Despite the consistent increase in robotic process automation (RPA) adoption, organizations are still struggling with its expansion. Scaling existing RPA initiatives is posing a challenge due to rising issues at the organization level. Unlike traditional technologies, RPA can be assimilated into your existing infrastructure without any increase in overhead expenses. The technology’s seamless integration and effectiveness in expediting processes are compelling its widespread implementation. Initially, companies deploy RPA techniques in one department and then consider scaling it to other departments. However, when it comes to large-scale adoption there are always some barriers that hinder the successful implementation.
So, here are some tested and tried tips for the successful scaling of your automation journey.
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Follow a well-defined Process:
For successful RPA scaling, a well-defined process is key. When outlining the process to RPA implementation purpose clarity, process blueprint and conflict resolution should be carefully considered.
Purpose clarity is critical to help individuals realize that RPA scaling is a step towards a digital transformation that aims to emphasize high-value tasks. A process blueprint helps in identifying areas that need RPA adoption. Additionally, it assists in finding out cross-functional processes that may be subject to conflicts. This way defining a process can prove effective in conflict resolution by promoting collaboration between different departments.
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Strong collaboration:
As you begin RPA scaling, several cross-functional processes will undergo automation. This will also involve the automation of several complex interdepartmental procedures which may result in arising conflicts between departments. Therefore, to combat such issues, IT and business teams should work in collaboration and should create a Centre of Excellence to extend support to teams across the organization.
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Use technologies that complement RPA:
To scale RPA, organizations need to use several technologies that leverage automation in use cases. For instance, many organizations rely on sophisticated processes which involve managing unstructured data. To further process information, this data needs to be converted into structured form. Now, here you are required to use a combination of technologies such as machine learning, optical character recognition, etc. to handle different steps involved in the process.
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Empower your workforce:
Even before you plan to adopt RPA, it is critical to have subject experts in your team. Preparing your RPA developers and analysts beforehand will help other employees accommodate changing technologies swiftly. Moreover, there should be a dedicated team to handle governance, maintenance, and implementation of RPA best practices. The governance team should be made responsible to administer the whole scaling process while keeping employees updated with upcoming transitions.
Conclusion
For successful RPA scaling, it is necessary to identify and understand best practices to be enforced throughout the organization. Although achieving full-fledged RPA scaling is not that easy, organizations can enjoy successful implementation by sticking to the aforementioned tips. With complete RPA adoption, businesses will become more productive and efficient. Plus, they will secure a competitive position in their niche market.