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Figure 1 – During the normal course of Contact Center operation, the Average Speed of Answer (red line) and Longest Wait Time (blue line) follow each other closely. However, at the two-circled areas, there is a huge gap between the two lines. The number of abandoned calls (indicated by red bars) is also highest during this period. Our client was able to analyze this problem scenario through metrics and reports and take corrective action.
Derive proper metrics in timely manner
Introduction
When it comes to measuring performance of your Contact Center, you may be challenged on what measures to look at, which system will deliver these measures, how to arrive at the operational metrics? and are the metrics accurate enough to base your strategies on?
Why is it important to derive the right metrics?
Executives need operational metrics in order to monitor and manage their Contact Center. It is important that they set performance goals and continuously assess them using the right set of metrics. Metrics help evaluate performance against industry benchmarks.
While it is important for Contact Centers to use metrics for performance measurement, surveys done by ?Ventana Research? shows that less than one-third of companies are able to implement such metrics.
What are the challenges today?
Complexity, proliferation and scale of systems have increased tremendously in the Contact Center, thereby making it difficult to derive metrics by analyzing these complexities.
Data for obtaining metrics is spread across multiple systems in a Contact Center. The measures provided by these systems are not standardized across leading to inconsistency in the metrics it derives. Let us look at an example where inconsistent measures affected performance reporting for our customer. The Contact Center environment had Avaya switch for processing the calls and they were in the process of implementing Genesys T-Server to support their growing business needs. Avaya switch was reporting calls based on the following types: inbound, outbound and transferred calls. Once Genesys T-Server was operational, it reported calls as inbound or outbound without reporting the transferred calls. Due to this, management lost visibility to all metrics that were derived from transferred calls.
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.
Data quality is a major challenge in deriving metrics in a Contact Center. Issues like data contradiction between systems hamper the integration process and failure to resolve them will have a cascading effect on the metrics that are derived from such data. Here is a case where variances in the same event information had an adverse effect on performance management. The Contact Center environment of our customer had multiple systems, which included switch, automatic call distributor (ACD), intelligent voice recognition (IVR), routing server etc.
They were using the data from ACD to derive metrics like average handle time, agent occupancy and cost per call. Such metrics were being used to measure agent performance and determine their compensation. When a manager was reviewing a call handling report from ACD, he observed that some calls had talk time of zero seconds. This raised a red flag and a quick analysis showed that Switch showed a talk time of over 2000 seconds for the same call. Further investigations revealed serious data discrepancies between switch and ACD affecting most of the metrics that were being used. The management was using the wrong scale to measure performance!
One of the critical aspects of performance management in Contact Centers is the ability to visualize data as per user?s requirements. This is required to analyze the huge amount of data accumulated in the Contact Center in an organized manner. A typical Contact Center stores data in a normalized structure. This design improves performance and scalability but constrains user from readily using the data.
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.
Solution to over come these challenges
To better manage the performance of your Contact Center, you should have timely visibility to organized Contact Center metrics. In order to reconcile the measures from different systems, data analysis is performed at beginning of the project. Test scenarios are run to populate data to the reporting layer. Source of data and its definition is studied across systems to identify any inconsistency. If the inconsistencies cannot be fixed, data transformation is applied to obtain simplified and streamlined view of metrics.
Data in the reporting layer is compared against the system of records to ensure its completeness and correctness. Data is first compared at an aggregate level and if a problem is identified, it is drilled down to the lowest granular level to find the root cause. Call logs are analyzed for flow of events if there is any discrepancy in the data reported. Times of the events are compared across systems to ensure there is one view of truth across the reporting layer.
To support users requirement to visualize and analyze Contact Center data in an organized manner, a semantic layer is built above the pre-presentation layer. In the example shown in Figure 2 ? Approach B, semantic layer provides a business view of data as required by the user using the underlying data infrastructure. This layer allows faster access to data with provision of implementing business rules with minimal effort and time. This layer consists of views along with an efficient data aggregation, filtering, consolidation and refresh mechanism.
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.
Summary
Addressing the challenges discussed is critical in performance management of your Contact Center. Timely visibility to the right metrics will lead to increased customer satisfaction and improve the overall efficiency of your Contact Center. With our expertise in implementing the right metrics for large Contact Centers we are in the best position to assist you in your performance management initiatives.
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Performance management in Contact Centers
Performance management in Contact Centers has been a challenge due to varied technologies and enormous data involved. Through our multi disciplinary approach, we can better support our clients in their performance management initiatives.
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.
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.
