Driving Automation in Technical Support Centers

A number of characteristics make technical support centers different from other types of contact centers:

• Support center analysts require special skills and technical training and that usually translates into higher payroll than your average contact center.
• Contacts are more complex and can take longer to handle, meaning that more support center analysts are required.
• Because the primary job of the support center is to get people back to work as quickly as possible, and because contacts take longer and labor costs are higher, first contact resolution (FCR) rates are an especially important metric.
• Automation in technical support centers could result in dramatic cost reductions and service quality improvements.

Let us take a closer look at some of these unique characteristics and the role that technology and automation can play in improving performance and controlling costs.

Higher Labor Costs

As mentioned, one of the characteristics that makes technical support centers different from other contact center environments is the complexity of the contact itself, whether it is by phone, chat, email, or another channel. Because of the increased complexity of the contact, the analyst is usually required to have special skills.

There is a general trend to open more contact channels, such as web chat and email, but based on the immediacy and complexity of the issues, the phone channel still dominates. Talk times may be longer in technical support centers than in other types of contact centers because fact-finding and troubleshooting steps are often contact components, and these add additional time.

The other characteristic of many technical support centers is a tiered staffing structure. Often, more routine calls are handled at Tier 1, and issues that are more complex are handled by Tier 2 staff. Tier 1 support center analysts might handle 70% of contacts while Tier 2 support center analysts handle 30% of contacts. The actual staffing plan is a pyramid with Tier 1 staff at the lower level and Tier 2 support center analysts at the upper end of the pyramid.

Higher labor cost and the increased business desire for speed in technical support centers makes the need for automation and heightened efficiencies more acute. Increasing automation is one way to address high labor costs. This allows an increased throughput of contacts across a reduced staff size. Let us discuss some ways that is done.

Increasing automation is one way to address high labor costs.

Driving Higher Levels of Automation

Automation decreases labor cost by reducing repetitive work performed by human staff and by freeing up resources for more proactive work.

For more about the rise of automation in tech support, read Roy Atkinson’s blog, Is the Automation Storm Coming to the Service Desk?

Automation in technical support centers can be divided into two broad areas:

1. Traditional Task Automation: Traditional task automation offloads work from human staff to specialized self-service systems and workflows that automate case management and back office processes. The figure below shows the web self-service and Interactive Voice Response (IVR) components for task automation. 
   
   
2. Capability Enhancements: Enhancements to staff capabilities utilize knowledge management (KM) and artificial intelligence (AI) tools to increase human performance. The result is increased quality and decreased contact processing time (time to issue resolution). The figure below shows the skill enhancement components for task automation.
   
   

Task Automation

Providing customers with self-service tools that eliminate the need to contact the support center is the goal of automation. Your bank’s ATM uses the same approach. Customers find that it can be faster and easier than going into a bank and dealing with a teller.

The most common self-service tool is a website. Users can connect to a support website to download updates and drivers, access diagnostic programs, reset passwords, or review information in user forums, libraries, and both text-based and video help information.

Traditional IVRs, although not popular with callers, are widely used across the industry and remain a popular self-service vehicle. Although, web self-service has stolen much of its thunder, the dominance of the phone/voice channel means that IVRs will be around for a long time. In some of the more innovative IVR applications, we will see a blending of IVR, web, SMS text, and email.

Smartphones are widespread, and this has allowed voice to remain the dominant contact channel. It also opened up some opportunities for other support self-service tools including Visual IVR and specialized mobile support apps.

Smartphones support video, and video is more impactful and effective than text-based information. Technical support via video chat and the transfer of help-focused textual information to animation and video will increase dramatically in the next few years. In addition to increasing automation around user self-service, behind-the-scenes automation can allow support center analysts to provide answers and solutions faster and more efficiently.

You can look at task automation as replacing any task that is performed manually by a customer or a service representative and performing the task by using technology to automate or eliminate it. Some primary steps to task automation follow:

Make it Easier. Customers take the path of least resistance, so if servicing themselves through automation is better and faster than calling into a technical support center and speaking to a service representative then that is what they prefer to do. The first step to increasing the level of automation and drive innovation is to analyze the “as is” state.

Examine the present state to review and analyze customer-facing self-service tools. This examination should focus on and assess ways to reduce the amount of customer effort required to complete tasks. There may be opportunities to offload customer activities and tasks to websites. Simplify processes, and make it easy. Consider all the things a customer must do, and determine how many of them can be eliminated. Specific steps should be:

• Present automation options on any contact channel the customer selects, such as phone, email, web/video chat, or SMS.
• Use mobile applications that automate tasks where possible.
• Utilize intelligent downloadable tools to automate diagnosis, troubleshoot, and fix issues.

Make it Faster. Regardless of the contact channel or self-service system, measure time when the customer is waiting for a response or being presented with choices. The key areas are eliminating time by speeding things up or skipping steps. The questions and tasks here are:

• Can information required of the customer be gathered from other sources? For example, can we identify the customer by the phone number they are calling from or on the web by an email or IP address? 
• Can system response times be decreased or can customer requests and responses be anticipated by utilizing artificial intelligence (AI) tools (e.g., using AI to formulate email replies).
• Use AI to minimize response intervals between web chat message segments.
• Utilize mobile applications to automate customer requests.

Make it Smarter. Make it smarter does not refer solely to the use of AI tools. Of course, making the process smarter using AI technology is a given, but also, it refers to the hard-to-duplicate ingredient in the mix: human ingenuity in the overall design. Innovation is indispensable in using technology in novel and creative ways to service customers and improve service quality and customer satisfaction. Some key tasks and activities in making the overall contact more customer focused and intelligent are:

• Integrate AI into overall process to anticipate customer requests.
• Integrate AI in processes to empower customers and put high-quality self-service tools at their disposal.
• Design all processes from the customer’s standpoint.
• If a change does not add value to the overall contact from a customer perspective, do not do it.
• It is no longer enough just to have customer information available when a customer calls, it is necessary to take some actions based on that information. Example of actions based on customer information may be:
• Use AI to enable contact-by-contact routing of all phone calls, email, web/video chat, and SMS based on what you know about the customer.
• Use customer information to initiate automatic channel blending across a single contact, so that IVR callers can receive text or video information and diagnostic apps via email or SMS.
• Use AI tools to anticipate the reason for the contact and provide customized information and in-queue treatment based on it.

Capability Enhancements

Customer relationship management (CRM) tools (also known as case management systems) often promise to increase human performance. The systems should allow support center analysts to function at the level of a software engineer, by facilitating problem diagnosis and solution identification. Unfortunately, in most cases, the promise of these systems has gone unrealized; most CRM systems do not do this or underperform in this area. In most cases, using these systems makes contacts take longer and has no impact at all on FCR.

Knowledge management systems can be an integrated or adjunct component of a CRM system. The systems allow support center analysts to search a support library or database in global fashion. An example of automation here would be if contact analytics were actively listening to a phone call in serving up knowledge management content automatically to the service representative based on what the user said. Most knowledge management systems have little to no automation and rely on support center analysts to search for the correct content for themselves.

In the large technical support centers, intelligent scripts with branching logic that walk agents through troubleshooting steps toward resolving issues are common.  Extremely large operations are pushing toward real-time contact analytics to assist support center analysts by using artificial intelligence to automatically diagnose issues or serve up appropriate knowledge management content. These systems also aid in troubleshooting by prompting agents on what to ask customers as well as suggest actions that may solve the problem.

Make People Smarter

The great promise of CRM systems is that it would increase the skill level of the people using it, such as allowing an English major to function at the level of an electrical engineer. Through the combined power of AI and knowledge management systems, that promise is being realized. Examples of this are:

• Utilizing intelligent scripts that gather information and facts from the customer and use that information to suggest solutions to the service representative while they are talking with the customer.
• Using real-time contact analytics and artificial intelligence to make suggestions to the service representative about what to ask, say, or do while they are talking with the customer.
• Automatically deliver conclusions about the data as well as suggest actions based on the data.
• Customize the service representative’s handling of a contact based on the customer’s last satisfaction survey
• Automatically identify return contacts on the same issue (FCR failures) for special handling.

The Majority Are Just Getting By

Many companies regard technical support as simply an expense to be controlled and decreased through aggressive cost management. Reducing costs is a necessary goal, but the methods matter. The methods used to achieve these goals say so much about a company’s customer vision and their level of management and operational sophistication.

Some companies deploy technical support centers with poorly trained and poorly equipped staff whose primary objective is to handle the contact, just answer the phone, email, and web chat. The goal may not necessarily be finding an appropriate solution for the customer, but simply handling the contact. These companies lack a clear customer technical support vision and roadmap to the future. They are on a treadmill of just getting by, and in most cases, the cost will eventually be paid.

Some technical support organizations take a different approach. They have used technology to enable customer-centric processes that both improve service quality and control costs. These industry standouts have turned support into a key differentiator that confers competitive advantage. They do it by letting their vision for technical support drive technology and process to intelligently use automation to serve customers and empower service center staff. This approach shifts the focus from meaningless numbers and metrics to quality and customer satisfaction and separates industry leaders from those who are struggling and just getting by.          

Doug Tanoury is a management consultant at Noblis and specializes in optimizing and improving the customer experience. He is a customer management expert, having held contact center operations and management positions at General Dynamics, AT&T, Electronic Data Systems (EDS), MCI Telecommunications, Eventus Solutions, eLoyalty, and Siebel Systems. Doug has published a number of whitepapers and articles that focus on customer relationship management, ways to manage customer contact centers more effectively, and innovative ways to improve the customer experience.