The Help Desk workforce management system is used to maximize employee productivity forecasting staffing levels using job and employee variables. One trait of a Help Desk is the work intake can vary by day and even the time of day. Workforce management can be very complex and never perfect. The utilization of a Help Desk agent is never 100%. The volume of work on Monday mornings can be quite different than the volume of work on a Friday afternoon. Since the utilization time of the Help Desk agents can fluctuate greatly, they may have available time to work on the improvement project.
Help Desk Workforce Management
Question 1 – Do you have a formally approved Help Desk workforce management process?
A critical process for the Help Desk is to build an agent coverage schedule that can handle Help Desk call volumes. Initially, it sounds easy, but there are a lot of variables to consider when building out a Help Desk agent schedule. Some of these variables include are call volumes, attendance patterns, agent performance, and other variables. WFM will analyze all this data to allow Help Desk management to forecast staffing needs accurately and eliminate over-staffing. An employee will enjoy the ability to offer flexible schedules based on the analysis the WFM system offers.
Staffing Schedule
Question 2 – Do you create your staffing schedule using output from a Help Desk workforce management application?
Staffing live support 24×7 can be very difficult. A normal workweek for agents is 8 hours a day for 5 days a week. 20 to 30% of that time is away from the phone for training, breaks, and other activities. In addition, agents have time off allowances for vacations and sick time. There are 168 work hours in a seven-day calendar week. Trying to assure there is at least one agent available to answer a call can be challenging. To allow for time off the phones and time away, you really need to staff at least two agents per shift. Even using flexible scheduling techniques, you will need at least 10 agents. Increasing staffing will be needed to meet the high-volume period. This increased staffing can lead to high labor costs and also excess labor capacity for the low call volume periods. For example, Monday mornings are typically a high call volume period. Whereas Friday morning can be significantly different. If you staff up to handle the high periods for things like password resets, what do you do with the excess labor capacity during slow periods?
Automatic Call Distributor (ACD) Integration
Question 3 – Is your staffing schedule based on data from your ACD or telecom system?
Companies working with workforce management systems can establish a connection between the ACD and the workforce management system. Data from the ACD can provide important information used for reporting. Also, ACD can provide real-time information to the workforce management system regarding call flow and agent behavior. An important behavior is agent adherence to schedules. This agent state information can maximize agent management and efficiency.
Agent Staffing Model
Question 4 – Does your staffing model utilize statistics such as number of calls/day, hours of coverage, number of calls/hour, outgoing calls, email, web, and the average length of call?
An agent staffing model can be created using a spreadsheet. This is a good start for a small Help Desk. Data can be gathered from sources and manually inputted into the spreadsheet. However, as the Help Desk grows and more workforce data is inputted, a spreadsheet can become unworkable.
Predicting Call Wait Times
Question 5 – Does the Help Desk use a call volume model that calculates delays or predicts waiting times for callers?
Wayne Schlicht author of a Help Desk Management book states, “callers waiting in hold queues lead to higher abandon rates and lower customer satisfaction.” Reducing the average call wait time is a goal of every Help Desk leader. There are many variables that can be analyzed to predict what the call volume will be for a certain day and time. Mondays are different than Fridays. Mornings are different than afternoons. Major changes or application upgrades can drive call volume. All of this data and more can be compiled and analyzed to predict the high and low call volume periods. Just having the same 5, 10, or 20 agents work a static Monday to Friday schedule can lead to call waiting times or low agent utilization rates. A mature Help Desk will use a call volume model to predict waiting times for callers.
Help Desk Agent Utilization Rate
Question 6 – Is the Help Desk agent utilization rate greater than 50%? Utilization equals (calls per month times minutes per contact) divided by (working days per month times work minutes per day).
The utilization of a Help Desk agent is never 100%. The utilization time of the Help Desk agents can fluctuate greatly. A way to keep costs per contact down and measure productivity is with the agent utilization metric. Agent utilization measures the percentage of time the agent is working. Basically, you take the total handle time of all calls handled by the agent divided by the total time the agent is working. For example, if an agent works an eight-hour shift, and their total call handle time is 5 hours, then their utilization is 62.5%. This means 37.5% of the time the agent was waiting for a call, on break, in a meeting, and such.
Non-working time
Question 7 – Does your staffing model take into consideration paid time off, training, holidays, and special projects?
All Help Desk staffing models must take into consideration non-working time. A mature Help Desk will create a staffing schedule based on the most accurate information. However, not all non-working time is equal. Some can’t be controlled such as holidays and sick time. Some non-working time can be scheduled such as training and planned paid time off. Finally, break time, call wrap-up time, and other agents behaviors can be managed and controlled. A comprehensive procedure is needed to manage and request time away from the phones. A good process is important to maintain high efficiency while ensuring agents still have a positive work environment.
Staffing Reports
Question 8 – Do you receive reports that compare your day and hour staffing level to call volume patterns?
A football coach will review game tapes after the game to adjust positions and plays. In a similar manner, a Help Desk manager will review the staffing levels to actual call volume data. By reviewing these reports, a manager can adjust upcoming work schedules. At a basic level, this can be done manually. However, to achieve a higher level of accuracy using long-term data, a workforce management system should be used.
Temporary Staffing
Question 9 – Do you use temporary or part-time staff to meet increased loads during peak periods?
In every industry, there are peak hours, days, and seasons. The Help Desk industry is no different. A Help Desk manager will attempt to maximize Help Desk agent efficiency to handle peak times. However, peak times may require the augmentation of temporary staffing to handle the volume. Temporary staffing can be internal such as call overflow to other teams. These teams could be from desktop support and it could be some IT engineers. Temporary staffing can also be part-time workers working flexible shifts. These shifts may include Monday mornings, holidays, and after major changes.
Staffing for Changes
Question 10 – Do you adjust staffing to assist with major rollouts (use temporary staff, increase staff during rollout, and a task force for specific rollout questions)?
Most user issues or incidents are caused by changes. So it only stands for reason that if a major upgrade or change is being implemented, there are going to be user issues. It is a best practice to ensure a representative is on the Change Advisory Board (CAB). When a major rollout is being planned, the Help Desk needs to have all the support documentation, answers for questions, and an identified escalation path. In addition, the staffing level at the Help Desk needs to be maximized the morning after the major rollout to handle the potentially high volume of calls.
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