Data quality, customer resistance and governance

Host: Bob Furniss (without co-host Amos) Guest: Daniel Thomas, Informa Location: ICMI Conference Expo Floor

Guest Background

• Daniel Thomas approaches contact center industry from a research background
• Surveys audiences and writes research reports
• Has "front row seat" to industry transformation
• Conducts the annual State of the Contact Center survey

About the State of the Contact Center Report

• Comprehensive benchmark study surveying contact center professionals
• Covers multiple verticals including:
  • Training and skills
  • Compensation and salary
  • Technology use
  • Leadership perceptions
  • Strategy
• Tracks year-over-year progress
• Recent additions include AI and workforce training questions

Key Surprising Findings 1. Contact Centers as Strategic Intelligence Hubs

• Major shift: Contact centers increasingly viewed as "strategic customer intelligence hubs" rather than cost centers
• Described as "customer intelligence and nervous system"
• No other department has closer customer proximity or more customer data
• C-suite now acknowledges value with direct data funnels informing executive decisions

2. AI Perceptions and Impact

• 72% believe AI will transform roles, not replace them
• Only ~25% think AI will lead to workforce reductions
• AI expected to handle "level one, rote, monotonous, repetitive work"
• Agents will focus on:
  • Complex needs and edge cases
  • Soft skills: empathy, communication, problem solving, critical thinking
• 90% of surveyed leaders believe humans necessary as AI overseers
• Gartner prediction: 40% of agentic AI projects will fail by 2027 (often due to neglecting human oversight)

Agent Evolution

• Agents increasingly viewed as:
  • Consultants
  • Solutions architects
  • Higher-tier problem solvers
  • "White glove service" providers
• Rising expectations due to AI support
• Agents becoming intelligence providers to C-suite
• More analytical roles: identifying trends, patterns, creating intelligent summaries

Top AI Implementation Concerns

1. Customer resistance (top concern)
2. Data accuracy
3. Data privacy and security
4. Lack of proper AI governance

Workforce and Quality Management Insights Workforce Models (Nearly Equal Three-Way Split)

• In-office full time
• Hybrid
• Fully remote
• Models remain transitional and subject to change
• Increased scheduling flexibility critical for retention

Quality Focus Shift

• Traditional metrics: CSAT, utilization, average handle time
• New priority: Agent experience rising in importance
• Recognition that internal customer experience drives external customer experience

Customer Satisfaction Challenges

• Current CSAT surveys often lack nuance
• Can't distinguish between:
  • Poor agent performance vs. poor company policy
  • Single bad experience vs. overall satisfaction
• Need for more qualitative feedback mechanisms
• "Watermelon effect": High metrics but poor actual experience

Channel Evolution

• Significant jump from multi-channel to omni-channel implementation
• Growth in non-traditional channels:
  • Social media
  • SMS/text
  • Video
• Technology enabling unified customer history across channels

Key Takeaways

• Successful organizations treat contact centers as "valuable strategic sources of intelligence"
• Organizations not recognizing this value are "dropping the ball" and will "see the consequences"
• Contact centers serve as the "hub" and "nervous system" reaching everywhere in the organization
• When no one knows the answer, they turn to the contact center

Notable Quotes

• "If your agents aren't excited about AI, then you actually haven't communicated to them how enriching and transforming it could be"
• "Agents are increasingly going to play a role where they are the eyes and the ears... providing the intelligence back to the C-suite"
• Contact centers as "the strongest data... the hub... the nervous system that reaches in everywhere else"