ease of automation:
Processes that are rule-based - The best process for automation is described by specific rules. That's because RPA bots need to be programmed by developers. If the rules of your process cannot be programmed, it's not a good candidate for RPA. Sure, bots can be trained with complex rules and even discover rules that aren't apparent to humans. But automating such a process will require a lot of time and money – as well as careful observation of the results it brings.
Processes that have few exceptions - If your process has a lot of undocumented rules (even if it's rule-based) and plenty of potential exceptions, it will be hard to identify them all through interviews with domain experts. Such a process isn't a good candidate for automation.
Processes that are company-specific - Is the process something that all companies in your industry carry out, or is it unique to your organization? For example, expense auditing usually takes place in a similar way in most companies of a particular size. That's why building an RPA system for expense auditing from the ground up doesn't make sense – it's going to be much more expensive and far less effective than an out-of-the-box solution developed specifically for handling such a process.
Processes that are mature - Automating a process that changes every week is a waste of your time. Developers will end up spending a lot of time on alterations and maintenance. Instead, pick processes that are stable and aren't going to change soon.
Make sure to streamline the process itself before working on its automation. This step might even reveal that the process in question isn't a good candidate for RPA.
3. Get executive and team buy-in
Next, you need to convince your organization that automating the process is a good idea. That's because implementing automation isn't only about technology – it's also about culture and people. In fact, forgetting about that is one of the greatest mistakes organizations make when implementing IT automation.
So, focus on getting the management's buy-in first. You know that the process can be automated, and you know what possible benefits this can bring. You're ready to build a compelling business case for company leadership. Make sure to include keywords like AI and Return on Investment (ROI). The first one is bound to catch their eye, and the second one will demand to know whether this idea works.
Next, it's time to get team buy-in. If you're automating an outsourced process, you're basically just bringing in savings, and the team that used to manage the outsourced process will likely be just as happy to manage an automated process.
But if you're automating an in-house process, things look a little differently. No employee wants to wake up one day to discover that their job has been made redundant by a bot. That's why it's essential to have an open and honest discussion about what automation means to the team and what value it will bring.
You need to do your best to convince the team of the change and need for automation. Show your plans for upscaling redundant team members and indicate which teams they will be joining next. Encourage automation by showing how much time team members are going to save and how many boring manual tasks will be taken off their backs.
4. Prepare for implementing RPA
First of all, you need to have a solid understanding of the process. The best way to understand the process is by interviewing operators who are currently running these processes. But if you rely only on this approach, you'll soon see that it's very costly. Interviews take time and are error-prone because people have imperfect memories and hold cognitive biases.
Alternatively, you can combine interviews with insights from analyzing tasks or process mining. Process mining software allows companies to analyze their logs and understand the flows of real-life processes. Task mining generates data by video recording of employee actions. Naturally, the vendors behind such software always remove nonpublic information from the video materials.
By combining these data sources, you'll learn what the actual process flow looks like and identify unnecessary steps or bottlenecks.
Then it's time to understand how you can improve it with automation. Processes usually change due to market or regulatory pressures. While sometimes they are improved with the top-down or lean approaches, these might end up being quite expensive.
Before proceeding with an RPA implementation, look for improvements in the process – they might simplify the process and make it more understandable. This will also reduce the effort required to programming and audit it (not to mention improving the overall customer experience).
5. Pick the right RPA implementation partner
At this point, you need to start looking for an RPA vendor or partner based on the technical requirements of your project. The selection process is a great opportunity for vendors to show how their work meets your requirements and the general criteria of your organization.
It's smart to pick a company that has in-depth domain knowledge and experience in implementing RPA for organizations in your industry. Most of the time, you will be invited to an on-site presentation or digital presentation that shows how the RPA can help with the company growth and the daily work of your teams.
While some vendors carry out the development, configuration, and testing, others are happy to sell ready-made bots and then teach you how to implement them. Finally, many enterprises bring in a vendor to code the initial pilot project or develop an internal RPA center of expertise for handling future RPA implementations.
If you're not sure how to proceed, it's worth meeting with the provider as well – these experts can point you to a potential solution or even build a team that could develop a tailor-made solution for you from scratch.
6. Run a pilot and test your solution
Testing is a critical aspect of RPA implementation. Minor differences in user systems, such as different screen resolutions or operating systems, can lead to unexpected bugs. All the major scenarios need to be tested thoroughly before you launch the pilot. You can use historical data to come up with even more realistic tests.
Once you're ready, it's time to run a pilot. Start by setting your targets for the pilot. You can focus on automation (number of tasks completed without human intervention) or accuracy (like the number of successfully processed invoices).
Then it's time to run a live pilot. Every day, the team responsible for the process will review a random selection of the bot's outputs to understand its quality.
Finally, you're ready to evaluate the results of your pilot. To do that, the team will run a detailed evaluation and consider all the rare cases and difficult inputs. You can only finalize the pilot when the previous targets you agreed upon are finally met.
There's no denying that RPA is on its way to becoming one of the most sought-after solutions among enterprises operating in sectors from financial services and insurance to healthcare and automotive.
At Maxima Consulting, we have been helping organizations across the sectors to implement IT automation and RPA to streamline processes, eliminate manual work, and bring inefficiencies across the entire spectrum from team productivity to customer experience.
If you're looking to launch an RPA at your company, our experts have the experience and know-how to carry out a pilot successfully and enable your teams to work faster thanks to automation.