Amazon Enters the Contact Center Workforce Management Space

The company bulks up its CCaaS solution with new forecasting, capacity planning, and scheduling tools

Amazon Enters the Contact Center Workforce Management Space
WFOLatest News

Published: March 30, 2022

Charlie Mitchell

New native forecasting, capacity planning, and scheduling are now available within the Amazon Connect platform.

As Amazon Web Services (AWS) announced in a LinkedIn post, these tools aim to:

  • Predict your customer service workload, including contact volume and average handling time, with high accuracy ๐Ÿ”ฎ๐Ÿ“…
  • Leverage capacity planning to estimate how many full-time equivalent (FTE) agents are needed to be hired ๐Ÿ‘จโ€๐Ÿ’ผ๐Ÿ‘ฉโ€๐Ÿ’ผ
  • Ensure you have the right agents at the right time to support customer contacts ๐Ÿค

Despite already offering integrations with leading WFM software providers such as Calabrio and Alvaria, this announcement highlights a significant step forwards for the Amazon Connect platform.

Now, users can access these capabilities directly from their AWS console with just one click. As such, Amazon can create a more well-rounded proposition to compete against the leading contact center vendors more closely.

Indeed, the announcement already includes the addition of advanced WFM capabilities such as automating โ€œwhat ifโ€ scenarios, KPI reporting, and a self-scheduling application for agents.

While there is no mention in the release of other innovative WFM features available elsewhere โ€“ including intraday management tools, shift bidding, and break optimization โ€“ the announcement seemingly enables Amazon to be very competitive within the WFM space.

Furthermore, Amazon promises to launch additional capabilities, which will allow users to monitor real-time adherence rates, accommodate agent scheduling self-service requests, and more.

Yet, early adopters seem to be enjoying the new tools. Indeed, Alex Miles, Director of Business Intelligence at Litigation Practice Group, said:

Amazon Connect stood out to us because of how easy it is to harness data and leverage machine-learning (ML) to deliver highly accurate (>95%) forecasts and optimized schedules. It is simple and flexible to set up, and allow us to create agent schedule with high efficiency, even when our agents have many unique schedule requirements.

The machine learning capabilities embedded into the WFM software โ€“ which Miles references โ€“ are something that Amazon was quick to draw attention to during their announcement.

Building on these may enable Amazon to differentiate its solution further in the future, as the provider strives to simplify interval staffing and the creation of efficient schedules.

Over time, these additions will perhaps enable the Amazon Solution to edge closer to CCaaS leaders, which โ€“ according to the latest Gartner Magic Quadrant โ€“ are Genesys, NICE, and Talkdesk.



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