RPA: Big Bang vs One at a time

When it comes to implementing Robotic Process Automation (RPA), there are two main approaches that organizations can take: the big-bang approach or the one-process-at-a-time approach. Both approaches have their advantages and disadvantages, and the decision on which approach to take will depend on the organization's goals, resources, and risk tolerance.

Let's start with the big-bang approach. This approach involves implementing RPA across multiple processes or departments simultaneously. The main advantage of the big-bang approach is that it can help organizations achieve rapid results. By implementing RPA across the entire organization simultaneously, organizations can standardize processes, create a sense of urgency, and build momentum for the transformation. Additionally, a big-bang approach can help organizations realize significant cost savings and operational efficiencies in less time.

However, the big-bang approach also has its risks. Implementing RPA across the entire organization can create a heavy workload for the RPA team and increase the risk of errors. Additionally, because of the large scope of the project, the organization may face a greater need for change management, including communication, training, and support. If not managed properly, the big-bang approach can also lead to a lack of buy-in from stakeholders, resistance to change, and even project failure.

Now, let's look at the one-process-at-a-time approach. This approach involves implementing RPA in one process or department at a time. The main advantage of the one-process-at-a-time approach is that it allows organizations to prioritize processes based on their importance and complexity. This approach also creates a culture of continuous improvement, where each process can be optimized and refined before moving on to the next. Additionally, the one-process-at-a-time approach allows organizations to ensure the success of each RPA project before moving on to the next.

However, the one-process-at-a-time approach can also take longer to achieve results. This approach may not create a sense of urgency or momentum for the transformation, and can lead to a more fragmented automation effort. Additionally, the one-process-at-a-time approach can be more difficult to manage as the RPA team may have to switch back and forth between processes, which can slow down the overall automation effort.

In some cases, a hybrid approach may be the most appropriate option. This approach involves combining elements of the big-bang and one-process-at-a-time approaches to achieve the organization's goals in a timely and effective manner.

For instance, a company could use RPA to automate one or two critical processes as a pilot project and subsequently expand the use of RPA to other processes gradually. However, it's important to create a Center of Excellence (COE) and mature the plan for a comprehensive adoption while launching a process discovery in a scientific manner, envisioning the working model and selecting the right platform, partner, and internal team. By adopting this approach, the company can test RPA while also preparing to achieve quick wins and build momentum for the overall digital transformation.

In summary, both the big-bang and one-process-at-a-time approaches have their advantages and disadvantages, and the decision on which approach to take will depend on the organization's goals, resources, and risk tolerance. A hybrid approach is also a viable option for many organizations. Ultimately, the key to success with RPA implementation is careful planning, effective communication, and strong change management. By carefully considering the organization's unique needs and constraints and selecting the right approach for RPA implementation, organizations can achieve significant benefits from automation, including improved efficiency, accuracy, and cost savings.