On the UCStrategies.com site a few of us have posted articles or opinions on how UC came from the contact center because so many UC functions, such as reporting, presence, etc. have been used for decades in contact centers. This concept is getting even more interesting as vendors are beginning to combine more of the tools of the contact center in with UC tools. Analytics-driven workforce optimization (WFO) has been optimizing people, processes, and communication in the contact center for years. So now we are starting to see an emerging category within UC called “UC analytics” that tie together tried-and-true contact center WFO tools such as quality monitoring and workforce management with advanced speech, data, and desktop analytics, to help organizations uncover trends and issues that may hamper business performance. This holds true not only in the contact center, but across the enterprise. Using UC analytics, organizations are better equipped to capture, analyze, and act on information about workforce performance, customer interactions, and overall business processes in the contact center, back-office operations, and even branch and remote offices.
1. . My first question is around the tremendous potential for analytics to help organizations better understand where there may be communication bottlenecks or broken processes that are impacting customer service, and in turn customer relationships. As an analyst, one of my favorite of these tools is speech analytics, as it provides great value in “mining for what is missing” from other analytics tools. In fact, more and more I’m hearing of companies evaluating speech analytics for the contact center, where the majority of customer interactions take place. Given this, how can the deployment of speech analytics, as one UC analytics tool help optimize more than customer service and processes resident in the contact center?
First off, investments in speech analytics attest to the growing adoption of business analytics in facilitating more efficient and effective business processes. Specifically in the contact center, with a greater emphasis on truly understanding the “voice of the customer,” speech analytics is becoming even more integral to understanding what is happening with customers and why. As such, those in the industry, like myself, see the deployment of speech analytics continuing to gain traction in 2010 and beyond.
Generally speaking, speech analytics works by employing technologies such as word spotting, indexing, and emotion detection to systematically analyze call content—from hundreds, thousands, or even tens of thousands of calls—and suggest root causes so you can quickly identify issues related to specific calls. In addition, speech analytics can often search unstructured audio data, such as CTI-tagged data, agent name, and customer segmentation, to facilitate deeper analysis of interactions, data mining, and drilldown to specific calls or sets of calls.
Given this, with the abundance of customer interactions that take place in the contact center, the value of speech analytics to this functional area is rather apparent. However, it’s important to remember that the contact center is only a component of the customer service value chain, and that processes in the back office and other functional areas often can impact customer service and the customer experience as much, if not more, than the contact center itself. In turn, this can affect the performance of an enterprise as a whole and its achievement of top and bottom line goals, particularly if issues go undetected or remain compartmentalized within an operational area (silo).
Therefore, in terms of overall business benefits, process optimization, and even ROI, the enterprise can stand to be the greatest benefactor from speech analytics. This is due to the fact that using speech analytics to analyze the content of customer interactions in the contact center can provide valuable customer intelligence relevant to many areas of a business. In the context of UC, this enables key departmental as well as broader enterprise issues and trends to be identified, shared cross functionally, and viewed more holistically for quicker, more informative, and more collaborative decision making that improves business processes and drives customer centricity.
These business processes may very well be directly related to customer service, such as how a customer’s technical issues are resolved, but they more often cross disciplines and functions and indirectly impact service, such as the development and launch of a new product offer that encompasses product management, marketing, finance, sales, and other areas across the enterprise. Thus, with speech analytics, an organization can more effectively identify and address communication bottlenecks and broken processes that span business functions and can impact everything from customer service to revenue generation to profitability.
Good point. When speech analytics was first introduced we really focused on agent training, such as doing a proper close or upselling, or using it to glean information on what customers were talking about, such as mentioning competitors names, for example. But its becoming a critical part of uncovering issues and opportunities throughout an organization as well. I hope someone jumps in with a customer example or two. If I think of one I'll post.
I wanted to add though, that speech analytics is one part of UC analytics. Blair and I both wrote UC Views on this, using what your company is doing by combining speech analytics with other analytics. Blair did an In the Spotlight article on Actionable Intelligence in UC, and I did one that had a different slant to it. This is going to be a big area that is just getting defined.
To provide some more color via customer examples, I have included a few links below to case studies where speech analytics played an important role in improving enterprise processes and performance.
UC analytics is more than just speech analytics. Speech analytics is just a great tool to enhance the combination of analytical tools that we have across the entire enterprise. I think in order to quantify or clarify what un analytics is we need to list the tools that are included. So what else besides speech analytics, and contact center reporting should we include in this category and why?
You mention the value of speech analytics extending beyond the contact center to the enterprise. How do data analytics, customer feedback, and desktop analytics contribute to enterprise process optimization? I think its the combination of all the tools that we can use that will provide the most benefit to companies.
Also, and this is for Jim, I think companies are using combinations of these already, and many just don't understand how powerful integrating more tools in can be.
These solutions contribute in a very similar manner to speech analytics. Most importantly, they provide a more holistic view into operations and performance across the customer service value chain. Increasing transparency amongst stakeholders, data analytics, customer feedback, and desktop analytics can unearth issues and trends that can be leveraged to drive more collaborative process improvement more broadly across the organization, which is particularly important given the fact that numerous departments and the processes they employ generally impact service delivery in one way or another.
Data Analytics employs data mining technology to scour the attributes associated with calls—and possibly even the business issues identified by speech analytics—to uncover contact scenarios that can positively or negatively impact an organization’s ability to meet its key performance objectives. With data analytics, organizations can better leverage the volumes of data generated by customer interactions to uncover hidden issues and opportunities. Measuring everything from call metrics, such as average talk time, to productivity metrics, like interactions handled by agent per day, to customer experience metrics, such as first call resolution and satisfaction scores, data analytics can help optimize processes that directly or indirectly influence these metrics inside and outside the contact center.
Customer Feedback enables organizations to collect customer data through IVR, Web, and email surveys to determine the drivers of satisfaction, identify improvement areas, and measure customer loyalty. Using short, context-sensitive, dynamic customer surveys, organizations can capture data not only on loyalty, satisfaction, and how well staff handled an inquiry, but on the very products and processes that shape the customer experience and contribute to organizational performance. Moreover, based on survey results, alerts and workflow items can be delivered right to the desktop, with links to actual call recordings for further analysis, to improve enterprise information flow.
Desktop Analytics captures desktop productivity and application usage, delivering graphical reports that illustrate which applications your staff uses—including how they use them, when, and for how long. Providing an analytical view of desktop workflow, organizations can surface and assess employee workflow patterns and the root cause of inefficient internal processes, isolate processes or applications that may require re-engineering, and reinforce usage policies. This is particularly powerful for contact centers as well as process-intensive operational areas, such as back-office administrative functions and branch/remote operations, where there is generally a heavy reliance on business applications to perform routine tasks that can directly impact objectives such as sales, service, and expense management.
Although I understand how UC Analytics can help optimize processes inside and outside the contact center, is it actually being adopted and deployed by other areas of the business? I know that individual business units will use different analytics packages, and solve problems that are specific to their own areas, but do they see the bigger picture of combining data from different areas to improve their department as well as others?
Workforce optimization (WFO) and, more recently, analytics-driven WFO have been driving performance gains in the contact center, helping organizations improve everything from the customer experience to sales, for many years. Now, with UC Analytics, we are starting to see the adaptation and deployment of these same technologies and concepts to other areas of business, most notably back-office and branch operations.
This is mostly being driven by the fact that numerous functions beyond the contact center can, whether directly or indirectly, impact service delivery and, thus, the customer experience, customer loyalty, and even profitability. How many times do people call customer service frustrated by a processing delay, billing mistake, or, perhaps, confusion over a product offer? In these instances, the underlying motive for the interaction has little to do with the performance of the contact center, but rather processes that lie in back-office or branch processing areas that can be a cause of customer dissatisfaction and defections and can significantly boost operating costs.
By leveraging UC Analytics in back-office and branch operations in addition to the contact center, organizations can further focus its analysis and optimization efforts on areas prone to potential bottlenecks, inefficiencies, and underutilization given their process reliance. Effectively armed with the root cause of issues across the customer service value chain, organizations gain a more holistic view of operations and can improve the efficiency of claims processing, order fulfillment, customer administration, transaction processing, billing, and other back-office functions to transform the back office into a strategic business asset. Furthermore, UC Analytics can help strengthen the forecasting and scheduling of staff to meet customer demand, which is vital to effective branch operations, as well as determine whether or not the business applications critical to achieving process optimization are efficiently deployed and utilized.
In today’s business climate, companies that devalue or underestimate the inter-departmental impact back-office and branch operations have on service, satisfaction, and sales will remain challenged to achieve customer centricity and process optimization no matter the UC strategy deployed.
Ryan, that is definitely true. Its funny that in presentations at trade shows or conferences companies will often give examples of how they uncovered some back office problem that was driving calls into the contact center and costing a ton of money. Usually these presentation examples are couched in terms of "we uncovered this problem and saved a lot of money". But I think we are getting to the point, especially as we start combining tools, that these kinds of relevations won't be one off events. So not only will we uncover more of them, but we will go looking for them.
That is why I'm kind of excited about bringing out the term UC analytics, because I think it will start getting people to think about using tools to go on witch hunts to see what they can find and how it can improve all areas of the business.
Nancy, I think you are right on the mark. With organizations turning to analytics to help them operate and act more strategically, the unearthing of broken processes and other issues hampering performance will not only become more commonplace, but more of a proactive business process with more formal measures and metrics. In fact, most companies I talk with today are already thinking about how tools such as speech analytics, desktop analytics, and customer feedback can help them improve the customer relationship across all areas of the business, and they want to proactively use these tools versus just merely reacting to problems. The outcome of these tools is becoming a big component of ROI for both vendors and end users in terms of how they can take out costs and increase sales and profitability.
How about taking a different approach to UC analytics? One of the things that we talked about when we said that UC really came out of the contact center was that there are a lot of features that the contact center has that UC has, such as presence. So, most organizations who have taken the plunge into UC do it not only to make processes more efficient and effective, but to improve “presence.” How does UC Analytics contribute, if at all, to the achievement of this objective?
Good question Nancy, and certainly applicable given the importance of "presence" in the overall scheme of unified communications. I'm actually going to ask a colleague of mine, Bill Durr, to respond to this. Bill is a fairly well-know figure in the contact center space and can offer some unique perspective into how UC Analytics can contribute to the improvement of presence across the enterprise. I will ask him to post a reply as soon as he can.
Hi Nancy. I’ve been following the thread and I think your question about UC Analytics and presence is an interesting one. Presence, of course, is the technology that enables the virtual enterprise. And virtual enterprises have some clear operational advantages, as well as some disadvantages. Not the least of which is that in a truly virtual enterprise there is a significant risk of chaos.
We’ve already had some experience in the contact center, as you know, with work-at-home employees. Generally, work-at-home employees are happier and more productive than traditional office employees. But staying connected to the ethos of the enterprise and feeling a sense of team , shared effort and success is really difficult. By some estimates, fully 20% of agents who opt to work from home, return to the physical contact center within 6 months. Nevertheless, work-at-home employees are more valuable in part because they are flexible. But the flexibility must be controlled or there will be chaos. They have schedules to adhere to in order for the operation to meet its service delivery goals.
Part of UC Analytics provides rigor. Rigor, a word describing a concept, implies that there are rules that apply to everyone. And that, I think, is the connection to presence.
In some presentations and future projections of virtual enterprises where presence stitches subject matter experts together with customer service representatives as they interact with customers, I am struck by the fact that the availability of subject matter experts cannot be simply a matter of whim, when they are “free” from their day jobs. A clear high-level value of UC Analytics is that it confers a grand view of the entire enterprise in terms of interactions with customers, partners and prospects. The entire enterprise can be modeled and simulations engines provide projections of service delivery measures as well as employee “presence” requirements and schedules based on each employee’s preferences.
By bringing the rigor of Workforce Management to employees bound to the enterprise by presence, UC Analytics helps enterprises avoid flexibility chaos.