This article is the second of a two-part series on Robotic Automation for customer engagement. Part one provides an overview of the technology. It explains how it can be used to assist customer service representatives and automate tasks of customer-facing processes. In part two, I want to explore the art of the possible and dig into the three most common models for leveraging this style of automation. But first, we need to do away with two misconceptions.
Robotic Automation and Artificial Intelligence
We are led to believe that robots are an application of Artificial Intelligence (AI). It is not the case. If AI can enhance robots, many software robots neither use nor require it. The industry shares some responsibility for that confusion. With Artificial Intelligence at the "peak of inflated expectations," vendors have been claiming its use or suggesting it by using imagery derived from science fiction movies.
AI can and will enhance robots. The two complement each other as described by Nice in its recent announcement of a Robotic Automation Cognitive Framework. But the delineation is important. You can start using Robotic Automation without Artificial Intelligence and its data prerequisites.
You can actually look at Robotic Automation as an enabler of AI. Providers such as Kryon Systems are planning to leverage it to gather the data needed to enable machine learning. Indeed, Robotic Automation provides the instrumentation for collecting data covering all steps — application and human — of process execution.
Robotic Automation and Jobs
Another misconception is that Robotic Automation is about replacing people. Surely, it has blossomed in the back office and at Business Process Outsourcers (BPOs) by reducing the number of full-time resources required to perform certain jobs. However, this is not its main purpose in the front office.
Robotic Automation can, of course, be a contributor to the ongoing productivity improvement imperative of customer service departments. But they already have many technologies at their disposal to do so. Self-service using intelligent assistants and smart bots is a perfect example. Moreover, as noted by Contextor Luc Cavelier, jobs in front offices are complex and diverse. It is harder to find tasks in high volume that can be automated without having to deal with exceptions. For customer-facing organizations, Robotic Automation must work with and for people. Its role is to help agents or to remove friction from processes by reducing errors and providing faster turnaround times.
Getting a New Assistant
The first model for deploying Robotic Automation in the front office consists in assisting agents. Many contact centers are using numerous applications with no path to consolidation. Customer Service representatives have to constantly switch between them. It is not just dull but takes time. It translates into these moments of silence or wait times that modern customers no longer tolerate. Furthermore, with increased interaction complexity, wrap-up grew to 20% of the total handling time according to the DiData Customer Experience Benchmarking Report.
Agents spend a lot of time logging or entering information into applications. Repeated data entry can be offloaded to a robot. Because the agent oversees the work of the robot, she can handle exceptions. Cavelier stresses two advantages of this model. It simplifies compliance by not inducing any data replication. And since the robot works under the agent supervision, it removes the need for extra security credentials.
Building a Digital Workforce
The second model for deploying software robots entails a division of labor between humans and robots. Software robots become a kind of back office department, hence the digital workforce metaphor. This model works with tasks that can be delineated and executed autonomously. Robots can be put in the cloud and provide an "elastic workforce."
With this model, robots need supervision. An additional software layer is required to orchestrate their work, control execution, and handle exceptions. IT governance is also needed to manage security, audit trails, and oversee data manipulation by robots in the cloud. It adds some complexity and makes sense when the organization can identify large workloads that can be given to this digital workforce. Nice' Oded Karev advocates using a software platform that can accommodate the two models. It gives you the freedom to adjust and optimize the breakdown of tasks.
Enabling Digital Transformation
If we take a step back, we can appreciate two other benefits besides cost savings. The technology reduces errors and removes points of friction such as data entry. Both are critical to improving the customer experience and have become table stakes in the digital world. They are important but often take a back seat to productivity improvements.
It begs the question though of being able to use Robotic Automation to digitize processes. Pegasystems' Francis Carden doesn't think so. He warns against the overhead of automating legacy processes. Instead, he recommends using Robotic Automation as a stepping stone and leverage other technologies, such as low-code or workflow platforms to redesign processes. In this context, Robotic Automation remains useful to integrate with legacy applications.
The versatility of the technology is a contributing factor to its limited adoption by customer-facing organizations so far. It can indeed become overwhelming to figure out where to start. A guiding principle is to stick to the promise of simple deployments and augmenting existing application stacks. Enterprises can and should adopt an agile approach and proceed step by step. The combined cost reductions and customer experience improvements should be enough to deliver a positive return on investment at each stage.
A Maturing Market
A growing number of players are addressing the needs of customer service departments:
It is hard to say how far the technology can and should be pushed. To some extent, the question is irrelevant. Robotic Automation can be deployed in baby steps and prove its value at every stage of the way. It is a “must-have” in the toolbox of any sizeable customer service organization having to juggle many applications to run its operations.