JP2020067725A - Personnel management support system - Google Patents
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Abstract
Description
本発明は、２４時間稼働操業する工場や、２４時間営業のコンビニエンスストア、国際線のある航空会社、多数の入院患者を抱える病院等の組織において、交替勤務を行う従業員や医師・看護師の交替勤務耐性に基づく離職・休職リスク及び／又は生産性低下リスク、或いは新規採用予定者の離職・休職リスクを確率計算によって算定し、組織の円滑な人事管理を支援するためのシステムに関する。 INDUSTRIAL APPLICABILITY The present invention replaces employees and doctors / nurses who perform shift work in organizations such as a factory that operates 24 hours a day, a convenience store that operates 24 hours a day, an airline with international flights, and a hospital that has a large number of inpatients. The present invention relates to a system for supporting the smooth personnel management of an organization by calculating the risk of leaving / leave of work and / or the risk of productivity decline based on work resistance, or the risk of leaving / leave of new hires by probability calculation.
企業等において、人事及び採用における重大なリスクの一つに、多大なるコストを投じて雇用した人材が、突然、離職あるいは休職してしまう問題がある。また、雇用した人材が何らかの心身の不調によって生産性が低下してしまうこと（プレゼンティズム）も、組織としては大きな問題である。 One of the serious risks in personnel employment and hiring in companies and the like is that there is a problem that a person who spends a large amount of money to hire suddenly leaves or takes a leave. In addition, the fact that the hired personnel lose their productivity due to some kind of physical and mental disorder (presentism) is also a big problem for the organization.
こうした社員の離職・休職や生産性の低下を防止するため、スキルミスマッチを起さない適性検査の実施や、綿密な採用面接の実施とともに、メンタルヘルス対策などが行われている。 In order to prevent such employee turnover / leave and productivity decline, aptitude inspections that do not cause skill mismatches, thorough employment interviews, and mental health measures are taken.
現在提案されている人事管理支援システムは、社員の性格や相性等に応じて、最適なグルーピングを図るものや（特許文献１参照）、メンタルヘルスに係る不調の実態を把握して、ヘルスケアが必要な社員を特定し、効率的な支援を行うもの（特許文献２参照）に限られている。 The currently proposed personnel management support system aims at optimal grouping according to the personality and compatibility of employees (see Patent Document 1), and grasps the actual condition of mental health disorders to improve health care. It is limited to those who specify necessary employees and provide efficient support (see Patent Document 2).
一方、一部従業員の交替勤務が前提となる２４時間稼働操業する工場や２４時間営業のコンビニエンスストア、多数の入院患者を抱える病院等の組織においては、交替勤務対象となる従業員、医師・看護師の交替勤務耐性は、個人によってそれぞれ相違する。例えば、スキルマッチ、報酬、職務環境などが同等であったとしても、個々人の交替勤務耐性の相違によって、その離職・休職確率、生産性の低下は有意に異なる。 On the other hand, in organizations such as a factory that operates 24 hours a day, a convenience store that operates 24 hours, and a hospital that has a large number of inpatients, where some employees are required to work shifts The shift work resistance of nurses differs depending on the individual. For example, even if the skill match, the reward, the work environment, etc. are the same, the probabilities of leaving or taking leave and the decrease in productivity are significantly different due to the difference in resistance to shift work among individuals.
上記のとおり、従来の人事管理支援システムは、社員の性格や相性等に応じた最適なグルーピングや、メンタル面での不調の実態を把握しているだけであり、特に、交替勤務を前提とする社員に対する人事管理の支援システムは存在せず、交替勤務者に対する離職・休職リスクや生産性低下リスクを事前に十分予防しきれていなかった。 As mentioned above, the conventional personnel management support system only grasps the optimal grouping according to the personality and compatibility of employees, and the actual condition of mental disorders, and is premised on shift work in particular. There was no support system for personnel management for employees, and it was not possible to fully prevent the risk of leaving / leave of work and the risk of productivity loss for shift workers.
本発明は、発明者らによる最新の研究で明らかになった個人の交替勤務耐性の相違による離職・休職状況や生産性低下状況が異なることに着目し、統計学的に有意な数の実証結果（アンケート結果）に基づき、これを回帰分析することによって各問診項目の回帰係数を求め、個人の離職・休職、生産性低下リスクを確率として算定し、その結果を組織の人事や新規採用に有効に活用するものである。 The present invention focuses on the fact that the leave and leave status and productivity decline status due to differences in shift work resistance of individuals revealed by the latest research by the inventors, and a statistically significant number of empirical results Based on the (questionnaire result), the regression coefficient of each inquiry item is obtained by performing regression analysis, and the risk of individual leave / leave and productivity decline risk is calculated as a probability, and the result is effective for personnel and new hiring of the organization. It is used for.
本願発明は、上記目的を達成するため、
組織に所属する者及び／又は新規採用予定者の交替勤務耐性による離職・休職確率及び／又は生産性低下リスクを算出することにより、当該組織の人事管理を支援するための人事管理支援システムであって、
前記組織が使用する組織端末と、
処理プログラムが記録され、かつ複数のデータベースが構築された管理サーバーと、を備え、
前記組織端末はオンラインで前記管理サーバーと接続され、
前記データベースには、個人の交替勤務耐性を測定するための複数の問診項目と、当該問診項目に対応する回帰係数が記録されており、
前記処理プログラムは、前記組織に所属する者又は前記新規採用予定者による前記問診項目の回答結果及び前記回帰係数に基づいて、前記組織に所属する者又は前記新規採用予定者の離職・休職確率、及び／又は前記組織に所属する者の生産性低下リスクを数値として算定し、当該算定結果を前記データベースに記録するとともに、前記組織端末に電子データとして送信する、及び／又は紙媒体で出力する、
ことを特徴とする。
The present invention, in order to achieve the above object,
It is a personnel management support system that supports personnel management of the organization by calculating the probability of leaving / leave of work and / or the risk of productivity loss due to resistance to shift work of persons who belong to the organization and / or new hires. hand,
An organization terminal used by the organization,
And a management server in which a processing program is recorded and a plurality of databases are constructed,
The organization terminal is connected to the management server online,
In the database, a plurality of inquiry items for measuring the shift work resistance of an individual and regression coefficients corresponding to the inquiry items are recorded,
The processing program is based on the answer result of the inquiry item by the person who belongs to the organization or the new hiring candidate and the regression coefficient, and the turnover / leave rate of the person who belongs to the organization or the new hiring candidate, And / or calculating the productivity reduction risk of a person who belongs to the organization as a numerical value, recording the calculation result in the database, transmitting it as electronic data to the organization terminal, and / or outputting it in a paper medium,
It is characterized by
上記構成を有する本願発明によれば、個人の交替勤務耐性を特定可能な問診項目を用い、各問診項目に対して統計学的に有意な数の実証結果（アンケート結果）に基づく回帰係数を付与し、個人の離職・休職及び／又は生産性低下リスクを確率として算定し、その結果を回答者個人や組織に提示し、改善すべきき勤務体制を明らかにすることにより、人事配置や新規採用の適切な指標（材料）とすることができる。 According to the invention of the present application having the above-mentioned configuration, using a questioning item capable of specifying the shift work resistance of an individual, a regression coefficient based on a statistically significant number of verification results (questionnaire results) is given to each questioning item. However, by calculating the risk of individual turnover / leave and / or productivity decline as a probability and presenting the result to the respondents individually and the organization and clarifying the work system that should be improved, personnel allocation and new hiring It can be an appropriate index (material).
以下、本願発明の実施形態について、各図面を参照しながら説明する。
なお、本願発明で言う「離職・休職確率」とは、人間の行動である離職、又は休職する可能性の程度を予測して数値化することを意味するものであり、純粋に数学的な確率を意味するものではない。
図１は、本願発明に係るシステム構成の全体図であり、管理サーバー１、当該管理サーバー１とオンライン接続されている組織端末２及びユーザー端末３から構成される。当該ユーザー端末３は、組織に所属する社員又は新規採用予定者が所有するＰＣ、タブレット端末、スマートフォン等の情報端末であり、また、本実施形態では問診票５を紙媒体として出力するためのプリンター４も接続されている。
Hereinafter, embodiments of the present invention will be described with reference to the drawings.
Note that the "probability of leaving / leave of work" in the present invention means to predict and quantify the degree of possibility of leaving or leaving, which is a human behavior, and is a purely mathematical probability. Does not mean.
FIG. 1 is an overall view of a system configuration according to the present invention, which includes a management server 1, an organization terminal 2 and a user terminal 3 that are online connected to the management server 1. The user terminal 3 is an information terminal such as a PC, a tablet terminal, or a smartphone owned by an employee belonging to the organization or a prospective new hire, and in the present embodiment, a printer for outputting the questionnaire 5 as a paper medium. 4 is also connected.
管理サーバー１内には、本サービスの開始時点までに蓄積された統計学的に有意な解析ができる充分な数の事前調査の結果（問診項目、回答結果データ、社員個人の離職・休職状況、社員個人の生産性状況、各問診項目に対応する回帰係数）が蓄積されたデータベースＤ１と、算定結果に基づいて抽出されるメッセージが記録されたデータベースＤ２と、問診票５を作成する問診票作成プログラムＰ１と、問診に対する回答結果に応じて、離職・休職確率及び／又は生産性低下リスクについて確率計算し、かつ上記メッセージを抽出する算出・判定プログラムＰ２と、問診回答の結果を表示する結果表示プログラムＰ３と、問診票５及びその結果を紙媒体で出力するための紙面作成プログラムＰ４と、新たな回帰分析を行う回帰プログラムＰ５と、組織端末２とのデータ通信を行う管理コンソールＩ１と、ユーザー端末に問診票５を送信し、かつ回答を受信する問診票送信・回答プログラムＩ２とが構築されている。 In the management server 1, a sufficient number of preliminary survey results (interview items, answer result data, employee turnover / leave status, etc.) that can be statistically significant analyzed until the start of this service. A database D1 in which the productivity status of each employee and a regression coefficient corresponding to each inquiry item) are accumulated, a database D2 in which messages extracted based on the calculation result are recorded, and an inquiry sheet for creating an inquiry sheet 5 are created. Program P1, a calculation / judgment program P2 that calculates the probability of leaving / leave time and / or the risk of productivity decline and extracts the above message according to the answer to the inquiry, and a result display that displays the result of the inquiry A program P3, a sheet preparation program P4 for outputting the questionnaire 5 and the result on a paper medium, and a regression program P for performing a new regression analysis If a management console I1 to perform data communication with the tissue terminal 2, and transmits the questionnaire 5 in the user terminal, and is a questionnaire sent and replies program I2 for receiving an answer has been constructed.
データベースＤ１には、図２に示すとおり、発明者らが東京都内のサービス業に勤務する約３０００名に対して実施した調査項目（問診項目）である、１）外国へ行ったことのある場合の時差ボケの有無とその程度、２）睡眠時間帯が短期間で大きく変動した場合の体調不良の有無、３）深夜ないしその者が通常睡眠をとっている時間に覚醒させられた場合の体調不良の有無、４）寝ようと思えばいつでも眠れるかどうか、５）日中眠気を感じたときに仮眠をしようとして実際に入眠できるかどうか、６）起床・覚醒に苦労することがあるかどうか、７）睡眠の問題あるいは睡眠障害を有するかどうか（データベース内においてはピッツバーグ睡眠問診票の結果が格納されている）、８）交替勤務を過去にしたことがある場合に不調になったことがあるかどうか、の８項目と、その回答結果、実際の離職・休職の状況、実際の生産性の状況、当該回答結果を回帰分析することにより求められた各問診項目に対応する回帰係数が、蓄積されている。 As shown in FIG. 2, the database D1 is a survey item (interview item) conducted by the inventors for about 3000 employees working in the service industry in Tokyo. Of jet lag and its degree, 2) presence or absence of poor physical condition when sleep time changes significantly in a short period of time, and 3) physical condition when awakened at midnight or during the time when the person sleeps normally Whether there is a defect, 4) whether you can sleep whenever you want to sleep, 5) whether you can actually fall asleep when you feel drowsiness during the day, and 6) whether you have difficulty getting up and waking up , 7) If you have a sleep problem or sleep disorder (the results of the Pittsburgh Sleep Questionnaire are stored in the database), 8) If you have worked in shift work in the past Whether there is or not, the response results, the actual leave and leave status, the actual productivity status, and the regression coefficient corresponding to each inquiry item obtained by regression analysis of the response results. Has been accumulated.
各問診項目に対する回答は、「１．大いにある、２．ややある、３．ほとんどない、４．全くない」のように複数の選択肢から選ぶようになっており、例えば、「１．大いにある」が選択された場合には３点、「２．ややある」は２点、「３．ほとんどない」は１点、「４．全くない」は０点として計算するようになっている。或いは「あり」「なし」のみとし、ありを１点、なしを０点として計算することもできる。また、７）の睡眠の問題あるいは睡眠障害を有するかどうかについては、それそのものを回答者に問うてもよいし、ピッツバーグ睡眠問診やアテネ不眠尺度などの既存の睡眠の問題を検出するための医学的問診票を用いて睡眠の問題があるかないかを評価してもよい。 The answer to each inquiry item is to be selected from a plurality of options such as “1. There is a large amount, 2. There is a small amount, 3. There is little, 4. There is no at all”, for example, “1. There is a large amount”. When is selected, 3 points, “2. Slightly” is 2 points, “3. Almost no” is 1 point, and “4. Nothing” is 0 point. Alternatively, it is possible to calculate with “Yes” and “No” only, with Yes as 1 point and No as 0 point. Regarding 7) sleep problems or whether or not they have a sleep disorder, they may ask the respondents themselves, or medicine for detecting existing sleep problems such as the Pittsburgh Sleep Questionnaire and Athens Insomnia Scale. You may use a physical questionnaire to assess whether you have sleep problems.
上記発明者らが行った実際の調査結果を回帰分析したところ、上記各問診項目への回答結果が、離職・休職、又は生産性の低下に有意に影響することが判明し、離職・休職及び生産性低下を目的変数とし、各問診項目を説明変数として、確度の高い確率を計算可能であることが明らかとなった。 A regression analysis of the results of the actual survey conducted by the above inventors revealed that the results of answers to each of the above-mentioned inquiry items significantly affected employee turnover / leave or productivity loss. It became clear that it is possible to calculate the probability with high accuracy by using productivity decline as an objective variable and each inquiry item as an explanatory variable.
離職・休職確率、生産性低下リスクについて回帰モデルを利用すると、その確率は、以下の式で示すことができる（ただし、ｐ＝離職・休職確率又は生産性低下リスク、ｂｎ＝各回帰係数、Ｘｎ＝各問診への回答結果とする）。
１．線形回帰モデルを使用した場合（式１）
ｐ＝定数項＋ｂ１Ｘ１＋ｂ２Ｘ２＋ｂ３Ｘ３＋ｂ４Ｘ４…ｂｎＸｎ
２．ロジットモデルを使用した場合（式２）
ｌｏｇｉｔ値＝定数項＋ｂ１Ｘ１＋ｂ２Ｘ２＋ｂ３Ｘ３＋ｂ４Ｘ４…ｂｎＸｎとすると、ｐ ＝ ｅｌｏｇｉｔ ／ １＋ｅｌｏｇｉｔ ＝ １／１＋ｅ−ｌｏｇｉｔ
If a regression model is used for the probability of leaving / leave of work and the risk of productivity decline, the probability can be shown by the following formula (where p = leave / leave risk or productivity decline risk, bn = regression coefficient, Xn = Assume the answer to each inquiry).
1. When using a linear regression model (Equation 1)
p = constant term + b1X1 + b2X2 + b3X3 + b4X4 ... bnXn
2. When using the logit model (Equation 2)
logit value = constant term + b1X1 + b2X2 + b3X3 + b4X4 ... bnXn, p = e logit / 1 + e logit = 1/1 + e −logit
なお、上記８つの問診項目は、実態調査に基づく個人の交替勤務耐性を把握する上で最も適切な必要最低限の項目であるが、更に関連性のある項目を追加しても良い。その場合、新たな大規模アンケート調査を実施し、その結果を回帰分析する必要がある。 Note that the above eight inquiry items are the most appropriate minimum necessary items for grasping the shift work resistance of an individual based on the fact-finding survey, but further related items may be added. In that case, it is necessary to conduct a new large-scale questionnaire survey and perform regression analysis of the results.
さらに、組織ごと、業種ごと、職種ごとにおける離職・休職確率、生産性低下リスクを特異的に同定し、問診項目に用いることも可能である。例えば、２４時間稼働操業する自動車メーカー等の生産工場及び生産ラインで働く従業員、２４時間営業のコンビニエンスストア等のサービス業及びそこで働く従業員、航空会社において国際線に乗務するパイロットやキャビンクルー、入院患者を多数要する大病院及びそこで働く医師・看護師等のように、業種や職種によって回帰係数を異ならせることもできる。 Furthermore, it is also possible to specifically identify the probability of leaving / leave of work and the risk of productivity loss for each organization, each type of industry, and each type of work, and use them as the items to be interviewed. For example, employees working at production plants and production lines of automobile manufacturers operating 24 hours a day, service businesses such as convenience stores that are open 24 hours a day and employees working there, pilots, cabin crews, and hospitalization on international flights at airline companies. The regression coefficient can be made different depending on the type of industry or occupation, such as a large hospital requiring a large number of patients and doctors / nurses working there.
この場合、組織ごと、業種ごと、職種ごとに十分なデータを予め取得して回帰分析しておけば精度の高い確率計算が可能となる。また、数千人、数万人規模の従業員を有する会社では、当該企業に限定したデータで解析することで、当該企業における個別の離職・休職確率、生産性低下リスクをより精密に算定することができる。データベースＤ１には、組織ごと、業種ごと、職種ごとに調査した結果が蓄積されてもよく、或いは、業種ごと、職種ごとに分析可能なように、業種別、職種別のフラグを立てておくことも出来る。 In this case, highly accurate probability calculation can be performed by acquiring sufficient data in advance for each organization, each industry, and each job type and performing regression analysis. In addition, in a company that has thousands or tens of thousands of employees, by analyzing with data limited to that company, the probability of individual leave and absence from work and the risk of reduced productivity can be calculated more accurately. be able to. The database D1 may store the results of the surveys for each organization, each industry, and each job type, or flags each industry and job type so that analysis can be performed by each industry and job type. You can also
なお実際の問診票には、その回答項目として、氏名、年齢、家族構成等のその他の項目も任意に作成しても良いが、上記５項目は必須の問診項目となっている。任意の問診項目は、本システムを利用する組織（会社等）の要求に応じて、適宜に選定することができる。任意の問診項目を含め、全体の問診項目は、組織端末上から決定し、問診票作成プログラムによって作成される。なお、任意の問診項目には、原則として回帰係数は付与されない。 Although other items such as name, age, and family structure may be arbitrarily created as the answer items in the actual inquiry sheet, the above five items are indispensable inquiry items. Any inquiry item can be appropriately selected according to the request of the organization (company or the like) using this system. All inquiry items including arbitrary inquiry items are determined from the organization terminal and created by the inquiry form creating program. In addition, in principle, no regression coefficient is given to any inquiry item.
また、本システムを利用する組織（会社等）は、当該問診票に基づいて、組織に所属する社員又は前記新規採用予定者の離職・休職確率を求めるのか、又は組織に所属する社員の生産性低下リスクを求めるのか、或いはその両方を算出するのかを、組織端末２上で予め決定し、管理サーバー１に送信しておく。 In addition, the organization (company, etc.) that uses this system, based on the questionnaire, asks for the probability of leaving or taking leave of the employees who belong to the organization or the prospective new hires, or the productivity of the employees who belong to the organization. Whether the reduction risk is calculated or both of them are determined in advance on the organization terminal 2 and transmitted to the management server 1.
上記のとおり、組織端末２の入力操作によって作成した問診票５は、問診票作成プログラムＰ１によって作成され、問診票送信・回答プログラムＩ２からユーザー端末１に送信され、社員又は新規採用予定者はユーザー端末３上から各問診項目に回答し、入力した回答内容は、ユーザー端末３から管理サーバー１に送信される。なお、問診を紙媒体で行う場合には、紙面作成プログラムＰ５によってプリンター４から問診票５が出力され、社員又は新規採用者が紙媒体で回答した結果を回収し、ＯＣＲ等によって読み込み、管理サーバー１に送信される。或いは、回答結果を手作業でデータ入力しても良い。 As described above, the questionnaire 5 created by the input operation of the organization terminal 2 is created by the questionnaire creating program P1 and transmitted to the user terminal 1 from the questionnaire sending / answer program I2, and the employee or the newly hired person is the user. The contents of answers entered by answering each inquiry item from the terminal 3 are transmitted from the user terminal 3 to the management server 1. When conducting an interview with a paper medium, the paper creation program P5 outputs the questionnaire 5 from the printer 4, and the employee or new employee collects the results answered in the paper medium and reads them by OCR or the like, and the management server Sent to 1. Alternatively, the answer result may be manually input as data.
上記のとおり、社員又は新規採用予定者による回答結果は、上記式１又は式２に基づき、算出プログラムＰ３によって離職・休職確率、又は生産性低下リスクが計算される。計算した結果は、結果表示プログラムＰ３によって数値として組織端末２に表示する。なおこの結果は、組織端末２だけでなく、回答した本人であるユーザー端末３にも送信してもよい。また、数値としてではなく、段階的な表示、例えば、Ａ、Ｂ、Ｃの表示や、危険性なし、やや危険性あり、危険度大、などの表示であってもよい。 As described above, the answer result by the employee or the newly hired person is calculated by the calculation program P3 based on the formula 1 or the formula 2, and the probability of leaving or taking a leave or the risk of productivity decrease. The calculated result is displayed on the organization terminal 2 as a numerical value by the result display program P3. It should be noted that this result may be transmitted not only to the organization terminal 2 but also to the user terminal 3 which is the respondent. Further, instead of numerical values, a stepwise display, for example, A, B, C display, no risk, slightly dangerous, high risk, etc. may be displayed.
上記結果を受取った会社は、交替勤務による離職・休職の確率が高い社員であるか否か、又は生産性低下リスクが高まっている社員であるか否かを数値として把握することができ、適切な人事配置や勤務体制の変更を行うための指標とすることができる。 The company that received the above results can figure out numerically whether it is an employee who has a high probability of leaving or taking leave due to shift work, or an employee who is at an increased risk of productivity decline. It can be used as an index for changing personnel assignments and work systems.
また、新規採用予定者の場合、交替勤務に適合する者であるかどうかを把握でき、採用後の離職・休職の確率を予測できるため、新規採用の基準としても有効に利用することができる。 Further, in the case of a newly hired person, it is possible to know whether or not the person is suitable for shift work, and it is possible to predict the probability of leaving or taking a leave after hiring, so that it can be effectively used as a criterion for new hiring.
更に、回答者が組織に属する社員である場合、算出結果に基づいて現在の勤務耐性を見直すべき具体的なメッセージ、例えば「回答者は、交替勤務に適さず、かなりの確度で離職・休職の可能性がある。」、「回答者は、交替勤務耐性が弱く、かなりの確度で生産性が低下する可能性がある。」等のメッセージを、データベースＤ２から抽出し、組織端末２及び／又はユーザー端末２に送信する。なお、各必須問診項目において、対応する回帰係数が大きいほど離職・休職確率、生産性低下リスクに与える影響が大きい項目であるため、当該項目が陽性回答された場合、その大きさに準じてメッセージを発信するようにしてもよい。 Furthermore, if the respondent is an employee who belongs to the organization, a specific message to review the current work resistance based on the calculation result, for example, `` The respondent is not suitable for shift work, , “Respondents have weak shift work resistance, and productivity may drop with a high degree of certainty.” From the database D2, and the organization terminal 2 and / or It is transmitted to the user terminal 2. For each mandatory inquiry item, the larger the corresponding regression coefficient, the greater the effect on the probability of leaving / leave of work and the risk of productivity loss. May be sent.
上記メッセージを受け取った会社（組織端末２）は、交替勤務勤に問題があると判断された社員に対し、離職・休職しないよう、又は生産性が低下しないような配置転換や勤務時間の変更を、ピンポイントで効率的に行うことができる。 The company (organizational terminal 2) that received the above message will not change leave or change work hours so that employees who are judged to have a problem with shift work will not leave or take leave, or that productivity will not decrease. , Can be done pinpoint efficiently.
交替勤務耐性は個々人固有の特性であり、生活習慣を変える等の対応ではこれを変えることは困難であり、離職・休職確率、又は生産性低下リスクを回避することがほとんどできないため、会社は人事による配置転換を図ることで対応する。 Tolerance to shift work is a characteristic peculiar to each individual, and it is difficult to change it by measures such as changing lifestyles.Since it is almost impossible to avoid the probability of leave / leave of work or the risk of productivity loss, the company will This will be dealt with by relocating by.
図４に示すとおり、問診票５への回答で得られたデータは、データベースＤ１に逐次格納し、その後、回答した者が離職・休職していないか、或いは生産性が低下していないかどうかのデータを追加し、一定期間経過後に、データベースＤ１に既に保存されている過去のデータと統合させ、回帰プログラムＰ５によって新たに回帰分析を行い、新たな回帰係数を算定し、データベースＤ１に記録されている回帰係数を書き変え更新する。 As shown in FIG. 4, the data obtained by responding to the questionnaire 5 is sequentially stored in the database D1, and thereafter, whether the respondents are not leaving or taking leave, or whether productivity is decreasing. Data is added, and after a certain period of time, it is integrated with the past data already stored in the database D1, a new regression analysis is performed by the regression program P5, and a new regression coefficient is calculated and recorded in the database D1. Rewrite the regression coefficient and update it.
この作業を定期的に繰り返すことにより、回帰係数は問診を行うたび、時間経過とともに精度を高くしていくことができ、更に確度の高い確率計算を行うことができる。また、組織ごと、業種ごと、職種ごとにデータを蓄積する、或いは組織ごと、業種ごと、職種ごとのデータを特定可能なようにフラグを設定することで、個別信頼性の高い、統計学的に有意な問診票を作成することができる。 By repeating this work regularly, the accuracy of the regression coefficient can be increased with the lapse of time each time an inquiry is made, and more accurate probability calculation can be performed. In addition, by accumulating data for each organization, each industry, and each job type, or by setting a flag so that the data for each organization, each industry, and job type can be specified, it is possible to obtain highly reliable individual statistics. A meaningful questionnaire can be created.
１ 管理サーバー
２ 組織端末
３ ユーザー端末
４ プリンター
５ 問診票
Ｄ１ 問診項目回答内容、休職・離職状況、生産性状況、問診項目に対応する回帰係数が蓄積されたデータベース
Ｄ２ 予め定めたメッセージが格納されたデータベース
Ｐ１ 問診票５を作成する問診票作成プログラム
Ｐ２ 問診回答に応じて確率を計算する算出・評価するプログラム
Ｐ３ 問診回答の結果を表示する結果表示プログラム
Ｐ４ 問診票及び結果を紙媒体で出力するための紙面作成プログラム
Ｐ５ 新たな回帰分析を行い、回帰係数を書き変え更新するプログラム
Ｉ１ 組織端末とのデータ通信を行う管理コンソール
Ｉ２ ユーザー端末に問診票を送信し、かつ回答を受信する問診票送信・回答プログラム
1 Management server 2 Organizational terminal 3 User terminal 4 Printer 5 Questionnaire D1 Questionnaire item reply contents, leave / leave status, productivity status, database D2 that stores regression coefficients corresponding to the question items D2 Predetermined message is stored Database P1 Question sheet preparation program for creating questionnaire sheet P2 Program for calculating / evaluating the probability according to the questionnaire answer P3 Result display program for displaying the results of the questionnaire answer P4 To output the questionnaire sheet and results on paper Program P5 for performing a new regression analysis and rewriting and updating the regression coefficient I1 Management console I2 for data communication with organizational terminals Sending questionnaires to user terminals and receiving answers Answer program
Claims (8)
前記組織が使用する組織端末と、
処理プログラムが記録され、かつ複数のデータベースが構築された管理サーバーと、を備え、
前記組織端末はオンラインで前記管理サーバーと接続され、
前記データベースには、個人の交替勤務耐性を測定するための複数の問診項目と、当該問診項目に対応する回帰係数が記録されており、
前記処理プログラムは、前記組織に所属する者又は前記新規採用予定者による前記問診項目の回答結果及び前記回帰係数に基づいて、前記組織に所属する者又は前記新規採用予定者の離職・休職確率、及び／又は前記組織に所属する者の生産性低下リスクを数値として算定し、当該算定結果を前記データベースに記録するとともに、前記組織端末に電子データとして送信する、及び／又は紙媒体で出力する、
ことを特徴とする人事管理支援システム。 It is a personnel management support system that supports personnel management of the organization by calculating the probability of leaving / leave of work and / or the risk of productivity loss due to resistance to shift work of persons who belong to the organization and / or new hires. hand,
An organization terminal used by the organization,
And a management server in which a processing program is recorded and a plurality of databases are constructed,
The organization terminal is connected to the management server online,
In the database, a plurality of inquiry items for measuring the shift work resistance of an individual and regression coefficients corresponding to the inquiry items are recorded,
The processing program is based on the response result of the inquiry item by the person who belongs to the organization or the person who is newly hired and the regression coefficient, based on the regression coefficient, the probability of leaving or taking a leave of the person who belongs to the organization or the person who is newly hired, And / or calculating the productivity reduction risk of a person who belongs to the organization as a numerical value, recording the calculation result in the database, transmitting it as electronic data to the organization terminal, and / or outputting it in a paper medium,
Personnel management support system characterized by
ことを特徴とする請求項１に記載の人事管理支援システム。 The personnel management support system further includes a user terminal used by a person who belongs to the organization and / or the prospective new hire, and when the user terminal is connected to the server, the processing program records the data in the database. The questionnaire is displayed on the user terminal, the person who belongs to the organization and / or the prospective new hire enters an answer on the user terminal, and the answer result is transmitted to the server online. And the calculation result is transmitted from the server to the user terminal,
The personnel management support system according to claim 1, wherein:
ことを特徴とする請求項１又は２に記載の人事管理支援システム。 The regression coefficient is determined by a regression analysis based on the results of a statistically significant number of preliminary surveys, with the probability of leaving / leave of work and / or the risk of productivity loss as the objective variable, and the inquiry items as explanatory variables. Will be
The personnel management support system according to claim 1 or 2, characterized in that.
ことを特徴とする請求項１ないし３のいずれか１項に記載の人事管理支援システム。 The regression coefficient differs depending on whether to obtain the probability of leaving or taking leave or the risk of productivity decline,
The personnel management support system according to any one of claims 1 to 3, wherein:
ことを特徴とする請求項１ないし４のいずれか１項に記載の人事管理支援システム。 The calculation result is displayed as a probability numerical value or a stepwise qualitative evaluation based on the numerical value,
The personnel management support system according to any one of claims 1 to 4, wherein:
ことを特徴とする請求項１ないし５のいずれか１項に記載の人事管理支援システム。 If you have ever been to a foreign country, you may have a sickness due to jet lag, or if you have a poor physical condition if your sleep time changes significantly over a short period of time. Whether you feel unwell when you are awake during a certain period of time, whether you can sleep whenever you want to sleep, whether you can actually fall asleep while trying to take a nap when you feel drowsy during the day, struggling to wake up and wake up , Whether you have a sleep problem or sleep disorder, and if you have had a shift job in the past and you have been sick,
The personnel management support system according to any one of claims 1 to 5, wherein
ことを特徴とする請求項１ないし６のいずれか１項に記載の人事管理支援システム。 The processing program extracts a message for reducing the probability of turnover / leave of absence and / or the risk of reduced productivity recorded in advance in the database according to the calculation result or the content of the answer to the inquiry item, and the organizational terminal Send the message to
The personnel management support system according to any one of claims 1 to 6, characterized in that.
ことを特徴とする請求項１ないし７のいずれか１項に記載の人事管理支援システム。 The processing program stores inquiry response results in the database, performs a new regression analysis together with the response results already stored, and rewrites the regression coefficients already stored into new regression coefficients,
The personnel management support system according to any one of claims 1 to 7, characterized in that.
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