Question: Securing a mortgage often is a time-
Securing a mortgage often is a time-consuming and frustrating experience for a homebuyer. The process involves multi- ple stages with many handoffs to independent organizations providing specialized services (e.g., property survey and title search). The mortgage service game is a computer simulation of the mortgage service process in which the human player will control the decisions of one entity and the computer will make decisions for the other actors. This game is used to explore the dynamics of a serial service process.
Figure 9.9 depicts a block diagram of the mortgage supply chain. Each mortgage application passes through four stages as shown on the right-hand side of the figure: Credit Check (employment confirmation and review of credit history), Survey (establish property boundary, note easements, and applicable zoning laws), Appraisal (establish value of property using com- parables), and Title Search (ensure the property is uncontested and without liens). Because all of the stages are modeled in a similar fashion, only one stage, the survey stage, will be described as an example of each stage’s processing.
Figure 9.9: Block Diagram of Mortgage Service Game
Note that the middle column of the block diagram contains a sequence of backlog boxes (queues of work-in-process) representing the movement of applications through the process to completion. For example, after each application is checked for the credit worthiness (Credit Check), the application moves from the inventory of applications waiting for credit check (Credit Check Backlog) to join the backlog of surveys (Survey Backlog). Each week, based on the backlog of surveys—which is the only information available to the player controlling the survey stage of the system when using a decentralized strategy—the player sets the target capacity of the system by deciding to hire or fire employees: in this case, surveyors. However, it takes time to find, interview, and hire or, conversely, to give notice and fire employees; so the actual Survey Capacity will lag the Target Survey Capacity by an average of one month. Those surveyors currently in the employ of the survey company will then carry out as many surveys as they can during the following week. On the block diagram this is shown as a “bow tie†representing a valve controlling the flow of applications between survey backlog and appraisal backlog. Thus, as each application’s survey is completed (Survey), the application will then leave the Survey Backlog to join the next backlog downstream—in this case, the Appraisal Backlog.
Although, the purpose of this process is to eliminate applications that are too risky, we will assume that each application ultimately is approved. This is a reasonable assumption because, despite the fact that a random survival rate for each stage does indeed complicate management of the service chain, the primary dynamic control problems derive from other sources. In particular, the largest problem arises because a separate company generally manages each stage of the process. Each of these companies controls its own individual capacity, but it usually sees only its own backlog when making its decisions, not the global new-application rate or the backlog of other stages. This situation creates a phenomenon similar to the bullwhip effect observed in physical goods supply chains, albeit here the “inventories†are strictly backlogs of work-in-process. As in any service there is no way to stockpile finished-goods inventory in advance as a buffer against fluctuating demand. Rather, each stage must manage its backlog entirely by managing its capacity, that is, the number of workers it employs. Because each employee has a productivity rate of four applications per day, the completion rate per day of applications at any stage is constrained to the minimum of the capacity as measured by the number of employees or backlog plus any inflow from the previous stage.
At the beginning of each week, each stage (company) can change its target capacity by deciding to hire or lay off employees. However, it takes time to advertise, interview, and hire employees; so the rate of capacity change is not achieved all at once but over several days. This translates into an average lag for hiring (or firing employees) of 20 days or four weeks. If the player makes another change before the original adjustment is reached, the old target will be discarded, and capacity will begin to adjust the following day from its current value advancing toward the new target.
GOAL
The objective is to minimize the total cost for the entire mortgage supply chain resulting from employee salaries and service delays. You will be asked to play one of the four stages (Credit Check, Survey, Appraisal, or Title Search) and the computer will play the other stages in the process. The entire supply chain begins in equilibrium with each stage having a backlog of 200 applications, arrival rate of 100 per week, capacity of 100 per week, and target capacity of 100 applications per week. Each employee costs $2,000 to hire or lay off and $1,000 per week to employ (or $50 per application when fully utilized). Each backlogged application costs $100 per week in potential customer alienation. The game is played for a period of 50 weeks.
Transcribed Image Text:
Applications Target Credit Check Capanity: Target Survey Capacity: Target Appraisal Capanity: Target Title Search Capacity Application Start Rate Credit Check Capacity Survey Capacity Appraisal Capacity Title Search Capacity Credit Check Backing Survey Backlog Appraisal Backlog Title Search Backing Completed Applications Credit Check Survey Appraisal Title Search
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