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Attributes of Solid Contact Center Performance Metrics - and Attributes of Poor Ones


Presented By: Sharpen


Ric Kosiba, Chief Data Scientist, and

Adam Settle, Vice President of Product, Sharpen

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About the Webcast

A great contact center leader and deep thinker, Tricia Payne from American Express, gave this insight: “Measurement should be a GPS and not a compass.” 

What does that mean?

What she means is that each measure we employ to help us determine how our teams are performing needs to be understandable and actionable to agents and management alike. Our metrics need to be more than a general heading for reaching our goal, they should be turn-by-turn directions. They should tell us what to do.

In our complicated, multi-site, multi-skill world, this is as tricky as it sounds. Common metrics, like service level, may not translate across channels; and comparing teams that share some (but not all) queues is not always straightforward. 

Our measures have to be clear and our goals need to be well thought through. Join this session where we chat about the attributes of common metrics that help agents and leaders focus on the right things. We’ll also talk briefly about agent performance scorecards and why you might want to skip using them.

About the Presenters

Adam Settle, Chief Experience Officer, Sharpen Technologies

Adam is an experienced education professional skilled in Sales, Coaching, Team Building, and Training. He is a strong facilitator, combining his study of education with experience from his time as a trainer at Apple and Angie’s List. At Sharpen, Adam and his team create the connection between advanced technology and the understanding required for clients to take advantage of its potential.

Ric Kosiba, Chief Data Scientist, Sharpen Technologies

Ric is responsible for developing data-driven initiatives to optimize agent performance and to use Sharpen's fantastic reporting tools and data layer to enhance the customer and agent experience. Prior to joining Sharpen in 2019, Ric co-founded Bay Bridge Decisions Technologies in 2000, where he developed the contact center industry’s first “what if” decision engine, a complex set of algorithms designed to forecast proper staffing levels. Ric received a Ph.D. in operations research from Purdue University.