Abstract:
A site/building decision facilitating apparatus including a database that correlates building characteristics with business driver factors, a processor linked to the database and running a program to perform the following acts: receiving business driver factor information for a first building project via an input device and identifying a subset of default building characteristics for the first building project using the database and the received business driver factor information

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
       [0001]    Not applicable. 
       STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT 
       [0002]    Not applicable. 
       BACKGROUND OF THE INVENTION 
       [0003]    The present invention relates to site and building selection methods and apparatus and more specifically to software that accounts for various disparate selection criteria or factors such as business drivers, intended business uses, the industry associated with a building project, construction costs, personnel costs when determining the overall costs associated with constructing and operating a facility at a particular location. 
         [0004]    Whenever an employee of a business is charged with real estate decisions (hereinafter a “real estate decision maker”) decide to design/locate a new building, the decision maker should account for many different factors or business drivers (e.g., factors that affect new building location and design) to optimally complete the design and locating process. Exemplary business drivers that may be associated with a new building include but are not limited to drivers related to employee productivity, customer experiences, availability and cost of different types of labor, environmental impact, first time cost to build, real estate related energy costs, the affect on recruiting, training and retaining employees, etc. 
         [0005]    Public databases have been developed that can be used by real estate decision makers to develop a general understanding of how different building locations may impact certain business drivers. To this end, public databases currently exist that store statistical information related to various labor related business drivers such as average employee salaries, skill sets of potential employees within geographic regions, employee retention rates, unemployment rates, etc. Similarly, databases exist that store statistical data regarding construction material costs and construction labor costs based on geographic regions. 
         [0006]    While public statistical labor and construction databases exist, currently there is no known way to easily access existing data regarding building construction costs and labor related factors in a format that would be meaningful/useful to a real estate decision maker. For this reason, in many building design and locating endeavors, location related cost and rate data may be only anecdotally considered because of its format and an inability to translate the existing data into building specific information. Thus, while data may exist that indicates that a software engineer can be hired for 30% less in Detroit, Michigan than in San Diego, Calif. while widget assemblers can be hired for 10% less in San Diego than in Detroit Mich., translating that information into labor cost savings associated with a specific building in each of the two locations where it is anticipated that 20% of the employees will be software engineers and 80% will be widget assemblers it not an easy task and therefore, in many cases, is simply not done. Instead, because 80% of employees are to be widget assemblers a decision maker may simply look to San Diego as the location where widget assembler wages are low and opt for that location over Detroit. 
         [0007]    When real estate decision makers require more geographically specific information to make building decisions, many real estate decision makers rely on design, construction and human resource consultants to provide advice. These consultants develop valuable expertise in their respective fields and can typically customize statistical information for decision makers so that decisions are made in a more informed environment. 
         [0008]    While building design and location selection processes have been developed by consultants, unfortunately, there are several shortcomings in the current building locating and designing processes that result in less than optimal decisions. 
         [0009]    First, while design, construction and human resource consultants each have developed various skills that are useful when selecting the location for a new building or for designing a building to meet a client&#39;s needs, typically these consultants work separately and in a vacuum (i.e., generally not knowing what other consultants are doing). For instance, human resource consultants may provide specific labor related statistical information (e.g., unemployment rate, average wages for different types of employees, turnover rates, typical educational background, etc.) for different locations to help a client select a location for a new building but typically have no special knowledge regarding building design or construction costs and do not care much about those statistics. In contrast, design consultants typically design a building that is consistent with business drivers related to building design and have no special knowledge about labor statistics or, in many cases, even costs associated with constructing the building that is being designed. In fact, in many cases design consultants are hired to design a building without even knowing where the building will ultimately be located and therefore the design consultants cannot know how much it will cost to construct the designed building as costs can vary appreciably as a function of location. Similarly, construction consultants typically bid on a building designed by a design consultant without any special labor related knowledge and with little or no input into the building design. 
         [0010]    Moreover, even where design, construction and human resource consultants do share information or all share information with a decision maker, there is no known way to quickly and relatively inexpensively integrate data from the various consultants to help real estate decision makers make well informed decisions. Thus, decision makers typically approach the location, design and construction portions of the decision making process in stages, first selecting a small number of possible building locations, then designing a building and thereafter selecting a final location at least in part based on location related construction costs for the designed building. 
         [0011]    While the location-design-construction cost progression may seem logical, such a sequential regimen can have unintended consequences. For instance, in some cases a decision maker may use labor related costs in an initial process to identify two possible building locations. After the two locations are identified and a building design has been selected, the decision maker may use construction costs to select one of the two locations as a final location for the building. In this case it may be that third, fourth and fifth locations have better overall mixes of construction and labor costs which could have reduced the long term costs associated with the building appreciably and therefore the sequential process results in a less than optimal decision. 
         [0012]    Second, in many cases real estate decision makers and their consultants never clearly define which of the business drivers are driving the design and location processes and/or the relative importance of the drivers. To this end, typically different business drivers are important to each of the different consultants used by real estate decision makers. For instance, human resource consultants are primarily interested in labor related business drivers like recruiting, retention and training of employees, wage rates, skill sets within specific geographical regions, etc., and are generally not concerned with design related factors such as how a building affects customer experiences, how a building fosters employee communications, employee cooperation, employee innovation, employee productivity or flexibility of a workplace. In contrast, a design engineer typically has no interest in labor related business drivers and instead is completely focused on design related drivers like how a building affects customer experiences, how a building fosters employee communications, employee cooperation, employee innovation, employee productivity and flexibility of a workplace. Similarly, construction consultants are typically interested only in cost related business drivers and have very little interest in the labor related and design related business drivers. 
         [0013]    Each consultant, having his or her own area of focus, naturally stresses the importance of the business drivers that are important in the consultant&#39;s field of expertise. The real estate decision maker often gets lost in the middle of the consultants and usually cannot even articulate a possible list of business drivers much less rank drivers in the order of importance for a specific building endeavor. In many cases the consultant that makes the greatest impression on the decision maker can end up driving the entire process such that drivers that are not related to the consultant&#39;s field but that should have been important to the decision maker are relegated to a secondary status at best. 
         [0014]    Third, because some of the business drivers are relatively easy to generate metrics for while others are difficult to quantify, many decision makers and consultants are inclined to simplify the decision making process by focusing only on easily quantifiable business drivers. For instance, it is generally accepted that a well designed and aesthetically appealing building can enhance employee recruitment, training efforts, collaborative activities and productivity and can increase employee retention rates. Nevertheless, because the degree to which building design affects employee factors is not easily quantifiable, often design takes a back seat to easily quantified construction costs. For example, where construction costs can be reduced by 10% by eliminating half of the planned windows in a building and there is no hard metric indicating how such a change would affect employee related factors, it is difficult to argue against the window cost reduction. In short, while cost and employee related factors may both be important business drivers for a building, in many cases building decisions are reduced to abbreviated decision processes wherein cost is a primary consideration while employee related factors are either not considered or are only secondarily considered. 
         [0015]    Abbreviated decision processes have short term appeal as they provide comfort to decision makers and consultants that, at least regarding the easily quantifiable metrics, the right decisions are being made. Unfortunately, in the long term, in many cases, abbreviated processes do not yield optimal results and can increase costs appreciably. For instance, it is generally known that building costs are a fraction of employee costs (e.g., wages, recruiting, training, insurance, retention, etc.). It is also generally accepted that when employees find the spaces in which they work appealing, employee costs can be reduced appreciably as the space aides recruiting and retention efforts, may increase productivity, may increase collaboration, etc. In this example it will be assumed that construction costs are only 10% of anticipated yearly employee costs. Here, if an initial construction cost increase of 10% for better furniture or building design results in a 1% employee retention rate increase, the 10% increase in construction costs can be offset in one year by the reduced employee turnover rate alone. In addition, recruiting and training costs may be reduced and collaborative activity may be enhanced by the increase in furniture costs and/or better building design so that the increase in construction costs is offset even faster. In this example, if construction costs are viewed in a vacuum without considering effects on employees, the end result is appreciably more costly in the long term. 
         [0016]    Fourth, even when a real estate decision maker is sawy enough to clearly understand which business drivers are driving the decisions to design and locate a building, because of the nature of the decision making process, the process itself often takes on a life of its own and begins to constrain the decision maker and consultants to other than optimal designs and locations. For instance, once the location selection and design processes have progressed and the decision maker and consultants have all spent substantial time and effort in moving a building project toward an end goal, obviously the costs associated with a decision maker&#39;s time and effort in considering specific designs and locations cannot be recouped. In addition, most consulting costs cannot be recouped when a real estate decision maker decides not to pursue an initial design direction or location (i.e., when a design change or building location change is made). 
         [0017]    For these reasons, at some point during the design and locating process, decision makers and consultants often feel compelled/constrained to continue along the path already started even after the decision maker and/or consultant suspects that the path is no longer optimal. As a simple example, consider a case where a decision maker initially contemplates constructing a building to house a customer call center in San Diego and only later, after extensive efforts related to a San Diego site, recognizes that there may be some advantages to placing the call center in Kansas City. While there may in fact be many advantages to the Kansas City location, the decision maker and/or consultant may be compelled to stick with the San Diego site in order to justify costs already incurred. Once again, here, the process leads to a less than optimal building location decision. 
       BRIEF SUMMARY OF THE INVENTION 
       [0018]    It has been recognized that many different rules of thumb can be developed and stored in a database that relate default/common facility characteristics to user specifiable factors. Here, after at least a small subset of factors related to an anticipated building have been specified by a user, a processor can use the rules of thumb to generate and render accessible a subset of facility characteristics related to an anticipated facility. In at least some embodiments the default building characteristics can be altered by the user to customize the facility subset and when at least some of the default characteristics are altered, the alterations ripple through the other characteristics in the facility characteristic subset. 
         [0019]    Exemplary factors related to an anticipated facility that may be provided by the user include but are not limited to any subset of business drivers, the number and types of employees that are expected to use the building, the location of the building, physical characteristics of the building, the industry in which the building is to be used, the location of the building and characteristics regarding labor expectations (e.g., turnover rate, wage rate, etc.). Exemplary business drivers include productivity related factors, customer/client related factors, real estate energy costs, availability and cost of labor, capital investment factors, environmental impact factors, factors related to communication with employees, factors related to customer service, factors related to construction costs, factors related to innovation fostering, factors related to recruiting, training and retention of employees, factors related to speed of construction, factors related to workplace flexibility and factors related to workplace culture. In at least some embodiments relative importance of the business drivers may be specifiable and the building characteristic subset may be selected as a function of the relative importance as specified. 
         [0020]    In at least some embodiments, after a small number of facility characteristics have been specified and during a characteristics customization process, a user can jump to a summary page independent of how much customization has occurred to get a quick summary of estimate of facility construction and furnishing costs, estimated labor costs, location related costs and workspace characteristics. 
         [0021]    In some embodiments it is contemplated that the system will be capable of identifying likely useful modifications to a facility specified by a system user and will render helpful suggestions to the user. For instance, where a user indicates that first time cost to build a facility is the only important factor to be considered but then specifies a relatively expensive building the system may identify a subset or all of the building characteristics that could be altered to reduce costs and may present that information in any of several different forms to the user. 
         [0022]    In some embodiments it is contemplated that the system will be able to identify cost differences other than construction cost differences associated with different building types. For instance, where a first building will reduce energy costs by $0.50 per square foot when compared to a second building, the system may be able to estimate the $0.50 cost savings. As another instance, where a first building will reduce churn (i.e., reconfiguration costs) costs by $0.60 per square foot per year, the system may be able to estimate the $0.60 cost savings. Where other than construction costs can be determined by the system, the system may also generate and present other useful metrics including but not limited to a net effective rent (NER) value which is the triple net lease cost of a facility minus other costs (e.g., the $0.50 and $0.60 energy and churn savings above) that would be incurred if a different type of facility were constructed. 
         [0023]    In some embodiments the system may also be able to identify estimated profit increases as a function of different building characteristics and report those increases either as raw data or reflect those increases in an NER value. 
         [0024]    To the accomplishment of the foregoing and related ends, the invention comprises the features hereinafter described. The following description and the annexed drawings set forth in detail certain illustrative aspects of the invention. However, these aspects are indicative of but a few of the various ways in which the principles of the invention can be employed. Other aspects, advantages and novel features of the invention will become apparent from the following detailed description of the invention when considered in conjunction with the drawings. 
     
    
     
       BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS 
         [0025]      FIG. 1  is a schematic view illustrating a computer and communication system according to at least some embodiments of the present invention; 
           [0026]      FIG. 2  is an exemplary building type/default employee database that may be included as a portion of the proprietary database shown in  FIG. 1 ; 
           [0027]      FIG. 3  is a primary operations center database that may be included as a primary operations center database of  FIG. 1 ; 
           [0028]      FIG. 4  is a flow chart illustrating at least one method that may be performed by the server of  FIG. 1  that is consistent with at least some aspects of the present invention; 
           [0029]      FIG. 5  is a flow chart illustrating a subprocess that may be substituted for a portion of the process shown in  FIG. 4 ; 
           [0030]      FIG. 6  is a screenshot that may be provided by the server of  FIG. 1  via the display shown in  FIG. 1  to enable the system user to rank or bucket various business drivers as mission critical, core drivers, drivers to be considered or not important; 
           [0031]      FIG. 7  is a similar to  FIG. 6 , albeit showing a summary of how different business drivers have been bucketed or ranked by a user; 
           [0032]      FIG. 8  is screenshot showing tools that allow a system user to select one of several different types of facilities to be constructed and to provide additional information related to the number of seats to be provided within a facility and the number of employees that it is anticipated will use a facility; 
           [0033]      FIG. 9  is a screenshot including tools that allow a system user to input targets and assumptions for a facility to be constructed; 
           [0034]      FIG. 10  is a screenshot including tools that allow a system user to input location related information corresponding to a facility to be constructed and also includes a subwindow that provides some summary information related to employees expected to use a facility; 
           [0035]      FIG. 10A  is an exemplary subwindow that provides summary information related to a building; 
           [0036]      FIG. 10B  is similar to  FIG. 10A , albeit providing workspace related summary information; 
           [0037]      FIG. 11  is a screenshot including tools that enable a system user to view default employee characteristics and wages and to alter those characteristics and wages; 
           [0038]      FIG. 12  is a screenshot including tools that enable a system user to view exemplary building shapes and to select one of the building shaped for a facility to be constructed; 
           [0039]      FIG. 13  is similar to  FIG. 12 , albeit allowing a system user to view and select building entry type; 
           [0040]      FIG. 14  is similar to  FIG. 12 , albeit allowing a system user to view and select roof types for a building to be constructed; 
           [0041]      FIG. 15  is similar to  FIG. 12 , albeit allowing a system user to view arid select different mixes of exterior skins for a building to be constructed; 
           [0042]      FIG. 16  is a screenshot allowing a system user to view and specify various characteristics related to a building and the location at which the building is to be constructed; 
           [0043]      FIG. 17  is a screenshot including tools that allow a system user to view and edit at least a subset of core choices for a building to be constructed; 
           [0044]      FIG. 18  is a screenshot including information related to user workspaces within a facility to be constructed; 
           [0045]      FIG. 19  is a screenshot including tools to allow a system user to view a basic image of individual workspaces and to specify various characteristics of individual workspaces; 
           [0046]      FIG. 20  is a summary screenshot including information related to the location at which a building is to be constructed, the employees that it is anticipated will use the building, building characteristics and characteristics of individual workspaces to be included in a building; 
           [0047]      FIG. 21  is similar to  FIG. 20 , albeit including highlighting boxes indicating building characteristics that are inconsistent with the way in which a system user has bucketed business drivers; and 
           [0048]      FIG. 22  is a screenshot showing an NER tool. 
       
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
       [0049]    Referring now to the drawings where in similar reference numerals correspond with to similar elements throughout the several views and, more specifically, referring to  FIG. 1 , the present invention will be described in the context of an exemplary computer and communication system  550  that includes, among other things, at least one server/processor  552 , one or more interface devices  554  (only one shown in  FIG. 1 ) and a plurality of databases  556 ,  558  and  555 . Server  552  is linked or linkable via a communication network  551  to each of the databases  556 ,  558  and  555  and also to interface device  554 . At least some of the databases in some of the embodiments will be public databases while other are proprietary. 
         [0050]    In  FIG. 1 , exemplary databases  556  and  558  are public meaning that the data stored therein can be accessed either free of charge or for a small fee by members of the public. Exemplary public databases in  FIG. 1  includes a cost construction database  556  and a human resource database  558 . Cost construction database  556 , as the label implies, includes various statistical information related to the cost of constructing various types of buildings. For example, database  556  may include geographically specific information related to the cost of labor to construct buildings, the cost of specific materials to construct buildings, permit and regulatory costs associated with building specific types of structures, real estate costs including the costs of buying property within geographic areas, etc. In many cases construction cost types of information are maintained by municipalities/governmental agencies which render the information accessible via the internet or the like. 
         [0051]    Human resource database  558 , as the label implies, may include periodically collected information related to employees within specific geographic areas. For example, employee related data in database  558  may include data related to unemployment rate, educational statistics for people living within specific regions including percent that have college educations, percent that have high school educations, percent that have masters degrees, percent that have doctorates, percent that are trained as managers, percent that are trained as scientists, etc., average hourly rates for employees within particular regions, average hourly rates for employees having specific skill sets within particular regions, retention rates for employees with particular skill sets within particular regions, etc. While databases  556  and  558  are described herein as being public, in at least some embodiments it is contemplated that one or both of databases  556  and  558  may be proprietary or at least supplemented by proprietary databases. Moreover, databases  556  and  558  may comprise a single database or may each comprise two or more public databases. 
         [0052]    Referring still to  FIG. 1 , proprietary database  555  includes one or more software programs  557  and a default database  560 . Programs  557  are various programs that are run by server  552  to perform various inventive methods and processes as described below. 
         [0053]    Default database  560 , as the label implies, includes a plurality of default settings usable by server  552  for specifying various characteristics of buildings/facilities/employees. To this end, default characteristics have been and are continuing to be generated where the characteristics include default or benchmark percentages of employees that work in different types of facilities, typical or common building and workspace features and choices given different building types, different business drivers associated with specific buildings and the number of employees that are expected use a building. The default database  560  includes two sub-databases, a building type/default employee database  562  and a facility characteristics default database  564 . 
         [0054]    Referring still to  FIG. 1  and also to  FIG. 2 , building type/default employee database  562  relates bench mark employee statistics to four different facility/building types. In the illustrated example, database  562  includes a facility/building type column  565 , a staff column  569 , a support staff column  573 , a manager column  575  and a senior management column  577 . Facility/building type column  565 , as the label implies, includes a list of different facility types including a primary operation center, a regional operations center, a general office/headquarters and a regional office/headquarters. Here, it is assumed that any new building to be constructed or occupied will be used as either a primary or regional operations center or as a general or regional office/headquarter and therefore the building can be categorized as one or the other of the four types in column  565 . 
         [0055]    For each of the facility types in column  565 , corresponding entries in columns  569 ,  573 ,  575  and  577  indicate the percentage of total employees at the facility type that can be categorized as staff, support staff, managers and senior management, respectively. Thus, as shown in  FIG. 2 , at a primary operations center it may be that statistical information derived from prior project experience has shown that 75% (e.g., 0.75) of the total number of employees will likely be staff employees (e.g., see the entry in column  569  that corresponds to the primary operations center type in column  565 ). Similarly, at a primary operation center, 10% of the total number of employees will typically or commonly be support staff, 10% will be managers and 5% will be senior managers as indicated in column  573 ,  575  and  577 , respectively, in the row associated with the primary operations center type in column  565 . Thus, for example, if a primary operations center is to have 500 employees, given the bench mark defaults in database  562 ,  375  of the employees will be staff (i.e., 0.75×500=375), 50 of the employees will be support staff, 50 of the employees will be managers and 25 of the employees will be senior managers. In contrast, given the employee breakdown bench mark data in database  562 , if 500 employees were to work at a general office headquarters, 225 of the employees would be staff, 100 of the employees would be support staff, 75 of the employees would be managers and 100 of the employees would be senior managers. 
         [0056]    Here, it should be appreciated that, while four different facility types are listed in  FIG. 2 , in other embodiments, more or less facility types may be listed, depending upon what is reasonable given how buildings are used in an industry. In addition, facility types and benchmark employee breakdowns may be different for different industries. For example, while the statistics and facility types in  FIG. 2  may be appropriate in the case of a manufacturing industry, entirely different facility types and benchmark employee breakdowns may be more appropriate in the health care industry, education industry, etc. 
         [0057]    Referring still to  FIG. 2 , in addition to the bench mark employee breakdown data provided in columns  569 ,  573 ,  575 , and  577 , bench mark turnover rates are provided for each of the facility/building types in column  565  which can be used to develop relatively sophisticated statistics related to employee or labor costs. In this regard, column  567  includes a separate entry for each one of the facility/building types in column  565 . For instance, for a primary operations center, the bench mark annual turnover rate in column  567  is 10% meaning that, where  500  employees work at a primary operations center, 50 of the those employees will turnover on an annual basis. Similarly, for a regional operations center the data in column  567  indicates that 15% annual turnover should be expected while only 5% annual turnover should be expected for an general or regional office/headquarters. 
         [0058]    Referring once again to  FIGS. 1 and 2 , building characteristics default database  564  includes a separate default database for each one of the facility/building types listed in column  565  of database  562 . Thus, database  564  includes a primary operations center database  566 , a regional operations center database  568 , a general office/headquarters database  570  and a regional office headquarters database  572 . Each of the databases  566 ,  568 ,  570  and  572  is similar in construction and is used or operates in a similar fashion and therefore, in the interest of simplifying this explanation, only primary operations center database  566  will be described here in any detail. The main differences between the databases  566 ,  568 ,  570  and  572  are the characteristics specified by the different databases. For example, comparing a regional operations center database to a general office/headquarters database, because headquarters buildings are often designed to be relatively more aesthetically impressive for recruiting and for customer relations purposes, the headquarters database may include defaults that require the best possible signage, wall coverings, furniture, relatively large executive management offices, etc., whereas the regional operations center database  568  may specify lower quality materials, design, relatively smaller executive management offices, etc. 
         [0059]    Referring still to  FIG. 1  and now to  FIG. 3 , an exemplary and simplified primary operations center database  566  is shown in  FIG. 3 . Database  566  includes a facility characteristics column  602  and a plurality of additional column  604 ,  606 ,  608 , etc., that specify default facility characteristics. As the label implies, column  602  includes a list of facility characteristics which, as shown, are broken down into sub-groups of characteristics including a building sub-group  609 , an individual space sub-group  614 , a team space sub-group  611 , a technology sub-group  613 , a communications/branding sub-group  616 , an amenities sub-group  615  and an “other” sub-group  617 . Under the building sub-group, labels beginning with the first label  610  include shape, level, entry, roof type, exterior skin, parking ratio, parking level, stairs-communicating, etc. 
         [0060]    The “shape” label in column  602  corresponds to the general shape of a building to be constructed or occupied. To this end see  FIG. 12  where a screen shot  218  shows various general building shapes including a rectangular shape  222 , a gull-wing type shape  226  and various other shapes. The “levels” label corresponds to the number of levels (e.g.,  1 ,  2 , etc.) of a building to be constructed or occupied. The “entry” label corresponds to the type of entryway into a building to be constructed or occupied. To this end, see  FIG. 13  where a screenshot  250  shows various building entry types including, among others, a simple entry  254 , an integrated porch entry  258 , an extended canopy entry, etc. The “roof type” label corresponds to the type of roof to be included on a building to be constructed or occupied. To this end, see  FIG. 14  that shows a screenshot  270  illustrating exemplary roof types including, among others, a flat roof type  274 , a barrel vault roof type  278 , etc. 
         [0061]    Referring still to  FIG. 3 , the “exterior skin” label in column  602  corresponds to the material used on the exterior of a building to be constructed or occupied. In this regard, see  FIG. 15  where a screenshot  290  shows images of different types of materials to be used on the exterior surface of a building including concrete, masonry, panelized metal, windows and curtain wall. Under the exterior skin label in column  602  a separate label for each of the types of exterior skin is provided, the separate labels collectively identified by numeral  612  in  FIG. 3 . The “parking lot ratio” label indicates a parking space ratio to be used to determine the number of parking spaces to be included around a building to be constructed. The “parking level” label indicates the number of parking levels to be included if a parking structure is to be constructed. For example, where a parking structure is to have three levels, a parking levels value would be 3. The “stairs/communicating” label indicates the number of stairwells to be included in common or customer related areas to be constructed. 
         [0062]    Referring yet again to  FIG. 3 , under the individual space portion  614  of column  602 , different labels are provided for different types of offices including senior manager, manager, support staff and staff. Although not illustrated, the individual space portion of column  602  may also include labels related to individual space or office amenities such as desk, a chair, side chairs, lighting, wall coverings, computer type, monitor type, file cabinets, bins, shelving, side tables, a credenza, etc. 
         [0063]    Under the communications/branding portion  616  of column  602 , labels are included that are related to “applied digital imagery wall covering”, “entry signage”, “individual name plaques”, and “information flat screens”. While no labels are shown under the team space, technology, amenities, and “other” portions of column  602 , it should be appreciated that various labels corresponding to various features will be provided under each one of those portions. Moreover, many other labels are contemplated that will be provided under the facility characteristics, the individual space and the communications/branding portions of column  602 . 
         [0064]    In at least some embodiments, it is contemplated that a list of business drivers may be provided for a system user that can be ranked in terms of their importance in relation to a facility to be constructed and furnished or fitted out for use. Here, the term “business driver” is used to refer to things that may be considered important to a real estate decision maker when going through the process of searching for a location for a building, designing the building and furnishing different parts of the building. To this end, referring now to  FIG. 7 , sixteen exemplary business drivers that may be provided for ranking by a system user are shown including “productivity effectiveness workflow”, “compelling customer experience”, “energy costs of real estate”, “changes in organization”, “availability and cost of labor”, “new service, new product”, capital investment”, “impact on the environment”, “communication with employees”, “customer service”, “first time cost to build”, “foster innovation”, “recruit, train, retain”, “zero down time”, “flexibility of work space” and “cultural change”. 
         [0065]    As shown in  FIG. 7 , in the illustrated example, a system user can bucket the business drivers into any of four different buckets to rank the importance thereof. In this regard, the four buckets of importance in the present example include a “mission critical” bucket  102 , a “core driver” bucket  104 , a “consider” bucket  106  (also referred to hereinafter as a “to be considered” bucket), and a “not important” bucket  108 . 
         [0066]    In at least some embodiments it is contemplated that the default facility characteristics that may be provided in the facility characteristics default database  564  (see again  FIG. 1 ) may depend upon the importance of the different business drivers to a system user. For example, where a compelling customer experience is the most important or most mission critical business driver, facility characteristics may be very different than in a case where the first time cost to build a building is the most important or mission critical of the business drivers. For instance, where a compelling customer experience is the only mission critical business driver for a particular building and where first time cost to build is not important, the facility defaults in database  564  may be consistent with a far more expensive building than in a case where the first time cost to build is mission critical and a compelling customer experience is not important. 
         [0067]    Referring once again to  FIG. 3 , each of the columns  604 ,  606 ,  608 , etc., in the primary operation center database corresponds to a unique group bucketing of the business drivers shown in  FIG. 7 . In  FIG. 3 , the abbreviated labels “MC”, “CD”, “C” and “NI” correspond to the mission critical, core driver, consider and not important buckets shown in  FIG. 7 , respectively. Thus, the information in column  604  corresponding to the labels  600  indicates that the characteristic values in column  604  correspond to the case where business drivers have been bucketed such that the first time cost to build is the only mission critical driver and all of the other business drivers (BDs) are not important (i.e., are in the NI row). Similarly, the information in column  606  corresponding to labels  600  indicates that the only mission critical business driver is a compelling customer experience and that all of the other business drivers are not important. In column  608 , the information related to the labels  600  indicates that a compelling customer experience is mission critical, the first time cost to build is a core driver (i.e., is in the CD row) and that all other business drivers are not important. 
         [0068]    Referring yet again to  FIG. 3  and specifically to column  604 , where the first time cost to build is the only mission critical business driver and all other business drivers are not important, it can be seen that, in general, a relatively inexpensive facility is specified by the facility characteristics values. To this end, the shape of the default building in column  604  is a rectangle which is generally the least expensive shape in which to construct a building. Only a single facility level is indicated in column  604 . The default entry in column  604  is a simple entry and the roof type is flat, both inexpensive options. Consistent with a relatively inexpensive building, the exterior skin is 90% panelized metal and only 10% windows in column  604 . Similarly, consistent with a relatively inexpensive building, the offices specified are relatively small and the communications/branding components and materials are indicated as good which is, in the present example, a relatively low cost indicator (e.g., better and best indicators correspond to relatively more expensive materials and building techniques than the good indicator throughout this description). 
         [0069]    Referring yet again to  FIG. 3 , in contrast to the low cost building defaults in column  604 , in column  606  where customer experience is the only mission critical business driver and all other business drivers are not important, a more expensive building is specified by the default values. In this regard, in column  606 , the shape of the building is a gull wing type shape as opposed to the simpler rectangular shape in column  604 , the building has two levels, the entry of the building includes a relatively expensive integrated canopy, the roof type is a barrel vault, the exterior skin of the building includes much more concrete and many more windows as well as a curtain wall, the offices specified under the individual space portion in column  606  are larger than the offices specified in column  604  and the communication/branding features and materials are indicated as being the best so that a compelling customer experience is more likely. 
         [0070]    Referring still to  FIG. 3 , in column  608  where a compelling customer experience is mission critical, first time cost to build is a core driver and all other business drivers are not important, the default values specify a building that is relatively high quality and is aesthetically pleasing in all areas where customers are expected to function and that is relatively inexpensive in other spaces where customers are not expected to function (e.g., any individual spaces, amenities, etc.). 
         [0071]    Referring once more to  FIG. 3 , it should be appreciated that the database  566  illustrated is extremely simplified and that, in most cases, a much more complex database is anticipated. In this regard, as shown, database  566  includes only three columns  604 ,  606  and  608  that correspond to three different ways of bucketing or ranking the business drivers. It should be appreciated that there are several thousand different combinations of the  16  business drivers shown in  FIG. 7  and that, in at least some embodiments, a database  566  would include a separate column for each one of the different possible ways of bucketing the business drivers. It should also be appreciated that while 16 business drivers are shown in  FIG. 7 , embodiments with fewer business drivers or a larger number of business drivers or indeed with completely different sets of business drivers are contemplated. Moreover, while four buckets are provided in  FIG. 7 , and in the example here, in other embodiments, fewer buckets or a larger number of buckets may be used for ranking business driver importance. 
         [0072]    In at least some embodiments, instead of providing a separate column in the primary operations center database  566  for each one of the different possible ways of bucketing the business drivers, it is contemplated that one or a subset of the business drivers may be associated with a specific set of facility characteristics such that only the subset of business drivers and how those business drivers are bucketed affect those facility characteristics. For example, in at least some embodiments the compelling customer experience business driver may be the only driver that affects the communications/branding portion of the default facility characteristics. Thus, for instance, regardless of how other business drivers are bucketed, a “best” value may be provided for each of the communications/branding labels in column  602  whenever a compelling customer experience is mission critical, a “better” value may be provided for each of the communications/brandings labels whenever a compelling customer experience is a core driver and a “good” value may be provided for each of the communications/branding labels when a compelling customer experience is either not important or only a consideration. Similarly, other single business drivers or subsets (e.g., two or three, etc.) of business drivers may drive subsets of the facility characteristics independent of how the other business drivers are bucketed so that a simplified primary operations center database can be constructed. 
         [0073]    Moreover, in at least some embodiments, some type of equation may be formulated that combines different business driver rankings to generate a single business driver value where the value then dictates which of several sets of facility characteristics to select as default. For instance, in some embodiments there may be one hundred different sets of facility characteristics where the 1 st  set corresponds to an inexpensive building, the 100 th  set corresponds to an expensive building and the sets between the 1 st  and 100 th  set increase in cost progressively. Despite there being thousands of ways to bucket the sixteen business drivers into the four buckets in  FIG. 7 , the equation may result in a second level of bucketing where each of the different ways of ranking the drivers corresponds to one of the 100 sets of facility characteristics and therefore corresponds to one of 100 different sets of facility benchmarks. 
         [0074]    Referring once again to  FIG. 1 , interface device  554  may take any of several different forms including a personal computer, a laptop computer, a palm-type computing device, a server, a workstation, a thin client type computing device, etc. In the illustrated embodiment, device  554  includes a keyboard or other input type device  549  such as a mouse and a display screen  557  for receiving output from server  552  and for providing input to server  552 . 
         [0075]    Referring now to  FIG. 4 , an exemplary method  640  that is consistent with at least some embodiments of the present invention is illustrated. Referring also to  FIGS. 1 through 3 , at process block  642 , default databases  560  are provided which are accessible by server  552 . At block  644 , a system user provides input regarding business drivers, anticipated facility type and anticipated number of employees to occupy a building to be constructed using interface device  554 . To this end, referring also to  FIG. 6 , a screen shot  50  that may be provided by server  552  via display screen  547  is shown. Screen shot  50  includes a graphical interface display having a primary navigation tool bar  54  along the lower edge thereof and a secondary navigation toolbar  52  along the top edge thereof. Between the primary and secondary tool bars, a data entry space  98  is provided. The exemplary primary navigation tool bar  54  includes a utilities icon  51 , a notepad icon  53  and a forward arrow icon  69 . Each of icons  51 ,  53  and  69  is selectable by moving a mouse controlled cursor there over and clicking one of the mouse buttons in a conventional manner. When utilities icon  51  is selected, a pop-up menu (not shown) including mouse selectable labels for various software features appears. When notepad icon  53  is selected, a window opens up in which a user can take notes by typing with keyboard  549  or the like to memorialize thinking during use of the inventive system. Forward arrow icon  69  is selectable to move to a next screen shot shown in  FIG. 7  after a user is done using the input tools in space  98  of screen shot  50 . 
         [0076]    Referring still to  FIG. 6 , secondary navigation tool bar  52  includes five separate mouse selectable icons including a “drivers” icon  58  a “location” icon  60 , a “people” icon  62 , a “building” icon  64  and a “workspace” icon  66 . Each of the icons  58 ,  60 ,  62 ,  64  and  66  is usable to enter different types of information to be associated with a building to be constructed and/or to navigate back and forth among different screen shots supported by the system. In this regard, it has been recognized that an optimal set of information needed when making a real estate decision can be broken down into several different categories and that the information entry tool can be arranged so that data entry progresses along a logical flow based on those categories. In the illustrated example, the information categories include the categories corresponding to the secondary tool bar  54  icons. 
         [0077]    As the label implies, “drivers” icon  58  is selectable to allow a user to enter information related to business drivers associated with a building to be constructed. “Location” icon  60  is selectable to allow a user to access various location related construction and labor statistics and to specify an anticipated location for a new facility. “People” icon  62  is selectable to allow a user to access and alter employee breakdowns for a facility. “Building” icon  64  is selectable to allow a user to examine and specify building characteristics and “workspace” icon  66  is selectable to allow a user to examine and specify characteristics of individual workspaces for a facility. 
         [0078]    Referring still to  FIG. 6 , when “drivers” icon  58  is initially selected, the information shown in space  98  of screen shot  50  is initially provided. Tools are provided in space  98  for considering different business drivers and bucketing those drivers as mission critical, core, to be considered or not important. To this end, a business drivers wheel  56  is provided along with a mission critical bucket  68 , a core driver bucket  70 , a to be considered bucket  72  and a not important bucket  76 . 
         [0079]    Referring to  FIGS. 6 and 7 , while there are 16 different business drivers in the illustrated example, the business drivers in this example have been subdivided into four separate business driver sets labels a “people in process” set, a “service the customer” set, a “reduce expenses” set and a “business dynamics” set, each of the separate sets provided with a mouse selectable arrow icon  78 ,  80 ,  82  and  84 , respectively, in space  98 . In the present example, each of the separate business driver sets includes four of the business drivers shown in  FIG. 7 . For example, the “people in process” set includes the “productivity effectiveness work flow” driver, the “communication with employees” driver, the “availability and cost of labor” driver and the “recruit, train, retain” driver. As shown in  FIG. 6 , when the people in process icon  78  is selected, the four drivers associated therewith are provided within a circular space defined by arrow icons  78 ,  80 ,  82  and  84 . Similarly, although not separately illustrated, the “compelling customer experience” driver, the “customer service” driver, the “new service, new product” driver and a “zero down time” driver in  FIG. 7  are all included in the “serve the customer” set associated with icon  80  so that when icon  80  in  FIG. 6  is selected, the four related drivers appear within the circle formed by icons  78 ,  80 ,  82  and  84 . In a similar fashion, when the “reduced expenses” icon  82  or the “business dynamics” icon  84  are selected, the four business drivers related to each of those icons would appear within the circle defined by icons  78 ,  80 ,  82  and  84 . 
         [0080]    Referring still to  FIG. 6 , after the people in process icon  78  is selected, the four drivers related thereto are provided as mouse selectable icons within the circular space defined by icons  78 ,  80 ,  82  and  84 . The icons in  FIG. 6  include the “productivity effectiveness work flow” icon  86 , the “recruit, train, retain” icon  88 , and “availability and cost of labor” icon  90  and the “communication with employees” icon  92 . When one of icons  86 ,  88 ,  90  or  92  is selected, additional information explaining the nature of that icon and that business driver is provided in space  59  to the left of tool  56  and the selected icon is highlighted. Thus, when icon  86  is selected, icon  86  is highlighted and information related thereto is provided in space  59 . 
         [0081]    To rank or bucket the business drivers corresponding to icons  86 ,  88 ,  90  and  92 , a user can select the icon associated therewith via a mouse controlled cursor and drag the icon to one of the mission critical, core driver, to be considered or not important buckets  68 ,  70 ,  72  or  76 , respectively. After all four drivers associated with the people in process icon  78  have been bucketed, the user can select one of the other arrow icons  80 ,  82  or  84  to access other business drivers and to bucket those drivers in a similar fashion. 
         [0082]    After at least one of the business drivers has been bucketed, a user can select forward arrow icon  69  to move to the next screen shot shown in  FIG. 7 . Referring now to  FIG. 7 , a next screen shot  100  provides a summary page indicating how business drivers have been bucketed. To this end, separate mission critical, core driver, to be considered and not important icons  102 ,  104 ,  106  and  108  are provided in space  98  along with lists of the business drivers that have been bucketed and associated therewith. In the illustrated example, a list  110  of four drivers have been bucketed as mission critical, a list  112  of four drivers have been bucketed as core drivers, a list  114  of four drivers have been bucketed as to be considered and a list  116  of four drivers have been bucketed as not important. At this point, it should be noted that, while four separate drivers have been bucketed in each one of the different buckets, fewer or greater numbers of drivers could have been put in any one of the buckets. In addition, it should be noted that while there are 16 drivers and while all of those drivers have been bucketed in the present example, a user may choose to only bucket a subset of the total number of drivers in which case drivers that are not bucketed are considered to be not important in at least embodiments. At this point, primary navigation tool bar  54  includes both forward and backward arrow icons  120  and  118 , respectively, so that a user can, if necessary, back up to screen shot  50  shown in  FIG. 6  to modify the way in which business drivers have been bucketed or can move forward to a next screen shot. 
         [0083]    Referring once again to  FIG. 1  and now also to  FIG. 8 , after business drivers have been bucketed and forward icon  120  (see again  FIG. 7 ) has been selected, server  552  in the present example provides a screen shot  130  which allows the system user to indicate a type of building to be constructed and to indicate the total number of employees to use the building and the number of seats or independent work spaces to be included in the building. To this end, screen shot  130  provides four facility or building type options in space  98  including a primary operations center, a regional operations center, a general office/headquarters and a regional office/headquarters. Binary mouse selectable buttons are provided next to each one of the building types including buttons  132 , 134 ,  136  and  138 . A system user can select one of the binary buttons to place a dot (see button  132 ) therein to indicate selection of one of the building types for the building to be constructed. Note that the building type options in space  98  correspond to the default databases  566 ,  568 ,  570  and  572  in  FIG. 1 . Seat and employee number fields  140  and  142  are also provided in space  98  where a user can input the number of work spaces that should be included in the new building and the anticipated number of employees to work in the new building, respectively. After the information required in space  98  has been provided, a user can select forward arrow icon  120  to go to the next screen shot. 
         [0084]    Referring to  FIG. 1  and now also to  FIG. 9 , a next screen shot  150  allows the user to provide target and assumption information regarding project cost, anticipated or desired total square footage and an expected move in date. In this regard, cost, square footage and move in date fields  152 , 154  and  156  are provided. Pull down menus like menu  158  may be provided to allow a user to qualify information in any one of the fields  152 ,  154  and  156 . Here, inputting information into fields  152 ,  154  and  156  is optional. To move to the next screen shot, a user selects forward arrow  120  or may select the “Location” icon  60  from bar  54 . 
         [0085]    Referring once again to  FIG. 4 , after block  644 , control passes to block  646  where a user uses device  554  to input location selection information indicating the location at which the user would like to construct a facility. Referring also to  FIG. 10 , a screen shot  170  to help a user select a location for a building is shown. Here, location specifying tools include a state/province field  172  and a city field  174  in which, as the labels imply, state/province and city names can be entered or selected from pull down menus (not illustrated) to specify a specific location for a building. In the illustrated example, the state/province and city selected are California and Fresno, respectively. When a state/province and city are selected, referring also to  FIG. 1 , server  552  accesses the public cost of construction and human resource databases  556  and  558  to obtain information therefrom related to cost of construction, unemployment, wage rates, energy costs, etc. General or basic cost and related types of information is immediately provided within space  98  as shown collectively by numeral  176  in  FIG. 10 . 
         [0086]    Referring still to  FIG. 10 , once a location has been specified via fields  172  and  174 , a summary icon  175 , a drivers icon  177 , a dashboard icon  179  and a scenarios icon  178  are provided along with other icons in primary tool bar  54 . Summary icon  175 , as can be selected at any point after which a location has been selected for a building in order to jump to a summary page (see  FIG. 20 ) for a building project. Here, in general, it has been recognized that, after the limited amount of information described above with respect to  FIGS. 6 through 10  has been specified by a system user, facility default characteristics and default employee mixes for specific building types can be used to generate a complete set of building summary information. In fact, in at least some embodiments, after location has been selected at block  646  in  FIG. 4 , control passes to block  648  where server  552  accesses the building type/default employee database  562  in  FIG. 2  and determines default quantifies of different employee types as a function of building type and anticipated number of employees. To this end, in the present example where 500 employees were specified in field  142  in  FIG. 8  and the building type is a primary operation center, referring to  FIG. 2 , the default employee mix would include 375 staff, 50 support staff, 50 managers and 25 senior managers. 
         [0087]      1  After block  648 , control passes to block  650  where server  552  accesses the building facility default characteristic database  564  and identifies default building characteristics based on business drivers, building type and default quantities of different employee types. Thus, for instance, referring once again to  FIG. 3 , where a compelling customer experience is the only mission critical business driver as shown in column  606 , all of the building characteristics in column  606  would be specified. Here, consistent with the above example, where there are 25 senior managers, as shown in column  606 , 25 private medium-sized senior manager offices would be specified as defaults for the building. Similarly, where the building is to house 50 managers, 50 private small offices would be specified as defaults for the new building as indicated in column  606 , and so on. At block  652 , location related labor and construction costs are accessed, and at block  654 , the default quantities of employee types and location related labor data are used to generate labor estimates that may include estimated wages, turnover rates, turn over costs, etc. At block  656 , default building characteristics and location related construction data are used to generate default construction cost estimates. After block  656 , all information needed to provide a summary as shown in  FIG. 20  has been generated. At block  658 , the default building and labor characteristics are presented to the system user. In the illustrated example, default characteristics are provided in the summary form when icon  175  is selected and, if not selected, are provided in a tabular fashion that allows a user to edit the default characteristics as shown in exemplary  FIGS. 11 through 19 . Here, a first screen shot  190  showing a portion of the default characteristics as in  FIG. 11  can be accessed by selecting forward arrow icon  120  or the “People” icon  62  in  FIG. 10. 100881  Referring still to  FIG. 10 , driver icon  177  can be selected to access information in a pop-up window (not illustrated) similar to the information shown in  FIG. 7  so that a user can refresh memory regarding how business drivers were bucketed. After refreshing memory, the drivers window can be closed. To edit how business drivers were bucketed, a user can reselect “drivers” icon  58  to go back to screen shot  100  shown in  FIG. 7 . 
         [0088]    Referring yet again to  FIG. 10 , dashboard icon  179  can be selected at any time after a building location has been specified in fields  172  and  174  to cause a dashboard window like window  482  shown in  FIG. 10  to pop up which provides summary information similar to the information in the executive summary shown in FIG.  20 ., albeit in an abbreviated form. To this end, dashboard window  482  includes a mouse selectable people icon  484 , a building icon  486  and a workspace icon  488 , along with an abbreviated summary space  490 . When the people icon  484  is selected, information related to labor or employees to be associated with the building is provided in space  490  including information corresponding to an annual estimated salary  473 , turnover  475  and building costs  477  as shown in  FIG. 10 . Here, the annual estimated salary is determined by using public wage information for different types of employees and the number of staff, support staff, managers and senior management that it is anticipated will work in a building based on default employee numbers or user specified numbers. 
         [0089]    Referring to  FIG. 10A , the dashboard window  482  is shown after the building icon  486  has been selected and building related information is provided in space  490 . The building related information includes general building specifying information  481  and a speedometer icon  483  that indicates the relationship between a target cost and a cost estimate. Similarly, in  FIG. 10B , dashboard window  482  is shown after workspace icon  488  has been selected and workspace related information is provided in area  490 . The information subsets in area  490  are only exemplary and other information subsets may be provided in other embodiments. 
         [0090]    Referring yet again to  FIG. 10 , scenario icon  178  is selectable to allow a user to move between any of three different building and location scenarios so that different building and location scenarios can easily be compared to each other. To this end, it has been recognized that system users like to be able to “game” the building and location selection process changing different business driver rankings, facility location and various facility and employee characteristics and to see how those changes effect the ultimate construction, furnishing and labor costs. 
         [0091]    In the present embodiment, when a first building and location scenario is specified, second and third scenarios that are identical to the first scenario are automatically specified and can be selected by selection icon  178 . Here, as shown in  FIG. 10 , initially a label “1” is provided in icon  178  indicating a first scenario. To flip to a second scenario, a user clicks on icon  178  once which changes the “1” label to a “2” label. Similarly, to change to the third scenario, the user clicks on icon  178  until a “3” label appears therein. When the user changes from one scenario to another, the user can change the location of a building via fields  172  and  174 , can go back to the driver&#39;s information by selecting icon  58  and change the bucketing of the business drivers, can change building or facility type by going to the screen shot corresponding to the other scenario as shown in  FIG. 8  and so on. In addition, in any of the scenarios, the user can customize the default facility characteristics in a fashion similar to that shown in  FIGS. 11 through 19 . 
         [0092]    This process of automatically creating multiple identical scenarios simultaneously where each scenario can then be customized is particularly advantageous as in most cases, where a real estate maker may want to compare very similar scenarios where only one or a small number of factors are different among the scenarios. For instance, in many cases anticipated number of employees and facility characteristics between two scenarios may be identical, the only difference between the two scenarios being location. Here, instead of requiring a user to specify all scenario characteristics two or three times, a single specification process is required where customization only requires selection of a second location for the second scenario. 
         [0093]    Referring still to  FIG. 10  and also  FIG. 11 , once forward arrow icon  120  or “People”  62  is selected, screen shot  190  is provided in the illustrated embodiment. As shown and consistent with the example above, where 500 employees are to use a building and where 75% of the employees will be staffed, 10% of the employees will be support staff, 10% will be managers and 5% will be senior managers, the information provided in space  98  includes an employee type column  192 , a percent of staff column  194  and a number of staff column  196  that indicates the percentages and numbers of each of the different types of employees. Thus, for the staff label in column  192 , column  194  indicates that 75% of the employees are staff. Column  196  indicates that the number of staff is  375 . Similarly, column  194  indicates that 10% of the employees are support staff and column  196  indicates that the number of support staff is  50 . Column  198  is an average hourly wage column and includes information obtained via the public human resource database  558  as shown in  FIG. 1 . Here, the average hourly wages for Fresno, Calif. (see again  FIG. 10 ) are shown for each of a staff employee, a support staff employee, a manager and senior management. Serve  552  automatically determines the total annual wage cost given the number of employees, types of employees and the average hourly wages for the location of the facility selected and provides the total cost at  206 . The default turnover rate from database  562  in  FIG. 2  is provided at  204  and a turnover cost estimate is provided at  210 . An annual base of employee cost including the wage cost and the turnover cost is provided at  208 . Here, a user can change the percentages in column  194  or the average hourly wage rates in column  198  and/or the turnover rate at  204  to customize the estimates. 
         [0094]    When default values are altered, the changes to the default values can have a rippling affect throughout other defaults and in general can affect the building and labor summary results. To this end, referring again to  FIGS. 3 and 11 , where the percentage of staff in field  201  corresponding to senior management is changed from 5% to 25% so that there are 125 senior managers instead of 25, an additional 100 senior manager offices have to be constructed which totally affects other building characteristics and the ripple affect occurs. 
         [0095]    Referring again to  FIG. 11 , after forward arrow icon  120  or “Building” icon  64  is selected, screen shot  218  in  FIG. 12  is provided. In  FIG. 12 , the default building is indicated by a dot provided in a binary button spatially associated with an image of the default building shape. In  FIG. 12 , the dot appears in button  220  associated with the default rectangular shape  222 . To change the default shape, a user simply clicks on one of the binary buttons corresponding to one of the other building shapes such as button  224  to select a gull wing building shape as illustrated at  226 . After building shape has been selected or accepted, a user selects forward arrow icon  120  and screen shot  250  in  FIG. 13  is provided. 
         [0096]    As in  FIG. 12 , images showing building entries are provided along with binary mouse selectable buttons where a default button initially includes a dot as shown at  252 . Other entries such as the integrated porch entry shown at  258  can be selected by clicking on the associated buttons (e.g.,  256 ). After an entry has been selected or accepted, a user selects forward arrow icon  120  which causes screen shot  270  in  FIG. 14  to be shown. 
         [0097]    In  FIG. 14 , roof types are selectable by selecting binary buttons. Exemplary buttons  272  and  276  correspond to images of buildings having different types of roofs  274  and  278 , respectively. After a roof type has been selected or accepted, a user selects forward arrow icon  120  and the system provides screen shot  290  as shown in  FIG. 15 . 
         [0098]    Screen shot  290  allows a user to either view default exterior building skins or to view and edit those default values by changing default percentages. To this end, default exterior skin percentages shown include 45%, 15%, 25% and 15% of concrete, panelized metal, windows and curtain wall, respectively. In addition to the percentages, images showing the different types of skins are provided including a concrete image  294  and a windows image  298 . To change the default exterior skin percentages, the user changes the value in a field corresponding to the specific skin type. Exemplary fields include a concrete percentage field  292  and a windows percentage field  236 . After skin selections have been made or accepted, a user selects forward arrow icon  120  and screen shot  310  shown in  FIG. 16  is provided where additional building default characteristics and some calculated values are shown. 
         [0099]    In  FIG. 16 , one calculated value includes the square feet of an anticipated facility given the previously specified information which is shown at  312 . Here, the square feet of the building is determined by adding the square feet of workspaces, conference spaces, circulating spaces, stairwells, restrooms and other spaces required in specific building types. A sliding button  316  is provided for changing the number of levels in the building at  314 . A sliding button is provided to adjust the parking ratio at  318 . Parking levels can be changed at  320 . At  322 , a balance for setbacks in green area square feet  330  is provided which, in the present example, cannot be changed because it is typically mandated by local municipalities. An average cost per acre  324  is provided in field  326  which is based on public information. The cost per acre in field  326  can be altered by a user to accommodate special circumstances. Calculated required acreage is provided at  328  and a total cost of land is provided at  332 . After a user is done using the tools associated with screen shot  310 , forward arrow icon  120  can be selected after which screen shot  350  in  FIG. 17  is provided. 
         [0100]    In  FIG. 17 , screen shot  350  includes core building choices in column  352 , quality columns including a good column  354 , a better column  356 , and a best column  358 , a quantity column  360 , a square foot column  362  and a total square foot column  364 . In column  352 , core choices for a building include restrooms, stairs, elevators, HVAC equipment, etc. Each of the good, better and best columns  354 ,  356  and  358  includes a column of binary mouse selectable buttons that can be selected to indicate whether or not one of the choices in column  352  associated therewith should be good, better or best quality. The quantity column  360  includes a number that indicates the quantity of each choice in column  352 . For example, column  360  indicates that five restrooms are required (see  366 ) and that six HVAC system or units are required (see  370 ). The square foot column specifies square feet for each one of the choices in column  352 . The total square foot column  364  includes an entry indicating the total square feet required for the quantity of specific choices specified in columns  360  and  352 . 
         [0101]    Referring still to  FIG. 17 , here, it should be appreciated that some of the quantities in column  360  may be altered while others cannot be changed. This is because municipalities routinely require specific numbers of the choices in column  352  and those numbers typically represent more than required resources so that it would be a very rare circumstance where a system user would want to increase the number of specific choices. For instance, five restrooms as indicated at  366  is generally a large number of restrooms given other default building characteristics and, to minimize costs of the building, most users would not opt to increase the number of restrooms. While some quantities in column  360  cannot be changed, other quantities can such as, for instance, the number of communicating stairs in field  368 , can be altered. Many other building related screen shots may be provided for examining default building characteristics and customizing those characteristics. After a user is satisfied with the information provided by screen shot  350  and other building characteristic screen shots, the user can select forward icon  120  or “workspace” icon  66  to access screen shot  380  shown in  FIG. 18 . 
         [0102]    In  FIG. 18 , screen shot  380  provides default information related to workspaces. Here, an additional toolbar  369  is provided that includes mouse selectable icons labeled “individual space”  382 , “team space”  384 , “technology”  386 , “communication/branding”  388 , “amenities”  390  and “other”  394 . A user can select any one of icons  382 ,  384 ,  386 ,  388 ,  390  or  394  to jump to either default or currently specified workspace characteristics and features related to the selected icons. Thus, for instance, individual space icon  382  can be selected to examine current characteristic settings for workspaces as shown in screen shot  380 . Screen shot  380  includes a workspace column  381 , a level of quality column  396 , a quantity column  398 , a square foot column  400  and a total square foot column  402 . In the illustrated example, it is assumed that a user has already modified the quantities in column  398  so that default values no longer apply. Thus, while the example above associated with  FIGS. 2 and 3  requires 25 private small offices, column  398  in  FIG. 18  indicates that only four private small offices are required. Other user specified customizations are reflected in screen shot  380 . Although not shown, various tools like those described with respect to  FIG. 17  will be provided to allow a user to alter default or current individual space settings. In at least some embodiments, information related to any one of the work place types such as the six by seven space at  410  in  FIG. 18  may be accessed by simply clicking on the workspace label  410 . To this end, referring to  FIG. 19 , when the label  410  in  FIG. 18  is selected, screen shot  420  may be provided to allow a user to see an image  422  of an exemplary default workspace type, to change quantity via a field box  424 , to select workspace quality via binary mouse selectable buttons  426 ,  428  and  430  and to save  432  or cancel  434  modifications. 
         [0103]    Although only a few screen shots are shown for viewing and altering default values, it should be appreciated that in complex systems several hundred different screens may be provided for altering and viewing default values. 
         [0104]    Referring now to  FIG. 20 , as indicated above, at any point during the process of examining default or currently set building characteristics or altering default or currently set characteristics, a user can select summary icon  175  causing server  552  to generate a summary page as shown in screen shot  450 . The summary page  450  includes five different sections including a short executive summary at  452 , location based information at  454 , employee information at  456 , building information at  458  and workspace information at  460 . 
         [0105]    After viewing a summary page, a user can select backward arrow icon  119  to move back through the default and customized data. In addition, once a user moves back to a screenshot that includes secondary tool bar  54  (see again  FIG. 19 ), the user can select any one of the bar  54  icons  58 ,  60 ,  62 ,  64 , or  66  to access specified information related thereto and to alter that information when necessary. Different summaries  450  can be printed out or saved in a database by selecting print and save icons  461  and  463 , respectively (see again  FIG. 20 ). 
         [0106]    In at least some embodiments, it is contemplated that programs  557  would allow a user to specify business driver ranking and building/facility characteristics and, as part of the summary screenshot, may provide feedback to the user indicating the specified characteristics that are inconsistent with the driver rankings. 
         [0107]    For instance, where first time cost to build and furnish a facility is mission critical and all other drivers are not important, if a system user specifies an extremely complex and expensive building, the summary screenshot  450  may indicate ways to reduce building costs in some fashion to bring the building more into alignment with the way the drivers were ranked. 
         [0108]    Referring now to  FIG. 21 , one way to indicate facility characteristics that are not consistent with how drivers were ranked may be to highlight or otherwise visually distinguish various characteristics on the summary page  450 . In the illustrated example boxes  722 ,  720 ,  724 ,  726  and  728  are shown around different summary characteristics to signify highlighting. Here, in at least some embodiments, it is contemplated that a user may place a mouse controllable pointing icon over any one of the highlight boxes causing a pop-up window to appear in which suggested changes to the information in the selected box are provided. For instance, where a pointing icon hovers over box  726 , a pop-up window could suggest that branding space be increased to 7% of the total space where a compelling customer experience is mission critical. In addition to including suggestions, the pop-up windows could include a “Accept” icon which, when selected, causes the server  552  to replace the information in the box  726  with the suggested value. 
         [0109]    Although not illustrated, in other cases suggested facility characteristics that are consistent with business driver ranks could be presented along with the default and customized characteristics on the summary screenshot  450 . In some cases suggested characteristics may be able to be toggled on and off via a mouse selectable icon (not illustrated). 
         [0110]    In still other cases where a specified facility is inconsistent with the way in which business drivers were bucketed by a user, server  552  may identify different levels of inconsistency and may only specify the most egregious inconsistencies for a user&#39;s consideration. For instance, where first cost to build is mission critical and all other drivers are not important but a user specifies a 100% window exterior skin, while other user specified characteristics may be inconsistent with a low first time cost to build, server  552  may be programmed to only suggest that the skin type be changed to a less expensive material. 
         [0111]    Referring now to  FIG. 5 , a subprocess  690  that may be substituted for a portion of the process  640  of  FIG. 4  is shown where modifications to user specified facility characteristics are identified and presented to a user to bring a facility more in line with business drivers. Referring also to  FIGS. 1 and 4 , after block  656 , server control may pass to block  692  where a user specifies building preferences and anticipated employee types and quantities. At block  694 , server  552  uses the user specified labor and location information to generate labor estimates associated with the user input. 
         [0112]    Referring still to  FIGS. 1 and 5 , at block  698 , a summary akin to summary  450  in  FIG. 21  is provided that is based on the user specified information. At block  700 , server  552  compares presented data and estimates with default data and estimates to identify inconsistencies and at block  702 , server  552  indicates inconsistencies and provides suggestions to the user in some fashion. 
         [0113]    In addition to the features described above, in at least some embodiments, new real estate and real estate to labor metrics are contemplated that it is believed will be particularly useful to real estate decision makers. To this end, it is known that specific facility designs can result in energy savings to run the facility. For instance, by using a concrete skin as opposed to sheet metal, heating costs may be able to be reduced by 5% for a facility. As another example, by using an open office plan where windows allow natural light to shine into 95% of all individual workspaces, lighting costs may be able to be reduced by 15%. 
         [0114]    Similarly, it is generally known that it is far more expensive to reconfigure drywall type office delineating structure than to reconfigure partition wall systems. It is also known that most all facilities are “churned” over time. Here, the term “churn” means inevitable relocating of personnel and equipment and related structural changes to a facility to accommodate the relocation. A typical churn rate may be 20% meaning that 20% of facility space has to be reconfigured on an annual basis. While partition wall type space delineating systems may be more expensive than drywall structures, the cost associated with churn may be substantially less in both materials and labor in the case of a partition wall system. 
         [0115]    Here, one interesting real estate related metric is referred to herein as “net effective rent” (NER) which means the triple net lease rate per square foot minus the other costs that would be incurred if a facility had some other baseline type characteristics. For instance, in some cases the cost of churn may be reduced by 0.94 cents per square foot per year and providing additional windows in a facility may reduce lighting cost by 0.38 cents per square foot per year. In this case, if the triple net lease rate is $14.50 per square foot per year, the NER would be $13.18 (i.e., $14.50−0.94−0.38=$13.18). 
         [0116]    To facilitate the NER calculation, referring again to  FIG. 1 , database  555  also includes an NER database  700  that stores data related to benchmark churn and energy savings statistics related to different facility characteristics. Although not shown in detail, it is contemplated that database  700  would include statistics related to percentage of exterior building skin formed by windows and related lighting cost savings, percentage of skin formed by concrete and heating cost savings, average churn cost savings when different building techniques are employed, etc. In addition, to support the NER calculation, in at least some embodiments, a third public database  702  may be accessible by server  552  to access geographically associated energy cost information. 
         [0117]    In addition to the NER metric, other potentially interesting metrics include a labor-to-NER ratio (e.g., employees/NER), a seat-to-NER ratio, a turnover-to-NER ratio and an amenity cost/seat ratio. Each of these metrics can be determined by server  552  and provided via display  547 . 
         [0118]    One other feature that is contemplated is one where benchmark retention costs are tied loosely to facility characteristics so that a real estate decision maker can gain insight into how facility changes can affect labor and overall operating costs. For instance, it is generally known that people like to work in workspaces that are at least in part illuminated via natural light. Thus, it is entirely possible and seems likely that retention rate can be increased by increasing the amount of natural light in a facility. A facility characteristics/retention database is contemplated that will include real life statistical information to show the relationship between natural light in a workspace and retention of employees. For instance, the database may indicate that where natural light in a facility is increased by 20% (e.g., exterior skin includes more windows), retention rates goes up 2%. In other cases the facility characteristics/retention database may not be based on actual statistics and instead may reflect knowledgeable perceptions such as an assumption that an increase in natural light of 20% will increase retention rate by at least 1% where the 1% value is at the low end of an expected range. 
         [0119]    In  FIG. 1  an exemplary facility characteristics/retention database is shown at  704 . It is contemplated that database  704  may include many other benchmark or assumed relationships between building characteristics and retention rates. Similarly, database  555  may include other facility characteristics/results databases (not shown) that relate characteristics to benchmark results or assumptions. For instance, data may be developed for medical facilities that indicates that repeat business can be increased by 15% by increasing the quality of certain facility spaces from good to better and by another 10% by increasing space quality from better to best.          have realized that patients increasingly select medical facilities as a function of the amenities provided to patients. Thus, where patient rooms in a first hospital are private, include private high end spa type rest rooms and entertainment centers as well as high end decorations (e.g., wall coverings, furniture, artwork, etc.) and in a second hospital rooms are shared, have utilitarian rest rooms and minimal other amenities, patients will routinely prefer the first hospital. In this case the inventive system can he used to show how increases in construction and furnishing costs can directly increase profits. 
         [0120]    All of the assumptions made when generating benchmark data can be used to generate other useful information for a system user and to affect the NER metric when appropriate. Thus, while increased construction and furnishing costs will increase a triple net lease cost per square foot, much if not all of the increase in triple net cost will often be offset by reduced turnover; increased work efficiency, increased profitability due to additional and more satisfied clients (e.g., patients), etc. 
         [0121]    Referring now to  FIG. 22 , an exemplary screenshot  750  is shown that can be used to see how an exemplary high end facility, when compared to a more traditional type of facility, can affect NER. Screenshot  750  and related tools may be accessible via the pop-up menu (not illustrated) associated with utilities icon  51  (see  FIG. 6 ). In  FIG. 22 , the high end facility is referred to as a “workstage” facility (see  774 ). In the illustrated example, it is assumed that facility quality and amenities only affect energy costs and the costs associated with churn. Consistent with the above comments it should be recognized that many other costs and sources of revenue (e.g., turnover rate, work efficiency, client satisfaction, full use of resources, etc.) may also be associated with facility quality and amenities and that those costs and revenue sources could be included in the NER calculation (see NER result at  770 ). 
         [0122]    As shown, exemplary screenshot  750  includes data entry tools and various output fields that report calculated costs and savings associated with the data input via the input tools. The input tools include a building size field  756 , a geographical location field  758 , a churn rate slider button and a triple net lease rate field  764 . A user can specify building size, location, anticipated churn rate and anticipated triple net lease rate via fields and button  756 ,  758 ,  762  and  764 , respectively. When a location is selected via field  758 , server  552  accesses the public energy cost database  702 , obtains an energy cost value for the specific location and provides the cost value in an energy cost field  760 . Once location specific energy cost has been determined and churn rate has been specified, server  552  generates energy savings and churn savings values per square foot and populates fields  766  and  768 , respectively. The values in fields  766  and  768  are subtracted from the triple net rate in field  764  to generate the NER metric in field  770 . 
         [0123]    Referring still to  FIG. 22 , comparison data for a traditional facility and the high end facility is provided in a table including a “traditional” column  772 , a “workstage” column  774 , a “%” savings column  780  and a “cost” savings column  782 . In the illustrated example, energy savings is divided into lighting in table row  784  and heating/cooling in row  786  while churn savings is divided into labor and material rows  790  and  792 , respectively. As values in fields  756 ,  758  and  770  and the churn rate specified by button  762  are altered, the resulting numbers output change in real time. Thus, for instance, where the location in field  758  is changed, the energy cost value in field  760  will automatically be changed which ripples through the data in fields  766  and  770  and rows  784  and  786  in the results table. Similarly, if the churn rate is altered via button  762 , data in fields  768  and  770  and in rows  790  and  792  is automatically altered. 
         [0124]    Referring yet again to  FIG. 23 , while a user can specify values/information in fields  756 ,  758 ,  762  and  764 , it should be appreciated that all of that data may simply be imported from default values generated by server  552  in the manner described above. Thus, for instance, a default building size for field  756  will result after a user has ranked business drivers (see  FIGS. 6 and 7 ) and identified building type and numbers of seats and employees (see  FIG. 8 ). Similarly, after a location has been selected (see  FIG. 10 ), the electrical cost for field  760  can be populated. 
         [0125]    One or more specific embodiments of the present invention have been described above. It should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions must be made to achieve the developers&#39; specific goals, such as compliance with system-related and business related constraints, which may vary from one implementation to another. Moreover, it should be appreciated that such a development effort might be complex and time consuming, but would nevertheless be a routine undertaking of design, fabrication, and manufacture for those of ordinary skill having the benefit of this disclosure. 
         [0126]    For instance, while databases  556 ,  558  and  702  have been described above as being public and in some cases proprietary, in some embodiments the public databases may routinely (e.g., every week) be downloaded into private databases for subsequent use. As another instance, embodiments are contemplated where business drivers are not ranked or even considered by a user and/or where facility types are not considered. 
         [0127]    Thus, the invention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention as defined by the following appended claims. For example, 
         [0128]    To apprise the public of the scope of this invention, the following claims are made: