Helpshift Agent Dashboard helps your customer service and support agents to engage with your consumers in real time, sometimes helping several at once. Such concurrency increases efficiency and productivity among your staff while shrinking consumer wait times.

In this modern world of digital customer service, though, it’s crucial to protect your agents from handling so many cases at once that they become overloaded. At the same time, it’s also useful to adjust the workload of any agent who has ample capacity for more. Understanding how many issues your agents can and do handle per day is key to optimizing team loads and capacity. Yet the work of measurement and optimization is more involved today than it was in the telephone-based call centers of decades past.

  • Concurrency means your agents can and do work on multiple issues in parallel.

  • Agents may even spend time away from the Helpshift Agent Dashboard while still helping your consumers.

Supplementing Helpshift with Microsoft Power BI can support you in fitting these pieces together.

Note: This article presumes that you have both of the following software products:

  • Microsoft Power BI Pro

  • Helpshift Agent Analytics, a template app for Microsoft Power BI Pro

Explore Agent Occupancy

The Online with Assigned Issues gauge measures the percentage of one agent’s (or one team’s) workday that includes open issue assignments across a date range that you specify. However, this gauge limits its consideration to only the subset of your agents who are online.

Likewise, the Marked Available with Assigned Issues gauge also measures the percentage of one agent’s (or one team’s) workday that includes open issue assignments, across a date range that you specify. However, this gauge further limits its consideration to only the subset of your agents who (A.) are online, (B.) are logged in, and (C.) have marked themselves available to take on additional work. Agents sometimes mark themselves unavailable so that they are not assigned to any new issues. An unavailable agent can continue working on assigned issues or possibly focus on some other aspect of their work before logging off for the day. 

Explore Agent Workload

The Average Workload by Moment gauge counts one agent’s (or team’s) typical and time-weighted number of active conversations — meaning, open and assigned issues at any one time across a date range that you specify. It’s time-weighted in the sense that it considers the average duration over which any open and assigned issue remains unresolved. When you mouse over the Average Workload by Moment gauge, you can see and click a ↓↓ button that “drills down” to half-hour increments. Having a more narrowly focused viewport helps you to review load trends and fluctuations during the day.

The Work Ongoing or Resolved gauge measures one agent’s (or team’s) average response rate — counted in unique issues — per half-hour, across a date range that you specify. In this case, a response is a countable action, which is adding a message to an issue or adding a message and closing it. These actions count as work performed and are thus measured here. When you mouse over the Work Ongoing or Resolved gauge, you can see and click a ↓↓ button that “drills down” to half-hour increments. Having a more narrowly focused viewport helps you to review response rate trends and fluctuations during the day.

Examples:

So, how can you apply insights from Helpshift Agent Analytics toward capacity planning? Consider the following examples.

LIVE CHAT

Suppose you know that Helpshift recommends roughly 80% as the optimal agent utilization percentage. And suppose that, in a live chat scenario, you expect one agent’s average workload to encompass just one or two issues at a time, accounting for occasional spikes in load during peak hours or days with high traffic.

You could then know — when the average load was between 1.0 and 1.5 issues per agent — that your agents and teams were at nearly their full load.

 

EMAIL OR ASYNCHRONOUS MESSAGING

In an email or asynchronous chat scenario, you might expect one agent’s average workload to encompass between four and six issues at a time, accounting for occasional spikes in load during peak hours or days with high traffic.

You could then know — when the average load was between 4.0 and 5.5 issues per agent — that your agents and teams were at nearly their full load.

 

OVERLOADED AGENTS

Your agents’ collective workload depends on how you set up your issue assignment workflows in Helpshift Settings. Workflows can include your preferred combination of bots, tags, custom issue fields, text templates, automations, quick replies, queues, auto-assignments, and consumer time limits to reopen their closed support cases. Usually, you will have set an auto-assignment limit that’s equal to or slightly greater than the number of issues that you consider ideal per agent.

It’s possible, however, for an agent to receive more assignments than you consider ideal. When this occurs, it’s generally due to automations, bulk actions, or manual assignments. If you observe numbers in the Agent Workload by Moment gauge that are consistently much higher than numbers in the Work Ongoing or Resolved gauge, you can either adjust your issue assignment workflows to correct an overreach or hire additional agents to correct a staffing shortfall.

Even so, workload alone is not sufficient to determine the ideal capacity for an agent or a team. Performance metrics — including customer satisfaction (CSAT), time to resolution (TTR), and time to first response (TTFR) — help you to measure the quality of work performed, given the workload. When performance falls short, one reason could be an increasing workload, due to the number of issues assigned or their complexity.