You compare RPA platforms by looking at five main criteria: ease of use, scalability, integration capabilities, cost and support. Each platform has different strengths, so your choice depends on your specific processes and organizational needs. A thorough evaluation through test scenarios and pilots will help you find the best match for your automation plans.
What criteria are important when comparing RPA platforms?
When comparing RPA platforms, focus on five key areas: ease of use, scalability, integration capabilities, support and total cost of ownership. These criteria determine whether a platform fits your organization and can successfully grow with your automation needs.
Ease of use is paramount because your employees need to be able to work with it. Look at the interface for building bots, how easy it is to model processes and whether you have drag-and-drop functionality. Platforms with visual development environments allow even non-programmers to build bots.
Scalability determines whether the platform will grow with your organization. Can the platform run both attended and unattended bots? How does it handle peak moments in process volumes? And can you easily add new processes without performance suffering?
Integration capabilities are critical to success. The platform must be able to communicate seamlessly with your existing systems, from legacy applications to modern cloud solutions. API connectivity, database integrations and desktop automation are important here.
Support and governance features help you manage your automation environment. Think monitoring tools, user management, security features and reporting capabilities. These aspects are often underestimated but are critical to long-term success.
What are the cost differences between RPA platforms?
RPA platform costs vary widely by vendor and include license fees, implementation costs, maintenance and often hidden costs. Enterprise platforms can cost between €5,000 and €15,000 per bot per year, while smaller solutions start from €500 per month.
Licensing models vary considerably between platforms. Some charge per bot, others per user or per process. Note the difference between development and runtime licenses. Many platforms have separate charges for building bots versus running them in production.
Implementation costs are often underestimated. In addition to the software, you have costs for consulting, training, process analysis and change management. These can amount to 2-3 times the annual license cost, especially for complex implementations.
Hidden costs are often in maintenance, updates, additional modules and scaling. Some platforms charge separately for OCR functionality, machine learning capabilities or premium support. Infrastructure costs for servers and databases are also added.
Always compare the total cost of ownership over 3-5 years. A low-cost platform may be more expensive due to high implementation costs or limited functionality that requires expensive add-ons later. Ask for transparent pricing and sample calculations for your use cases.
How do you test an RPA platform before making a final choice?
Test an RPA platform by setting up a proof of concept with an actual process from your organization. Choose a process that is representative but not too complex, so you can measure and evaluate results on functionality, performance and user experience within 2-4 weeks.
Start by defining test scenarios that cover your key use cases. Select processes with different levels of complexity: a simple data entry process, a process with decision logic, and an integration with existing systems. This will give you a realistic picture of platform capabilities.
Set measurable criteria before you begin. Consider development time, execution speed, error rates and usability. Involve various stakeholders in the evaluation: process owners, IT staff and end users who will be working with the bots.
Organize hands-on workshops where your team can actually work with the platform. Have different people build bots to experience how intuitive the platform is. Also test the monitoring and management tools, as you will use them daily once the platform is live.
Document all findings systematically. Create a scorecard with your criteria and evaluate each platform on the same points. Don’t forget to also include the quality of support during the testing period in your evaluation.
What pitfalls to avoid in RPA platform selection?
The biggest pitfall is technology-first thinking instead of process-first. Organizations often choose the most advanced platform without considering whether it fits their processes and organizational culture. This leads to expensive implementations that do not deliver the expected results.
Don’t underestimate change management. RPA changes how people work, and many projects fail due to resistance or lack of adoption. Choose a platform that fits your team’s technical level and invest adequately in training and mentoring.
Legacy system compatibility is often taken too lightly. Don’t assume that every platform can integrate with your existing applications without problems. Test specifically the integrations you need and ask about experiences with similar environments.
Avoid vendor lock-in by choosing platforms with open standards and export capabilities. You want to be able to migrate or expand later without having to rebuild everything from scratch. Ask about portability of your bots and process definitions.
Don’t start too big. Many organizations want to automate everything right away, so they choose the most comprehensive platform. Start with a limited number of processes, learn from the experience and then scale up. A simpler platform can often give better results than a complex system that you don’t fully utilize.
How does Pegamento help choose the right RPA platform?
We take a vendor-neutral approach to RPA platform selection and help you choose the best platform for your specific situation. With our 15 years of experience in process automation, we know the strengths and weaknesses of different platforms and can make an objective comparison.
Our expertise lies primarily in connecting RPA platforms with legacy systems. We understand the challenges of organizations that stick to proven systems but still want to automate. Through smart integrations, we create customized solutions with standard building blocks, without costly customization.
We guide the entire selection process, from process analysis to platform evaluation and implementation. Our consultants help set up proof of concepts, define test scenarios and objectively assess results. This way you make an informed choice that suits your organization.
Pegamento has advanced RPA to Agentic AI: an evolution from executive bots to self-thinking assistants that not only follow instructions, but take initiative and act independently. This experience with AI-driven intelligence helps us prepare you for the future of process automation.
Our “One Stop Shop” approach allows you to purchase everything under one roof: from platform selection to development, implementation and management. We are ISO 27001, ISO 9001 and ISO 26000 certified, which ensures reliable processes and high-quality service on every automation project.
Frequently Asked Questions
On average, how long does it take to implement an RPA platform?
A typical RPA implementation takes 3-6 months, depending on the complexity of your processes and organization size. The initial pilot can run within 4-6 weeks, but full rollout with governance, training and change management requires more time. Plan at least 2-3 additional months for organization-wide adoption.
What happens if the chosen RPA platform does not meet expectations?
In case of disappointing results, you can usually migrate to another platform, but this involves costs and time. Therefore, a thorough proof of concept is essential. Choose platforms with open standards and export functionality to avoid vendor lock-in. Many vendors also offer upgrade paths or hybrid solutions.
Can employees without a technical background really build bots themselves?
With modern low-code/no-code RPA platforms, business users can indeed create simple bots via drag-and-drop interfaces. For more complex automations with decision logic or API integrations, technical support usually remains necessary. You get the best results by having business and IT working together.
How do you prevent bots from breaking on system updates or changes?
Make bots robust by using stable selectors, error handling and fallback scenarios. Establish change management processes where IT changes are communicated to the RPA team. Many platforms also offer self-healing capabilities that automatically make adjustments for minor interface changes.
Is it possible to start with a low-cost platform and upgrade later?
Yes, many organizations start with an entry-level platform and later upgrade to enterprise solutions. Just be aware of migration challenges: not all bots are portable and you may have to rebuild processes. Preferably choose a vendor with different product tiers or platforms that offer standard export functionality.
What ROI can you expect from RPA and how do you measure it?
Typical ROI of RPA is between 200-300% over 3 years, but this varies greatly by process and implementation quality. Measure ROI by quantifying time savings, error reduction and cost reduction. Don't forget to include soft benefits such as improved compliance, employee satisfaction and 24/7 processing capability.
How do you ensure RPA is secure and meets compliance requirements?
Choose platforms with enterprise-grade security: encryption, audit trails, role-based access control and compliance certifications. Implement governance frameworks with clear authorization processes for bot development and deployment. Work with your security and compliance teams to establish policies for automated processes.
