The Self-Optimizing 'Real-Time' Contact Center
Real-time analytics and real-time optimization of contact center technologies are converging trends that will, in short order, dramatically enhance productivity and customer satisfaction, change how call centers are deployed and managed, and alter the expectations of both customers and the companies that service them. This convergence represents a fundamental paradigm shift in the science of customer satisfaction delivery one that will have a determinative impact on current technology life cycles and on the metrics that drive technology buying decisions.
This paper will focus on what current buyers of technology need to know about these trends and what criteria should be applied to imminent buying decisions, in order to 'future-proof' those investments in the context of this emerging paradigm shift. At the root, these trends are unified by the overarching vision of the contact center as a real-time organization that can automatically adapt its technologydriven business processes to changing needs and circumstances.
The Status Quo
Traditional contact centers have had to cobble together a diversity of different technology point solutions via systems integration in order to create their multichannel customer service communications infrastructures. This has typically made contact center technology expensive to buy, expensive to maintain and notoriously rigid, requiring significant time and money to implement changes. As a result, companies who have deployed technologies in this paradigm typically shy away from implementing expensive changes to their software investments – and instead often opt to postpone resolving many problems until the life cycles of their current investments are fully depreciated. The consequence is that technology efficiency tends to decline steadily over the life cycle of traditional technology investments.
Of course, there are other challenges inherent in the status quo. For example, most companies cant effectively capture, unify, structure and mine the data flowing through their various contact center technology point solutions. As a result, they often cant effectively recognize traffic bottlenecks, customer opportunities, trends or underserved needs on a timely basis. Those companies that have invested in analytics technology to address these issues typically find themselves challenged to actually leverage the data on a timely basis, because traditional contact center point solutions were never designed to empower real-time business process optimization.
The Emergence of Adaptive Real-Time Technology
The best next-generation IP contact center solutions encompass all communications channels and their related quality assurance technologies and unify them in a comprehensive solution that is integrated by design. The core purpose of this integration-by-design approach is to provide contact centers with the ability to adapt to changing business and customer needs instantly, in real-time. Adaptive solutions enable any technology-driven business processes to be modified in real-time, without sacrifice. Adaptive IP contact center technology, while relatively new (available since 1998), has nevertheless seen rapid adoption over the last few years among a wide diversity of fortune-class companies and government agencies because of its compelling ROI-related benefits.
Companies that have deployed adaptive solutions can fix problems in real-time across all media channels and therefore run in a more optimized state more of the time, enabling them to enjoy competitive advantages in both productivity and customer satisfaction. Companies that have deployed adaptive technology have reported productivity gains of 30 percent and 100 percent ROI in the first year (as reported in the Enterprise Telephony supplement in the March 1, 2004, issue of Business Week), often increasing to many times that number depending on the size of company (larger companies tend to have a history of fewer bad gut infrastructure decisions) and how much time has passed since the companys last upgrade. Of course, it should be intuitively obvious that the ability to fix infrastructure problems in realtime not only constantly renews the life cycle of legacy investments, but also inevitably yields significant productivity gains.
Adaptive solutions are driven by the same needs-analysis questions that integrators rely on to define their scope of work for traditional point solution deployments, but now the entire range of outcomes and their related technologies are preprogrammed for deployment in realtime via browser menus. Changes are also implemented in real-time from those same menus. If an outcome hasnt been preprogrammed because it represents a new and unique idea, a mature adaptive solution will empower you to leverage Web services to create new potential outcomes without sacrificing adaptability.
The Impact on Analytics
As a result of integration with adaptive IP contact center technology, the science of analytics is now poised to extend beyond merely analyzing historical data and suggesting proactive changes to business logic. While proactive insight obviously has tremendous value, a great many operational bottlenecks might not be foreseeable by human or machine and these unpredictable bottlenecks will inevitably take their toll on revenue production if they cannot be addressed in realtime. Analytics engines will soon be capable of supplementing their commonly understood role as advisor with the capability of actually overseeing business processes as a real-time autopilot one that can react to changing circumstances directly by implementing business process changes to any technology, in real-time. The speed and depth of analysis driving such decisions, enriched by integration with both the CRM and communications technologies to more accurately identify root causes of business challenges, will extend the benefits of adaptive technology to levels that would simply be otherwise unattainable. Of course, a prerequisite for those changes to take place is the linkage to an adaptive IP contact center platform. The emerging paradigm of the self-optimizing contact center promises to dramatically change how contact center technologies are implemented and managed. In the near term, selecting an adaptive solution should obviously be a prerequisite for companies that see an analytics autopilot in their futures.
The Impact on Customer Satisfaction Management
While the integration of adaptive IP contact center technology with performance analytics is ongoing, the adaptive approach to IP contact center technology is already changing the assumptions that underlie the discipline of customer satisfaction management.
Dynamic customer satisfaction management (DCSM) is an emerging discipline that extends and merges CRM objectives with contact center communications infrastructure. While many basic customer satisfaction management solutions have been cobbled together on a custom basis by organizations focused on maximizing customer satisfaction, until recently there has been little if any access to solutions that are integrated by design into IP contact center infrastructure. Such integration by design delivers value that goes beyond what can be achieved by integrating aftermarket solutions.
The corporate focus on customer satisfaction management is generally driven by the fact that those companies with the highest customer loyalty rates generally enjoy much higher growth rates as compared with the average growth rates for their industries. In fact, research across industries validates a direct connection between customer loyalty and business growth with the loyalty leaders growing fastest in virtually every category.
Of course, every company wants loyal customers. Very few, however, actually measure the customer satisfaction that their business growth depends on. Instead, traditional approaches to quality assurance measure customer satisfaction indirectly, by measuring adherence or compliance to company policies rather than actual customer reactions to the quality of service that was delivered. One of the key innovations of integrated DCSM solutions is that they can measure customer satisfaction directly and take appropriate action as needed. This is because DCSM-compliant solutions actually ask customers how they were treated. Customer satisfaction is measured directly with endof- call and end-of-Web-transaction surveys that supplement traditional service level data analysis. While this might sound like simple quality assurance surveys, the difference lies in the core integration with contact center systems.
DCSM-compliant solutions dont just measure satisfaction on a historical basis, they react and adapt. One of those reactions is dynamic change to routing logic by leveraging survey results to drive future automatic call distribution (ACD) routing decisions. With DCSM, customer-driven assessments can be dynamically incorporated into weighted routing decisions, along with traditional skills-based routing metrics. As a result of ACD integration by design, post-call (or post Web-transaction) DCSM surveys results can automatically and dynamically update the agents skill rating in the area of customer satisfaction delivery or any other metric. Consider the example of the disgruntled employee who used to deliver great service and is therefore ranked highly for receiving calls from priority customers. A DCSMcompliant system would detect that this disgruntled employee was no longer delivering that same quality of service and would automatically stop routing priority callers to that agent (in addition to alerting the agents supervisor to the decline in performance).
Besides agent skills, relative proficiencies in those skills and performance in customer satisfaction delivery, another dimension can also be included in DCSM-influenced routing decisions. With DCSM-compliant solutions, agents can define how much they like working on different types of calls based on the campaigns they are assigned to and their preferences can be taken into account by the ACD on a customizable, weighted basis. Since agents who like their work perform better and are less likely to leave their jobs factoring agent preferences into routing decisions simply makes sense. By taking the agent, customer and supervisor perspectives into account for important routing decisions, this multidimensional routing approach can effectively maximize efficiency, increase customer satisfaction and enhance agent retention.
Of course, solutions designed with DCSM must also act on negative customer feedback in real-time to rescue relationships and customer satisfaction as soon as theyre jeopardized. Here the end-of-call survey information is used to dynamically and automatically alert supervisors or overlay workgroups to immediate customer relationship emergencies. With DCSM, supervisors or overlay workgroups charged with rescuing customer relationships can not only be alerted in realtime to a dissatisfaction event, they can also immediately listen to the call that triggered the poor review and decide what actions are warranted. Once they have context for the complaint, the supervisor can decide if the customer should be called back immediately with an apology and perhaps a special offer or discount on their last transaction.
As part of the DCSM post-call survey, companies can also enable customers to choose to be transferred to a supervisor immediately an option that can be dynamically enabled when overlay agents are available. Once the transfer is requested, the caller can be transferred with skills-based routing discipline to a dedicated overlay workgroup that specializes in repairing damaged customer relationships.
While DCSM clearly leverages call-recording technologies, instead of (or as a supplement to) random call reviews, now all calls can be buffered in real-time and dynamically stored as recordings only when customers have expressed dissatisfaction with how theyve been serviced. This approach also empowers companies to focus their limited supervisor resources on listening to those specific call recordings that customers themselves have identified as problem transactions.
Another benefit is that, where appropriate, an agent can now be disciplined within minutes of any offending behavior instead of the weeks or months later you would expect with a traditional survey application. The benefit: agents who expect to be disciplined immediately following prohibited behavior are statistically less likely to engage in that behavior.
A key benefit of DCSM is that post-call customer feedback can also be leveraged to establish satisfaction service levels with real-time delivery of feedback data to relevant agents, supervisors and workgroups. The establishment of customer satisfaction service levels can be valuable both for training purposes and to motivate agents to achieve the performance goals that should drive incentive-based compensation. An effective DCSM approach should also enable data to be sliced and diced to provide such information as average satisfaction scores for the top quartile of agents, comparisons to other groups and/or corporate targets, etc. Agents can also be provided with access to their personal satisfaction history records, searchable by date range and individual campaigns, which will enable them to review their aggregate reviews and drill down into specific survey responses to see where they went wrong. Those agents can also see whether satisfaction was recovered by the supervisor or overlay group for alarmed transactions and listen to the recovery call to learn how that recovery was achieved.
DCSM is attracting corporate attention because it addresses the core challenge of how to maximize customer satisfaction and accelerate business growth with automated adaptive processes that effectively deliver on corporate objectives without adding incremental costs. DCSM survey information also provides richer data than is normally available to data mining and analytics applications, thereby empowering even greater ROI and productivity gains.
After 30 years, billions spent in R&D and thousands of industry implementations, you would assume that contact center infrastructures would have become increasingly flexible and responsive to changing needs. In fact, for most companies, the contrary is true. Contact centers have, for the most part, become increasingly rigid in their response to changing needs, in no small part due to the deployment paradigms in which ever-greater numbers of contact center technologies have been incrementally deployed.
Newer adaptive solutions, however, offer compelling value by eliminating this core impediment to business efficiency, while providing competitive advantage to those companies who empower themselves with the ability to fix strained technology-driven business processes in real-time at no cost. Automated, self-optimizing approaches to implementing business process change, whether driven by dynamically obtained customer satisfaction data and/or by more traditional analytics insight, represent the next step in the evolution of the contact center.
