August’s Topic of the Month for SSPA Research is Remote Support. When asked in the July issue of the SSPA News which title you most wanted to see this month, the winner with 80% of the vote was “The ROI for Remote Control Solutions.”

SSPA Research defines remote support platforms as the bundle of functionality used to take control of a customer’s desktop via a secure internet connection to diagnose and resolve issues. Leading remote support platforms are expanding, with new features added in each release. Core components in most platforms include:

• Remote desktop control. Agents can access the customer’s equipment via a secure web connection, and take control, performing functions as if they were sitting in front of the machine.
• Web chat. Agents may chat with a customer using a Web chat dialog during the remote control session, freeing up the customer to take a call or perform other work, with the agent prompting them with the chat dialog when additional information is required.
• Web collaboration. Some platforms also support Web collaboration, allowing other agents to join the remote control session to provide assistance.
• Screen sharing. With screen sharing, the agent can view the customer’s desktop, with an option to allow the customer to view the agent’s desktop as well. This allows agents to walk customers through procedures they may be struggling to attempt on their own.
• Session monitoring. A new feature now available with some platforms, supervisors can select a remote control session currently in progress to see how the agent is handling the situation. Useful for quality control monitoring or to keep tabs on new agents.
• Customer log files. Different platforms offer various diagnostics that can be used to pull complete log files of a customer system for real-time or historical analysis. Log files typically are sent to the agent as a text file at the end of the session and attached to the case.

By putting agents in the driver’s seat, issues are easier to diagnose and faster to resolve than by walking the customer through checking system values and attempting recovery procedures.  This speed and accuracy impacts many support metrics and forms the basis for the ROI model discussed in this article.

When interviewing companies and reading customer case studies for remote support success, it is clear that companies approach ROI metrics differently, and a variety of metrics are given as proof of cost savings for remote support projects.  Key metrics for calculating remote support ROI include first contact resolution rate, talk time or incident handling time, number or percent of escalations, and customer satisfaction.  In the sections that follows, the cost impacts of these metrics and how each is influenced by remote support will be explored. 

First Contact Resolution

When customers are surveyed for what they most want in a support experience, having a smart, efficient agent that solves their problem on the first interaction is at the top of the list.  First call or first contact resolution, then, is a great indicator of the health of a support organization.  Besides being a major contributor to customer satisfaction, increasing first call resolution creates significant cost savings to an organization through:

• Decreasing interactions.  When issues can be resolved on the first interaction with the customer, subsequent phone calls and emails are eliminated.  Multiple call backs or email interactions drive up incident handling time, and subsequently incident cost.
• Cutting incident handling time.  When issues can be resolved quickly, on the first interaction, average incident handling time goes down. By freeing up agents to handle more incidents per shift, agent productivity is increased.
• Reducing escalations.  Issues resolved on the first interaction are not escalated to Level 2 or beyond, cutting the number of incidents escalated to these more expensive support agents.

Remote support technology increases first contact resolution by allowing agents to take control of a customer desktop to quickly diagnose and resolve the issue, collecting all needed information in the first interaction.

Average Talk Time

Average talk time is derived from automatic call distribution (ACD) systems that track how long an agent is connected to the customer via phone.  Alternately, some companies measure incident handling time, which includes after call work time, such as updating the notes of an incident in the case management system.  The average time agents spend on each interaction is a base metric that influences many aspects of support operations, including:

• Capacity.  If interaction times are shorter, agents handle more interactions per shift, and overall capacity of the support operation is increased with the same staffing levels.  Capacity is a key metric in calculating staffing levels and predicting staffing needs for future volume peaks.
• Customer hold times.  When talk time decreases and agent productivity increases, inbound interactions are processed faster, reducing customer hold times.

Remote support technology decreases average talk time by streamlining problem identification and resolution.  By allowing agents to investigate problems directly using remote control, instead of walking customers through diagnostic questions and processes, talk time for issues in which remote support is leveraged typically trend down.  Also, if additional research needs to be performed to resolve the issue, the agent can automatically pull customer system logs into the support case to study after the call, cutting the actual time spent on the phone with the customer.

Escalations

Issues that cannot be resolved at Level 1 are escalated to Level 2, and as calls escalate to higher levels, cost of the incident increases.  By increasing training and adding additional tools, companies attempt to increase the number of issues resolved at Level 1, and over time, shift resources so that a higher percentage of agents reside at Level 1.  Reducing escalations cuts operating costs by having the most cost effective resources resolving issues.

As seen in Figure 2, enterprise support (B2B) companies average less than half of staff, 46% at Tier 1.  Higher tiers involve more skilled agents with higher salaries, handling the most complex issues.  Consumer support (B2C) companies, with lower average complexity of products and issues, have a much higher percentage of agents, 77%, at Tier 1.  Small to medium enterprises (SME) average 50% of agents at Tier 1.

Calculating cost savings by reducing escalations involves understanding the current cost of resolving incidents at each tier, and figuring the reduced cost by resolving a higher percentage of issues at lower tiers.

Customer Satisfaction

While hard-dollar metrics like decreased talk time and escalations lend themselves to a clear ROI calculations, improvements to soft metrics should also be included when building the business case for remote support.  In particular, customer satisfaction.  Though it is difficult to create a formula showing the bottom line impacts of increasing customer satisfaction, support executives do look at average satisfaction scores as a key component in measuring quality and effectiveness of support.  And with incentive compensation for support management and agents tied to satisfaction scores in most organizations, it is easy to encourage user adoption for new tools that promise increases in satisfaction scores.

Remote support technology impacts customer satisfaction through:

• Improved service levels.  The operational metrics already discussed, average talk time and first contact resolution, are major influences to customer satisfaction.  When a customer issue is resolved quickly, efficiently, and on the first interaction, satisfaction scores will climb.
• Transparency.  Companies using remote support say that customers enjoy using the tool, as they can follow along and see exactly what the agent is doing. 

With many factors influencing customer satisfaction, it may seem risky to directly contribute an overall rise in satisfaction to the use of remote support.  However, some companies report that satisfaction scores are higher on average for cases resolved using remote support. 

The SSPA Recommends

Creating an ROI model before initiating a search for new technology is definitely a best practice.  Understanding the likely payback helps prioritize projects, and also gives companies an idea of appropriate project budget.  In technology areas with practically guaranteed ROI, such as remote support, vendors typically offer an ROI audit to help you benchmark your current performance against other companies within the vendor’s installed base, and help estimate projected cost savings.

When preparing an ROI model for a remote support project, SSPA Research recommends that companies:

• Evaluate your current metrics program.  If you don’t have benchmarks for current performance, you can’t track improvements and calculate accurate cost savings.  Be sure you have current statistics for key metrics detailed in this article before continuing.
• Include both hard and soft metrics when modeling ROI.  While hard metrics, such as escalations or average talk time, offer obvious cost implications, don’t forget to include important soft metric performance and goals, such as customer satisfaction or loyalty.
• Have realistic expectations.  ROI is easy to achieve, but beware the “law of diminishing returns.”  A company with highly trained and productive agents, an effective, mature knowledgebase and strong case workflow will not receive as dramatic an ROI for remote support as companies with little or no knowledgebase available, and few formalized case handling processes.  This doesn’t mean adding remote support will not prove cost effective, but the period of time to realize full project ROI may be 12-18 months instead of 3 to 6 months.
• Train, incent and reward to promote adoption of remote support tools.  Lack of user adoption is the biggest cause of project failures.  Simply put, the technology can’t pay for itself if no one uses it.  Be sure to include links to launch remote support from within the agent desktop used for incident tracking, and update knowledgebase articles to advise agents to initiate remote support sessions where applicable.  Also, monitor agent use of remote support tools (usage reports included with remote support platforms), and provide additional training and coaching for low adopters.

About John Ragsdale…………………………………………………………
John Ragsdale is Vice President of Research for the SSPA.  Ragsdale spent 10 years managing tech support operations before moving to Silicon Valley where he held product management and marketing positions at eService and CRM vendors. He spent 5 years at Forrester Research as VP and Research Director before joining the SSPA.