Leveraging Data-based Intelligence to Increase Employee Engagement

By John Ruby, CEO, GCOM Worldwide

Employee engagement is the extent to which employees feel passionate and committed to their work. Engagement has a direct impact on organizational profitability, correlating closely with productivity, efficiency, and reduced turnover. Like many managers, call center leadership, management and supervision have direct experience grappling with these issues and are familiar with the direct impact they have on the bottom line.

  • Gartner Research predicts that by 2020 agent engagement will be the key difference that defines the top 20 % of contact centers.
  • Top performing call centers have 60% more engaged employees.
  • A five percent increase in employee engagement can drive a three percent increase in revenue.
  •  McKinsey reports that hiring and training of a new agent costs a call center between $10,000 and $20,000 dollars.
  • Gallup reports only 31 % of U.S. and Canadian workers were engaged in their jobs.

As persuasive as the data is, solving these issues has proven elusive in every function of the enterprise. One advantage call center’s have over most is access to a lot of data—the raw material that form the basis of analytical work.

This data is used to construct information. The typical call center uses as many as 25 metrics distinct metrics to group and analyze data: SL, CSAT, ASA, AHT, FCR, SSR, Response Time, Blocking Rate and many more.

Professionals overseeing call centers combine and curate this information to form insights that aid in tactical operations, improve performance, and identify emerging trends.

At this point information has been distilled into intelligence. Intelligence can be understood as the product of information that been processed and refined to provide a sufficient understanding of a situation to serve as the basis for action. The more intelligence we have, the better able we are to solve some employee engagement problems.

Intelligence allows a call center manager to:

  • Identify opportunity. A good example is retail stores. Most are great at using SKUs to manage inventory and identify top sellers.
  • Improves customer sales and service. Amazon does a great job using intelligence and predictive analysis. They are one of the best at improving our buying experience and selling us more “stuff”.
  • Better efficiency and production. Today we are seeing the Healthcare industry improving their patient care and scheduling with intelligence.
  • Reduces costs. Most all industries gain some savings benefits with intelligence.

For more insights, register today for CCS 19 today.

2019-03-13T15:35:20-04:00March 11th, 2019|
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