RPA spends are now more mature. According to Gartner, the RPA market’s growth rate was 22% in 2022. Compared with the 31% growth rate in 2021 and 63% in 2020, this slower growth shows that the initial excitement phase is over and now investments are more calculated and mature. By the end of 2025, the RPA market size is anticipated to surpass $5 billion, reflecting its increasing adoption across various industries.
Cloud-Based RPA Takes Flight: Cloud-based RPA solutions are soaring in popularity due to their ease of deployment, scalability, and cost-effectiveness. Gartner predicts over 20% of RPA initiatives will move to the cloud by 2025, offering organizations agility and flexibility.
Considerations before you embark on your RPA journey:
- Infrastructure: Evaluate your IT infrastructure's capacity to handle RPA deployment. Consider scalability and integration needs with existing systems.
- Data security: Ensure your RPA solution adheres to data security regulations and best practices. Protect sensitive data throughout the automation process.
- ROI and cost analysis: Calculate the potential return on investment (ROI) and total cost of ownership (TCO) for your RPA implementation.
- Proof of concept: Start with a small-scale proof-of-concept project to assess the feasibility and benefits of Robotic Process Automation in your specific context.
- Training and support: Train your team on using and managing RPA tools. Provide ongoing support for bot development, maintenance, and troubleshooting.
- Vendor selection: Choose an RPA vendor that aligns with your technical needs and budget. Evaluate features, ease of use, scalability, and security. Look for partners that have experience in your line of business, are willing to understand your problem space, and employ a design-led methodology for your automation success.
It’s not always a bed of roses with RPA:
- Choosing the wrong processes: Not all processes are created equal for automation. Selecting overly complex, non-standardized, or unpredictable tasks with frequent human intervention can lead to failure, especially for beginners.
- Focusing on low-impact tasks: Automating simple tasks might only provide minimal value, especially if it only benefits one user. Look for processes with broader impact and potential for significant improvement.
- Poor planning and governance: Lack of clear goals, proper planning, and robust governance can lead to confusion, delays, and ultimately, failure.
- Inadequate resources: Underestimating the technical and human resources needed for successful implementation can hinder progress and create bottlenecks.
- Unrealistic expectations: Setting unrealistic expectations for ROI or immediate results can lead to disappointment and discouragement.
Marlabs designs and develops digital solutions that help our clients improve their digital outcomes. We deliver new business value through custom application development, advanced software engineering, digital-first strategy & advisory services, digital labs for rapid solution incubation and prototyping, and agile engineering to build and scale digital solutions. Our offerings help leading companies around the world make operations sleeker, keep customers closer, transform data into decisions, de-risk cyberspace, boost legacy system performance, and seize novel opportunities and new digital revenue streams.