All Posts By

Shirley Hung

Using Technology to Assess Contact Center Agents’ Language Skills | Blog

By | Automation/RPA/AI

Do you know anyone who hasn’t had a frustrating experience because the contact center rep they interacted with didn’t speak their native language? We didn’t think so.

The truth is that while enterprises have multiple business reasons for establishing their contact centers in offshore locations in Eastern Europe, Latin America, and Asia Pacific, the reps’ language and communication skills often have a negative impact on the overall customer and brand experience.

And although many companies have developed their own solutions to assess candidates’ language capabilities, they’re plagued with multiple challenges, including:

  • Resource intensive: Developing language assessment solutions takes considerable time and resources. They need to be thoughtfully designed, particularly around the local nuances of the markets where they are being leveraged. This can escalate the development budget and timelines, and put an additional burden on L&D teams.
  • Lack of standardization: Most language assessment tests are developed by in-house experts in a specific region. This approach can be detrimental to organizations with operations in multiple geographies, because it lacks consistency across regions, and can leave gaps in the evaluation criteria.
  • Involvement of human judgment: Because humans are responsible for evaluating candidates, a lot of subjectivity comes into play. And human bias, whether intentional or not, can greatly reduce transparency in the candidate selection process.
  • Maintenance issues: The real value of these solutions depends on their ability to test candidates for unprepared scenarios. But regularly updating the assessment materials to keep the content fresh and reflect changing requirements further strains internal resources.

Third-party vendors’ technology-based solutions can help

Commercial language and communication assessment solutions have been around for years. But innovative vendors – such as Pearson, an established player in this market, and Emmersion Learning, which incorporates the latest AI technology into its solution – are increasingly leveraging a combination of linguistic methodologies, technical automation, and advanced statistical processes to deliver a scalable assessment that can predict speaking, listening, and responding proficiency.

For instance, technology-driven solutions may test candidates’ “language chunking” ability, which means their ability to group chunks of semantic meaning. This concept is similar to techniques that are commonly used for memorizing numbers. By linking numbers to concepts, a person can be successful in retaining large sequences of digits in working memory. Without conceptual awareness, memorization is hard.

During an assessment, through automation and AI, the candidate may be asked to repeat sentences of increasing complexity. Success in this exercise relies on the candidate’s ability to memorize complex sentences, which can only be done when they can chunk for meaning. A candidate’s mastery of an exercise to repeat sentences of increasing complexity is a great predictor of the candidate’s language proficiency.

Organizations that embrace technology-based solutions for language assessments can anticipate multiple benefits: reduced costs, decreased hiring cycle times, improved quality of hires, better role placement, freed time to devote to value-add initiatives, and improved customer experience and satisfaction. Ultimately, it’s a triple win for the organization, its candidates, and its customers.

Race to Reality: Full Contact Center Automation vs Fully Automated Cars | Blog

By | Automation/RPA/AI, Blog

The contact center industry is changing considerably due to technology enablement. Contact center automation is rapidly becoming a priority as centers increasingly embrace technologies such as artificial intelligence (AI), chatbots, robotic process automation (RPA), and robotic desktop automation (RDA) to handle customer interactions on rote queries like account balances, package tracking, and reservation confirmations.

A similar transformation is also taking place in personal transportation. Advancing technologies and intense competition are driving amazing strides in the autonomous vehicle industry. While cars aren’t yet 100 percent self-driving, companies like Tesla are already offering advanced driver assistance solutions that can pretty much take control of driving, albeit with human supervision.

With the perceived nature of each of these two industries, it’s easy to assume that contact centers will be fully automated in far less time than the two to three years some believe it will take for autonomous driving solutions to get you from one point to another without human intervention.

However, this is an incorrect assumption.

Indeed, counter-intuitive as it seems, it’s much more difficult to completely automate contact centers than it is to automate driving. Why?

Driving involves a large, but still finite, number of scenarios that need to be programmed for. But a contact center environment can throw up potentially infinite unique problem statements and challenges that enterprises cannot possibly predict and program for in advance. Yes, AI helps, but even that can only get you so far. At the end of the day, the human mind’s problem-solving ability far exceeds anything that the current or foreseeable technology can offer. And while most people would be more than happy to let robots take over the wheels on the road, they still expect and require human touch, expertise, and judgment for the more complex pieces that usually make or break the customer experience. Technology just isn’t sophisticated enough to handle these yet.

The degree of contact center automation that can be leveraged within an industry varies by process complexity

Although technology use in contact centers is in the early stages, we are already witnessing higher agent satisfaction and lower attrition rates in an industry that has one of the highest churns globally. And as robots increasingly take care of customers’ simple, straightforward asks, we certainly expect agents’ satisfaction to increase.

Of course, agent profiles will continue to evolve as they are required to deal with more challenging and complex issues leveraging machine assistance. This will, in turn, demand greater investments into talent acquisition and upskilling programs.

It will be interesting to see how all of this plays out in the next few years as technology becomes increasingly advanced and capable. The only thing we can say with certainty is that the customer experience of the future will be much more pleasant as irritations like long wait times, inept IVR responses, and repetitive conversations with agents who hold incomplete information become issues of the past…or, shall we say, smaller and smaller objects in our rearview mirrors?