Tag Archives: Human Resource Management Articles

Three Ways for Contact Centers to Maintain Post-Holiday Momentum



By Ben Bekhor

For retailers and contact centers, the holiday season doesn’t end January 1. The fact is, post-holiday sales, gift returns and exchanges, and questions about setting up new devices, toys, furniture, and more keep customer experience (CX) centers humming well into the new year.

Combined with the wide plethora of digital options consumers have to connect with brands (including in-app messaging, social media chatbots, voice assistants, and more), contact centers can expect a higher-than-average number of consumer touch points during the post-holiday season.

The challenge is keeping employees motivated and engaged once the holidays are over, which is critical when you consider the steady rate of low unemployment and resulting labor shortage. In truth, it’s a challenge contact centers need to address proactively if they want to retain the top talent they worked so hard to win ahead of the holiday season.It’s important that contact centers endeavor to make CX agents feel they can share in their employer’s successes and reap the rewards of their labor Click To Tweet

While wages are always an important contributing factor to employee happiness and retention, the fact is there are multiple avenues through which contact centers, and the brands they represent, can boost employee satisfaction year-round. Options include continuous learning, alternative pay options, and long-term incentives.

Here are three ways contact centers can look beyond wages to retain top talent and keep post-holiday momentum alive:

Invest in Growth for Lasting Engagement

Learning and development (L&D) is one of the primary benefits applicants seek when evaluating a potential employer. However, more than half of companies do not have L&D programs in place to train workers for skills of the future. This naturally sets in motion fears and rumors of job automation and displacement. However, artificial intelligence (AI) has the potential to create more jobs (133 million by 2022) than it’s poised to displace (75 million by 2025).

The post-holiday season is the perfect opportunity for contact centers to skill up employees to work alongside AI-driven tools—chatbots, voice assistants, or automated texting—if they want to stay relevant, maintain a highly skilled workforce, and beat out competitors. Walmart, for example, has invested nearly $3 billion in training, education, and higher wages. Their training programs boast a strong focus on technology, as well as a blend of traditional classroom learning with experiential, on-the-job training. As the nation’s largest employer, this means providing hundreds of thousands of US employees with skills they might not have acquired otherwise.

Contact centers may also consider offering continuous learning opportunities in the form of massive open online courses, which offer instruction on a wide variety of subjects such as coding, business management, and languages. These enable CX agents to stay engaged in their day-to-day tasks while improving skills in areas that foster their long-term growth within CX. Additionally, L&D offerings create an opportunity for agents to grow into promotions (and, inherently, higher wages), which in turn allow contact centers to benefit from a more professionally driven and motivated staff.

Prioritize the Perks That Matter to Individuals

While high-profile brands such as Amazon and Disney are paving the path for even more competitive hourly wages for customer service representatives, contact centers might consider offering alternative pay options to retain top talent—either instead of or in addition to increased wages.

Perks and benefits most sought after by employees include flexible hours or remote work options—favored by 38 percent of employees according to a recent survey by beqom; incentivized bonuses, such as more paid time off or cash prizes as the result of high resolution numbers (that is, resolved inquiries); and personalized benefits, which enable employees to better achieve work-life balance, such as on-site childcare, fitness reimbursements, or tuition assistance.

What’s key is for contact centers to leverage relevant employee data (ascertained through AI-driven compensation management platforms, or even employee surveys) about the types of benefits that would most support employees’ individual needs and, as a result, help to ensure their long-term employment. Remember that people are interested in certain benefits at different stages of life. For example, a Gen Z employee might appreciate tuition assistance as part of their compensation package, whereas a late-millennial might be more geared toward higher 401(k) matches.

Consider Long-Term Incentives for Loyalty

Contact centers that want to retain workers and keep them motivated long-term should explore long-term incentives (LTIs). Sweetening 401(k) plans with higher matches or increased vesting over time, as well as profit sharing or deferred cash, can be critical to ensuring the longevity of top talent. What’s more, employees will have the incentive to stay if they feel their employer has their long-term financial security at heart.

LTIs also incentivize employees to focus on (and hopefully surpass) specific performance goals. For example, profit sharing might be a benefit exclusive to employees that exceed performance metrics, while sabbatical programs might only become available to employees after they’ve achieved a certain status or worked a certain number of years at their contact center. The goal of LTIs in terms of achieving employee retention is to align employee needs with the contact center’s expectations for individual job performance so employees feel that they are recognized and valued contributors to their contact center’s success.

These strategies to foster growth, personal balance, and long-term financial security are three easy methods for contact centers to leverage year-round, but they are critical steps to deploy when employee motivation slumps after the busy holiday season. When it comes to incentivizing workers to maintain productivity after January 1, it’s important that contact centers endeavor to make CX agents feel they can share in their employer’s successes and reap the rewards of their labor. Doing so helps contact centers retain the top talent they need to make the post-holiday season a success and grow a dedicated, motivated, and high-performing staff for many years to come.

Ben Bekhor serves as vice president, human resources, Americas for Sitel Group, a leader in the delivery of traditional and transformational customer experience management—business process outsourcing (BPO). Bekhor oversees all aspects of HR operations for the US, Canada, Mexico, Panama, Nicaragua, and Colombia, including compensation and benefits, talent acquisition, talent management, and learning and development.

Automation Success Requires Human Involvement



By Dan Somers

Automation and artificial intelligence (AI) can help save contact center costs, but primarily it increases customer satisfaction by speeding up responses and reducing customer efforts. Contact center automation falls broadly into three categories:

  1. Speeding up or automating the helpdesk agent (staff who capture and triage queries)
  2. Speeding up or automating the case handler (staff who resolve queries)
  3. Increasing self-service automation (chatbots, searchable FAQs, and self-help tools)

AI Challenges

Certain limitations of AI cannot guarantee the accuracy expected by customers, however. Some of these limitations are temporary, such as the comprehension capabilities of speech recognition, which will continue to improve. But other limitations relate to how machine-learning robots work.

All machine learning relies on studying real-life training data to predict or classify current data. The training data needs to be “labeled”—that is, it must have an outcome or class (tag) assigned to it, as judged by a person. For example, if a query comes in that says, “My server has crashed and is showing a blank screen,” then the chatbot will assign the best label it has in its training set, which might be “server crashed.”

However, in this example, a label of “faulty screen” might be assigned instead. The customer would be annoyed if the bot attempted to address a faulty screen issue instead of a server crash. This is an example of potential ambiguity. Furthermore, new issues will appear from new product launches, changes in quality, and evolution in the market. Lastly, the way people describe or view the same problem is more variable for certain issues than others.

Human-in-the-Loop

The only safe way of deploying bots within a contact center is to have a human-in-the-loop. This person will validate what the bots are doing, preferably with minimal impact to the customer.

So, who and where is the human-in-the-loop? It turns out that there are four general ways for humans to validate some or all of the process:

  1. A helpdesk agent can validate suggested responses before sending.
  2. The customer can validate that the response—or the question they asked—was comprehended.
  3. A third-party solution provider can check the performance of the bots and curate the process; this might be an internal or external data science team.
  4. The knowledge base manager can check the bots for satisfactory performance.Automation of contact centers yields promise, although not without humans-in-the-loop to maintain its performance. Click To Tweet

Considerations of Humans-in-the-Loop

There are pros and cons of different human-in-the-loop approaches. Some of these points are technical in nature but have substantial implications.

Agent: Some solutions on the market have AI recommend the next “best response” for the agent. The agents validate the response, not the categorization. For example, if two queries—“The strawberries I bought were tasteless” and “The strawberries I bought made me sick”—both lead to the same recommended response, “We’re sorry; please accept our voucher,” then the categorization models will degrade as they are not being updated with the accurate root cause.

Also, the insight generated by the models won’t allow executives to monitor product quality, design, and usability to then generate the self-service tools that can reduce contact center traffic. With this solution, other humans-in-the-loop will still be required elsewhere.

Customer Validation: If customers provide the required validation, it is scalable, but customers may not like having to correct their original query or the responses. If the query produces a new category, then there must be a process to deal with it. Fundamentally, the system cannot be relied upon with just these humans-in-the-loop.

Solution Provider: This is the status quo for most machine-learning deployments in real-world environments: a data science team, either internally or a third-party, sets up, curates, and retrains the models on a regular basis to maintain their performance. The pros are that these are the only humans-in-the-loop required. The cons are that these professionals are in short supply.

Knowledge Base Manager: This role has the most hidden potential benefit for having a human-in-the-loop. In a nontechnical environment, they will provide business rules on how to handle queries, as well as the training, trouble-shooting guides, and fault tree analysis to resolve issues.

In terms of their day-to-day role, they will be aware of product launches and modifications, but they also can use the rich insight of the labels coming from the contact center (both triage and resolution) to make improvements to both the knowledge base and the process. This includes updating the FAQs so customers can better use self-service. Also, this insight can inform other functions, such as product quality, product design, and customer experience, to help guide improvements.

Optimized Learning

A new approach that only requires a few humans-in-the-loop can exist because of a new technology called optimized learning. This is a form of machine learning that builds models but invites training from a human in such a way to minimize human input and still provide maximum performance. It is ideal for spotting new signals and improving existing ones.

Optimized learning doesn’t need to be in-line and suffers from none of the downsides of other approaches. Instead, it requires a fraction of the labeling otherwise required, even in a changing environment. The implications of this are profound. It means that a call center would only need to retain a few agents after the automation implementation, and they would handle the training that the optimized learning invited them to do in an offline capacity. This would maintain the models for labeling queries to generate both automation and insight, thus speeding up and reducing issues.

The rest of the automation would come from the rules originating from the knowledge base manager, as informed by the bots. This paves the way for improving chatbots and self-serve, searchable FAQs to free up contact center staff.

Conclusion

Automation of contact centers yields promise, although not without humans-in-the-loop to maintain its performance. There are many different flavors for human-in-the-loop AI automation. With new technology appearing, an optimized system is possible with a minimum number of humans who don’t need any data science skills. There is now no reason why the contact center of the future needs to look like those of the present. The same applies for the customer experience too.

Dan Somers is the CEO of Warwick Analytics, which provides call center automation solutions to address voice of customer (VoC) data, chatbots, service desks, and complaint handling.