In today’s digitally-focused age of business, tech buyers are more motivated than ever to invest in software to help them achieve digital transformation. Many companies were prompted to begin or accelerate digital transformation initiatives this year as the impact of COVID-19 amplified the inefficiencies within their business. It became harder to ignore the negative impact of legacy or disconnected business systems that echo throughout an organization in the form of dysfunctional processes, disparate data silos, and lengthy cycle times. Robotic process automation, or RPA, can act as a functional layer across business systems old and new to facilitate cross-platform communication. However, companies must take care to thoroughly integrate RPA and digital transformation strategies to reduce rework and ensure both projects progress forward together.
What is Digital Transformation?
Digital Transformation is the integration of digital technologies throughout a business to transform how it operates and meets the needs of consumers. Such an initiative requires a radical mind shift in how the organization will use its’ technology and people to achieve desired goals. To begin, companies will need to take a hard look at the business to determine where the inefficiencies lie and what is driving those inefficiencies. Thorough evaluation of the current tech stack and underlying business processes is performed to determine where investments and improvements should be made. Some companies will have the resources to upgrade the tech stack en masse, while others may have to make difficult decisions about which technologies should be prioritized. In either case, there will be a massive shift in how the business operates as the old way of doing things is rapidly expiring.
Applying RPA in Digital Transformation Initiatives
The adoption of modern, interconnected systems paves the way for sunsetting clunky business processes that were formerly dictated by legacy systems. However, there is a common misconception that RPA is only useful for helping manage the issues that arise from disparate or legacy systems, which is simply not true. RPA is centered on automating human processes. The application in which the process is performed is insignificant. Modern applications offer interconnectivity and may facilitate more efficient automation methods, like the use of APIs. Still, employees will build processes around newly-adopted technologies, just as they did with legacy systems (albeit more efficiently, fingers crossed.) Those newly-minted processes will still be excellent candidates for automation because humans still perform them.
As new technologies are adopted, the business will find itself having to account for the old and new way of doing things. The RPA layer over systems and processes old and new will also have to account for that dynamic as well. This is where proper planning and project management will be crucial to keeping the project from going off the rails. To start, complete documentation of current business processes is highly recommended to establish a clear frame of reference for both the current and planned states of the business. Business analysts and process owners will need to work together on this documentation so the business has a complete view of the process and its dependencies. The automation Center of Excellence (COE) will also need to drive cross-departmental collaboration as new systems come on line to develop the RPA strategy around them. New business processes will also require thorough documentation to accelerate the development of robots that will interact with these new systems.
Enterprise-wide coordination and close alignment across the COE, Operations, and IT is crucial to keep both projects on track. DevOps, or Development Operations, is a methodology that combines principles of software development and IT Operations. Many companies are utilizing DevOps practices to accelerate development cycles without sacrificing quality. This methodology can be applied in both RPA and digital transformation initiatives so that the organization can deliver applications and services in tandem at a higher velocity. Under a DevOps model, development and operations teams are no longer siloed so that crucial operations information can be incorporated earlier in the product or robot development cycles. This kind of collaboration ensures each project is fed crucial, relevant information as it progresses to reduce rework, keep momentum going, and raise your chances of success.