Next In Queue: Pivot! featuring Natalie Perez

Key Take Aways

1. Workforce Management (WFM) encompasses forecasting multiple contact channels, including calls, web chats, and emails, integrating both human and AI labour, with real-time environment analysis to enhance operational efficiency.
2. Existing WFM systems are often built on antiquated architecture, creating significant challenges for integrating modern functionalities and innovative technologies such as AI.
3. There is a recognised gap in the market for new entrants in the WFM space, partly due to the complexity and maturity of existing solutions.
4. AI agents are transforming contact centre operations by handling routine transactions, but their deployment raises concerns around customer experience, empathy, and appropriateness.
5. Effective measurement and real-time monitoring of AI versus human agent performance are key to optimising utilisation and maintaining quality customer interactions.
6. Managing customer experience with AI involves balancing efficiency and empathy, especially in sensitive sectors such as healthcare and financial services.
7. There are ongoing concerns regarding AI replacement fears, but proper application and measurement of AI’s capabilities can support outcomes like customer SLAs and agent well-being.
8. Average handle time (AHT) is a problematic metric if not regularly revisited and contextualised within continuous improvement efforts; it should not be a static target but adaptable based on actual customer needs.
9. Agent burnout and psychological safety are critical factors impacting turnover, customer satisfaction, and operational continuity.
10. Leveraging AI allows real-time insights into agent performance and well-being, enabling proactive management to reduce burnout and improve staff retention.
11. Virtual contact centres create a gap in immediate visual cues for supervisors, which can be mitigated through technological advancements in AI-based real-time monitoring.
12. Organisational agility, including willingness to pivot and incorporate feedback, is essential in developing effective, up-to-date WFM solutions.

Key Statistics

• In the 1990s and early 2000s, NBC’s Thursday night line-up, including Friends, Seinfeld, and ER, was watched by approximately 25 million Americans—a cultural reference illustrating the significance of “must-see TV.”
• A contact centre in FEMA handled calls during Hurricane Andrew in 1992; typical calls involved emotionally charged issues with no opportunity for agents to pause or breathe.
• AI’s capability to handle a significant portion of contact volume is projected to increase over the next five years, although specific figures are not given.
• AI chatbots can sometimes sound indistinguishable from human agents, achieving “amazing” quality as of recent reports.
• It is suggested that 70% AI handling is a vendor claim, but real-world operational data often shows closer to 20–30%.

Key Discussion Points

• The importance of modernising legacy WFM architectures to enable functionality such as AI integration and real-time analytics.
• Challenges associated with applying AI in contact centres, especially related to customer experience, emotional connection, and appropriateness of automation.
• The critical need for precise performance measurement and KPIs comparison across AI and human labour pools.
• The impact of AI on managing agent wellbeing, burnout, and psychological safety, particularly in virtual contact centres.
• The limitations and pitfalls of using average handle time as a performance metric, and the importance of regular review within a continuous improvement framework.
• The balancing act between operational efficiency, customer satisfaction, and agent happiness.
• The significance of real-time data and AI-driven insights for proactively managing agent workload and preventing burnout.
• Cultural and organisational adaptability, especially the willingness to pivot based on market feedback and technological advancements.
• The importance of defining appropriate use cases for AI agents, avoiding over-automation where human empathy is essential.
• The potential of AI to support agent development and career progression within contact centres.
• Challenges faced by traditional WFM providers and the emergence of innovative platforms developed from scratch with no technical debt.
• The role of customer experience technology patents in shaping future WFM solutions and their integration with AI.

Podcast Description

This podcast explores the evolving landscape of Workforce Management (WFM) within contact centres, with a particular focus on technological advancements, notably AI. It features insights from industry veteran Natalie Perez, who discusses the importance of modernising legacy WFM architectures, the strategic deployment of AI agents, and the measurement of performance to optimise both customer experience and agent wellbeing. The conversation addresses the challenges of integrating AI into daily operations, maintaining organisational agility, and creating balanced, customer-centric solutions amidst technological disruption. Aimed at senior managers in financial services, the podcast offers a critical look at innovative strategies to improve operational efficiency, foster staff retention, and deliver exceptional customer outcomes in a rapidly changing environment.