UC Analytics: Is This the Real Human Centric Data Model…Where Organizations Can Connect All the dots?

In today’s era of customer relationship management, businesses must strategically invest in tools that will improve the customer experience and maximize customer lifetime value. Best-in-class organizations are increasingly deploying powerful tools for customer analytics—including tools for automated modeling, real-time scoring, interaction optimization, and incremental response modeling.

So what does this have to do with Unified Communications? Everything! Achieving customer centricity requires a holistic, enterprise-wide view of the customer experience.

Organizations need to take a broader view of information, a more effective process to analyze data to understand what is happening and why, and determine a way to improve workflow across and within departments, including external stakeholders.

	In today’s business climate and digital age, driving efficiency and productivity in compartmentalized functional areas is no longer acceptable. Information must be captured, analyzed, shared and acted upon cross-functionally to improve enterprise operations.

With UC Analytics, companies can powerfully leverage and put to use the wealth of information generated by customer interactions across the enterprise—from branch offices to back-office operations to the contact center. From the volumes of data generated, UC Analytics helps organizations uncover critical business trends—both obvious and hidden—as well as the drivers of employee and customer behavior. Companies that devalue or underestimate the inter-departmental impact not only contact centers, but back-office and branch operations have on service, satisfaction and sales, will remain challenged to achieve customer centricity and process optimization no matter the unified communications strategy deployed.

So let’s take a step back in time to explain the game-changing potential of UC Analytics to both organizations and the customers they serve.

A state-wide utility client recently asked for some assistance with their call center operations. The objective was to reduce operational costs. Per the client’s own calculations, their cost per call was $7.00 and their average talk time was five minutes and 19 seconds in duration. Asked how they arrived at those numbers, the client indicated that it had divided the total budget by headcount and then factored in management overhead, schedules produced by excel spreadsheets and other relative factors. Based on this, the initial recommendation made was to map a call process mapping to a business alignment process to validate the costs. The client had a fairly current release of ACD and IVR software, WFM, reporting, chat and email, all operating in parallel but not interactively.  

Based on a business process review, the following was discovered:

• The cost per call was not relevant, as they were failing to track the total transaction from cradle to grave
• The actual handling cost of a transaction was not $7.00 a call, but ranged from $9.24 to $300.00 for the total transaction based on the entire business process and closing the loop
• The actual handling time was not 5:19, but anywhere from 24 hours to two weeks based on the business request or query
• A percentage of calls were customers calling back on an issue that had not been previously resolved
• The call center did not track emails and escalation to other parties outside the center, and failed to account for those factors in transaction or call handling time, resource effort, cycles, SLAs or cost
• The call center did not track activity, non-real-time, after work, or special project time
• Transaction issues were not documented on the desktop or in the case management database, while Isolated emails were prepared and sent with no history trail to refer back to
• There was no external accountability to close a ticket or issue and virtually no ownership
• There were no documented SLAs within the call center
• The client was unable to define First Call Resolution
• When adding technology, there was no audit of ROI

As stated earlier, with UC Analytics, companies can leverage and put to use the wealth of information generated by customer interactions across the enterprise—from branch offices to back-office operations to the contact center–to uncover critical business trends. If this client had considered UC Analytics, the following would have happened…

UC Analytics would have helped to break down the barriers between different departments, allowing them to effectively capture, analyze and act on cross-functional information. This client did not understand that external commitments outside their control affected their deliverables and created gaps and weak links in their processes and commitment to delivery.

UC Analytics would have enabled the client to identify the underlying motive for calls into the contact center relating to processing delays, data entry errors, billing mistakes, and credit and collections to name a few of the issues that became apparent. The client used a third party to process bills. A new ERP system had changed the formula of the bills so that a client bill was not the same as what was on the agent’s screen. The billing cycles had increased and dates of the billing cycles changed. There was a down time between bill disconnect requests for non-payment and re-instatement. An effective UC strategy with the contracted fleet, such as mobile work force management tied to agent screens and credit and collection lists reporting in parallel would have helped to resolve this or at least reduce the  handling times and efforts. 

UC Analytics would have gone a step further in identifying not just “what” had happened, but “why” it had happened. It could have been determined why customers were calling and emailing requests? Why customers kept calling back? Why abandon rates were high on certain dates and not others? What was driving spikes in the call center? What was the real average handle time?

Operationally-aligned and customer-centric UC Analytics like Verint’s analytics-driven Impact 360 workforce optimization suite, which combines proven applications such as quality monitoring and workforce management with speech, data, and desktop analytics, can help answer these questions and provide even more telling insight into issues such as how should the organization respond to trends, and how external forces (such as distribution or fleet) affect calling and touch points into the organization. 

In particular, Verint’s speech analytics uses audio mining and indexing, with advanced motion detection, where large volumes of customer calls are intelligently categorized and can be searched for occurrences of specific words and phrases. In the case of the utility client, a review of agent-customer interactions would have revealed high occurrences of phrases such as “I don’t know” or “I need to check with field operations for that available date.” This would have revealed agent knowledge gaps that could be filled easily with coaching and eLearning tips and clips.

A summary of this refined process would be:

So how do you compare these new products and opportunities? Here are some tips on what to look for in a UC Analytics solution:

• Speech analytics should be based on more than key word spotting or a limited number of predefined words. These technologies are not enough to generate the intelligence needed. Look for a solution that automatically generates meaningful business categories from call content and uses categorization algorithms that understand call content.
• Look for a data mining solution that can automatically surface intelligence from large volumes of data without prior knowledge of trends and associations.
• An analytics solution should be easy to use and readily available. Make sure it is designed for business users and requires no specialized system training.

UC analytics is brand new, and it will take time to figure out how best to utilize the tools and data available. While Verint is the first vendor to provide UC analytics tools, others will be following suit. Expect to see an accelerating number of organizations starting to deploy UC Analytics solutions. Can your organization afford not too?

1 Responses to "UC Analytics: Is This the Real Human Centric Data Model…Where Organizations Can Connect All the dots?" - Add Yours

Art Rosenberg 5/25/2010 6:15:34 PM

Good article, Samantha! UC analytics has to take into all forms of communication contact and response, as well proactive, self-service applications that will initiate contacts with different types of end users. We need the analytics to understand what is going on operationally and why, not just to evaluate staff performance. With the flexibility of UC, we also need to track the cross traffic between the various forms of contact, especially as users become more mobile. Such information won't be coming from a single source of activity data, but from a variety of sources. Correlating communications activity with business process work flow, is, of course, always an important source of metrics.