Front-office multitasking between service encounters and back-office tasks

Abstract

We model the work of a front-line service worker as a queueing system. The server interacts with customers in a multi-stage process with random durations. Some stages require an interaction between server and customer, while other stages are performed by the customer as a self-service task or with the help of another resource. Random arrivals by customers at the beginning and during an encounter create random lengths of idle time in the work of the server (breaks and interludes respectively). The server considers treatment of an infinite amount of back-office tasks, or tasks that do not require interaction with the customer, during these idle times. We consider an optimal control problem for the server's work. The main question we explore is whether to use the interludes in service encounters for treating back-office, when the latter incur switching times. Under certain operating environments, working on back-office during interludes is shown to be valuable. Switching times play a critical role in the optimal control of the server's work, at times leading the server to prefer remaining idle during breaks and interludes, instead of working on back-office, and at others to continue back-office in the presence of waiting customers. The optimal policy for use of the interludes is one with multiple thresholds depending on both the customers queueing for service, and the ones who are in-service. We illustrate that in settings with multiple interludes in an encounter, if at all, the back-office work should be concentrated on fewer, longer and later interludes.

Does Physician's Choice of When to Perform EHR Tasks Influence Total EHR Workload?

“…A related set of papers on multitasking are queuing models with one server or group of servers balancing two work queues (Gans andZhou 2003, Legros et al 2020). Legros et al (2020) discuss service operators' switching between customer interaction and back-office tasks. They derive optimal threshold policies for using the interlude time between customer interactions.…”

“…Although much emphasis is placed on the primary tasks to be completed, such as patient treatment or surgery (Bartel et al 2020, Youn et al 2022, assembling a car in a factory (Bernstein & Kok 2009), or answering a call in a call center (Aksin et al 2007), operations also include secondary tasks that support the primary work (Dai et al 2015, Legros et al 2020. These might consist of EHR use, hand hygiene (Dai et al 2015) or lab tests in healthcare (Batt and Terwiesch 2017), supply positioning or tool preparation in manufacturing, or data entry in call centers.…”

Dynamic policy for idling time preservation

“…This also makes a difference with our context, where urgent customers can interrupt the treatment of some back-office tasks. In a context with switching time allocation between urgent and nonurgent tasks, Legros et al (2020) showed that idling in the presence of waiting customers may be optimal to avoid too many switches. Further references on queue-blending operations include Keblis and Chen (2006); Pichitlamken et al (2003); Pang and Perry (2014).…”

“…Although nonoptimal, this policy has the advantage of not letting the agent leave any customers waiting in the queue since this would not be appreciated in visible systems. It also reduces the frequency of switches between idle and busy states for the agent (Legros et al, 2020). The stationary probabilities are computed via a two‐dimensional Markov chain analysis.…”

A dynamic prioritization policy for the callback option in a call center

“…Then, the agent reservation policy can be implemented, that is, when the number of agents reserved for the inbound calls reaches a threshold, an agent can make an outbound call or respond to an email request. We refer the interested reader for further reading on call blending to Deslauriers et al (2007), Pang and Perry (2014), Legros et al (2015Legros et al ( , 2020.…”