In the age of voice assistance, chatbots, and AI, it’s tempting to be an early adopter and implement the latest automated capabilities. But there’s a price to pay if the implementation is poorly executed. So, what do companies need to do to win the automation race if winning means delivering support that’s fast, convenient, and personalized?
The answer is a combination of the right people, processes, and technology to support the strengths and weaknesses of human and digital capabilities. On that note, we’ll take a look at where companies stand in blending those three areas to harness automation and AI in the ultimate race—winning the customer.
Pragmatism trumps trends
As companies learn more about advanced automated applications, leaders are increasingly making the distinction between what is trendy versus practical. A key observation in Forrester’s 2019 prediction report, Transformation goes pragmatic, is that organizations were too eager to automate the entire customer experience, leading to uneven results. By focusing on the broad effects of automation, leaders failed to consider the extensive operational changes going forward.
The leaders that are succeeding are focusing on a narrower take on automation. As the report states, “Tangible efforts, such as shifting customers to lower-cost digital channels, launching digital products, monetizing data assets, and automating processes to improve margins, will come to the fore.”
To move forward, customer leaders have to understand the factors that are holding back successful implementations:
- Garbage in, garbage out. Organizations that are unprepared to provide the data and skills necessary to train an automated system significantly curtails its value and limits it to performing basic functions.
- Insufficient testing. Automation implementations have fallen flat due to insufficient testing before it was rolled out, or the technology wasn’t properly integrated into the departments that it was designed to support.
Successful automation depends on an effective collaboration with humans. However, the notion that automation is synonymous with job loss is not entirely accurate, argues J.P. Gownder, vice president and principal analyst at Forrester. Job creation will grow, “as CIOs hire bot masters to manage RPA [robotic process automation] bots, creatives and designers to improve user interfaces of chatbots and voice skills, and process experts to solve business problems,” Gownder writes in a blog.
Key takeaway: Automating CX for the sake of it is a waste of resources. A smarter approach is to take a measured look at the areas that would benefit from automation, identify specific use cases, and determine whether the resources and data are available to successfully support the implementation.
An AI Reality Check
There continues to be an immense amount of buzz around artificial intelligence as a transformative technology. In fact, 20 percent of organizations want to deploy AI enterprise-wide, and another 15 percent plan to deploy in multiple areas in 2019, according to PWC. But in addition to the technology, the right people and processes must be in place to successfully leverage the benefits of AI. Here are three tips to do exactly that:
- AI ownership takes on many forms. In a PWC survey of over 1,000 executives, 24 percent indicated that the AI center of excellence “owns” AI in the business, 19 percent pointed to data and analytics groups, and 11 percent pointed to outside providers. The risk of having one department oversee the technology is that AI projects will have a limited scope. As the report notes, “the answer is oversight from a diverse team that includes people who have business, IT and specialized AI skills and represents all parts of your organization.”
- Employees possess different levels of AI knowledge and experience and all relevant levels should be encouraged to provide input. The PWC identified three levels of AI savviness: Citizen users (employees who use basic AI tools), citizen developers (those who work with specialists to develop new AI capabilities), and data scientists (those who create and deploy AI tools.) Creating a workforce strategy that represents employees’ various levels of AI usage and expertise ensures that future implementations are tailored for the right user.
- Combining the strengths of humans and AI is more effective and realistic than using AI as a replacement. For example, contact center associates at a leading automotive manufacturer were struggling to quickly locate the right information to assist customers. We introduced an AI-powered bot to listen to the conversations and provide suggested responses as well as supporting knowledge articles, which allowed the associate to focus on the conversation. The partnership between bots and humans resulted in a 2 percent increase in first call resolution and a 5 percent increase in customer satisfaction.
Key takeaway: AI implementations are only as successful as the people that are prepared to utilize it. While AI is making some jobs obsolete, in other cases, it makes more sense to use AI to enhance existing roles.
Digital and human minds combined
The race for automation is like a hurdle race. Humans and their automated co-workers need to practice cooperation and successful handoffs to bring the best out of each other. Every organization is at a different point in the journey to automate, and while some are more ahead than others it’s important to do it right and reach the destination on your terms.