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NICE

NICE CXone now available natively on Azure

 960 640 Stuart O'Brien
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NICE has expanded its partnership with Microsoft, delivering CXone on Azure to create what it says will be frictionless, personalised digital customer experiences.

NICE has received Top Tier status, Microsoft’s highest level partner designation, for Azure IP Co-sell driving deeper collaboration and a strong go-to-market momentum.

The partnership leverages the power of CXone to help organizations globally to transform their customers’ experiences and build a digital first customer service operation.

With a joint global go-to-market co-selling strategy working together with key strategic accounts enabling rapid time to value, extreme agility and a faster path to the cloud, NICE and Microsoft will accelerate organizations’ adoption of CXone.

CXone’s advanced AI and full portfolio of voice and digital solutions and with its integrations with Teams, Dynamics, Nuance, ACS (Azure Communication Services), and Customer Insights, allows organizations of all sizes to create proactive, brand-differentiating interactions that exceed the expectations of the digital-first customer and goes beyond the boundaries of the contact center.

Paul Jarman, CEO, NICE CXone, said: “Consumers today expect fast, convenient digital and self-service options. Through the expanded partnership with Microsoft and with CXone now available on Azure, and with our co-sell partnership, we are taking another step in the frictionless revolution allowing organizations to meet their customers wherever they choose to start their journey and create a cohesive digital experience. This better-together offering will foster customer experience interaction (CXi) modernization and provide a standard-setting choice for customers.”

Consumers want more self-service options

 960 640 Stuart O'Brien
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81 percent of consumers say they want more self-service options yet only 15 percent of consumers expressed a high level of satisfaction with the tools provided to them today whereas businesses believe 53 percent of consumers are very satisfied with their self-service.

That’s according to the NICE 2022 Digital-First Customer Experience Report, which highlights significant gaps between company and consumer perceptions of current digital- and self-service channels.

This despite 95 percent of companies reporting a major increase in self-service requests in 2021, indicating a rapid growth in consumer demand for greater speed and convenience.

The 2022 Digital-First Customer Experience Report was designed to compare the perspectives of businesses and consumers regarding self-service and digital channels, drawing on responses from 1320 respondents in the United States and the United Kingdom.

NICE noted that consumer expectations are increasing as digital and self-service channels proliferate and evolve, which has led to companies searching for insights into customer experience and brand loyalty. The NICE report is intended to meet that need, revealing potential blind spots among service providers and helping them improve their digital and self-service options. For example, although 36 percent of consumers say they would like to see companies make their self-service smarter, less than 11 percent of businesses are making that a priority.

More generally, the NICE report indicates that 95 percent of consumers place great importance on customer service which impacts brand loyalty. Online self-service and easy access to their preferred channels are two of the top customer service factors in their decision regarding brand loyalty. The majority of consumers (57%) surveyed said they would abandon a brand after one or two negative digital customer service interactions, yet most businesses tend to underestimate how quickly that could happen. Nonetheless, the survey does show that companies recognize the importance of current digital channels to consumers and are attempting to improve their availability. In 2022, the top digital channels companies are planning to expand significantly are chat (47%), website access (44%), and search options (42%).

Paul Jarman, NICE CXone CEO, said, “Avoiding friction is the key factor today in shaping opinions and differentiating between brands consumers love and those they feel are not worth their time. We undertook the 2022 Digital-First Customer Experience Report in order to provide companies with the consumer’s viewpoint and to help them set priorities that drive frictionless experiences. While focusing on digital-first interactions, our report underscores the importance of both agent-assisted and self-service channels, with businesses primarily wanting the ability to choose whichever option they prefer at any given time. This confirms the need for CXi–Customer Experience Interactions–a new approach that focuses on the end-to-end digital customer journey, requiring a complete customer experience platform that only NICE CXone offers.”

You can download a copy of the report is available here.

NICE launches Enlighten XO

 960 640 Stuart O'Brien
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NICE has commerced the roll out of Enlighten XO, which automatically generates insights from human conversations to build smart self-service with advanced AI.

Additionally, the platform streamlines the development of digital self-service applications by injecting data from past interactions to optimise future self-service experiences.

NICE says organisations can now take a data-driven, self-learning, empirical approach to increase self-service effectiveness and drive exceptional experiences.

In Forrester’s publication, “Predictions 2021, Customer Service,” the analysts reported, “Customer behaviors and communication preferences have permanently shifted; in 2021, brands will see a 40% increase in digital customer service.”

NICE says that in today’s digital-first world, organisations need to deliver an effortless experience on the consumer’s channel of choice to compete in a transformative industry.

The new solution analyses 100% of interactions from any platform to discover the best opportunities for automation, taking the guesswork out of self-service development with purpose-built AI models that identify customer intents, training phrases, and problem-solving activities that ensure success.

Armed with superior data and insights, organizations can accelerate their digital transformation and turn self-service into a competitive advantage.

“Soaring demand for digital service is driving organizations to accelerate their digital CX transformation and drive full resolution on their digital platforms,” said Barry Cooper, President, NICE Workforce & Customer Experience Group. “Enlighten XO makes self-service applications smarter by deriving intelligence from consumer conversations across all channels. We’re excited to introduce Enlighten XO to the market and make self-service capable of creating engaging experiences.”

NICE launches of CXone Expert following acquisition of MindTouch

 960 640 Stuart O'Brien
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NICE has announced the launch of CXone Expert, following the acquisition of MindTouch Inc., a San Diego-based cloud-based knowledge management software for customer experience.

CXone Expert is a comprehensive artificial intelligence (AI)-powered knowledge management solution that reduces friction by projecting personalized content to customers seeking self-service while injecting crucial insights throughout the customer journey.

CXone Expert eliminates the frustration with today’s self-service experience by infusing AI and data, turning bots into smart AI-based agents.

When communicating with customer service organizations, today’s consumers expect choice and flexibility similar to what they enjoy with friends and family. CXone Expert brings effortless self-service experiences through the digital channels customers turn to first, from mobile applications and search engines to chatbots and websites by surfacing the right content when, where and how they want it. The solution provides a seamless experience all the way to human assistance by giving agents the full context and power to see the customer’s journey and create an intelligent, constructive conversation.

“We face a new breed of next-generation consumers who live in a digital world,” said Paul Jarman, NICE CXone CEO. “They want smart self-service, and they would like to get things done digitally on their own if they can. With CXone Expert, we are helping companies apply smart self-service best practices using AI technology to meet consumer demand for faster, more convenient experiences.”

According to the 2020 NICE CXone Customer Experience (CX) Transformation Benchmark, Consumer Wave, 8 in 10 consumers are more willing to do business with companies that offer self-service options, yet only 61 percent agree that companies are offering easy, convenient self-service. When rating self-service channels, only one-third of consumers are highly satisfied.

Moreover, half of consumers who start with self-service report they are transferred to a live agent. Two-thirds of those who are transferred say they need to repeat the information they previously provided in the self-service channel. CXone Expert helps close that gap by showing agents what customers have searched for and seen prior to submitting a case, offering a truly seamless omnichannel experience.

CXone takes a holistic approach to improving both agent and customer experiences, helping organizations of all sizes modernize and remain agile and resilient in today’s increasingly digital landscape. CXone provides the most comprehensive digital-first omnichannel offering in the Contact Center as a Service market, as the first and only platform unifying best-in-class omnichannel routing, analytics, workforce optimization, automation, and artificial intelligence on an open cloud foundation.

Analyst Report: AI Helps Align Agent Performance with Customer Expectations

 960 640 Abby Monaco
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By Abby Monaco, Senior Product Marketing Manager, NICE

Using AI capabilities to deliver agent guidance in real time, at the exact moment it’s needed, helps contact centres maximize agent performance, delight customers and reduce costs. That’s the finding of a report by Aberdeen, which surveyed more than 300 contact center leaders across industries around the world.

Aberdeen found that the No. 1 priority of contact centres, regardless of industry, is to improve the customer experience, followed by reducing service costs to drive operational efficiency.  In the report, “The ROI of Real-time Agent Guidance: How AI Helps Align Agent Performance with Customer Expectations,” Aberdeen Vice President and Principal Analyst Omer Minkara details opportunities for improvement for contact centres considering implementing AI.

Aberdeen defines contact center AI as encompassing:

  • Artificial intelligence: Automated reasoning and decision-making capabilities based on insights uncovered through machine learning algorithms.
  • Machine learning: Technology applications that learn by themselves by analysing a pattern of historical and recent data.
  • Prescriptive guidance: Tools used to analyze structured and unstructured historical data to make predictions and suggest decision options.
  • Predictive analytics: Tools to predict future behavior of customers.
  • Automation: Tools used to automate the execution of tasks such as customer routing, agent scheduling and quality assurance.

AI enables organizations to monitor and analyse 100% of customer interactions in real time and give agents the contextual guidance they need to turn the conversation around in the moment. Supervisors gain relevant and accurate insights that help boost their productivity and inform the one-on-one coaching and guidance they offer to agents. In fact, firms using AI report a 2.9% annual improvement in the amount of time supervisors spend helping agents, compared to a 0.1% worsening by contact centers without AI capabilities.

The benefits of AI in the contact center extend to customers as well. According to the report, contact centres leveraging AI capabilities like speech analytics, text analytics and journey analytics enjoy superior CX performance improvements that include:

  • A 10.5% increase in customer retention (compared to a 3.2% improvement for contact centers not using AI).
  • A 3.5x greater improvement in customer satisfaction (10.1% vs. 2.9%).
  • An 8.8% improvement in customer effort score (compared to 1.1%).

“Modern contact centers leverage AI capabilities to take quality assurance to the next level,” Minkara wrote. “Instead of periodic reviews and subsequent agent coaching and guidance, they use AI capabilities to review all interactions in real time – using the resulting insights to provide agents with real-time contextual guidance.”

“This helps shorten the time to make necessary improvements in agent skills and activities to address evolving client needs,” he added. “It also minimizes customer frustration and churn due to inefficiencies in service delivery activities.”

Minkara concluded the report with a strong recommendation that contact centers not currently using AI to boost agent productivity and performance consider doing so. AI models can learn from and be trained using an organization’s historical interaction data, enabling quick results. Read the full report here.

How – and Why – to Analyze Sentiment

 960 640 Abby Monaco
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By Abby Monaco, Senior Product Marketing Manager, NICE Nexidia

“I have terrible news,” your boss wrote in an email late last night. “The project has officially been delayed.”

Without any additional context, this news could be cause for joy – you’ll no longer be working all weekend to deliver on a deadline – or significant trepidation, particularly if the delay was caused by an error you made. The same word – terrible – can be used sincerely or jokingly, with very different sentiment attached to it as a result.

Sentiment is critical when it comes to customer service, and sentiment analysis is being increasingly used to measure emotion in customer and agent interactions.  After all, it’s not always about what is said but rather how it’s said and what emotions are conveyed. As important as it is to analyze the words that are spoken or written in an interaction to gain clues as to whether a customer interaction is positive or negative, it’s even more important to analyze sentiment in agent-customer interactions.

Sentiment analysis is the practice of assessing customer input to determine attitudes and opinions about brands, products, marketing campaigns and more. It relies on natural language processing, machine learning and computational linguistics to identify, extract and quantify subjective information from phone, chat, email, social media and more. Its use is increasing in part due to the widespread shift toward omnichannel customer service. With thousands, or hundreds of thousands, of interactions over a variety of channels, contact centers simply can’t rely on manual analysis of interactions to understand how customers feel about their business.

Sentiment analysis has far-reaching applications. The Obama administration famously used it to measure public opinion in the weeks and months leading up to the 2012 presidential election, and politicians and brands alike have since embraced the approach to better understand public attitude and opinion.

In the contact center, sentiment analysis allows the organization to analyze customer interactions to:

  • Uncover areas in the business that need improvement.
  • Monitor areas critical to customer loyalty and retention.
  • Monitor agent behaviors.

“When you measure people’s reactions interacting with your support team, you get a clearer picture of their level of satisfaction,” Jia Wertz wrote in Forbes. “This allows you to address customer service issues more efficiently, based on a different type of feedback – unfiltered, less intrusive and more honest.”

There are two basic techniques for sentiment analysis:  traditional, rule-based sentiment analysis, which relies on a dictionary of words labeled by sentiment, and artificial intelligence-powered sentiment analysis, in which a machine learning model is trained to recognize sentiment – and to continue to learn and evolve.

To be truly effective, the sentiment measurement must be sophisticated enough to identify the relative emotion of agents and customers separately for more accurate results. AI-powered sentiment analysis employs language models to find positive and negative words and phrases, spoken or written, as well as AI machine learning that has been trained to predict the outcome of the interaction. Models must be trained to score words and phrases carefully within the context in which they’re spoken.

Sentiment models go beyond language with added features that create greater accuracy in sentiment scores. Among the factors they consider are:

  • Laughter detection, which can indicate a positive change in an otherwise negative conversation.
  • Crosstalk (where both parties talk over each other), which can indicate confusion or frustration.
  • Changes in pitch, tone or speaking rate, which can signal changing satisfaction during the interaction.
  • When in the interaction the words or phrases occurred; studies show that the latter portion of an interaction drives customers’ reported satisfaction more heavily than the former.
  • Interaction length; the longer the interaction, the more opportunities there are to drive a sentiment score, so effective sentiment analysis normalizes longer interactions with shorter ones.

AI-powered sentiment models also score interactions as starting positive and moving to negative, or vice versa, to allow organizations perform root cause analysis. There are many causes of positive and negative interactions, such as problems with a process or product or frustration with an agent. An interaction that begins positive and ends negative can be due to a confused agent who’s unable to help or the customer not liking the answer they get (i.e., that an overdue bill has been sent to collections).

Organizations around the world are already using sentiment analysis with advanced AI techniques to better understand the customer and act on that understanding. While sentiment models score 100% of interactions, measuring sentiment is most effective when considering the larger picture; while it’s important to identify a single interaction, particularly when you can provide real-time guidance to turn a call around, it doesn’t provide insight into trends surrounding negative calls and the topics driving them.

“As with any new technology, the value is not in the information you mine, it’s in what you do with it,” Futurum Research Analyst Daniel Newman wrote in Forbes. “The power of AI isn’t in replacing our need to understand our customers, it’s in using tools to understand them better and then act on those understandings, for the better.”

Learn more about how sentiment analytics is only one of the many ways to drive organizational success, and how AI-enabled contact center analytics transcends the limits of traditional analytics. Our easy to read guide explains how businesses using AI-enabled contact center analytics are taking action to improve customer experiences, identify complaints, prevent fraud and more.

How Analytics Can Help You Deliver Superior Customer Service

 960 640 Lauren Maschio
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Lauren Maschio, Product Marketing Manager, NICE

Consumers today expect world-class customer experiences, and delivering the fast, personalized service they demand requires that you build analytics into the core of your business. Analytics can deliver a competitive advantage by improving the quality of your interactions with customers, and with the contact centre the most vital point of contact between your company and your customers, that’s critically important.

Analytics encompasses far more than trends and insights, however; trends and numbers will get you nowhere unless your analytics program is driving the business outcomes you desire rather than simply identifying trends. Here’s what you need keep in mind to truly impact CX and CSAT:

Leverage the power of AI

AI technology has become the driving force behind innovation ranging from self-driving cars to e-commerce recommendations. In the contact center, the use of prebuilt AI technology for analytics has moved from a nice-to-have to an imperative due to its ability to transform customer service, both in terms of quality as well as efficiency. While machine learning examines and compares data to find patterns and explore nuances, AI takes it a step further, continually evolving in how it enables machines to behave in a way previously thought to require human intelligence.

In the contact center, that takes a variety of forms, including:

  • Autodiscovery, or the use of unsupervised machine learning to surface unknowns in interactions data, which makes it possible to focus deeper analysis on the topics that are most critical to your business.
  • Sentiment analysis, which is a proven predictive indicator of customer satisfaction such as tNPS or CSAT surveys.
  • AI behavior models, which score the agent soft-skill behaviors that influence the sentiment analysis on all interactions.

Move beyond speech analytics

Your agents’ interactions with customers are no longer limited to the phone; increasingly, customers are reaching out via chat, email, social media and more. If you really want to know what your customers are talking about, you must be analyzing interactions over all channels – text and audio.

An omnichannel approach that covers all channels of interactions enables you to analyze a variety of characteristics, including:

  • Speech time/non-speech time, or the presence and amount of speaking vs. silence in calls over a period of time. You can identify both the agents who have the highest speech or non-speech time as well as the reasons for call silence.
  • Agent response time in a chat, or how long it takes the agent to respond to a chat request.
  • Customer sentiment on social channels, including through text, hashtags and more.

Focus on outcomes, not data collection

When implemented in a way that drives outcomes rather than simply outlining trends, analytics offers tremendous potential to improve CX and CSAT, as one financial services provider found. After implementing an analytics program across its contact center, the provider discovered that agents were missing information, leading to long hold times. By training agents better, the provider was able to:

  • Decrease hold times.
  • Increase customer satisfaction.
  • Save more than $540,000 annually.

Keep evolving

If there’s one constant today, it’s that change is ongoing. Your sales and service models aren’t static, so your analytics program shouldn’t be either. Your business — and the language your agents and customers use when speaking about your unique environment, products and services – will naturally evolve, and your analytics program must be able to adapt in response.

To learn more about how analytics can give you the tools you need to drive the outcomes your business desires and the service your customers demand, download the ebook, AI-Enabled Contact Center Analytics For Dummies.   

NICE unveils NTR-X for financial services

 960 640 Stuart O'Brien
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NICE has introduced NTR-X, a fully integrated, cloud-ready omnichannel compliance recording and assurance solution.

Building on NICE Trading Recording, NTR-X captures all modalities of regulated employee communications – traditional, unified and mobile – in a single platform.

Offering a consolidated, centralized approach to managing recording estates and footprints, NICE’s NTR-X can be deployed globally while still enabling firms to adhere to local capture and storage requirements. Offering financial services firms the benefit of a central vantage point into all global regulated users and communications, NICE’s NTR-X reduces regulatory risk, removing maintenance hurdles and reducing the need for costly, dedicated, local IT resources.

Two top 10 global investment financial institutions that have already selected NICE’s NTR-X, cited its higher performance, lower total cost of ownership (TCO), smaller footprint, and its ability to simplify and centralize management of their global recording requirements.

Anna Griem, Senior Analyst, Opimas, a leading capital markets consulting firm, said: “Although the rest of the world has changed, trade-related recording obligations have not. Firms are adjusting to monitor their workforces, which are now often remote. Now more than ever, firms are demanding a lot from their communications recording solutions, especially in terms of the channels they are able to cover, the flexibility of deployment options, and the option to roll out improvements and new services easily across their user base.”

Chris Wooten, Executive Vice President, NICE, added: “As the environments in which financial services and energy trading firms operate become inherently more risky, costly and complex, NICE’s passion for innovation has led us to create a one-of-a-kind compliance recording and assurance solution, offering simplified compliance for a complex world. Regardless of the communication modalities regulated employees use or where they work from, firms can cost-effectively manage their entire global recording footprint to increase compliance with key regulations. NTR-X also provides a seamless upgrade path for current NICETrading Recording (NTR) customers and a proven cloud-ready platform that speeds future migration.”

NICE helping with COVID-19 vaccine global distribution efforts

 960 640 Stuart O'Brien
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NICE is ramping up support for service and information centers across the entire COVID-19 vaccine supply chain with its CXone cloud platform.

The vaccine supply chain is comprised of three main critical stakeholders: vaccine manufacturers, federal and state agencies responsible for distribution and healthcare providers that are administering the vaccine.

As governments around the globe are working diligently to build and scale this supply chain, NICE says CXone is playing a critical role in eliminating bottlenecks, ensuring a smooth process and guaranteeing flawless and clear communication throughout.

Organizations are now working to quickly supply and administer tens of millions of doses worldwide to help end the devastating pandemic. They are moving quicker than ever before to produce, distribute and communicate about the vaccine and need a reliable platform to allow them to be successful.

For example, two of the leading approved vaccine manufacturers are now using CXone, dozens of state and government agencies are ramping up their capacity with CXone to prepare for increases in demand and numerous healthcare providers and pharmacies are already relying on CXone to serve their patients and customers.

“This is a historic moment, and contact centers play a critical role in efficiently distributing and building trust in the COVID-19 vaccine,” said Paul Jarman, NICE inContact CEO. “As the vaccine rollout unfolds, information and service centers across the pharmaceutical industry, health departments, government agencies, distribution companies and pharmacies need to quickly ramp up customer service as needed. CXone equips all of them with innovative cloud technology that drives flexibility, reliability and agility in the face of such a grand-scale effort.”

Given the high stakes, now more than ever, extreme agility, scalability and speed to turn-up is crucial for the information and service centers of all the parties involved in distributing, administering, and monitoring the vaccine rollout. To provide the required extreme agility, CXone customer experience cloud provides rapid deployment on a scalable, secure and reliable platform to support agencies that are serving on the front line in the fight against this global pandemic.

Contact center agents can efficiently respond to inbound inquiries about the vaccine as well as proactively push information to citizens via SMS or digital messaging. Furthermore, the increased adoption of the CXone digital self-service and chatbot technologies acts as a force multiplier scaling and simplifying service in light of the sharp increase in volumes.

Working from Home: How Blurred Boundaries Affect the Contact Center

 960 640 Adam Aftergut
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Part three of a three-part series by Adam Aftergut, Product Marketing Manager at NICE, on the root causes of work-from-home challenges faced by contact center agents and their employers…

As we detailed earlier in this series on work-from-home challenges, changing boundaries are having an impact on staffing and performance in the contact center. In addition to a new separation between the employee and the workplace, there’s also a blurring of boundaries in the employee’s workday: With many agents now working from home, the boundaries between work and home life have gotten a lot fuzzier.

While many agents enjoy the ability to work from home, it nevertheless creates new challenges. Living spaces have been converted into makeshift offices and interruptions are unavoidable, making it difficult or impossible to truly focus. Over time, distractions and a lack of structure can affect productivity – in fact, 78% of business leaders think hybrid and home-working models have a negative impact on productivity. Over the long term, a lack of boundaries can hamper work-life balance and ultimately also increase burnout, which has a detrimental effect on employee engagement.

Overcoming the challenges this blurring of boundaries causes for agents also overcomes them for the contact center, and vice versa, ensuring that operations run smoothly. Here’s how.

Employers need staffing agility; employees need flexibility

With many families working and learning from home simultaneously, call volumes are less predictable and don’t conform to previous contact patterns, which means that employers need to be very agile in their workforce management capabilities, tools and policies. At the same time, agents working from home need greater scheduling flexibility to deal with unexpected interruptions and obligations in the home environment – but they can also have an easier time pivoting from free time to work time in order to cover unconventional shifts. A failure to recognize these changes runs the risk of greater staffing gaps for the operation and increased employee frustration.

How technology can help you solve this challenge: Contact center leaders can leverage Intelligent Intraday Automation® for more elastic staffing. A solution that continuously analyzes fluctuating staffing needs, identifies shift change opportunities and communicates them to agents can help contact centers prevent overstaffing and understaffing. The agent can interact with such a solution in multiple ways, including through a portal for automated self-service schedule changes and automated “push” offers of preapproved schedule change opportunities sent via text message, email, in-app messaging or displayed as alert popups on the agent’s desktop.   

Employers need occupancy; employees need to avoid distractions and interruptions

Contact centers need to maintain occupancy levels, a key metric that shows the percentage of time employees are occupied, performing call center activities.  However, remote employees are more easily interrupted or distracted at home.

A University of California Irvine study found that it takes an average of 23 minutes and 15 seconds to return to a task following an interruption. This means that home-office distractions can lead to lower agent productivity, effectiveness and service quality. Agents are then unable to meet performance goals, and customer experience suffers.

How technology can help you solve this challenge: Automated KPI-based notifications alert supervisors and agents via text, email, in-app notifications or desktop alert popups when the team or individual agents have hit occupancy and other key goals – regardless of where employees are working from. Alerts and calls-to-action can be used to notify agents that they’re overrunning scheduled activities or have an upcoming event, prompt agents to switch tasks (which can improve focus while adjusting occupancy) and more.

In addition, automated self-scheduling for agents enables employees to achieve unique schedule adjustments that reduce the disruptions inherent in a work-from-home routine, while still ensuring net staffing. One such example of this is NICE Employee Engagement Manager’s (EEM’s) automated self-swap functionality. Rather than having to work through a distraction, such as a repairman working in the home or a child practicing piano, the agent can simply use a preapproved self-swap to move his or her hours around rather than having to take time off or reduce the number of hours they’re scheduled to work.

Employers need consistent team performance; employees need work-life balance

For effective customer service, contact centers need to ensure that their frontline teams operate with consistency and reliability, especially during times of instability. Supervisors and workforce management personnel need to be able to quickly communicate with agents and depend on their commitments. However, when agents feel overworked and overburdened due to a blurring of the lines between their personal and professional lives – and studies have found that the average workday has increased by 48.5 minutes since the widespread move to remote work – burnout sets in and customer service suffers. Unfortunately, just one in three employees say their employers have increased flexibility in recent months to deal with burnout, according to an Eagle Hill Consulting survey.

How technology can help you solve this challenge: Burnout soars when agents have many consecutive days of intense work without breaks or are unable to manage their work-life balance and find themselves pulled into work frequently. Automated self-scheduling, including adjustments like automated shift trades, can help. If opportunities for voluntary time off (VTO), paid time off (PTO) and self-swaps – which are preapproved based on the contact center’s needs – are unavailable in EEM,  there is still the possibility of automated shift trades, which have a neutral impact on net staffing. EEM thus provides a multilayered set of options for agents to achieve work-life balance through highly flexible and patented self-scheduling capabilities while optimizing net staffing.

In addition, communication controls help agents set boundaries between their personal and professional lives to ensure that work does not encroach. Agents can select days and times they can be contacted with scheduling offers, performance notifications and the like. They can choose both when they are willing to be contacted while “off the clock” and how (e.g., email or text message, in addition to in-app messaging and alert popups). If an agent feels the need to completely disconnect from work in order to refresh, EEM’s communications can be silenced during personal time.

Different perspectives, common solutions

With workday boundaries blurred and personal and work responsibilities increasingly intermingled, achieving both productivity and work-life balance can feel like an obstacle course each day. Over time,  the cumulative effects of work repeatedly encroaching on an agent’s personal life can cause burnout. Giving employees a sense of control with automated self-service scheduling increases their satisfaction, and doing so with an intelligent solution ensures alignment with the contact center’s operational needs to consistently improve both day-to-day and long-term operational results.

NICE Employee Engagement Manager (EEM), a key component of the NICE Intelligent WFM Suite, enables contact centers to preserve work-life boundaries in a remote employee’s workday while meeting the needs of the contact center.  The broad capabilities of EEM’s intelligent automation engine not only improve staffing levels intraday and near-term but also drive a wide variety of employee actions for improved performance. Learn more about how EEM helps contact center teams adapt to changing boundaries in the work-from-home environment.

For a more complete understanding of the work-from-home challenges faced by the contact center, see the previous two installments in this series here and here.

Do you need help in generating more efficient schedules and automating the challenge of optimizing your net staffing?

Download our complimentary eBook:  Intelligent Automation and Simulation in WFM for Dummies. 

This book will help you understand how using machine learning based simulation can help create schedules based on true multi-skill efficiencies based on ACD routing rules and skills not just static percentages. It will also help you see how you can automatically and proactively create offers for voluntary time off and overtime based on skills to the exact right agents, thus solving the age-old issue of net staffing optimization.