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Master standard data quantity food production code

P C Zemel, M E Matthews

    Journal of the American Dietetic Association
    |December 1, 1982
    PubMed
    Summary
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    The Master Standard Data (MSD) Quantity Food Production Code overestimated hospital roast entrée production times by 27 minutes. Variability in employee performance and product demand significantly impacted actual food production times.

    Area of Science:

    • Food Service Operations
    • Industrial Engineering
    • Healthcare Management

    Background:

    • Accurate production time estimation is crucial for efficient hospital food service operations.
    • The Master Standard Data (MSD) Quantity Food Production Code is a tool used for predicting food production times.
    • Previous studies have not fully evaluated the MSD code's accuracy in real-world hospital settings.

    Purpose of the Study:

    • To assess the accuracy of the Master Standard Data (MSD) Quantity Food Production Code for roast entrée production in a hospital food service.
    • To identify factors contributing to discrepancies between predicted and actual production times.

    Main Methods:

    • Ten stopwatch time studies were conducted to measure actual production times for roast entrées.
    • Actual production times were compared against MSD-predicted times.

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  • An analysis of 13 macro elements within the food service operation was performed.

    • Main Results:

    • Median actual production times for roast entrées exceeded MSD-predicted times by 27 minutes.
    • Significant variability in production times was observed, attributed to individual employee performance and fluctuations in product demand.
    • 13 macro elements were analyzed for their impact on production time.

    Conclusions:

    • The MSD Quantity Food Production Code may overestimate production times in hospital food service settings.
    • Employee performance variations and demand fluctuations are key factors influencing production time accuracy.
    • Further investigation within the specific facility is recommended to pinpoint contributing variables.