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What Is Predictive Work Aging Analytics?

By Nicole Nevulis

On 26 Sep 2013

1 minute read

What Is Predictive Work Aging Analytics?

By Nicole Nevulis


Posted in Customer Engagement

  • Back-Office Operations
  • Workforce Management
  • Enterprise Workforce Optimization
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Aging doesn’t just affect people. Predictive Work Aging tracks the status of individual work items against service goals, predicting which items are or will be at risk of missing service goals. To effectively predict if items will meet service goals, managers expect their workforce management solutions to consider:

  • Current age of individual items in inventory
  • Backlog volumes
  • Service goals by work type s
  • Future scheduled resources (number of staff, schedule work rules and staff proficiency)

These elements help ensure that back-office operations meet service goals and provide excellent customer service. So how does predictive work aging, well, work? Predictive Work Aging Analytics is part of the VerintRegistered Impact 360Registered for Back-Office OperationsTm Workforce Management (WFM) solution.  Within it, the work item tracking (WIT) feature provides analytics that track individual work items against their service goals. Managers can see the current work aging status of all items—by employee, queue or work type.

shutterstock_CrystalballPredictive Work Aging Analytics takes WIT one step further and gives managers a crystal ball into the future. Now instead of just a “current state” view of work item aging, the solution peeks into the  future—and based on existing backlog, forecasted new volumes, and current and future scheduled resources—it  predicts if work items can be completed within service goals. Predictive Analytics categorizes the work into these categories:

  1. Well within Service Goal
  2. Likely to Miss Service Goal (estimated to be completed within 60 minutes before the service goal)
  3. Predicted to Miss (estimated to be completed within 60 minutes after the service goal)
  4. Already Out of Service Goal

Armed with this data, managers and employees can reprioritize work items and scheduled activities to ensure the at-risk items are completed before lower priority ones. Given today’s regulatory environment, with more and more emphasis being placed on meeting industry standards for service goals, this capability greatly helps companies  meet their service requirements.

Based on the rules configured by your organization, alerts can be sent to managers as well as the employee calling out details of work items that require attention. Predictive Work Aging Analytics (first time we have used the words in this order – we should be consistent) makes it easier for managers to focus their efforts where they are needed most. 

Would Predictive Work Aging help you in your operations?  Share your thoughts with us below.

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