Abstract:
A system and method to optimize rent for rental property management is disclosed. The system allows a user to calculate optimal rents for any variety of rental strategies using the same general algorithm. The system stores past and present competitor rents in a storage base. The rent data is taken from different users who may be in different rental locales. The system also has data relating to the last reference rent, a factor indicating aggressiveness in renting, a medium brake factor at which rent is lowered to that of the competitors and a high brake factor. The reference rent is calculated by a rent engine using these variables. The user may adjust the data for different rental strategies. The system allows a user to display the rent values for different unit types and break down the data into discrete samples.

Description:
FIELD OF INVENTION  
         [0001]    This invention relates to a method and system to determine the market rent of lease properties and more specifically to a system and method that determines the optimal rent for a variety of different rental strategies.  
         BACKGROUND OF INVENTION  
         [0002]    A primary challenge for a property management company is to maximize revenues from new and renewal leases by setting a maximum rent but still keeping all their units occupied. Under pressure to increase revenues from operations, property-management companies face extremely complex issues of pricing and capacity allocation. Multi-family units are large fixed assets whose single greatest liability is vacancy cost or exposure. Units cannot be allowed to remain vacant if suitable demand for them exists, but attempting to maximize revenue means more than simply maximizing occupancy. A property manager&#39;s rental products are not determined by the actual units, but rather a combination of timing and a balance of supply and demand. Successfully meeting this complex pricing challenge in the most efficient and profit maximizing manner involves determining market rent.  
           [0003]    In order to maximize revenues, a property manager must precisely forecast and analyze market demand unit availability to set a market rent which is optimal. The ideal market rent is obtained by measuring dynamic consumer demand. To achieve these goals, the property manager must calculate the economic value of each unit type in the marketplace and determine the optimal effective base rents as well as rents for move-ins and renewals. The property manger also preferably forecasts rental demands during different time periods, as well as regularly re-optimizes rents in response to changing demand, availability and market conditions. Moreover these calculations need to be repeated on a periodic basis.  
           [0004]    Recently, this has been simplified by the availability of software decision support tools that apply differential pricing strategies and the smart allocation of capacity. However, calculations made by existing rent calculation software is rigid and cannot be adapted to individual pricing strategies which often vary according to market conditions. In order to adapt standard formulas to pricing formulas, a great deal of time must be spent to adjust variables making the existing calculation software cumbersome to use or in some cases not useful in a rapidly changing rental market.  
           [0005]    Thus, there is a need for an automated system to calculate market rent given dynamic consumer factors. There is a further need for a system which may be adapted to different strategies for pricing rents. There is also a need for a system which does not require constant updating of additional data to determine changing optimal rent values.  
         SUMMARY OF THE INVENTION  
         [0006]    These needs and others may be met by the present invention which is a method of calculating the optimal rent for a property. Competitive data relating to past and current competitor rent is gathered. Previous reference rent data is stored. Parameters for rental strategy including an aggressive factor, a high brake factor, and a medium brake factor is determined. Optimal reference rent is calculated based on weighting current competitor rent, the reference rent data, the aggressive factor, the high brake factor, the medium brake factor and the past competitor rent  
           [0007]    Another example of the invention is a system for calculating optimal rental rates for a variety of renting strategies. The system has a storage device storing data relating to past reference rents, past competitor rents and present competitor rents. An input device accepts initial parameters including an aggressive factor, a high brake factor, and a medium brake factor. A rent optimizer engine is coupled to the storage device and the input device which periodically calculates the optimal rent based on weighting current competitor rent, the reference rent data, the aggressive factor, the high brake factor, the medium brake factor and the past competitor rent.  
           [0008]    It is to be understood that both the foregoing general description and the following detailed description are not limiting but are intended to provide further explanation of the invention claimed. The accompanying drawings, which are incorporated in and constitute part of this specification, are included to illustrate and provide a further understanding of the method and system of the invention. Together with the description, the drawings serve to explain the principles of the invention. 
       
    
    
     BRIEF DESCRIPTION OF DRAWINGS  
       [0009]    These and further aspects and advantages of the invention will be discussed more in detail hereinafter with reference to the disclosure of preferred embodiments, and in particular with reference to the appended Figures wherein:  
         [0010]    [0010]FIG. 1 is block diagram of the system for determining market rent according to one example of the present invention;  
         [0011]    [0011]FIG. 2 is a flow diagram of the process used by the system in FIG. 1 to determine the optimal market rent;  
         [0012]    [0012]FIG. 3 is a screen print of a community data entry screen for the system of FIG. 1 for determining market rent;  
         [0013]    [0013]FIGS. 4A-4C are screen prints of competitor data entry screens which are accessible through the community data entry screen of FIG. 3;  
         [0014]    [0014]FIG. 5 is a screen print of an entry screen for lease term category data;  
         [0015]    [0015]FIG. 6 is a screen print of an entry screen for market conditions data;  
         [0016]    [0016]FIG. 7 is a screen print of an entry screen for reference rent;  
         [0017]    [0017]FIG. 8 is a screen print of a rent graph which may be displayed by the system of FIG. 1;  
         [0018]    [0018]FIG. 9 is a screen print of a web page accessible for field data entry by property managers. 
     
    
     DESCRIPTION OF THE PREFERRED EMBODIMENT  
       [0019]    While the present invention is capable of embodiment in various forms, there is shown in the drawings and will hereinafter be described a presently preferred embodiment with the understanding that the present disclosure is to be considered as an exemplification of the invention, and is not intended to limit the invention to the specific embodiment illustrated.  
         [0020]    [0020]FIG. 1 shows a system  10  for calculating rents used by a property manager or a property management company. The system  10  includes a computer  12  which has a central processing unit  14  which is coupled to a monitor  16 . The computer  12  has a storage device  18  that is preferably a hard disk drive. Various software may be loaded into the storage device  18  for configuring the central processing unit  14 . The storage device  18  contains lease rental optimizer (“LRO”) software  20  which will be explained below. The preferred embodiment uses a spreadsheet program  22  which may be the Microsoft Excel spreadsheet program to implement presentation and input of data in conjunction with the LRO software  20  but may also be a web based application with a central database. The computer  12  further has a database  24  stored on the storage device  18 . The database  24  is preferably a SQL Server type configuration, but any suitable software or hardware configuration may be used. The database  24  contains data relating to competitors rents and other information as will be detailed below.  
         [0021]    The system  10  also includes a network port  26  that is used to compile data from other sources. The network port  26  is coupled to a network  28  that is preferably the Internet although other networks such as Intranets, LANs or WANs could be used to send the system  10 . It is preferable to insure the security of the transmitted data through well known methods. The system  10  is contemplated to be used at a central office  30  of a property management business. Various properties are managed in diverse locations such as property management offices  32 ,  34  and  36 . Each of the offices  32 ,  34  and  36  contain a network accessible computer  42 ,  44  and  46  respectively. Employees at each of the offices  32 ,  34  and  36  may thus compile data relating to rent, availability etc. as will be explained below and report the data to the system  10  via the network port  26 . The data is preferably entered via a web based interface on a browser program installed on the computers  42 ,  44  and  46 . Each office  32 ,  34  and  36  manages the leasing a number of rental units. The rental units are classified by number of bedrooms, number of bathrooms, floor plans etc., and different rents are determined for different types of units.  
         [0022]    A user may operate the system  10  using a number of variables and develop a pricing model for the reference rent depending on the particular business permutation. The software  20  functions as a rent optimizer engine which takes data stored in the storage device  18 . FIG. 2 is a flow chart of the general process used to determine the optimal rent. The flow chart includes a setup routine  200  and a periodic routine  202 . The setup routine  200  includes first having a user creating and configuring competitors data in step  204 . The competitor data includes unit type, unit description, lease term, low rent, high rent and other data as will be explained below. The program then proceeds to step  206  where a user creates and configures the community. The system authority makes any adjustments to default parameters such as low and high exposure thresholds and factors that define how aggressive the corporate strategy is in reacting to competitors in step  208 .  
         [0023]    The periodic routine  202  take place at periodic intervals such as each week and includes a user entering competitor rents for that period in step  220 . The user then requests a reference rent calculation in step  222 . The process validates that the reference rent is not too high or too low in step  224 . If the rent is too high or too low, the system branches to step  226  and displays an error message. If the rent is within acceptable parameters, the system  10  then outputs the reference data in the form of competitor previous rents and current rents as well as previous reference rents and current reference rents in step  228 .  
         [0024]    There are a variety of set up variables used by the system to calculate the optimal rent in step  208 . These include Competitor Weights, Competitor Position, Low Threshold, High Threshold, Brake Factor High Exposure, Brake Factor Medium Exposure and Aggressive Factor. The value of the set up variables is typically determined by a central administrative office for multiple leasing areas such as the central office  30  in FIG. 1. Of course the individual user may also input these values at a property management office or to reflect the relative differences in that area. The Competitor Weights is a percentage weight that each competitor contributes to the market composite. The Competitor Position is the relative position of the user versus a competitor at demand/supply equilibrium. The Competitor Position is a combination of physical factors (e.g. relative square footage, crown molding, etc.), equalization factors (e.g. utilities or parking included, etc.) and brand factors (e.g. achieving better rent per  2  square foot due to personnel, reputation, brand, etc.). For example, a competitor&#39;s property may be several years newer and a comparable unit type may have additional  4  features such as crown molding and larger square footage. In this situation, the position might be −$50, indicating that the unit type being analyzed is equivalent to competitor&#39;s price less $ 50 . Similarly, if the unit type being analyzed had features that were superior to the competitor&#39;s unit type, the position would be a positive dollar value.  
         [0025]    The Low Threshold variable is the maximum exposure in terms of rental units that have not been leased or are otherwise not committed that would still be considered “low” or acceptable for a 60-day exposure. The High Threshold variable is the minimum exposure that would still be considered “high” or unacceptable for a 60-day exposure.  
         [0026]    The Brake Factor High Exposure is how much the user wants to put a brake or a stop on steeply declining reference rents caused by declining market composites when exposure is high. For example, a value of 100 would mean ignore the decline, i.e. “brake 100%” and keep rents at the present level while 0 would mean stay with the market composite no matter the decline. The Brake Factor Medium Exposure is how much a user wants to put a brake on steeply declining reference rents caused declining market composites when exposure is moderate. A factor of 100 would mean ignoring the decline, i.e. “brake 100%” while 0 would mean stay with market composite no matter the decline. Finally, the Aggressive Factor is the minimum the reference rent will be raised when exposure is low and the corporate strategy calls for raising the reference rent.  
         [0027]    The user-entered variables entered in steps  204  and  206  include Competitor Rents, Competitor Concession, User Exposure, Recent Reference Rent Declines Significant and Recent Lease Velocity. The Competitor Rents is the typical rent currently being charged by the competitor for that unit type but is not a single unit price leader. The Competitor Concession is the typical concession or discount currently being offered by the competitor for that unit type but not a single unit price leader. The User Exposure is the low (less than low threshold percentage for 60-day), medium (between low_threshold percentage and high_threshold percentage for 60-day) or high (larger than high_threshold percentage for 60-day) threshold of exposure for the market. The Competitor Exposure is Low (less than low threshold percentage for 60-day), medium (between low_threshold percentage and high threshold percentage for 60-day) or high (greater than high_threshold percentage 60-day), or Ignore (either user doesn&#39;t know or user doesn&#39;t want the system to consider competitor&#39;s exposure). The Recent Reference Rent Declines Significant factor determines whether recent rent declines are deemed significant by the user. The Recent Lease Velocity is classified as high (which indicates that there has been no problem leasing units as they come available), medium (which indicates that a user has been able to lease units as needed), or low (a user has units which have been coming available faster than they can be leased).  
         [0028]    The system generated input variables include a Reference Rent0 variable, an Override Reference Rent0 variable, and a Market Composite0 variable. The Reference Rent0 variable is the last iteration&#39;s reference rent as calculated by the system  10 . The  
         [0029]    Override reference rent variable is the last iteration&#39;s reference rent as accepted or overridden by the user. The Market Composite0 variable is the last iteration&#39;s calculation of the Competitive Market Composite variable.  
         [0030]    The Output values from the system generated in step  222  include a Recommended Reference Rent value, a Market Composite 1  value, an Override Reference Rent1 value, and a Text box values. The Recommended Reference Rent is the system&#39;s recommendation for the new reference rent. The Market Composite 1  is the system&#39;s new calculation of the Competitive Market Composite of rents. The Override Reference Rent1 is a box for the user to override the reference rent. The Text box is for text that allows the system to explain which business zone it is in, provide other tips or prompts for action, etc.  
         [0031]    After receiving the parameters outlined for user entered and system weights, an appropriate model is determined to produce the optimal rent, Ref1. The creation of the model to calculate the reference rent is based on the general formula of  
           a 1*Comp1+ a 2*max(Comp1, Ref0*[1+Aggressive_Factor])+ a 3*Ref0+ a 4*(1+Aggressive_Factor)+ a 5*[Ref0+(1−Brake_Factor —   h )]*(Comp1−Comp0)+ a 6*[Ref0+(1−Brake_Factor —   m )]*(Comp1−Comp0)+ a 7*(Comp1−Comp0)+ an* ( Fn )  
         [0032]    Where  
         [0033]    a1-an are additional functional variable terms which may be weighted depending on the model desired;  
         [0034]    Comp1 is the current competitor rent;  
         [0035]    Comp0 is the competitor rent of the previous period;  
         [0036]    Ref0 is the reference rent of the previous period;  
         [0037]    Aggressive_Factor is the aggressive factor;  
         [0038]    Brake_Factor_h is the high brake factor;  
         [0039]    Brake_Factor_m is the medium brake factor; and  
         [0040]    Fn is a variable for future influencing terms.  
         [0041]    Several cases illustrate the flexibility of this approach. A first case is where exposure is low. In general, it is desirable to push the market rent up in this situation. If the market composite is up, it is also desirable to make sure that the market rent increase is at least as much as the market composite is going up. Coefficients are then set as:  
         [0042]    Market composite going up: a2=1 all others=0  
         [0043]    Market composite not going up: a4=1, all other=0  
         [0044]    If the strategy is only to raise market rent when exposure is low and leasing velocity (LV) is favorable, then the LV parameter can be brought in so that the above is only true if LV is medium or high. If LV is low, the model can be set to have a1=1 and all other coefficients=0. Of course, users wishing a more or less aggressive strategy have the flexibility to choose different coefficients.  
         [0045]    Similar strategies can be put into play when exposure is medium or high. The coefficients a5 and a6 allow the flexibility to be more aggressive in bringing prices down when exposure is high versus when it is medium. For example, if exposure is high and the market composite is going down, then a5 is set to 1 and all other coefficients set to 0. This lets the model bring down the rent towards the new market composite but not all the way down as driven by the Brake_factor_h setting.  
         [0046]    If the exposure is medium and the market composite is going down, then a6 is set to 1 and all other coefficients set to 0. This lets the model bring down the rent towards the new market composite but not all the way down as driven by the Brake_factor_m setting.  
         [0047]    It should be noted that, in normal operation, it is expected that Brake_Factor_h will be set to bring the new rent closer to the market composite than Brake_Factor_m would do since it&#39;s more imperative to be at or near market composite when exposure is high.  
         [0048]    Coefficients a1, a3, and a4 can be turned “on” by setting them=1 and all other coefficients=0 for scenarios when it is desirable to match the composite market (a1), leave the reference the same as before (a3), or drive the aggressive factor independent of any other adjustment (a4). Practical examples of these scenarios include, but are not limited to the following.  
         [0049]    When it is desirable to match the composite market (a1). In this case, exposure is high and leasing velocity is low (i.e. the situation is not good and getting worse so the strategy is to match the market immediately rather than using the brake_factor to slow down the rent decline).  
         [0050]    Another example is leaving the reference rent the same as before (a3). In this case, exposure is low and leasing velocity is low (i.e. the market is resisting the current reference rent but the strategy is to wait until exposure gets worse before changing the rent).  
         [0051]    A third example is driving the aggressive factor independent of any other adjustment (a4). In this case, exposure is low and it is known that the market composite has not been rising (i.e. there&#39;s no concern rent will be below market composite, so the strategy is simply to start testing higher rents).  
         [0052]    Coefficient a7 is set to 1 and all others set to 0 when the business scenario calls for a strategy of maintaining the current spread between rent and market composite. For example, exposure could be medium or high which generally indicates rent should move towards the market composite, if rent is already above it. However, in circumstances where leasing velocity is high, prudent business logic would say the market is not adversely reacting to the “premium” vs. market. If the market composite is rising, then the corporate strategy in this case could be to maintain that spread. Setting coefficient a7 to 1 and all others to 0 enables this strategy to be implemented in these scenarios.  
         [0053]    Coefficient an indicates how this process invention makes it possible for other calculations to be used should corporate strategy dictate adding other business cases and/or change the specific calculations for cases already identified.  
         [0054]    The net result is a completely flexible response by creating a business-rule driven matrix of coefficient values for input permutations of exposure, leasing velocity and any other relevant data.  
         [0055]    [0055]FIG. 3 shows the screen print of a community input screen  300  of the system  10  in FIG. 1 on the monitor  16 . The community input screen  300  is the screen initially displayed by the system  10  where a user enters information about the community. The screen  300  includes a property code box  302  and a series of unit types boxes  304 . The unit types boxes  304  include codes that represent different property unit types. A competitors box  306  allows a user to select a go button  308  to display a screen for each competitor and update the rents and concessions for those competitors. A command area  310  includes an exit worksheet button  312 , an e-mail worksheet button  314 , an e-mail archives button  316 , an edit parameters button  318 , an import old data button  320 , a create back up file button  322  and:a close window button  324 .  
         [0056]    A competitor weight button  326  and a competitor positions button  328  allow a user to display data entry screens to update the competitor weight and position variables. Typically such positions will be updated periodically such as on a quarterly or monthly basis.  
         [0057]    A reference rents button  330  allows a user to enter the number of available units for each unit type and select the current leasing velocity for the week from a drop down list on a separate screen.  
         [0058]    [0058]FIG. 4A shows a competitor rents worksheet  400  that is displayed when a user selects the Go buttons  308  in FIG. 3. The worksheet  400  has a competitor name row  402  and a unit type column  404  with codes for the unit type. A description column  406  has a floor plan description column  408  and a base rent column  410 . A concession column has a 12 month concession column  412 , a 6 month concession column  414  and a short term concession column  416 . The main menu screen in FIG. 3 may be accessed by selecting a show main menu button  418 . The user may enter different data relating to the competitor such as the floor plan in column  408 , the base rent in column  410  or the concessions in columns  412 - 416   
         [0059]    [0059]FIG. 4B shows a competitor weights worksheet  430  that is displayed by selecting the Comp Weights button  326  in FIG. 3. The competitor weights worksheet  430  displays unit types in a unit type column  432 . A number of competitor columns  434  are listed and the percentage weights for each competitor when determined as explained above is entered for a totals column  436 . The totals column  436  shows the net result of all the competitors in a particular unit type. The initial screen  300  may be displayed by selecting a show main menu button  438 .  
         [0060]    [0060]FIG. 4C shows a competitor positions worksheet  440  that is displayed by selecting the positions button  328  in FIG. 3. The competitors positions worksheet  440  includes a show my rents button  442  which allows user to display rents relating to their units. The competitors positions worksheet  440  also displays a unit type column  444  which uses the unit types defined in FIG. 3. A number of competitor columns  446  show all of the competitors that rent similar units. Each entry in the unit types column  444  for a particular competitor data under the competitor columns  446  includes an entry for the difference between the user rent and the competitor rent for that type of unit. A show main menu button  448  allows a user to return to the main screen  300  in FIG. 3.  
         [0061]    [0061]FIG. 5 shows a reference rent setup screen  500  for lease term categories LTC premiums. These premiums are built into the base rate premium setup for each lease term category and set by a percentage amount. The data entered by the user in the setup screen  500  establishes the initial conditions for the reference rent calculation in an LTC premiums area  502  and a rent adjustment settings area  504 . The screen  500  includes a lo long term box  506 , a mid term box  508 , a short term box  510  and a month to month (“MTM”) box  512  for entering percentages for premiums for each lease term category. These are heuristic assessments (or assessments from offline analysis) that adjust for the fact that customers expect to pay a higher rate for shorter lease terms. The rent adjustment settings area  504  includes a low exposure threshold entry box  520 , a high exposure threshold entry box  522 , a brake factor high box  524 , a brake factor medium box  526 , an aggressive factor box  528  and a reference rent flag box  530 . The various percentages in the rent adjustment settings may thus be adjusted for the reference rent calculation described in FIG. 2.  
         [0062]    [0062]FIG. 6 shows a market conditions screen  600  that is displayed by selecting the reference rents button  330  in FIG. 3 and allows a user to enter data on specific numbers of units in the particular rental market. The market conditions worksheet  600  includes a column list of unit types  602 . Each unit type has a total units box  604  and a units available box  606 . The user enters the current number of units in each type in the appropriate total units box  604  and the units available of that type in the units available box  606 . Such data entry is performed on a periodic basis such as weekly. In addition, the screen  600  has a leasing activity box  608  that allows a user to select whether their anticipated exposure is high, normal or low on a periodic such as weekly basis. Finally, the screen  600  has a calculate reference rents button  610  that allows a user to determine reference rents.  
         [0063]    [0063]FIG. 7 shows a competitors rents worksheet  700  that is displayed by selecting the calculate reference rents button  610  in FIG. 6. The information for the first unit type is displayed. The worksheet  700  includes a market composite column  702 , a reference rent column  704  and an override reference rent  706 . The market composite column  702  and reference rent column  704  have set values for long, medium, short and month to month (“MTM”) term leases. These values are obtained the algorithm discussed above. The user may override the reference rent with their own entry by entering a new value in the override reference rent column  706 . The worksheet  700  includes a next unit type button  710  and a previous unit type button  712  that allow a different unit type to be displayed. A user may move forward and backward along the unit types in the worksheet  700  by using the next unit type button  710  and the previous unit type button  710  respectively. A print rent graph button  714  will print a graph of the reference rents. An auto-update LRO button  716  will automatically update the LRO based on the entered values. A manually update LRO button  718  will print a set of the file information needed to enter reference rents manually into the LRO or any other system the user desires.  
         [0064]    [0064]FIG. 8 shows a rent graph  800  generated as a result of the input data and by selecting the rent graph button  714  in the screen in FIG. 7. The rent graph  800  shows the reference rents for each unit type broken down by the term of the lease. The rent graph  800  has a vertical axis  802  which shows different levels of rental prices. A horizontal axis  804  has a number of bars representing the rents for each term lease of a particular class of rental unit. For example, the unit type a1 has a long term bar  806 , a mid term bar  808 , a short term bar  810  and a month to month bar  812  which show the reference rents for each of the lease terms.  
         [0065]    A user in the field such as a property manager can input data such as competitor rents and discounts via a web accessible data entry page. Of course other means for data transmission may be used such as computer transmission of electronic data, hard copy copied by a system administrator or direct input into the system  10 . A web data entry page  900  is shown in FIG. 9 which is preferably displayed on a computer such as computer  42  in a property management office  32  in FIG. 1. The web page  900  may be accessed by any authorized property manager to report competitor and other field data. The web page  900  also allows a property manager to obtain data produced by the system  10  relating to reference rents.  
         [0066]    The web page  900  has a series of tabs that allow data input an display. The tabs include a daily activities tab  902 , a business statistics tab  904 , a reports tab  906  and a settings tab  908 . Various information may be displayed by selecting a forecasts area  910 , an inventory area  912 , a recommendations area  914  and a competitor rents area  916 . The competitor rents area  916  has been selected in FIG. 9. A competitor rents table  920  is displayed. The competitor rents table  920  has a competitor column  922 , a unit type column  924 , a lease term column  926 , a base rent column  928 , a total concessions column  930 , an effective rent column  932  and a selection box column  934 . The user may enter base rent and concessions for each unit type and for each lease term in the boxes in the base rent column  928  and the total concessions column  930  as this information becomes available. Once a user has finished changing the various values, the user can submit the new data by selecting a submit button  936 .  
         [0067]    Additional functionality may be realized by the program that allows a user to attach a file to an email. The user may also create an archive via an email and create backup files for the various data discussed above.  
         [0068]    It will be apparent to those skilled in the art that various modifications and variations can be made in the method and system of the present invention without departing from the spirit or scope of the invention. Thus, the present invention is not limited by the foregoing descriptions but is intended to cover all modifications and variations that come within the scope of the spirit of the invention and the claims that follow.