Portfolio Planning

    Panda Restaurant Group - Selling More Orange Chicken with Simulation


    Panda Restaurant Group

    California based Panda Restaurant Group (PRG) operates about 1,400 restaurants in 38 states, and is also expanding internationally. PRG includes the original Panda Inn fine dining restaurants, Panda Express, and Hibachi San. It takes a vast IT organization to support this volume of restaurants and IT project management is one of the most challenging areas within this IT functional operation.

    Only 30% of PRG IT projects were completed on time, most were 200% over-budget and some were never even completed. Given the slower economy, delivering critical projects on time and within budget was absolutely necessary. Leonard Yip, PRG CIO had previous experience with ProModel technology.

    Currently using spreadsheets to manage projects and make project resource decisions and analyze other portfolio data, Leonard and his team decided to formulate a project management methodology using Microsoft Project Server and ProModel's Enterprise Portfolio Simulator (EPS) to help them analyze their full portfolio of IT projects and make portfolio decisions.


    • Establish a project management methodology using Microsoft Project and EPS

    • Create a single source for managing all IT projects

    • Make accurate resource capacity decisions

    • Deliver projects on time and within budget at least 80% of the time

    "Simulation is the only way that would give us the data to substantiate our claims or provide us a better way to complete the portfolio of projects."

    —  Leonard Yip, CTO, PRG


    The results of this project planning and resource management approach were very dramatic. The first project completed using the new tools was examined in detail and determined to be a troubled project. The original plan predicted a six month delay. Examining the impact of using additional resources to improve timing and financial performance, PRG identified ways to accelerate the project such that it could be delivered according to the committed deadline.

    The first year PRG used Project and EPS they completed over 80% of their IT projects on-time. PRG continued to use this project management methodology with EPS and plans to improved their on-time project completions to more than 85% in the second year.

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    Process Improvement


    Retail Bank Branch - Staffing Capacity Cost and Customer Service Analysis


    Customer service requirements at the client's typical retail bank branches vary over the course of a day and week for its products and services. For example, mornings might be 'teller services heavy' whereas after 2 PM might be 'banker services heavy'.

    A representative branch had the following characteristics:

    • High variability in transaction types (deposit, withdrawal, ATM, loans, etc.)

    • High transaction volume varied by type and time of day

    • 8 teller windows, 6 customer service desks, 3 drive thru lanes, and 1 ATM

    It appeared that branches were staffed using a "Just-In-Case" approach in order to maintain an acceptable service level. The current staffing method could not adequately address these fluctuations in customer demand other than by over scheduling its employees.


    Management saw an opportunity to increase profitability while maintaining or improving service by developing more efficient branch staff assignments. Could labor costs be reduced, without negatively affecting service, by doing a better job of matching skills to both 'what is needed' and 'when it is needed'? Applying this concept of "Skill-to-Demand" staffing would increase profitability and possibly increase service levels.

    The challenge was how to generate a staffing schedule according to this new approach? If they could predict which skills and in what quantity were required by time and day, costs and service would improve. With thousands of branches, the savings multiplied across their network of retail locations could be very significant.


    The client's business objective for this initiative was to determine if changes to staffing policies at its retail banking branches could reduce labor cost and increase profitability while simultaneously improving customer satisfaction.


    The analysis showed how $120,000 of savings annually per branch came from matching the specific assignments of staff to "fuzzy" data about when a client would need them. Wait times at walk-up and drive-thru windows also decreased providing an improved customer experience.

    The project's key to success was the software's ability to replicate demand by when it occurred during the week. This enabled the branch managers to match staff schedules closely to "Customer Demand" as opposed to the more costly "Just-In-Case" approach.

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    Custom Solutions / Custom Development

    Proceedings of the 2010 Winter Simulation Conference
    B. Johansson, S. Jain, J. Montoya-Torres, J. Hugan, and E. Yucesan, eds.


    David Kalasky, Melanie DeGrano; IBM Corporation
    Michael Coffman; Transportation Security Administration
    Kevin Field; ProModel Corporation


    The Transportation Security Administration (TSA) staffs and operates over 450 airports in the US. TSA has been using simulation to determine staffing requirements since 2005 and has recently completed a re- fresh of their manpower planning and scheduling system.

    The objectives of the effort were to replace the GPSS simulation engine, optimizer and user-interface (UI) to take advantage of current network-based systems technologies. The previous system was distributed to the 200+ users as a stand alone application. This presented maintenance, security and performance issues, especially during the annual budgeting process.

    This paper focuses on the creation and integration of the simulation engine which was required to replicate and improve on the existing GPSS model accuracy and performance. Additional considerations included providing TSA an easy-to-use simulation platform to maintain the simulation engine, make model and data edits and expand the use of simulation technology within TSA.

    Click here to see the entire white paper.

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