Webinar on call center WFM: Man versus machine: the human factor in WFM … · 2020-04-20 ·...
Transcript of Webinar on call center WFM: Man versus machine: the human factor in WFM … · 2020-04-20 ·...
Webinar on call center WFM:Man versus machine:
the human factor in WFMApril 17, 2020
Ger Koole, PhD
The topic
• Small call centers forecast and schedule by hand• When scale increases manual scheduling becomes impossible:
automation• Human touch is lost and employee satisfaction decreases• Can we avoid this?• Is there really a dichotomy: man versus machine?
• First: current state of AI/machine learning• Then: consequences for WFM
Man versus machine
What men are good at:• Decision making in complex
environmentsWhat computers are good at:• High-dimensional decision
making in simple environments
Complexity environment
Dim
ensio
nalit
y
tic-tac-toe
chess
go
imagerecognition
car driving
Examples
Dog or muffin?Easy for humans – hard for computers
Where is Waldo?Easy for computers – hard for men
How about AI?
• Computer doing “difficult” human tasks• Considerable success, especially when environment/rules are clear • But: methods are different, AI-enabled programs “think” different
than humans• Machine learning = non-linear regression using lots of data• Artificial neural networks are different from real neurons!• Humans analogs (“learning”, ”AI”, etc.) are misleading
WFM
Rules in WFM are highly complicated• Labor rules• Personal preferences of agents• Fairness between agents
How to schedule when size (= dimension) increases without losing human touch?
Complexity environment
Dim
ensio
nalit
y
tic-tac-toe
chess
go
imagerecognition
car driving
WFM in small center
WFM in big center
Human touch
What is a “human touch”?• Respect for/understanding
of personal preferences• Understandable
decisions/forecasts• Too difficult for computers
Solution:• symbiosis of man &
machine
costs
WFM goals
Easy for computers & humans
servicelevel
Easy for computers, hard for humans
agentsatisfaction
Hard for computers, easy for humans
Symbiosis
the new common way… … but the role of the computer gets bigger
Symbiosis in WFM
• For symbiosis outcomes of tooling should be understandable
• Easy analysis of alternatives: No decision making but decision support
FORECAST FORECAST +REASON
WHAT IF I CHANGE THE SHIFT OF AGENT X?
The future of WFM
• Automated machine learning: No configuration needed – tooling learns by itself• Autodetect of outliers and holiday effects• Autodetect of preferences of agents – by rating of schedules• WFM tool is emphatic rational agent
• Learning more rules
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The future of WFM
• The Gig economy?• Self-employed people working short intervals from home• Lower costs – or hidden costs?• How to match demand & supply? Financial incentives to work at right time• Parallel to airline pricing – based on demand & supply forecasting
• Self-scheduling?• Works for back-office tasks• Or really good decision support
Takeaways
• From symbiosis to “one button scheduling”• Taking all rules into account• Showing consequences of decisions• Explainable forecasts
• No black boxes – explainable AI• The future: empathic WFM tooling
Next week
• Friday April 24, 16:00 AMS time• Subject & speaker: to be determined• Suggestions: [email protected]
• Questions? Chat or voice