| Experts Corner |  CRM investment is wasted if the intelligence it delivers fails to influence despatched communications. How can businesses ensure that money spent on CRM analytics actually begins to benefit the messages that are delivered to customers and prospects?
David Jefferies, Marketing Director, Pitney Bowes
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An Analytical Approach to Workforce Management
Tom Lockwood, Senior Product Marketing Manager, Analytical and Self-Service Solutions, Aspect Communications
 How New Advances in Data Analysis Can Help Agents Enhance Service, In Real-Time
If the contact center is the primary touch point a customer has with a company, then it’s clear that the customer service workforce is critical to CRM success. Whether interacting with customers on the phone, via e-mail or on the Web, CSRs need to have the right information at their fingertips, at the right time, to provide optimal service. And contact center managers need to have equally rich data to make smart decisions about how to best utilize the CSR workforce — information driving forecasting, scheduling and staffing -- so that the contact center is not only meeting customer needs, but also doing it efficiently and cost-effectively.
Traditionally, contact center managers have relied on production reports to make these decisions. But while production reports are great for analyzing long-term trends, the mountains of statistical data generated are usually too broad and cumbersome to be of much use in real-time. When it comes to making day-to-day decisions, its critical that organizations be able both to extract the most relevant data from the clutter, and then to use this data to drive greater efficiencies across the contact center.
The merging of analytical applications with best practices in workforce management are presenting new opportunities for companies looking to reap even greater returns on their contact center investments. This article will look at the critical differences between analytics and reporting, the must-have characteristics of a good analytical application, and at examples demonstrating how contact center managers can leverage analytics in workforce management to drive new gains in customer service, agent performance, cost effectiveness, and efficiency.
Analytics vs. reporting: what’s the difference?
The old way: production reports
Traditional call center reporting is based on the ability of automatic call distribution (ACD) systems to generate statistics. ACDs are great at measuring things like the number of calls handled, the length of time that callers waited before their calls were answered, how long customers and agents remained on the line, and how many calls were routed to particular agents, agent groups or call center sites.
Standard practice in most call centers has for many years been to bundle these kinds of statistics into production reports that regenerate regularly for distribution to supervisors and managers. Production reports are simple, one-dimensional tools, but their use is widespread -- owing to the fact that, until recently, they’ve been the only game in town. While useful for tracking long-term trends and a good source for detailed statistics that must be shared with regulatory agencies and other stakeholders, production reports fall short when it comes to managing the contact center workforce and optimizing day-to-day operations in real time.
One disadvantage is that production reports are static — providing snapshots of contact center activity at a particular point in time, but out of date as soon as they are generated. Another, more serious problem is that production reports give a very broad and general view of the contact center, collecting vast amounts of unsorted information, much of which has little relevance to effective operations.
It is the need to sort and organize statistics that makes using production reports a clumsy and inefficient way to seek actionable information. For this data to be of any use, managers need to know not only know what statistics are relevant, but also figure out a way to extract relevant information from the clutter. Only then can they analyze the data and decide what to do with it. This means they spend a lot of time working with spreadsheets to crunch the raw numbers and draw conclusions — time that could be spent on other critical tasks such as coaching and supervising agents. And in spite of all this effort, the results are often of minimal value, produced far too late to be of much practical use in real time. It’s not uncommon, for instance, for agents to receive their performance results for a particular quarter after the quarter has ended, making this information useless in terms of helping agents improve in time to impact their quarterly bonuses.
A better way: analytical applications
Analytical applications, on the other hand, do all the heavy lifting for the user. Analytical applications don’t just dump statistics on manager desktops — they deliver specific, relevant information that applies directly to the most pressing concerns of running the contact center efficiently and supporting business goals. The time-consuming work of sorting the data is done by the application, and presented to the user in a structured format that is easy to comprehend. All of this makes analytical applications much more desirable — both from the standpoint of cost and the standpoint of effectiveness, than traditional production reports.
The Elements of an Effective Analytical Application
A good analytical application is a focused management tool that:
• Selects information based on pre-defined application logic tailored to specific activities and business drivers;
• Offers different views for different users, based on their job requirements;
• Provides an interface that lets users navigate through the information, looking at it from different perspectives and drilling down to the most granular level of detail in order to identify root causes for events and truly understand the data;
• Presents information in a structured, easy-to-navigate format that enables even non-technical users to participate in analysis;
• Includes tools for communicating with key stakeholders in order to take action on insights gained from the data.
Applying analytics to workforce management
Datamonitor reports that eLearning and agent analytics will make up 43 percent of the total workforce optimization market in 2007, up from 22% in 2001 (Report: “Workforce Optimization Technology Markets to 2007).
While analytics may be applied to all types of contact center reports and functions — workforce management is a great place to start. For one thing, there’s plenty of data to work with, as workforce management applications are a source of detailed information about forecasts, schedules, and schedule compliance. And, managing the workforce effectively is one of the most important contact center functions: staffing accounts for the greatest percentage of contact center costs (by some estimates, as high as 70 percent of contact center expenditures), thus, preventing over or understaffing is critical to both maintaining service levels and controlling costs.
Furthermore, all of the advantages that analytics offers — quick access to relevant information, job-specific displays, and tools to communicate and take corrective action — are directly applicable to the processes of managing and motivating the contact center workforce for maximum efficiency.
Effectively leveraging analytics in workforce management requires the use of key performance indicators (KPIs) that present only data and measurements that are specifically relevant to workforce efficiency and effectiveness. Ideally, the KPIs are determined by specialists in contact center best practices and may include measurements such as average talk time, number of contacts handled and schedule compliance. For example, KPIs can enable managers to more accurately pinpoint data like which agents generate the most revenue, or which are able to resolve issues for Spanish speaking callers the quickest. The result is a much deeper understanding of contact center activity than can typically be gleaned from system reports alone.
Once key information is extracted, KPIs may then be displayed on dashboards tailored to the specific job requirements of different groups, such as agents, supervisors, managers and control desk staff. Two important characteristics of a good dashboard: clear, easily comprehended displays of information, and flexible, intuitive navigation based on the specific requirements of the user. For example, color-coded displays may be used to tell users at a glance, in real time, whether performance is above, at or below target levels. In addition, a good analytic application will give users the choice between numeric and graphic displays, and allow them to change views, drill down, and quickly pinpoint root causes for specific outcomes.
What makes analytics such a revolutionary advance over traditional reporting is its effect on contact center efficiency and productivity. Once workforce managers, supervisors and agents can see what is going on in the contact center, and why, they are armed with the information they need to make intelligent decisions related to forecasting, scheduling, performance, and more.
Agents who are falling short of goals can adjust their performance or communicate with supervisors about the reasons behind the shortfalls. Supervisors can coach agents, set group and individual goals, and provide incentives. And managers can efficiently guide the workforce without getting bogged down in minute detail. This type of job-specific information makes the difference between just “doing the best with what you have” and planning for, and ensuring, outstanding performance, service and efficiency both now and in the future.
| Tom Lockwood is a senior product marketing manager for analytical and self-service solutions at Aspect, and is part of the team responsible for assessing market need in the area of contact center technology, and crafting messages and marketing strategies for delivering Aspects solutions to the market. Before joining Aspect in 1999, Mr. Lockwood held a number of technical, marketing and management positions at both IBM and PeopleSoft. He holds a masters degree from the University of California, Santa Barbara.
Aspect Communications
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