Next-Gen WFM: What Is Coming Down the Line?

Next-Gen WFM will undoubtedly leverage AI to provide precision, adaptability, and strategic insights, ensuring that businesses stay ahead of workforce demands.

So what’s coming next to make forecasting, planning, and scheduling even smarter and more efficient? We asked our panel of technology experts to find out.

1. Automatically Searching for Scheduling Opportunities for Agents

Using AI to empower contact centre employees, Grant, our self-scheduling chatbot, automatically searches for scheduling opportunities for agents and offers time-off or extra time when the contact centre needs it.

AI also plays a crucial role in intraday management and optimization, allowing managers to make real-time adjustments to staffing based on actual call volumes and unexpected fluctuations during the day.

This capability ensures that contact centres can respond dynamically to changing needs, optimizing resource allocation and minimizing wait times for customers.

Contributed by: Raj Shankar, Global Senior Vice President, Product Management, Calabrio

2. Modelling How Seasonal Changes Will Affect Staffing Needs

AI will enable more strategic capacity planning. Businesses can now simulate different scenarios, modelling how external factors like market shifts or seasonal changes will affect staffing needs.

This empowers WFM professionals to not just react to immediate challenges but to plan proactively for the long term.

Contributed by: Paul Turner, WEM Leader, Genesys

3. Keeping Coverage Strong During Unplanned Spikes in Traffic – Whilst Still Ensuring Agents Get a Break

AI can make intraday changes and rescheduling both quicker and more effective, benefiting both managers and agents – for example, managers can define conditions where they can delegate certain types of approvals to AI, speeding up the change-request process.

We can also empower AI to very efficiently manage the complexities of digital channel scheduling, including virtual agents, again giving time back to contact centre leaders.

Once the schedule is set, AI can optimize break times to keep coverage strong, especially during unplanned spikes in traffic, but still ensure agents get a break.

Contributed by: Mark Ligi, Director of Product Management CCaaS/VCaaS, Enghouse Interactive

4. Optimizing Happiness Across the Business

injixo introduced employee-centric planning in 1998 and our customers tell us that happy employees are more productive and deliver a better customer experience.

The next step is WFM that focuses on optimizing happiness across the business. It’s not simply about optimizing for employee happiness under the umbrella of employee centricity – although that remains vital.

It’s about finding the perfect balance for all stakeholders: satisfying your business needs, your customers’ expectations and your people’s preferences, which in return delivers a happy business.

Contributed by: Chris Dealy, WFM Evangelist, injixo

5. Monitoring Employee Sentiment and Predicting Attrition Risks

Advanced analytics in WFM solutions will provide deeper insights into employee sentiment, performance, and overall operational efficiency.

By leveraging data from various sources, organizations can proactively address issues before they escalate and make data-driven decisions to improve the workplace.

This could involve predicting attrition risks, analysing individual and team performance data for targeted coaching, monitoring employee sentiment, and identifying operational inefficiencies.

These insights will enable the creation of a more positive work environment, reducing turnover costs, and continuously improving operations.

Contributed by: Jim Fleming, WFO Solutions Consultant, Sabio Group

6. Analysing Peak Call Times to Reduce Call Abandonment Rates

Efficient workforce management is essential for delivering high-quality customer service. Looking at financial institutions, for example, they can use advanced tools to optimize staffing levels, schedule agents effectively, and monitor performance in real time.

By ensuring that the right agents are available at the right times, organizations can reduce wait times, improve response rates, and enhance customer satisfaction.

According to PwC, 39% of CEOs expect to increase their headcount to meet growing demands. One of our financial services customers used workforce management software to analyse peak call times and adjust staffing levels accordingly.

This optimization reduced call abandonment rates, improved CX by having better staffing levels and enhanced agent productivity. This will continue to increase with the support of AI tools.

Contributed by: Anita Stein, Senior Director Field Marketing, UK&I, Five9

7. Empowering the “Liquid Workforce” With Greater Control Over Their Work Lives

As we enter the era of the “liquid workforce,” characterized by flexible work arrangements and a demand for greater autonomy, traditional WFM models simply can’t keep up with this dynamic environment.

That’s where AI comes in. AI-powered WFM solutions can now decipher vast amounts of data to predict staffing needs, optimize schedules in real time, and empower employees with greater control over their work lives.

Employees can then effortlessly swap shifts and request time off, while AI proactively identifies potential scheduling conflicts and offers solutions.

Contributed by: Mitch Todd, Product Marketing Manager, NICE

8. Anticipating Demand Fluctuations More Precisely to Help Align Staffing Accordingly

AI-driven forecasting provides real-time, continuous updates. This new approach ensures that forecasts stay current, reflecting up-to-the-minute data on interaction volumes and resource needs.

Continuous forecasting delivers forecasts with granular accuracy (e.g., 15-minute intervals), allowing businesses to anticipate demand fluctuations more precisely and align staffing accordingly.

Contributed by: Paul Turner, WEM Leader, Genesys

9. Predicting Future Workforce Needs to Proactively Manage Understaffing

By analysing data over time, AI can predict future workforce needs.

This can help organizations proactively manage issues such as understaffing and ensure that agents’ performance targets and wellbeing needs are being met, contributing to improved employee satisfaction.

Contributed by: Raj Shankar, Global Senior Vice President, Product Management, Calabrio

10. Blending Statistical Analysis With Machine Learning Algorithms to Forecast Future Outcomes

There have been many sensational news stories about artificial intelligence (AI) being the 4th industrial revolution. Most of the hype was about generative AI (ChatGPT, etc.). This is a type of artificial intelligence that responds to a user’s prompts with generated text, images, software code or video.

Of more relevance to WFM is predictive AI. This blends statistical analysis with machine learning algorithms to find data patterns and forecast future outcomes. Predictive AI is coming to WFM.

In fact, it’s already here: leading vendors have used AI pattern recognition in their forecasting engines for years. injixo pioneered AI-based forecasting in 2017.

Coming up: even more sophisticated predictive AI that automatically generates more accurate forecasts, taking into account more drivers, covering a wider range of applications across the business.

Contributed by: Chris Dealy, WFM Evangelist, injixo

11. Combining Multiple Internal and External Activity to Predict Demand

AI tools excel at processing enormous quantities of data quickly and accurately, which is transformative for correlating historical and recent data to optimize workloads.

It can combine multiple internal and external factors about activity levels, including daily enquiry rates, seasonality, staff holidays, and the impact of marketing promotions, to predict demand and adjust staffing levels and schedules to match these needs.

Contributed by: Raj Shankar, Global Senior Vice President, Product Management, Calabrio

12. Catering to Individual Preferences and Wellbeing

Employee experience will be optimized by offering personalized interfaces and features that cater to individual preferences and wellbeing.

This might include self-service portals or dedicated AI-powered integrations for easy time-off requests or shift-swaps, gamification elements to encourage engagement, personalized development plans, and features promoting employee wellbeing.

By focusing on employee experience, contact centres can expect higher job satisfaction, reduced burnout, and improved retention rates.

This, in turn, will likely result in better customer service, as engaged and satisfied employees are more likely to provide high-quality customer interactions. The overall impact will be a more positive work environment that attracts and retains top talent.

Contributed by: Jim Fleming, WFO Solutions Consultant, Sabio Group

For more great insights and advice from our panel of experts, read these articles next:

• CCaaS Pulse Check – What’s Now Possible?
• Prioritize Urgent Queries – Key Strategies for Success
• Is ChatGPT Really Suitable for Contact Centres Right Now?

Author: Robyn Coppell
Reviewed by: Xander Freeman