What is the difference between occupancy and utilization




















If an agent determines that a device replacement is required, instead of writing up a lengthy report explaining the decision, they can simply save an image of the broken or defective device to the system.

Reducing training time, on the other hand, will lead to poorly trained agents who could wreak havoc on customer satisfaction and overall productivity. Visual Assistance provides an excellent solution to the training dilemma. During the initial training process, agents can see live issues in real environments, enabling them to grasp concepts more quickly.

Since training is always an ongoing process with new call center training technologies constantly being released, the visual database allows agents to effectively learn on the job, reducing shrinkage and improving productivity at the same time.

A collaborative work environment allows agents to draw on shared knowledge and resolve customer issues more efficiently. But constant team meetings can be a serious time drain, significantly reducing call center agent utilization.

Collaboration through Visual Assistance reduces the need for traditional time-consuming meetings. Agents are constantly contributing to the visual knowledge base and even communicating with each other in real time, once again performing a shrinkage activity at the same time as the productive work of handling calls. In cases where the issue cannot be resolved over the phone, agents must usually dispatch a technician to make an on-site visit.

However, miscommunication can leave technicians inadequately prepared for the visit. With Visual Assistance, the agent provides an image of the issue, ensuring that the technician brings all the right equipment and parts, and alerting them to any access problems or potential dangers. This visual solution allows departments to communicate with each other in a language that everyone can understand. Customer service centers are known for notoriously high rates of employee turnover. Not only are the terms themselves important to distinguish, the implications they have portend a significant amount of workplace decision-making.

What is occupancy and utilization in the context of the workplace? Space occupancy is the measure of total employees in a workplace at a given time. You can also measure space occupancy within the context of square footage, which is most common when facility managers seek to understand utilization. Generally, space occupancy is a measure of people.

Space utilization is the other side of the workplace equation and represents a measure of usage. Utilization can be a static measure, as well as a dynamic one.

For example, you can measure the utilization of a space right now or over a period of months, weeks, days, or even hours. Both occupancy and utilization have their own formula.

These figures serve important purposes in everything from KPI tracking to data-driven decision-making about the workplace. Each metric applies to different aspects of space management, but more often than not, facility managers will use them in conjunction with one another for a more holistic measure of space efficiency.

Occupancy and utilization go hand-in-hand. Occupancy represents the people within a workplace; utilization represents their interaction with those surroundings. This is demonstrated in the examples below:. In aggregate, the number of occupied rooms out of the total number of rooms capacity measured gives us the occupancy.

Using a single WorkSpace Counter or multiple WorkPoint Sensors, we detect the number of individuals occupying the room 12B at this point in time. Utilization is essentially a rate defined by the averaging of occupancy readings over a period of time. If using CoWorkr, our devices would typically report a minimum of between occupancy readings during a standard 8AM—5PM workday. When calculating the utilization of conference rooms, all of the rooms in the set of data would be analyzed and aggregated to provide the utilization metric.

Utilization may be calculated based on a single hour, day, week, or month of occupancy data.



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