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  • ANGELO APOLONIO

  • 問題数 28 • 10/13/2023

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    問題一覧

  • 1

    in hospitality and gaming represent a wide variety of guest facing functions on property, as well as the supporting infrastructure at the regional or corporate level. Such as the front desk, concierge, and housekeeping, as well as food and beverage, banquets and catering, retail, spa, and other related services and, pricing and revenue management for all outlets

    Operations

  • 2

    They capture labor costs for the line-level employees, and the costs associated with ordering the various products used in the delivery of service

    Operations Data

  • 3

    in this context means the number of people served or number of "jobs" executed at any given service area.

    Demand

  • 4

    are generally very well aware of all of the factors that might influence demand for all of the outlets across the enterprise.

    Operations manager

  • 5

    refers both to the time of day that something happens

    Time

  • 6

    refers to the amount of time it takes to complete a service

    duration

  • 7

    tells us that it is the variability in the service time-these occasions when the service deviates from typical patterns-that creates lines. disgruntled customers, or idle employees eating up payroll.

    queuing theory

  • 8

    have evolved over time, but the value of understanding reactions to the service experience remains the same.

    Guest surveys

  • 9

    is probably the most useful, and widely used, advanced analytic application for operations.

    Forecasting

  • 10

    this forecasting method predicts the amount of demand that existed for your service, regardless of whether there was space to accommodate it.

    Unconstrained demand forecasts

  • 11

    by this capacity - in the historical data, you will never actually "see" more demand than was able to be served, even if the restaurant turned guests away.

    Constrained

  • 12

    is a useful forecasting method in the cases where there are small amounts of data that roll up to an overall number.

    Disaggregation

  • 13

    This method can help balance the need for more detailed forecasts with the challenge of decreasing accuracy as the number of observations becomes smaller.

    Aggregated

  • 14

    allows you to model complex real world systems in an artificial environment so you can test options before you implement them and they impact the guest experience.

    Simulation

  • 15

    One of the more interesting predictive analytic applications that is not yet widely used in hospitality or gaming operations.

    Simulation Analysis

  • 16

    is a branch of analytics that predicts the behavior of lines. As it turns out, this modeling is among the most complex mathematical techniques, because it needs to account for uncertainty.

    Queuing theory

  • 17

    can predict what will happen under a variety of service conditions, ultimately determining the best way to design a service process to better manage waits

    Queuing models

  • 18

    this is the group from which guests are obtained. calling population isn't homogeneous. It is comprised of many market segments and many guests or patrons with different needs.

    Calling population

  • 19

    this is the rate at which guests arrive to the service system and if necessary join the queue. This can vary by time period.

    arrival process

  • 20

    this refers to the way the queue is designed. For example, single line, single server, a snake line to multiple servers, and multiple lines to multiple servers.

    queue configuration

  • 21

    this refers to the rules that govern the order in which guests or patrons are selected from the line. For example, the available server could simply take the next guest in line, or pass over that next guest in favor of a guest with a more immediate need or a higher status.

    Queue Discipline

  • 22

    this final feature describes the process of delivering service. This could range from self-service to a multistage server process.

    Service Process

  • 23

    what drives the amount of work-is it cars to park, rooms to clean, and guests to check

    Forecast entity

  • 24

    for each entity, does the time it takes to serve vary significantly enough that the duration and the variability around it should be accounted for?

    Duration of job

  • 25

    how much does demand vary by time period and how do you - schedule your labor? Can you stagger shift start and end times? Do you have part-time workers who can cover busy periods?

    Time period to forecast

  • 26

    operations departments that are in early stages of analytical capability operate in a highly manual environment.

    Beginners

  • 27

    the typical operations department is able to look at their data at a pretty detailed level.

    Average

  • 28

    the most sophisticated operations groups in hotels and casinos are heavy users of very sophisticated forecasting techniques.

    Most sophisticated