By introducing automation, organizations can offer a better customer experience while improving process efficiencies and productivity. To get the full benefit of automation, it’s important to look at processes end to end and often redesign them with a customer-first approach. Process automation can be for customer-facing operations or backend processes. Examples of automation in the customer-facing process include image recognition, natural language processing, intelligent chatbots, etc. And examples of backend processes could be fraud detection, churn analysis, etc. Some of the ways automation and AI help organizations include:
Automation can be broadly classified into three areas.
Some of the key factors driving the adoption of automation include:
Organizations must evaluate the following while deciding about automation:
For automation to deliver desired results, business and technology must work in close collaboration. A challenge for automation is identifying and selecting the right data set which is often fragmented and resides within multiple functions and silos. Getting a single view of customer data is one of the biggest hurdles. Another challenge is identifying good quality data from a large data set. It’s essential to determine what are the dependent variables and controlling variables for better outcomes. Training the models and finding the suitable training dataset is the final challenge. But the benefits outweigh these constraints, and a proper strategy for automation and execution can ensure that the enterprise benefits from improved customer-facing and backend processes.