Subscribe To Newsletter AI/Automation Driving Automation Value Delivery at Scale Over the years, there have been numerous discussions around AI and automation, and their potential impact on the future of business. This has now reached a crescendo with organizations expecting to drive zero latency in business process execution by leveraging the latest automation and AI technologies. While most enterprises have been through a phase of experimentation and have the organization experience of delivering Proof of Concepts (PoCs) or pilot programs the imperative for them now is to scale these projects to drive enterprise wide adoption. Successful organizations that have leveraged automation to drive business transformation have taken a multi-pronged approach to enterprise scaling and are now investing in increasingly sophisticated automation to drive greater business value. However, driving enterprise-wide adoption of automation can be a truly daunting task for organizations. While PoCs and pilots have undoubtedly given them enormous experience in areas such as Robotic Automation, Machine Learning (ML), Deep Learning, and Neuro-Linguistic Programming (NLP) among others, organizations are still unsure of how and where to start an enterprise-wide adoption journey for automation. Given the limited number of successful use cases and presence of considerable legacy infrastructure, adoption of automation at scale remains a challenge for many organizations. We have always relied heavily on our understanding of our clients’ landscape and domain, as well as our strong partner ecosystem to help them make a successful digital transformation journey. Based on our experience, here are some considerations that organizations find useful when they embark on a journey to adopt automation at scale: Asking the Right Questions With most new technologies, there is often a tendency to look at the capabilities and features of the technology and then try to fit it into the organization’s digital aspirations. Most questions revolve around what RPA/AI can do for the organization and the pivot tends to be around technology adoption. The right question to ask is not what the technology can do but to ask what is the business problem that we are trying to solve. Once there is a clear definition of the problem, organizations can explore how automation can help solve it efficiently and effectively. One also needs to give some thought to the process of adopting automation. What is the best approach to take while implementing automation? Should you start from task automation and then move to process automation? At what stage should you incorporate automation in the business model? Also, which process should you automate? Not all processes lend themselves to automation. If you pick a bad process to automate, it’s unlikely to benefit the organization. Asking the right questions can ensure a smooth implementation. Agile Mode of Delivery for Automation Cycles Given the dynamic nature of automation technologies, program teams within the organization need to move with speed, yet retain flexibility in their implementations. Regular automation cycles are typically long. From identifying the right automation opportunities to going through design, build and development, it can take several months even in very efficient organizations. Therefore, standard software development life cycle (SDLC) methodologies are not well suited to deliver the required results for implementing automation. Most IT managers worry about the agile mode of delivery particularly when they are not ready for it at an enterprise-wide level. An agile approach can get complicated because of the accompanying change management at the organization level. However, to deliver automation in an agile mode, it is important to take cognizance of the fact that automation is non-intrusive and resides as an additional layer on top of the existing enterprise landscape. Our experience tells us that this enables a delivery cycle which can be reasonably independent of the enterprise development and release cycles. Automation cycles can therefore be accelerated by bringing in the necessary digital assets for ideation, opportunity identification and delivery can be fine-tuned to meet the current structure of the organization. Organizational Redesign Considerations Technology alone is not sufficient to give enterprises the competency to disrupt the market. There has to be a deeper change in organizational processes and structure to support the technology implementation. Automation implementation demands for an organizational redesign along three key dimensions. The first is a rethink of business processes and its implications for team structures. The second is enabling the teams to handle the new technology by refactoring skills and providing the necessary training. And last is to reskill employees affected by automation so that they can be redeployed in other functions or roles within the organization. For instance, with automation, there will be job roles that will get released, resulting in unutilized productive time. The organization will have to consider each task that comes under automation under the ‘stop’, ‘continue’ or ‘start’ model to determine the next best action for employees who are directly impacted by automation. They need to be trained to move into roles that are more cognitive and value adding. Platform Selection When establishing a platform for enterprise-wide adoption of automation, one needs to factor in multiple capabilities across the automation spectrum. These include data ingestion, processing, process automation, machine learning and other similar cognitive capabilities. While these are not mandatory to have at the start of the implementation, they are helpful to foster a more strategic approach. As the organization dives into enterprise-wide adoption, this will ensure smoother scaling of the platform to meet future needs. Enterprise-wide adoption of automation technologies can confer solid competitive advantage and potentially transform business models. However, it requires a strategic approach, careful planning, and deep vertical and horizontal expertise to make it a success.