KR20190058947A - Method of Performance Evaluation Using Equi-Distributional Scoring - Google Patents

Abstract

The present invention relates to a system of performance evaluation using a uniform distribution scoring method and a method thereof. According to an embodiment of the present invention, the system of performance evaluation using a uniform distribution scoring method comprises: a standard score conversion unit converting a raw score for each indicator into a standard score for each indicator; and a final score calculation unit calculating a final score by reflecting weight to the standard score for each indicator.

Description

[0001] The present invention relates to a method for evaluating performance using equidistant scoring,

The present invention relates to a performance evaluation method using an equidistant scoring method, and more specifically, to a manpower evaluation system and method having a data-based numerical model capable of measuring the quantitative performance of manpower.

As a representative measure for performance evaluation, absolute evaluation and relative evaluation can be mentioned. In this evaluation method, a method of objectively quantifying the employee performance is needed. Typical performance measurement methods include GRS (Graphic Rating Scales), MBO (Management By Objectives), FR (Forced Ranking), and others.

GRS is an evaluation method suitable for production manpower and is evaluated based on job duties list and evaluation standard.

The MBO method is usually known as a useful method for management positions. It is one of the methods to set and manage the goals of the organization at the beginning of the evaluation period and cascading them. The target value of the individual indicators is set, and the evaluator evaluates by taking the difficulty and the weight into account.

FR is known to have gained a bad reputation by creating a highly competitive work environment by comparing and evaluating the performance of employees in the evaluation period with those of other employees, rather than comparing the performance of employees in the past.

Korean Patent Publication No. 10-2015-0142125

The technical problem to be solved by the present invention is to improve the labor performance evaluation method according to the prior art which is relatively low in satisfaction of the evaluator and the evaluator due to the lack of quantification and objectivity so that it is possible to quantitatively measure the performance, The present invention also provides a system and method for evaluating performance using the equally divided scoring method.

According to an embodiment of the present invention, there is provided a performance evaluation system using an equidistant point scoring method, comprising: converting a raw score for each indicator into a standard score for each indicator; And calculating a final score by reflecting the weight to the standard score for each indicator.

In addition, the step of converting the raw scores of the indicators into the standard scores of the indicators may be performed by standardizing the raw scores of the indicators through the following equation (1)

(1)

(One)

X _i is the standard score of indicator i, x _i is the origin score of indicator i, x _{t, i} is the target score of indicator i, and σ _{o and i} are the origin, which means m _i ± n _i σ _i , Where m _i means an average of x _i , n _i is a non-zero real number, and σ _i is the standard deviation of x _i . In the step of converting the origin score by indicator into a standard score by indicator, the x _t, it can be selected for the _i as the average, maximum value or designated value of x _i.

The method may further include the step of calculating an applied score for each index obtained by linearly converting the standard scores for each indicator, wherein the step of calculating the applied score for each indicator obtained by linearly converting the standard scores for each indicator comprises: 2) to linearly convert the standard scores for each indicator,

(2)

(2)

XL _i is the index i applying scores, XL _{i _M} is the index i after the linear transformation peak, XL _{i _m} is the index i after linear transformation flop, X _{i _M} is the culmination of the index i after normalization, X _{i _m} after standardization flop of the index i, X _i denotes the standard score of the index i.

The step of converting the origin score for each indicator into a standard score for each indicator includes the step of recalculating the standard score except for the singularity for the index in which the singularity is found, The step of recalculating the standard scores again, excluding the singularities, may exclude the singularities by calculating a standard score exceeding a preset full-scale standard for each indicator as the full score.

The step of calculating the final score by reflecting the weight to the standard score for each index is performed by multiplying the standard score for each index or the applied score for each index by the weight set for each index, Calculating a final score; And calculating a second final score by adding the additional achievement or the observed evaluation score of the evaluator to the first final score.

According to the performance evaluation system and method using the equally divided scoring method of the present invention, the satisfaction of the evaluation results of the evaluator and the evaluator can be improved through objectification and quantification of the researcher performance evaluation.

In addition, it is possible to identify the strengths and weaknesses in the business area by objectively grasping the achievement level and so on for each individual performance evaluation index, thereby making it possible to derive the business capacity improvement field.

In addition, it is possible to induce the direction of the entire organization required by the management through weight adjustment, thus enabling strategic personnel management.

1 is a block diagram of a performance evaluation system using a uniformly distributed scoring method according to an embodiment of the present invention.
FIG. 2A is a graph representing a singular point to be excluded from the index by a standard scoring unit according to an exemplary embodiment of the present invention, and FIG. 2B is a graph illustrating an index in which a singular point is absent.
FIG. 3 is a graph showing a linear conversion of the standard scores of the applied score calculating unit according to the embodiment of the present invention.
FIG. 4 is a flowchart of a performance evaluation method using a uniform distribution scoring method according to an embodiment of the present invention.
FIG. 5 is a flowchart of a step of calculating a final score by applying a weight to an applied score according to an embodiment of the present invention.

The details of other embodiments are included in the detailed description and drawings.

BRIEF DESCRIPTION OF THE DRAWINGS The advantages and features of the present invention and the manner of achieving them will become apparent with reference to the embodiments described in detail below with reference to the accompanying drawings. The present invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. To fully disclose the scope of the invention to those skilled in the art, and the invention is only defined by the scope of the claims. Like reference numerals refer to like elements throughout the specification.

FIG. 1 is a block diagram of a performance evaluation system using a uniform division scoring method according to an embodiment of the present invention. FIG. And FIG. 2B is a graph showing an index in which a singular point does not exist. The performance evaluation system 10 using the uniform distribution scoring method according to an embodiment of the present invention may include a standard score converting unit 100, an applied score calculating unit 200 and a final score calculating unit 300. [

The term "module" or "module" or "table" used in the present embodiment includes hardware such as software, an FPGA (Field Programmable Gate Array) or an application specific integrated circuit Means a component, and the module performs certain functions. However, a module is not limited to software or hardware. A module may be configured to reside on an addressable storage medium and configured to play back one or more processors. Thus, by way of example, a module may include components such as software components, object-oriented software components, class components and task components, and processes, functions, attributes, procedures, Microcode, circuitry, data, databases, data structures, tables, arrays, and variables, as will be appreciated by those skilled in the art. The functionality provided within the components and modules may be combined into a smaller number of components and modules or further separated into additional components and modules. In addition, components and modules may be implemented to reproduce one or more CPUs in the device.

First, the standard score conversion unit 100 converts the origin score per indicator into a standard score for each indicator.

In order to understand the meaning of the number of origin by indicators, the following [Table 1] and [Table 2] are explained.

In general, task tasks excluding R & D related administrative work can be objectified as in [Table 1].

Utilization and performance indicators of R & D personnel Steps for discovery Steps to accomplish the task Task completion stage activity Suggest Ideas
Refine the contents of the assignment
Participation in planning activities Experiment / Calculation Research Activity
Utilization of Research Activities Use task performance result
(Performance index) Planning Report
Task proposal Project Plan (Business Plan)
Achieve research goals
Research Projects and Contributions
Academic activities (presentation and participation)
Intellectual property application and registration Utilization evaluation (performance utilization)
Technology business revenue (technology transfer, commercialization) Considerations proponent
Plan participation participation Task Scale
Participation participation (MM, man-month, etc.)
Contribution rate Awards, recognition, etc.

As shown in [Table 1], it is possible to derive a performance index item as shown in [Table 2] below for objectized task tasks.

Definition of indicators and indicators for performance quantification Indicators Indicator name Indicator Description Remarks x1 Suggested task Ideas for finding new assignments.
Project proposal: Proposal registration result x2 Participation in the task Participation performance: Task ratio, participation rate, MM, etc. x3 Research project
Performance Contribution Participants' contribution to completed project performance:
Consideration such as project cost, participation rate, MM, completion score x4 Evaluate the task utilization Participants' Contribution to the Assigned Task:
Task ratio, participation rate, MM, etc. After completion of utilization evaluation, x5 Patent Domestic and foreign patent applications: Number of applications, Contribution rate x6 Academic Activities Presentations of domestic and international conferences, publication of papers and presentations: Number of cases, Contribution rate x7 Technology Business Revenue Individual contributions to royalty and business revenue x8 Additional performance Awards, awareness raising, financial contribution less than a certain amount (deduction), etc. Simple sum to final score

The standard score converting unit 100 identifies basic statistics such as average and standard deviation from the raw data (x _i ) of each index and the score distribution pattern, and normalizes the number of origin according to each index. As described in Table 2, each origin score for indices X1 to X7 is converted to a standard score. In this case, the conversion to the standard score is performed by the following equation (1).

(1)

(One)

But here, X _i is the standard score of the index i, x _i is a raw score of the index i, x _{t, i} is the target point of index i, σ _{o, i} refers to the origin, the origin is m _i ± n _i σ _i , where m _i means the mean of x _i , n _i is a non-zero real number, and σ _i means the standard deviation of x _i .

σ _{o, i} can mean, for example, the 6σ origin. The reason for the standardization through Equation (1) is that when converting the origin score to the standard score, the standard deviation should be calculated on the same scale with considering the average and the average for each index. Here, the origin means (mean ± n * standard deviation), and the 6σ origin means the origin when n is 6. In the following description, n is set to 6, but n may have a different value (n = 3, for example) if necessary.

Also, the origin can be taken differently depending on the nature of the indicator. Here, the nature of an indicator, for example, a tower indicator that is closer to a target value as its value increases, that is, an indicator that generally wants to have a larger value, In general, it can be classified into a small scale index, which is an index to be desired to have a small value, and a mesh index, which is a better index to a certain target value. If any of these indicators is a tower indicator, the "average - n × standard deviation" is calculated as the origin, and if the technical indicator is a map indicator, the "average + n × standard deviation" can be calculated as the origin.

As described above, n may be set to 6, or n may be set to 3, but calculating the origin by using " 6 x standard deviation " means statistically a pursuit of a defective rate of 0 , And a statistically small process error (about 0.3%) that the origin is calculated using "3 × standard deviation".

The indexes covered in the performance evaluation system using the equilibrium point scoring method of the present invention are characterized by the indicator of the tower which is generally desired to have a large value, and therefore, the "average - n × standard deviation" is often calculated as the origin. In the following embodiments of the present invention, the 6? Origin set at n = 6 will be described, but the present invention is not limited to this.

As a result, the 6? Origin in the present invention means m _i -6σ _i . Here, m _i means the average of x _i .

Further, the target value can be selected in advance as an absolute value, or can be determined by looking at the distribution pattern of the indicator. The choice of x _{t, i} can change the value and distribution of the standard score. For example, if x _{t, i} is chosen as the highest point on the surface, then Xi is the distribution with a maximum of 1, and if x _{t, i} is chosen as the mean of the top 5% Of the respondents are considered super-talent.

As an embodiment, the m _i (average value) that can be generally selected to enhance the perception by the subject can be selected as x _{t, i} . When the average is set to the target value and standardized, if the evaluated person has a value of 1 or more, it can be known that the relative position is lower than the relative position if the relative position is higher than 1. In other words, there is an advantage that it is easy to grasp the relative position of the subject to be evaluated by positional standardization.

x _{t, i} In addition to the maximum and average values, the value specified according to the intention of the evaluator may be selected as x _{t, i} .

Thereafter, the standard score conversion unit 100 can recalculate the standard score again for the index for which the outlier is found, excluding the outlier. Specifically, after calculating the standard score, the standard of the scale of each indicator is selected in consideration of the point distribution pattern and the orientation point (the tower, the mesh, and the moon characteristic) according to the index. As a general criterion, if it is out of 3σ, it can be determined as a singular point. Therefore, as shown in FIG. 2A, a score P out of 1.5 or more can be calculated as a perfect score. As shown in FIG. 2B, when there is no singular point, the standard scoring unit 100 does not need to recompute the standard score again except for the singular point. On the other hand, the criterion is determined by whether or not to recognize the singularity. In the case of an indicator where a singular point is found, the average, standard deviation, and 6σ origin are calculated again and the standard score is recalculated. In this way, the calculation of the standard score can be repeated if necessary (when there is a singular point, a perfect point, etc.).

FIG. 3 is a graph showing a linear conversion of the standard scores of the applied score calculating unit according to the embodiment of the present invention. In the above-described embodiment of the present invention, when x _{t, i} is calculated by setting m _i (average value), that is, when x _{t, i} is set to a value other than the maximum value of x _i , And a process of calculating the applied score by the score calculating unit 200 may be further included.

The applied score calculation unit 200 linearly calculates a standard score for each index computed by the standard score conversion unit 100 (linear equation, linear equation) in order to facilitate weighting and identification of the subject, And calculates the applied score for each indicator. In this case, the applied score calculation unit 200 linearly converts the standard scores for each index by the following equation (2).

(2)

(2)

Here, XL _i is the index i applying scores, XL _{i _M} is the index i after the linear transformation peak, XL _{i_m} is the index i after the linear transformation flop, X _{i _M} is the culmination of the index i after normalization, X _{i _m} is The lowest point of indicator i after standardization, X _i means the standard score of indicator i.

In an embodiment of the present invention in the first peak (XL _{i _M)} in such a conversion process, the lowest point (XL _{i_m)} was set to 0.4. This criterion may vary according to the calculation of the minimum and maximum points. In this specification, a standard score converted into a linear form for the weight application is referred to as an application score. Thus, the reason for going through the linear transformation process is that the final score distribution of each workforce is kept within a certain range, that is, between the lowest point (XL _{i _m} ) and the highest point (XL _{i _M} ) In order to facilitate the convenience of the user. If so, out of the reference is due on the basis of the highest point (XL _{i _M),} the lowest point criteria being able to finally calculated on the basis of the lowest point (XL _{i_m).}

However, in another embodiment of the present invention, in the case where x _{t, i} is set as the highest point on the indicator and converted into a standard score for each indicator, the applied score calculating unit 200 calculates the applied score The process may be omitted. In the case of converting x _{t, i} to the highest point on the indicator of x _i and converting it to a standard score for each indicator, the maximum value of the standard score for each indicator will not exceed 1. In this case, It is easy to set a perfect score according to the criteria.

Even if x _{t, i} is not set as the highest point on the surface _, the process of calculating the application score by the application point calculating unit 200 may be omitted. The reason for deriving the applied score is that the objective is to facilitate the evaluation by setting the full-scale standard and the low-grade standard as described above.

x _t, in one example for the _i when not set to the highest point on the surface, if a bit more specifically for the case that normalized by setting the average of the target value, a x _{t, i} in the above formula (1) When setting the average value (m), the standard score (X _i ) standardized using the average value (m) and σ can be linearly converted to the standard value z (0,1). In this case, equation (1) is simply expressed as Xi = 1 + zi / n through the process of the following equation (3).

(3)

(3)

Here, zi is given by the following equation (4).

(4)

(4)

For example, if the score is 3σ or higher, Xi = 1 + 3 / n is determined as a perfect score.

The final score calculation unit 300 calculates the first final score by summing the index values of the indicators obtained by multiplying the standard scores of the indicators or the applied scores of the indicators by the weights w _i set for the indicators. In the case of multiplying the standard score for each indicator by the weight w _i set for each indicator, it can be done when the application score calculation unit 200 does not calculate the applied score, The case of multiplying each of the weights w _i can be performed in a case where the application score calculating unit 200 calculates the application score.

The first final score is the score without additional performance or the evaluator's observation score. In addition, the final score calculation unit 300 may calculate the second final score by adding the additional achievement score or the observed evaluation score of the evaluator to the first final score.

On the other hand, the score of the first final score is, for example, 90 points excluding the evaluation score of the evaluator, 90 points, and the second final score is 100 points including the evaluation score of the evaluator .

The function and operation of the performance evaluation system 10 using the uniform distribution scoring method according to the present invention will be described below by applying more specific numerical data. [Table 4] shows the descriptive statistics of the total subjects (mean, standard deviation, maximum value, minimum value, 6 σ-origin, 6 σ-origin, (Upper).

Number of Raw Points by Individual Indices Researcher's name Department New tasks
suggestion New tasks
Participation Patent Academic Activities Technology Business Revenue Research project
Performance Contribution assignment
Utilization evaluation Additional performance
Sum R001 Groupe 0.0 1334608353.3 4.1 0.0 31308938.0 429786436620.4 0.0 0.0 R002 Group B 10.0 1705485770.0 8.0 1.2 13615098.0 100499494236.0 0.0 1.0 R003 Group C 10.0 1560513491.1 1.8 0.0 22502700.0 79917216999.1 176008363.5 0.0 R004 Groupe 0.0 1097787136.5 5.3 0.0 26608758.0 0.0 0.0 0.1 R005 Group D 10.0 1742704971.2 4.4 0.0 14400000.0 169423934504.6 106757253.8 0.5

Descriptive statistics such as mean, standard deviation, 6σ origin, etc. X1 X2 X3 X4 X5 X6 X7 AVG 6.469799 1053717303.285 2.132886 0.191275168 2125189 98577217902.429 31753429.585 STDEV 7.857306 548992707.181 1.921542 0.36618244 5089478 77434879221.990 67529754.617 STDEV / AVG 121% 52% 90% 191% 200% 78% 2.127 MAX 50 2506044921.246 10 2.01 31308938 429786436620.360 288153212.220 min 0 0.000 0 0 0 0.000 0.000 6s-origin -40.674 2240238939.801 -9.39637 -2.005819471 -28411678 -366032057429.509 -373425098.116

[Table 5] shows that the performance evaluation system 10 using the equidistant scoring method according to the present invention obtains the standard score for each indicator by using the numerical data shown in [Table 4] And the final score is calculated. As shown in [Table 5], ranking (Y_Rank) and percentage rank (Y_Percent, lower%) based on the final score can be shown.

Linear transformation score and final score (Y_90) XL1_8 XL2_12 XL3_10.5 XL4_7 XL5_17.5 XL6_21 XL7_14 Y_90 Y_Rank Y_Percent 3.2 8.634401 7.554545 2.8 17.5 20.11959 6.02708 65.8356205460778 One 98.7% 5.485714 9.699951 10.5 6.217931 11.56606 12.02381 5.974075 61.4675465410559 2 97.4% 5.485714 9.283438 5.631818 2.8 14.54667 12.48739 8.811043 59.0460817217206 3 96.1% 3.2 7.954001 8.536364 2.8 15.92371 14.01123 6.363254 58.7885570352693 4 94.8% 5.485714 9.806884 7.783636 2.8 11.82929 13.16673 7.826447 58.6987007888019 5 91.0%

According to the performance evaluation system and method using the equally divided scoring method of the present invention, the satisfaction of the evaluation results of the evaluator and the evaluator can be improved through objectification and quantification of the researcher performance evaluation. In addition, it is possible to identify the strengths and weaknesses in the business area by objectively grasping the achievement level and so on for each individual performance evaluation index, thereby making it possible to derive the business capacity improvement field. In addition, it is possible to induce the direction of the entire organization required by the management through weight adjustment, thus enabling strategic personnel management.

FIG. 4 is a flow chart of a performance evaluation method using a uniform distribution scoring method according to an embodiment of the present invention, FIG. 5 is a flowchart illustrating a method of calculating a final score by reflecting a weight on a score applied to each indicator according to an embodiment of the present invention FIG.

As shown in FIG. 4, in the performance evaluation method using the equidistant point scoring method according to the embodiment of the present invention, a step of converting the origin score according to the indicators into the standard score according to the indicators (S100) (S200) of calculating the applied score for each of the converted indicators, and calculating a final score by reflecting the weight to the standard score for each indicator or the applied score for each indicator (S300).

Step S100 normalizes the number of origin by the index through the following equation (1).

(1)

(One)

X _i is the standard score of indicator i, x _i is the origin score of indicator i, x _{t, i} is the target score of indicator i, and σ _{o and i} are the origin, which means m _i ± n _i σ _i , Where m _i means the mean of x _i , n _i is a non-zero real number, and σ _i means the standard deviation of x _i .

Step S100 may include a step (S110, not shown) of recalculating the standard score again for the index for which the singular point is found, excluding the singularity. Also, in step S100, x _{t, i} can be set to m _i . The detailed description and the technical effect thereof can be referred to the explanatory part of the standard score converting unit 100 of the performance evaluation system using the equally divided scoring method corresponding to FIG. 1, FIG. 2 and corresponding description, Description will be omitted here.

Step S200 linearly converts the standard scores for each index by the following equation (2).

(2)

(2)

XL _i is the index i applying scores, XL _{i _M} is the index i after the linear transformation peak, XL _{i _m} is the index i after linear transformation flop, X _{i _M} is the culmination of the index i after normalization, X _{i _m} after standardization flop of the index i, X _i denotes the standard score of the index i. XL _{i _M} and XL _{i _} for such settings for _m can see the description part of the Figs. 1, 3 and this applies score calculating unit 200 of using a corresponding one uniformly distributed scoring method and evaluation system, and, repeatedly, The description thereof will be omitted here.

Step S300 may include a step S310 of calculating a first final score by summing up the result values of the indicators derived by multiplying the indexes applied to the indexes by weights set for each index, (S320) of calculating the second final score by summing the additional evaluation results or the evaluation evaluation scores of the evaluator. The detailed description and the technical effect thereof can be referred to the description of the final score calculation unit 300 of the performance evaluation system using the uniform distribution scoring method, and a description thereof will be omitted in order to avoid repetitive explanations.

It will be understood by those skilled in the art that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. It is therefore to be understood that the above-described embodiments are illustrative in all aspects and not restrictive. The scope of the present invention is defined by the appended claims rather than the foregoing detailed description, and all changes or modifications derived from the meaning and scope of the claims and the equivalents thereof are included in the scope of the present invention Should be interpreted.

10: Performance evaluation system using equidistant scoring method
100: Standard scoring unit
200: Applied score calculating unit
300: Final score calculation unit

Claims (5)

Converting the raw scores for each indicator into standard scores for each indicator; And
And calculating a final score by reflecting a weight on the standard score for each indicator. The method according to claim 1,
The step of converting the origin score by indicator into standard score by indicator may be performed by standardizing the origin score by the index through the following equation (1)

(One)
X _i is the standard score of indicator i, x _i is the origin score of indicator i, x _{t, i} is the target score of indicator i, and σ _{o and i} are the origin, which means m _i ± n _i σ _i , Where m _i means the mean of x _i , n _i is a real number except 0, σ _i means the standard deviation of x _i ,
In converting the raw score by index as an index by the standard score, performance evaluation method using the x _{t, i} x _i a mean, uniformly distributed scoring method of selecting a maximum value or designated value. 3. The method of claim 2,
The performance evaluation method using the equidistant scoring method further includes a step of calculating an applied score for each indicator obtained by linearly converting the standard score for each indicator,
The step of calculating an applied score for each index, which linearly converts the standard scores for each index,
The standard score for each index is linearly transformed through the following equation (2)

(2)
XL _i is the index i applying scores, XL _{i _M} is the index i after the linear transformation peak, XL _{i _m} is the index i after linear transformation flop, X _{i _M} is the culmination of the index i after normalization, X _{i _m} after standardization The lowest point of indicator i, and X _i the standard score of indicator i. The method according to claim 1,
The step of converting the origin score for each indicator into a standard score for each indicator may include:
And recalculating the standard score again for the index on which the singularity was found, excluding the singularity,
The step of recalculating the standard score again for the index on which the singularity is found, excluding the singularity,
And a standard score exceeding a preset scale score for each indicator is calculated as the score, thereby excluding the singularity score. The method of claim 3,
The step of calculating the final score by reflecting the weight to the standard score for each index may include:
Calculating a first final score by multiplying the standard score for each indicator or the applied score for each indicator by the weight set for each indicator, and summing the result values of the indicators derived from the indicators; And
And calculating a second final score by adding the additional achievement or the observed evaluation score of the evaluator to the first final score, and evaluating the performance using the uniform distribution scoring method.

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