Actionable Intelligence Through UC

In today’s economic climate, information has never been more critical to business – information about customers, employees, and about how processes are working or not working. In fact, the very success of an organization can often be tied to how much information it collects and, more importantly, how well it analyzes this information for key trends to drive its business forward.

Every part of an organization’s value chain produces and processes information. However, more than any other area, the part of the enterprise that collects and analyzes the most information is the contact center. This information is used to assist the enterprise in providing superior service, better deploying resources, and reducing costs – primary goals of any organization. Key performance indicators (KPIs) such as average speed of answer, average hold time, call abandonment rate, etc. – the context of customer interactions – have been collected and analyzed for years for incoming and outgoing phone calls, as well as IVR interactions, helping call center managers and supervisors improve service to customers.

With the transformation of the “call center” to the “contact center,” companies expanded the information collected and analyzed to include other media, such as email and web chat. In addition, data based on workforce optimization was added to the mix, integrating information on quality monitoring and workforce management (including agent scheduling) to gain a more holistic view of contact center operations.

In terms of business processes, the contact center is highly process oriented – probably more so than any other department – in that there are strict procedures and workflows, as well as means to measure and drive adherence. Generally speaking, calls get routed based on the subject of the call or the skills needed to best handle it; a contact center agent receives the call and may or may not have an associated screen pop to identify the caller; the agent processes and handles the call in a specified and sometimes scripted manner, entering information into a CRM or other system; and, finally, the agent wraps up the call. Such processes are usually documented so that every contact center agent can handle incoming calls in the same manner, helping to achieve a consistent level of service.

Given its position on the customer front line, it’s easy to understand why the contact center is a major focus area for most organizations when it comes to the customer experience. However, although the contact center often has the most impact on this measure, other areas of the business, particularly back-office functions and branch operations, can significantly impact service delivery and customer satisfaction. A prime example of this is found in the insurance industry, where back-office business processes for underwriting, claims, and billing can have as direct an impact on the customer as the contact center. The same is true for other process and back-office intensive organizations, such as banks, financial services firms, and healthcare providers.

With customer touch points abound across an organization – all influencing the customer experience to some degree – it raises the question as to why they all are not held to the same standards of quality and performance. As previously mentioned, a great deal of attention is paid to the contact center in terms of KPIs and metrics, but what about the back office and branch/remote offices? One reason for this disconnect is the fact that these areas of an organization tend to have less stringent workflows, making it more difficult to determine how successful their business processes are in meeting customer-facing goals and identifying where improvements can be made.

Another and perhaps more telling reason is the fact that making sense of the volumes of information businesses gather is a complex proposition, requiring tools to analyze data and identify trends and problem areas to generate real actionable, enterprise business intelligence. Whether it’s phone conversations between agents and customers in the contact center, emails exchanged between co-workers in the back office, chats, SMS texts or other interactions, it’s important for companies to gain insights from the myriad of customer touches that occur inside and outside the contact center. By capturing and uncovering operational and business insights not only from interactions in the contact center, but from front- and back-office interactions, it’s possible to discover the underlying “root cause” of issues and understand process performance holistically. By doing so, companies are empowered to make more intelligent, non-compartmentalized business decisions about workforce performance and staffing, business processes, compliance, etc.

Tools to gather and analyze or mine information captured in the contact center have been around for a while, and new tools to extend these capabilities to the rest of the enterprise are starting to appear. Most notable is analytics-driven workforce optimization (WFO), which for a number of years has been helping contact centers capture and analyze information on workforce performance, customer interactions, customer service processes, and customer loyalty, and is now seeing wider deployment across back-office and branch operations. With analytics-driven WFO leveraged across previously thought of operational silos, companies can improve cross-departmental transparency and workflow to more effectively change and optimize processes, adjust staffing, and make other decisions to impact the quality of the customer experience enterprise-wide.  

Introducing UC Analytics

What does all of this have to do with unified communications? In the UCStrategies definition, UC is communication integrated to optimize business processes. UC is about using communication tools to improve the flow of the business processes in order to help organizations meet their business objectives. In addition, companies deploying UC to enable and streamline their business processes need to have defined metrics to determine how successfully they are or aren’t meeting their goals, and where improvements need to be made.

Similar to analytics-driven workforce optimization (WFO) for the contact center, a new category within Unified Communications called “UC Analytics” enables organizations to uncover trends and issues in the customer service value chain and the enterprise that may hamper business performance. Tying together tried-and-true contact center WFO tools such as quality monitoring and workforce management with advanced speech, data and desktop analytics, UC Analytics better equips organizations to capture, analyze and act on information about workforce performance, customer interactions, and overall business processes. When tied in with CEBP and business processes, UC Analytics gives companies the tools to take action and achieve true process optimization.

UC Analytics is a tool that enables companies implementing UC to see where and how improvements in processes and communications can be made and, in some cases, how well the UC solution is working in terms of meeting business goals.

As shown in Figure 1, when deployed properly and cognizant of multiple customer touch points – primarily the contact center, back office, and branch or remote offices – UC Analytics can be applicable across the spectrum of UC solutions to provide greater insights into interactions and processes. For example, UC Analytics can enable companies to capture, leverage, and put to use the wealth of information generated by customer interactions – transactional data and vital “voice of the customer” information – across communication channels to help identify bottlenecks, inefficient processes, and underutilized resources. From the volumes of data generated from multiple interaction channels, UC Analytics should be able to uncover critical business trends – both obvious and hidden – as well as the drivers of employee and customer behavior throughout the enterprise.

Here’s an example of how it works: Marketing launches a new product offer that it hopes to cross-sell and up-sell to existing customers. As a means to gain traction, reach targeted customers, and drive sales, marketing engages the contact center, providing the necessary scripts and access to product information to assist agents in effectively conversing with customers. After a period of time and little product uptake, contact center management, as part of routine business analysis, uses UC Analytics to systematically drill down into thousands of customer interactions and, through automated root cause analysis, bubble up specific business trends and issues. Listening more intently to a subset of calls tagged with a specific root cause, it becomes clear that the primary driver for the failure of the new product offering is a perceived complexity of payment terms and options. Armed with this actionable intelligence, the contact center can easily share the findings, even making recorded interactions available to support its business case, with the marketing department instead of internalizing the data. In turn, marketing can then engage with finance personnel to address the actual business issue negatively impacting the performance of the product offer. Overall, information flow is maximized, making pertinent data not only available to those closest to it, but to those closest to the business process in question. In this example, UC Analytics enables the organization to cross-functionally fix the current problems, streamline the business process, and make more informed decisions about future product offers.

Verint and UC Analytics

The first company to offer UC Analytics tools is Verint, which adapted its next-generation Impact 360 workforce optimization contact center solution specifically for back-office and branch operations. A synergistic suite of capabilities, including workforce management, call recording and quality monitoring, performance management, eLearning, and coaching, combined with speech, data, screen, desktop, and customer feedback analytics, form the basis for Verint’s UC Analytics offerings.

Impact 360 Speech, Data, and desktop Analytics help organizations surface key business-enabling and disabling trends across the enterprise that might otherwise go undetected. Automatically categorizing and analyzing call content and interaction data, suggesting the root causes of specific performance metrics, these tools reveal drivers of customer perceptions, business outcomes, and call volumes that can help companies reduce human latency in business processes, improve customer satisfaction and loyalty, enhance employee productivity, increase revenue, or reduce costs. Moreover, they provide insight into employee desktop application usage to show adherence to schedule, measure workload, and perform capacity and productivity planning.

Impact 360 Application Analysis captures desktop activities and application usage to show employee workflow patterns and the root cause of inefficient internal processes that may cause unnecessary customer inquiries into contact centers, service centers, or branch offices. From this insight, contact center, back-office, and branch managers can determine if their business applications and employee productivity tools are correctly configured for optimum use and take appropriate follow-up action.

Impact 360 Customer Feedback Surveys enables companies to use short, context-sensitive, dynamic surveys to capture data on products, processes, staff performance, and customer loyalty and satisfaction levels in real time. This provides insight into the effectiveness of people, products, and processes, allowing for quicker, more decisive action.

While UC on its own serves to digitally integrate communications, UC Analytics adds an analytical (“Tell me Why”) dimension that enables more effective use of resources – ensuring the right person is in the right place at the right time – and creates a more unified work environment whereby the optimization of business processes is based on the corresponding value to the customer service value chain and enterprise, not merely on departmental efficiency and effectiveness.

As such, with these advanced analytical solutions from Verint and others, companies can identify the underlying motive for interactions, which often turn out to be related to such things as processing delays, data entry errors, billing mistakes and confusing product offers that feed customer frustration – the very processes that UC strives to optimize. Effectively armed with the root cause of issues in the contact center, back-office operations, and branch/remote offices, organizations can improve quality and productivity more effectively and intelligently as a cohesive cross-functional organization.

We are in the very early stages of UC Analytics. With this said, we expect this new area to evolve quickly, with innovative vendors strengthening existing capabilities as well as developing new features to account for emerging communication trends. For example, it will be important for UC Analytics firms such as Verint to ensure that information is captured from self-service applications (online, IVR, IVVR, etc.), which will only grow as a key driver for initiating contacts with appropriate customer-facing staff. In addition, the increasing role of mobile, multimodal endpoint devices (smartphones) that enable real-time contacts between customers and customer-facing staff must also be taken into account, with mobile interactions feeding into UC Analytics in a similar manner as land-line interactions are today.

The bottom line for customers of companies who deploy UC Analytics:  Reduced costs, improved revenue and a better customer experience.

This paper is sponsored by Verint.