Key Challenges:

• Workforce optimization (WFO) suites are superior to integrated point solutions, but old ways of thinking hold back innovation within larger and more complex organizations.
  

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• Departmental siloes that occur within larger organizations – especially those linked to specific WFO functions like quality management and workforce planning – encourage a narrow/siloed functional mindset when it comes to technology investment.

Automate and Elevate the Agent Evaluation Process:

• Interaction selection: The ability to automate the selection of interactions used based on speech analytics, interaction categorization, post-interaction customer feedback, or other relevant metadata. Selected interactions will automatically appear in an “evaluations to conduct” screen for the quality assessor. For example, if an agent receives a low score on a customer survey, or a high level of emotion is detected in a recording, then this would trigger a review of that interaction.
  

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• Time management: The ability to automatically schedule time for quality assessors to conduct assessments, thus linking WFM and QM. Organizations that encourage agents to perform self-evaluations can also have time assigned accordingly via the WFM solution.
  

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• Ad hoc evaluations: The ability to drill down into a report (such as a daily postcall survey report, or speech analytics report) to connect the survey response/speech analytics insight with the relevant interaction/agent and conduct an ad hoc evaluation there and then without having to separately open the QM tool.
  

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• External validation: The ability to associate other WFO metadata with the evaluation. For example, post-call survey scores are attached to the evaluation to help balance internal scoring with an external customer perspective. Specific evaluation fields can also be pre-populated via input from the speech analytics function (such as a script-adherence check).
  

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• Automated detection: The ability to analyze a variety of WFO data sources – such as post-call customer feedback, quality evaluations or speech analytics insights – and automatically assign a coaching/e-learning session with relevant content as appropriate. As an intermediary step, all training recommendations are routed via the associated supervisor/training manager for their approval, giving them full access to the data behind why the training was recommended. Once they are confident that all training requests linked to a specific topic are correctly recommended by the system, they can tag it as “fully automated” and thereby do not get further requests for approval.
  

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• Automated scheduling: The ability to automatically send learning and coaching assignments to WFM for scheduling with minimal impact on service levels. Rather than manually adding coaching requests into the WFM system and relying on a fixed time-slot, their addition is automated and a delivery time scale is linked to the severity of the request. For example, if it is essential to conduct the coaching before the agent’s next shift, then it will be prioritized accordingly, and the overall schedule for that shift will be adjusted to accommodate that head-count reduction. Something of less significance can be assigned during a quieter period sometime over the next month. The ability to adjust when the training is delivered based on the balance between its severity and operational service levels helps optimize operational performance.