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Figure 1 – This diagram illustrates the call flow (black arrows) along with the flow of information from Call Center transaction systems. Performance related data is extracted from the individual transaction systems and transformed for visualization in the form of reports and charts. Conventionally, for performance management focus was on the data present in data transformation and reporting layers (highlighted area). This led to inconsistencies in metrics and reports affecting performance management. Data analysis of the underlying transaction systems and building a robust technology infrastructure are essential for effective Contact Center Performance Management.
Contact Center performance management overview
Introduction
Performance management has been a challenge due to varied technologies and data intricacies often involved in Contact Centers. While numerous systems integrate to support the operation of Contact Center, data from these systems are not processed and visualized in the right manner to aid performance management.
Derive Proper Metrics
Contact Centers generate huge volume of transaction data in numerous systems. This data is used to derive its performance metrics. However non-standardization of data elements across systems, leads to inconsistency in the derived metrics and reports. Usability of these derived metrics is also greatly affected by ability to quickly visualize the required information.
Understanding the nature and source of data is essential to derive proper metrics in a contact center. Reporting infrastructure has to be abstracted from the raw data and a semantic layer has to be built, so that users get faster access to metrics and reports.
Derive the right Contact Center metrics
Metrics help spot issues, identify root causes and control factors affecting customers. However, complexity and proliferation of systems in a contact center makes it difficult to derive the right metrics.
Insight thru Analytics
While Contact Centers use traditional reports and charts to monitor performance, they lack the ability to obtain insights into their operations. Often complex relationships and patterns remain hidden in the data, which are revealed through manual analysis.
Analytics is required to uncover hidden relationships and patterns in the data. A multi-disciplinary team is required to perform the tasks involved in implementing analytic projects. Understanding of Contact Center processes and data that drive them are essential for a successful implementation.
Gain insight from customer interactions
Conventional reports cannot uncover complex patterns and relationships present in interaction data. Analytics improves performance management of contact centers by providing such insights.
Data Quality
Poor data quality makes an otherwise helpful report and insight useless. It is very important to realize that a functioning contact center is not automatically ready for implementing performance management strategies. This is because the rigor applied to validate data quality during implementation may not rise to the standard expected for performance management.
Data Analysis is an important step in any performance management initiative. During this process, data has to be compared against system of records to identify inconsistencies. This activity has to be performed on a periodic basis to ensure clean data.
Are your contact center reports effective?
Data quality in Contact Center impacts accuracy and completeness of performance reports. Comprehensive approach to data analysis considering diverse technologies involved will result in cleaner data.
Summary
Performance Management is key to effective Contact Center operations. However implementing a good Performance Management solution requires multi disciplinary approach and attention to details. Clients should demand the same from their implementation partners. With our integrated approach, we have prepared ourselves to be better partners to client’s in realizing their Performance Management initiatives.
Recent Links :
Derive the right Contact Center metrics
Metrics help spot issues, identify root causes and control factors affecting customers. However, complexity and proliferation of systems in a contact center makes it difficult to derive the right metrics.
Gain insight from customer interactions
Conventional reports cannot uncover complex patterns and relationships present in interaction data. Analytics improves performance management of contact centers by providing such insights.
Benchmarking contact center performance
This case study is centered on how EXILANT helped the client to establish & improve performance management solution for their contact center despite having subsystems in diverse technologies.
