JP2004021565A - Detection system of break-even point of building for rent - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a detection system of break-even point of a building for rent capable of visually presenting income and expenses situation of a rental building by using numerical values and charts instead of relying on experience and conventional know-how. <P>SOLUTION: The break-even point of a rental building is calculated based on an operation ratio at the break-even point. An average value P<SB>AC</SB>of the operation rates, the most important value, is calculated by the following formula; P<SB>AC</SB>=[F+Z-ä(A+C)×12+E}]/ä12×S(T<SB>T</SB>-T<SB>S</SB>)}. In the formula, F is the fixed expenditure, Z is the maintenance cost, A is the rental fee of affiliated companies, C is the car parking income, E is the other incomes from affiliated companies, S is the other incomes from companies other than the affiliated companies, T<SB>T</SB>is the average rental unit price and T<SB>S</SB>is the average expenditure unit price. <P>COPYRIGHT: (C)2004,JPO

Description

但し；Ｂ_Ｅは、算定終了日
Ｂ_Ｓは、算定開始日
である。
【００５４】
算定開始日（Ｂ_Ｓ）も算定終了日（Ｂ_Ｅ）も、本システムを用いた損益状況のシミュレーションに適用する数値であるが、これらはシミュレーション上必要となる数値であって、必ずしも何らかの意味における事実データ（日付）を用いる必要はない。算定期間（シミュレーション上のスパン）は、必要に応じて自由に可変し、さまざまな視点から営業状態をチェックする必要性があるからである。もちろん、算定開始日（Ｂ_Ｓ）も算定終了日（Ｂ_Ｅ）も固定数値を用いても構わない。例えば、本システムの導入日などである。日付の数値を固定すればシステムの操作は単純化する。算定開始日（Ｂ_Ｓ）や算定終了日（Ｂ_Ｅ）の設定はユーザの自由であるから、調整（可変）可能な状態での固定方式によって運用する機会が多いと考えられる。
【００５５】
本実施形態では、賃貸室の契約において、まず、契約解除の事前予告（通常は６ヶ月前に行う）に基づく退去情報及び数ヶ月後に入居予定の契約情報等の予約情報を賃貸契約の履歴情報（２１）として用いる。そして、算定開始日（Ｂ_Ｓ）及び算定終了日（Ｂ_Ｅ）を、シミュレーションしようとする期間に応じて適宜設定することにより実稼働率を算出する。
【００５６】
これにより、現時点から、例えば数ヶ月先の将来に亘る経営収支状況を、リアルにシミュレーションすることができ、ビルオーナーは、そのシミュレーション結果を経営情報として役立てることができる。
【００５７】
なお、本発明のシステムにおいて使用している計算式内の数値１２は、年間月数である。年間月数である１２を乗算する数値は原則として月単位の数値であり、１２を乗算していない数値は、年単位の数値または年月に無関係な独立の数値（例えば単位面積などの数値）である。
【００５８】
【実施例】
図３は、本発明に係る損益分岐点の検出システムを利用して試算（シミュレーション）を行う場合の、表示画面の一例を示すものである。この表示画面は、すでに述べた各種の数値項目（試算上必要な数値データ）を、所定の格納エリアから自動的に呼び出して利用者（ユーザ）に視覚的、具体的に表示する。
【００５９】
表示する数値データは、例えば、実賃貸面積の計算を行うための数値群７１、単位面積当たりの収入を計算するための数値群７２、固定費を計算（または調整）するための数値群７３、固定的な収入を計算するための各種の数値群７４、単位面積当たりの費用（支出）を計算するための数値群７５である。これらの数値群７１〜７５は、主として賃貸契約の履歴情報を格納してある履歴格納部２１から読み出すことが出来るが、必要に応じてその他のデータ格納部、例えば、収入データ格納部３０や、支出データ格納部４０のデータ数値を読み出す。
【００６０】
この表示画面には、試算を行う時点での稼動坪面積または／および平均稼働率を同時に表示し、或いは算定条件となる年月日を自動表示またはマニュアルによる人為的な条件設定項目として表示しても良い。
【００６１】
表示画面は少なくとも、これらの数値に基づいて損益分岐点の試算を実行処理させるためのクリックボタン表示部８１、あるいは損益分岐点の試算結果をグラフ図として表示させるためのクリックボタン表示部８２を備えることが望ましい。マウス操作によってクリックボタン表示部８１をクリックすれば、前述した手法に基づいて損益分岐点における平均稼働率或いは実稼働率の演算処理が実行され、例えば、結果数値を他の各種の参考数値データとともに切替表示する。マウス操作によってクリックボタン表示部８２をクリックすれば、損益分岐点における平均稼働率或いは実稼働率の演算処理結果を、視覚的に理解容易なグラフ図の形式を用いてモニタ画面に表示する。これらの試算結果は、ユーザの選択操作によって自由に記録保存可能としてくことが望ましい。
【００６２】
尚、損益分岐点における平均稼働率或いは実稼働率の演算処理に先だち、最終的な試算を行う前に利用者側において数値データを変更して試算を行いたい場合もあり得る。例えば、固定費を増減させて各種ケースにおける試算結果を得たいという場合である。そこで試算に先立ち、賃貸契約の履歴情報を格納してある履歴格納部２１から読み出した固定費関係の数値を、ユーザ側で任意に調整可能とし、さまざまなケースにおける試算結果を取得可能とすれば、ビル管理の経営分析における試算ヴァリエーションの自由性と利便性が格段に向上する。
【００６３】
【発明の効果】
以上説明したように、本発明に係るシステムによれば、経験やノウハウに任されがちだった賃貸ビルディングの収支状況を、事実として記録された未加工データに基づいて信頼性高く提示することが可能となる。
【図面の簡単な説明】
【図１】本発明に係る検出システムの実施形態を示すブロック図である。
【図２】賃貸ビルディングにおける損益バランスを例示するグラフ図である。
【図３】本発明に係る検出システムの具体的表示画面を示す図である。
【符号の説明】
１　支出（営業費用；ビルの維持管理に絶対に必要となる経費）
２　収入（営業収入）
１０　数値加工部
１１　収入データ加工部（賃貸平均単価算出部）
１２　支出データ加工部（平均経費単価算出部）
２０　基本データ群
２１　履歴格納部
２２　請求明細格納部
２３　支払明細格納部
３０　収入データ格納部
３１　関連収入データ格納部
３２　一般収入データ格納部
４０　支出データ格納部
４１　特別支出データ格納部
４２　固定費用格納部
５０　損益分岐点検出部
６０　経営状態の分析部
７１　実賃貸面積の計算を行うための数値群
７２　単位面積当たりの収入を計算するための数値群
７３　固定費を計算（または調整）するための数値群
７４　固定的な収入を計算するための各種の数値群
７５　単位面積当たりの費用（支出）を計算するための数値群
８１、８２　クリックボタン表示部[0001]
TECHNICAL FIELD OF THE INVENTION
The present invention relates to an apparatus for detecting a breakeven point in a rental building, and more particularly to a technique for calculating a profit and loss based on the detection of a breakeven point.
[0002]
[Prior art]
In any field, profit activities require a balance calculation based on income and expenditure, and various methods for calculating balance have been proposed in various economic activity fields.
[0003]
With respect to the system for managing the income and expenditure of a rental building, various computer programs for building management have been developed since computer terminals became popular. According to these systems, for example, for each room, a user name, a rental unit price, a rental area, a deposit history of rent and utility bills are recorded, an invoice is issued, and a slip processing (payment check, etc.) is performed. Can be.
[0004]
[Problems to be solved by the invention]
By the way, although such a conventional system for managing the income and expenditure of a rental building uses a computer device, issuance of an invoice and accounting processing are main functions, and are generated for each floor and each room. It simply kept a record of income and expenditure.
[0005]
It should be noted that simulations relating to the profitability of real estate housing (for example, simulations relating to the profitability of real estate housing (JP-A-2001-159238)) and accounting processing systems for supporting real estate agents who own a plurality of real estate properties (JP-A-11-1999) -250124) and the like, but these cannot be applied at all to the income and expenditure management of rental buildings.
[0006]
The invention according to Japanese Patent Application Laid-Open No. 2001-159238 is for performing a profit simulation of newly built real estate. Although they are common in terms of technology for checking the income and expenditure of rental real estate, they take the useful life of each part of the building into the parameters of profitable simulation and are excellent in considering the useful life of members and maintenance costs. However, the income and expenditure management of a rental building is not suitable for processing based on such one-point intensive calculation parameters. Because such parameters are generally reflected in the unit price of the room from the beginning, even if calculations are made with the service life of the members and the maintenance cost as the main parameters, results that surpass the conventional management system can be obtained. Because they cannot do it.
[0007]
The invention described in Japanese Patent Application Laid-Open No. H11-250124 is based on the premise of a plurality of real estates, for example, to prevent omission or double collection of management fees, and to accurately determine the financial relationship between the real estate owner and the user. / Appropriate. This technique is essentially the same as the function of issuing a slip or checking a payment in a conventional system.
[0008]
On the other hand, the core of economic activity that the owner (or management organization) who owns a rental building wants to know most is the present or future (especially in the future of 6 to 12 months) in the owned (or managed) rental building. ), To realize (understand) the real income and expenditure situation.
[0009]
Understanding the income and expenditure of a rental building is fundamentally different from the handling of general products with market circulation. For example, fluctuations in line prices and fluctuations in economic conditions (social phenomena) tend to be influenced by factors that cannot be compensated for by self-help efforts alone. This is because of the inherent difficulty.
[0010]
FIG. 2 illustrates a general concept (principle) for grasping the balance of a rental building. This will be described briefly. The expenditure indicated by reference numeral 1 (operating expenses; expenses absolutely necessary for the maintenance and management of the building) has little fluctuation due to the occupancy rate. As the occupancy rate rises, it rises slightly. On the other hand, the income (operating income) indicated by reference numeral 2 increases according to the occupancy rate and exceeds expenditure 1 at one point. This intersection is the breakeven point. This relationship is natural, and owners and management organizations that are sensitive to understanding the income and expenditure of rental buildings are fully aware of this principle as basic knowledge.
[0011]
However, heretofore, such a relationship between expenditure / income has only been vaguely known as an empirical rule or personal know-how by synthesizing numerical values in books. Even if there are sufficient rules of thumb and know-how, it is extremely difficult to grasp (or forecast) the current or near-term financial situation (numerical value) as a realistic numerical value because there are so many items to consider. is there.
[0012]
Therefore, an object of the present invention is to make it possible to easily and concretely present the income and expenditure status of a rental building, which is often left to experience and know-how, by using numerical values having objectivity. In this case, the numerical value used for the detection trial calculation uses the item data in the conventional building management system used for the slip creation and accounting management as much as possible, so as to utilize the data assets.
[0013]
[Means for Solving the Problems]
In order to achieve the object, a break-even point detection system in a rental building according to the present invention includes:
Based on the information in the basic data storage unit that stores the history information of the rental contract and the information on income and expenditure, the average rental unit price T per month_TAnd monthly average cost unit T_SAfter asking for
This average rental unit price T_TAnd average cost unit price T_SAnd the average value P of the occupancy rate at the breakeven point using unprocessed data on income and expenditure stored as individual data._ACTo
P_AC= [F + Z-{(A + C) × 12 + E}] / {12 × S (T_T-T_S)｝
However, $ F is the fixed cost per year
Z is annual repair cost
A is the monthly rent of affiliated company
C is monthly parking revenue
E is yearly other income
S is the actual leased area
Detected as
[0014]
In addition, in order to enable more specific calculation of the balance, the actual operating rate K at the time of detection is calculated._TTo
K_T= {(Sn × Kn)} / S_T
However, Sn is the actual area of the leased room (the leased area of each operating room).
Kn is the actual occupancy rate of n rental rooms (the occupancy rate of individual operating rooms)
S_TIs the total actual leased area ($ Sn)
In some cases.
[0015]
[Action]
The break-even point detection system according to the present invention utilizes, as a data resource, a numerical value that has been individually converted into data for each rental room or floor by the individual owner or management company of the rental building, and uses the business state of the building, that is, the break-even point. This makes it possible to easily detect (estimate) various management decision data centered on points.
[0016]
As already mentioned, the management decision (understanding and recognition of the management status) of a rental building is mainly based on empirical rules, so-called numerical analysis of the mainstream, and it has been difficult to reliably check the breakeven. The reason for this is that the occupancy rate and rental room rates of rental buildings are unique due to various factors including social phenomena, and the sales volume / profit ratio is macro-like for products with market distribution. This is because, unlike a simple calculation method, a more detailed micro analysis method was considered necessary.
[0017]
The profit and loss analysis of rental buildings is based on the sudden entry and exit based on the free will of the rental contractor, and the entrance and exit due to social conditions, so if you do not fully acquire specialized management know-how on rental buildings, It is considered difficult to perform a trial calculation process based on individual data recorded in various formats.
[0018]
However, in the profit and loss analysis of a rental building, it is possible to obtain a highly reliable analysis value of the occupancy rate by carefully checking the occupancy rate (hereinafter simply referred to as occupancy rate) at the breakeven point of the building.
[0019]
In the conventional system, general judgment items regarding income and expenditure were used as parameters. However, it is extremely difficult to perform a concrete and clear analysis check required for building management with such a conventional estimation calculation method. This is because long-term / short-term fluctuation factors related to rental rooms are not taken into account at all.
[0020]
On the other hand, the present invention is based on raw data on income and expenditure as a usual way of economic analysis, but is characterized by using history information of lease contracts.
[0021]
According to claim 1, based on the rental contract history information, the monthly average rental unit price T_TAnd monthly average cost unit T_SAnd average rental unit price T_TAnd average cost unit price T_SAnd the raw data on income and expenditure to obtain the final detection result. The difference from the conventional estimation system is that the monthly average rental unit price T_TAnd monthly average cost unit T_SAnd obtain the operation rate based on this.
[0022]
The difficulty of profit and loss analysis in a rental building is the fluctuation (instability) of tenant entry / exit caused by various factors. Well reflected as a characteristic. The raw numerical data can be processed as objective data including all causes, even if the causes and factors of the fluctuations vary directly or indirectly, and this is the monthly average rental unit price T._TAnd monthly average cost unit T_S, Which is the basis of the technology for detecting the occupancy rate at the breakeven point.
[0023]
The detection of the occupancy rate at the break-even point includes detection of an average occupancy rate on a yearly or monthly basis and detection of an actual occupancy rate performed by specifying a specific date to be detected. Claim 1 relates to the average operation rate, and claim 2 relates to the actual operation rate.
[0024]
Also in the detection of the actual occupancy rate according to the second aspect, the history information of the rental contract including the factor of the fluctuation of the balance of the rental building as objective data is used.
[0025]
BEST MODE FOR CARRYING OUT THE INVENTION
FIG. 1 shows a specific configuration example of a breakeven point detection system according to the present invention. Explaining the entire structure, a portion indicated by reference numeral 10 is a numerical processing section for obtaining a trial calculation value characteristic of the present invention based on various raw data stored in the computer terminal device. The numerical processing unit 10 calculates a monthly average rental unit price T_TData processing unit (rental average unit price calculation unit) 11 for obtaining a monthly average unit cost T_SAnd an expenditure data processing unit (average cost unit price calculation unit) 12 for obtaining
[0026]
20 is the monthly average rental unit price T_TAnd monthly average cost unit T_SThis is a basic data group that stores the raw data for obtaining. The basic data group 20 stores at least a history storage unit 21 that stores history information of rental contracts, a billing statement storage unit 22 that stores billing statement numerical values for each tenant, and a payment statement numerical value generated in building management. And a payment details storage unit 23.
[0027]
The storage location of these data is arbitrary within the basic data group 20. It is not always necessary to store various raw data (numerical values) separately from the beginning (separate items). For example, the data stored in the billing statement storage unit 22 may be stored in the history storage unit 21. This is because it is generally preferable to treat the billing numerical value for the tenant as history information of the rental contract. In other words, the raw data in the history storage unit 21, the billing statement storage unit 22, and the payment statement storage unit 23 only need to be in a selectable state based on the program that drives the numerical value processing unit 10, and Apparent item names and storage locations are not limited.
[0028]
The rental contract history information includes at least data of a unit area, a date of entering a room, a date of leaving a room, and a monthly billing amount for each rental room. The lease contract history information may be recorded in addition to, for example, document data of the lease contract, the specific type of business of the lease contractor, the name and address of the guarantor, and specific information on business days and business hours. However, when conducting a trial analysis on management and management of a building, it is only necessary to provide data on the unit area, the date of entry, the date of exit, and the monthly billing amount for each rental room. When the data of the monthly billing amount completely overlaps with the data to be stored in the billing statement storage unit 22, there is no need to provide the billing statement storage unit 22.
[0029]
It should be noted that the data to be stored in the billing statement storage unit 22 includes billing items that are individually generated for the lease contractor on a monthly basis, such as a rent, a common service fee, a heating / cooling fee, a utility fee, and a cleaning fee. For example, there are actual bills such as billboard usage fees and fluorescent lamp replacement fees. These billing data may be stored independently in the billing statement storage unit 22, or may be stored as monthly billing items in the rental contract history information. Regardless of the storage area, there is no substantial difference since each numerical data can be linked to a calculation formula in the total calculation of the billed amount per month or the trial calculation of the break-even point. From the viewpoint of ease of data storage, it is preferable to store numerical data from the beginning in the separately provided billing statement storage unit 22. However, the billing numerical value stored in the history information of the rental contract may be diverted as it is in the link format. Therefore, there is no particular advantage or disadvantage in the storage location of the billing statement data.
[0030]
Reference numeral 30 denotes an income data storage unit that stores raw data relating to income. This is composed of, for example, a related income data storage unit 31 for storing in-house related billing statement information, a general income data storage unit 32 for storing other income data, and the billing statement storage unit 22. The company-related billing statement information is an income figure that can be regarded as fixed income unless there is special circumstances, such as rental income for a subsidiary (or parent company). The other income data is variable income that cannot be said to be fixed income, such as parking lot income, miscellaneous income, and interest income.
[0031]
Reference numeral 40 denotes an expenditure data storage unit that stores raw data related to expenditure. This includes, for example, a special expenditure data storage unit 41 that stores special expenditure data such as repair expenses required for building maintenance, and a fixed expenditure storage that stores fixed expenses that are continuously generated regardless of a change (movement) of a tenant. And a payment details storage unit 23. Like the basic data group 20, the storage location of each raw data is not limited.
[0032]
The fixed expenses that are continuously generated regardless of the change (movement) of the tenant are, for example, depreciation expenses, cleaning fees for public halls such as corridors and toilets, elevator maintenance fees, insurance fees, taxes and taxes. , Executive compensation, salary, rent, etc. of the building management company itself. The fixed cost itself is an item (numerical data) that can be arbitrarily set by each management entity.
[0033]
50 is a breakeven point detection unit. The break-even point detection unit 50 calculates the numerical value obtained by the numerical value processing unit 10, the raw numerical data stored in the income data storage unit 30, and the raw numerical data stored in the expenditure data storage unit 40. Is used to calculate the occupancy rate at the breakeven point. Reference numeral 60 denotes a business condition analysis unit that performs various numerical processings on income and expenditure based on the trial calculation of the average occupancy rate in the breakeven point detection unit 50.
[0034]
Hereinafter, the operation of each unit will be described together with the processing principle.
The simulation of the profit and loss balance in the rental building is basically based on the relationship between expenditure 1 and income 2 as shown in FIG. The intersection of Expenditure 1 and Income 2 is the break-even point. In this case, the relationship of Income = Expense is established.
[0035]
Looking specifically at the income and expenditure in the rental building, the annual income Q is calculated as the actual leased area (S) and the average rental unit price (T_T), Average operation rate (P_AC), Rent of affiliated company (A), parking lot revenue (C), and other income (income derived from affiliated company and other income not derived from affiliated company) (E)
Q = S × T_T× P_AC× 12 + A × 12 + C × 12 + E
Can be represented as Numerical value 12 used here means the number of months in the year. Therefore, the numerical value multiplied by 12 is a numerical value relating to monthly (monthly) income in principle.
[0036]
On the other hand, the expenditure W for one year is the fixed expenses (F), the repair expenses (Z), the actual leased area (S), and the average unit cost (T_S), Average operation rate (P_AC), In relation to
W = F + Z + S × T_S× P_AC× 12
Can be represented as Numerical value 12 used here also means the number of months in the year. Therefore, the value multiplied by 12 is a value related to monthly (monthly) expenditure in principle.
[0037]
The numerical values used here are the numerical value obtained by the numerical processing unit 10, the raw numerical data stored in the income data storage unit 30, and the raw numerical data stored in the expenditure data storage unit 40. Only numerical values to be obtained by the numerical processing unit 10 require special processing.
[0038]
As already described, the numerical value obtained by the numerical data processing unit 10 is the monthly average rental unit price T acquired by the income data processing unit 11._TAnd the average monthly unit cost T acquired by the expenditure data processing unit 12_SIt is. These numerical values are important values directly related to the processing in the breakeven point detection unit 50.
[0039]
In the present invention, the value of the area obtained by subtracting the area used by the company and the leased area of the related company from the total unit area is used as the denominator, and the sum of the amount charged by the company and the amount charged by the related company is subtracted from the total billed amount. With the average value per month as the numerator, the average rental unit price T by dividing_TIs calculated. Each numerical value used here is a raw numerical value stored in the basic data group 20.
[0040]
On the other hand, the average cost unit T_SIs calculated by dividing the total expenditure per month by using the figure of the area obtained by subtracting the area used by the company and the leased area of the related company from the total unit area as the denominator. Rental average unit price T_TIn the same manner as in the calculation of, each numerical value to be used is a raw numerical value stored in the basic data group 20.
[0041]
Next, at the breakeven point, income (Q) = expenditure (W),
S × T_T× P_AC× 12 + A × 12 + C × 12 + E = F + Z + S × T_S× P_AC× 12
It is. To sort this out,
S × P_AC× 12 × (T_T-T_S) = F + Z− (A + C) × 12−E
It is. This allows
P_AC= [F + Z-{(A + C) × 12 + E}] / {12 × S (T_T-T_S)｝, And the break-even point detection unit 50 calculates the average operation rate (P_ACGet).
[0042]
Average occupancy rate at breakeven point (P_AC) Is a numerical value that should be grasped most accurately as a single numerical value when performing various simulations in a rental building, and the average occupancy rate (P_AC) Enables free simulation processing in building management.
[0043]
For example, in terms of break-even point detection, even if the operating cost (expenditure 1) may slightly move up and down in the Y-axis direction due to a difference in the calculation method, the line (2) indicating the operating income is determined substantially uniformly. Therefore, the position of the breakeven point hardly depends on the X-axis direction, and a substantially accurate simulation result can be obtained.
[0044]
Average occupancy rate in rental buildings (P_AC), The owner and manager of the building can perform various numerical processings in business analysis. For example, if the ordinary profit in the current year is R,
P_AC= [F + Z + R-{(A + C) × 12 + E}] / {12 × S (T_T-T_S)｝
It is. In this case, since R (target sales) is added to the numerator factor, the average occupancy rate P_ACIs constant, it is understood that the fixed cost (F) and the repair cost (Z) should be mainly suppressed in order to keep the molecular components constant, and the specific numerical values can be easily calculated.
[0045]
Average occupancy rate (P_ACThe specific numerical data for obtaining (1) is a numerical value recorded in various existing management systems for rental buildings. Therefore, there are not many data item types to be recorded for the first time by introducing this system.
[0046]
Numerical data for computer processing required to operate this system, which is unlikely to be recorded in the conventional management system, is the rental contract history information recorded with a clear intention (especially numerical data ). In addition, the rent (A), parking lot revenue (C), and other revenues of affiliated companies (income from affiliated companies and other income not attributed to affiliated companies) (E) are also clearly expressed in the conventional management system. Is not recorded accurately.
[0047]
However, in most cases, these numerical data are simply not journalized so as to effectively drive the present system, and it is highly possible that the data itself is included as other items. Therefore, at the beginning of the introduction of the present system, numerical data on past income / expenditure may be re-translated so that the operation of the present system becomes possible, thereby enabling the system to operate smoothly from the beginning. Become.
[0048]
By the way, the average operating rate (P_ACThe break-even point detection and management analysis in a rental building based on the above) are excellent methods for grasping the situation in a unit period (for example, 12 months). However, like other economic fields, the profit and loss balance in a rental building It fluctuates every day. Therefore, strictly speaking, the average operation rate (P_AC) Does not mean that the current accurate balance is accurately simulated. However, due to social / economic stability or geographical advantage, the average occupancy rate (P_AC) And the actual operation rate are not rarely changed. In such a case, the average operation rate (P_AC), The break-even point detection based on the actual occupancy rate and the results of business analysis, which will be described later, are almost the same.
[0049]
Average occupancy rate at breakeven point (P_AC) Is a value indicating the overall performance of the past operation rate in an arbitrary specific period. On the other hand, the actual occupancy rate (K) at the breakeven point is the actual operation performance of a specific room or the whole building in the past several months. Average occupancy rate (P_AC) Is a past average result, the actual operation rate (K) is a numerical value that faithfully reflects a large change. Both figures are important in business analysis.
[0050]
The actual operation rate (K) is the actual operation rate (K_T) And the actual operating rate (Kn) of a specific room. Both are important figures, but from the viewpoint of business analysis, the actual operating rate (K_T) Is the more important number.
[0051]
In the present invention, the overall actual operation rate K_TTo
K_T= {(Sn × Kn)} / S_T
However, Sn is the actual area of the leased room (the leased area of each operating room).
Kn is the actual occupancy rate of n rental rooms (the occupancy rate of individual operating rooms)
S_TIs the total actual leased area ($ Sn)
Detect based on % ({Sn × Kn)} / S_T× 100.
[0052]
Both the n-rent room actual area (Sn) and the n-rent room actual occupancy rate (Kn) can be obtained from individual data of the rental room in the rental building. The actual area of the rental room (Sn) is constant in the operating rental room, and this numerical value can be easily obtained from the individual data of the rental room. On the other hand, the rental room actual occupancy rate (Kn) is based on the occupancy start date (E_S) And move-in end date (departure date; E_E) Is used as a factor.
[0053]
That is,

However; B_EIs the calculation end date
B_SIs the calculation start date
It is.
[0054]
Calculation start date (B_S) Is also the calculation end date (B_E) Are also numerical values applied to the simulation of the profit and loss situation using the present system, but these are numerical values necessary for the simulation, and it is not always necessary to use fact data (date) in some sense. This is because it is necessary to freely change the calculation period (span in the simulation) as needed and check the business condition from various viewpoints. Of course, the calculation start date (B_S) Is also the calculation end date (B_E) May use a fixed numerical value. For example, the date of introduction of the system. Fixing the date number simplifies the operation of the system. Calculation start date (B_S) And calculation end date (B_ESince the setting of ()) is freely performed by the user, it is considered that there are many opportunities to operate by a fixed method in a state where adjustment (variable) is possible.
[0055]
In this embodiment, in the contract of the rental room, first, the departure information based on the advance notice of the contract cancellation (usually performed six months before) and the reservation information such as the contract information scheduled to move in several months later, the rental contract history information Used as (21). Then, the calculation start date (B_S) And calculation end date (B_E) Is set as appropriate according to the period to be simulated to calculate the actual operation rate.
[0056]
Thereby, for example, the management balance over the future several months ahead can be simulated realistically, and the building owner can use the simulation result as management information.
[0057]
The numerical value 12 in the calculation formula used in the system of the present invention is the number of months per year. Numerical values multiplied by 12 which is the number of months in a year are, in principle, numerical values in units of months. Numerical values not multiplied by 12 are numerical values in units of years or independent numerical values unrelated to years and months (for example, numerical values such as unit area). It is.
[0058]
【Example】
FIG. 3 shows an example of a display screen when a trial calculation (simulation) is performed using the breakeven point detection system according to the present invention. On this display screen, various numerical items (numerical data necessary for trial calculation) described above are automatically called out from a predetermined storage area and visually and specifically displayed to a user (user).
[0059]
Numerical data to be displayed include, for example, a numerical value group 71 for calculating the actual leased area, a numerical value group 72 for calculating the income per unit area, a numerical value group 73 for calculating (or adjusting) the fixed cost, A numerical value group 74 for calculating fixed income and a numerical value group 75 for calculating cost (expenditure) per unit area. These numerical value groups 71 to 75 can be read from the history storage unit 21 mainly storing the history information of the rental contract, but other data storage units, for example, the income data storage unit 30, The data value of the expenditure data storage unit 40 is read.
[0060]
On this display screen, the operating area and / or the average occupancy rate at the time of performing the trial calculation is simultaneously displayed, or the date as the calculation condition is displayed automatically or manually as an artificial condition setting item. Is also good.
[0061]
The display screen includes at least a click button display unit 81 for executing a breakeven point trial calculation based on these numerical values or a click button display unit 82 for displaying the breakeven point trial calculation result as a graph. It is desirable. When the click button display section 81 is clicked by a mouse operation, the arithmetic processing of the average occupancy rate or the actual occupancy rate at the breakeven point is executed based on the above-described method. Switching display. When the click button display section 82 is clicked by a mouse operation, the calculation processing result of the average operating rate or the actual operating rate at the breakeven point is displayed on the monitor screen in a graph diagram format that is easily understood visually. It is desirable that these calculation results can be freely recorded and saved by a user's selection operation.
[0062]
It should be noted that, prior to the calculation of the average operating rate or the actual operating rate at the break-even point, the user may wish to change the numerical data and perform a trial calculation before performing the final trial calculation. For example, there is a case where the user wants to increase or decrease the fixed cost and obtain a trial calculation result in various cases. Therefore, prior to the trial calculation, if the fixed cost-related numerical value read out from the history storage unit 21 storing the history information of the rental contract can be arbitrarily adjusted on the user side, and the trial calculation results in various cases can be obtained. In this way, the flexibility and convenience of trial calculation in building management analysis will be greatly improved.
[0063]
【The invention's effect】
As described above, according to the system according to the present invention, it is possible to reliably present the income and expenditure status of a rental building that was liable to experience and know-how based on raw data recorded as facts. It becomes.
[Brief description of the drawings]
FIG. 1 is a block diagram showing an embodiment of a detection system according to the present invention.
FIG. 2 is a graph illustrating a profit / loss balance in a rental building.
FIG. 3 is a view showing a specific display screen of the detection system according to the present invention.
[Explanation of symbols]
1) Expenditures (operating expenses; expenses absolutely required for building maintenance)
2. Revenue (operating revenue)
10 Numerical processing section
11 $ Revenue Data Processing Department (Rental Average Unit Price Calculation Department)
12 Expense data processing unit (Average cost unit price calculation unit)
20 Basic data group
21 History storage unit
22 @ Billing statement storage
23 Payment details storage
30 income data storage
31 Related revenue data storage
32 General revenue data storage
40 Expense data storage
41 Special expenditure data storage
42 fixed cost storage
50 breakeven point detector
60 Analysis of business condition
71 A numerical group for calculating the actual leased area
72 Numerical group for calculating income per unit area
73 $ A group of numbers to calculate (or adjust) fixed costs
74 Various numerical groups for calculating fixed income
75 Numerical group for calculating cost (expenditure) per unit area
81, 82 click button display

Claims (2)

A system for detecting a breakeven point of a rental building based on an occupancy rate at the breakeven point,
Equipped with a basic data storage unit that stores history information of rental contracts and information on income and expenditure,
The rental contract history information, at least for each rental room, unit area, date of entry, date of exit, data of monthly billing amount,
On the basis of the information related to the history information and income of the rental agreement, and rental average unit price calculation unit for obtaining the lease average unit price _T T of the month,
Based on the information on spending history information lease, and an average cost bid calculation unit for obtaining an average cost bid T _S monthly,
The rental average unit price calculation unit,
The denominator is the figure of the area obtained by subtracting the area used by the company and the leased area of the related company from the total unit area. With the function of calculating by division with the value as the numerator,
The average cost unit calculation unit,
Equipped with a function to calculate the actual leased area by subtracting the area used by the company and the leased area of the related company from the total unit area as the denominator and the total expenditure per month as the numerator,
Such average and cost bid T _S and the average expense unit price T _S thus obtained, on the basis of the income and information about expenditure,
The average value P _AC of capacity utilization in the break-even point,
_{P AC = [F + Z -} {(A + C) × 12 + E}] / {12 × S (T T -T S)}
Where: F is fixed cost per year Z is repair cost per year A is rent of affiliated company per month C is monthly parking revenue E is other revenue per year S is detected by actual leased area A break-even point detection system in a rental building. A system for detecting a breakeven point of a rental building based on an occupancy rate at the breakeven point,
Equipped with a basic data storage unit that stores history information of rental contracts and information on income and expenditure,
The rental contract history information, at least for each rental room, unit area, date of entry, date of exit, data of monthly billing amount,
The overall production rate K _T at the detection time point,
_{K T = {Σ (Sn ×} Kn)} / S T
However, Sn is the actual area of the leased room (the leased area of each operating room).
Kn is the actual occupancy rate of n rental rooms (the occupancy rate of individual operating rooms)
S _T is the total actual leased area (ΣSn)
A system for detecting a breakeven point in a rental building, wherein the system detects the break-even point.

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