The measurement of competition is one of the aspects that has become important in companies that have opted for the development of human capital. There are various ways of measuring competence, in this work, using elements related to fuzzy logic, a set of methods for the evaluation and contrast of variables with different degrees of vagueness are exposed, which allow us to narrow the existing uncertainty at the time of evaluate how competitive our groups of people are.
Development.
When we need to know the competitive levels of people or to know the existing competitive gaps, we are faced with how to objectively measure such an intangible aspect. Undoubtedly, the measurement of competition from the profiles required in each environment becomes a rugged and vague topic that we face day by day.
determination-of-labor-competenciesTo solve this problem, there are a series of tools linked to fuzzy logic that allow us to determine results with less uncertainty for subsequent decision-making. There are different methods for determining competencies that allow us to contrast the results obtained and reflect on them.
There are different concepts of competition. After the analysis of various sources, competence is considered to be: "successful results from cognitive and emotional aspects that individuals or groups possess to develop in certain environments".
The use of different methods to determine the competences is part of the measurement process. Having different evaluation methodologies is important for those cases where you want to choose people within certain work groups and need to contrast the results.
When the competence measurement is carried out in order to know how competent the individuals or groups of them are, the use of a single tool is sufficient. In these cases, it is common for competencies to be evaluated based on optimal profiles that are designed with the application of group techniques. To make a more specific evaluation, several measurement methods should be used so that a deep evaluation can be made from the contrast. Below are some methods to measure the competences that are:
- Optimal requirement (d) Highest level requirement (h) Requirement of properties with different importance (Õ). Adequacy coefficient (K)
Practical application
For the best understanding of this work, the explanation will be based on a real application. The Cienfuegos Branch of the consulting firm CONAS, decided to determine the competence of its consultants / auditors and using the aforementioned measurement methods that also served to contrast the measurement results. The experience is detailed below.
For the application of the calculations, a confidence interval (m) is defined for the evaluation of the different profiles . The evaluation criteria are valued in the interval Îm. Table No.1 shows the qualitative ratings given in the confidence interval.
Table No. 1 Valuation Interval.
| Value | Qualification | Value | Qualification |
| one | Perfect | 0.5 | Regular |
| 0.9 | Very good | 0.4 | Rather bad |
| 0.8 | Okay | 0.3 | Pretty bad |
| 0.7 | Pretty good | 0.2 | Bad |
| 0.6 | Rather good | 0.1 | Very bad |
Source: self made.
Through a group exercise with experts and following the concept of competence previously exposed, the corresponding criteria and acceptance intervals were determined. Table No. 2 shows the optimal evaluation criteria for the different competencies.
Table No. 2. Optimal evaluation criteria for determining competence.
| . Item. | Profiles | Optimal evaluation | Optimal assessment requirements |
| one | Productivity | 0.7 | 2880.00 pesos |
| two | Cognitive level | 0.7 | MSc (Master of Science). |
| 3 | Professionalism. | 0.6 | Customer satisfaction |
| 4 | Teamwork | 0.8 | Academic categorization |
| 5 | Professional image | 0.6 | Evaluation |
The determination of productivity was taken as obtaining the results measured in money contributed to the company, taking the planned budget as a reference. This so-called competition due to its non-orthodox character has many detractors, but its pragmatic nature was determined to include it. The cognitive level is related to the knowledge obtained through studies, university and scientific degrees obtained. It was considered that a consultant / auditor should optimally have at least one scientific category (Master of Science). Professionalism would be related to the way knowledge is given so that the opinion of customers regarding the service performed would be an explicit measurer.Teamwork could be evaluated to the ability to interact with an audience or group of people that would be well determined by obtaining the academic categorization that gives mastery in the interaction with people. The professional image would be linked to the means available for the exhibition of knowledge and bearing and personal appearance. Table No. 3 shows the evaluation of the actual profiles of six consultants / auditors of the consulting company in question. The determination of the optimal parameters of the evaluated criteria were determined by means of group techniques with experts. The measurement was carried out with the participation of 6 consultants / auditors determined by the lettersThe professional image would be linked to the means available for the exhibition of knowledge and bearing and personal appearance. Table No. 3 shows the evaluation of the actual profiles of six consultants / auditors of the consulting company in question. The determination of the optimal parameters of the evaluated criteria were determined by means of group techniques with experts. The measurement was carried out with the participation of 6 consultants / auditors determined by the lettersThe professional image would be linked to the means available for the exhibition of knowledge and bearing and personal appearance. Table No. 3 shows the evaluation of the actual profiles of six consultants / auditors of the consulting company in question. The determination of the optimal parameters of the evaluated criteria were determined by means of group techniques with experts. The measurement was carried out with the participation of 6 consultants / auditors determined by the lettersThe determination of the optimal parameters of the evaluated criteria were determined by means of group techniques with experts. The measurement was carried out with the participation of 6 consultants / auditors determined by the lettersThe determination of the optimal parameters of the evaluated criteria were determined by means of group techniques with experts. The measurement was carried out with the participation of 6 consultants / auditors determined by the lettersB, L, G, RCS
Table No. 3 Evaluation of the optimal profiles.
| Item. | Profiles | Optimal fuzzy subset (D 5) | Real fuzzy subset | |||||
| B | L | G | R | C | S | |||
| one | Productivity | 0.7 | 0.7 | 0.7 | 0.7 | 0.7 | 0.7 | 0.7 |
| two | Cognitive level | 0.7 | 0.7 | 0.5 | 0.6 | 0.6 | 0.7 | 0.7 |
| 3 | Professionalism. | 0.6 | 0.5 | 0.4 | 0.6 | 0.4 | 0.4 | 0.7 |
| 4 | Teamwork | 0.8 | 0.7 | 0.6 | 0.7 | 0.6 | 0.6 | 0.7 |
| 5 | Professional image | 0.6 | 0.6 | 0.6 | 0.5 | 0.5 | 0.6 | 0.7 |
Source: self made
With these data registered and evaluated by a group of experts, we can apply the different tools declared at the beginning that will allow for a comprehensive evaluation of the specialists,
- Approach to the optimal process (d)
Formula (1) is used to determine the relative distance from the optimal competition. Then we have:
d (D5, Pj) = 1 / n ïm i - m j ê = 1 / n ïm i1 - m j1 ç + ïm i2 - m j2 ç + ïm in - m jn ç (1)
Where:
D 5 = Fuzzy subset of optimal competition.
P J = Fuzzy subset of actual skills.
N = Number of selected competitions.
m I = Assessment of optimal competition.
m j = Assessment of actual competence assessed
From this formula the real profiles of the different evaluated are evaluated and their relative distances to the optimum required are calculated. Substituting in (1) we have to:
| d B = 0.04 | d G = 0.08 | d C = 0.06 |
| d L = 0.12 | d R = 0.1 | d S = 0.04 |
Then for this distance the consultants / auditors establish that:
d S = d b < d C < d G < d R, < d L
This method is widely used for its simplicity and objectivity, being able to evaluate the optimal competences that are to be achieved with the possibility of including a large number of variables.
2.0 Highest level requirement (h)
For this case, the analysis of real competences is used against those of the highest level, using formula (2) for its calculation and analysis.
h (D5, Pj) = 1 / n (2)
and the required competence value has the maximum value in the confidence interval (1). Finally, the relative distances are calculated having:
| h B = 0.34 | h G = 0. 38 | h C = 0.4 |
| h L = 0.44 | h R = 0.44 | h S = 0.3 |
Then: h S, < h B < h G <h C < h L = h R
The one with the smallest distance will be the most competent in this measurement. This method of measuring competence is used to contrast with other methods since its individual application would lead us to evaluate maximum competencies that are sometimes not as convenient.
- Requirement of properties with different importance (Õ).
For the analysis, starting from the requirements of properties that do not have the same importance, a summation of the optimal profiles is made and then they are weighted according to the importance of each of the profiles determined in the selection. The basic formulas of this method are as follows:
Õ (D5, Pj) = V 1 ïm i1 - m j1 ç + V 2 ïm i2 - m j2 ç + V 3 ïm in - m jn ï + V 4 ïm in - m jn ï +…. V n ïm in - m jn ï (3)
Where V i = w i / w n (4) and w are the competing weights.
Then if W = 28 we have table No.4
Table No.4 Weights
| Coefficient W | W 1 | W 2 | W 3 | W 4 | W 5 |
| (28) | 7 | 5 | 6 | 6 | 4 |
| Coefficient V | V 1 | V 2 | V 3 | V 4 | V 5 |
| 0.25 | 0.18 | 0.21 | 0.21 | 0.14 |
Source: Own elaboration
Then the formulation substituting in (3) is as follows:
Õ (D5, Pj) = 0.25 ïm i1 - m j1 ç + 0.18 ïm i2 - m j2 ç + 0.21 ïm in - m jn ï +0.21 ïm in - m jn ï + 0.14 ïm in - m jn ï
For each evaluated consultant, a coefficient is obtained from the selected profiles. Whoever has the lowest coefficient is the most suitable. Then we have:
| Õ B = 0.065 | Õ G = 0.056 | Õ C = 0.084 |
| Õ L = 0.172 | Õ R = 0.116 | Õ S = 0.056 |
Then: Õ S = Õ G < Õ B < Õ C < Õ G1 < Õ L
This method of measuring competences by weighing them according to their importance is widely accepted, since it is more objective when one wants to evaluate certain competences, avoiding the bias that conventional means produce.
- Adequacy coefficient (K)
The adequacy coefficient (K), is a relationship that takes into account the previous criteria (optimal, ideal and weighted) and is a way to comprehensively measure people's competence. This method responds to the formulation:
K (P ® I) = 1 Ù (1- m j + m i) (4) and adding all the coefficients
K (P, i) = 1 / n K (P ® I) (5)
Substituting in (4) and (5) we have
| : K B = 0.97 | K G 0.88 | K C = 0.92 |
| K L = 0.88 | K R = 0.89 | K S = 0.96 |
Then: K B > K S > K G > , K c > (K G1, K L)
The result of the total sum of all the coefficients will be the resulting coefficient of the element. In this case, the higher the coefficient, the more feasible the result will be.
Each of the evaluation methods based on relative distances gives criteria that can be contrasted for better decision-making, as shown in table No. 5
Table No. 5 General results
| Item | d (D5, Pj) | h (D5, Pj) | Õ (D5, Pj) | K (P ® I) |
| B | one | two | two | one |
| L | 4 | 4 | 5 | 5 |
| G | two | 3 | one | 3 |
| R | 3 | 4 | 4 | 5 |
| C | 3 | 4 | 3 | 4 |
| S | one | one | one | two |
Source: self made
General Analysis .
Depending on the interests of the organization, specific and general analyzes can be carried out according to the degree of competence and the valuation method used. Of the results that are exposed in the table No. 5 can be said:
In general sense, the competence of people in descending order is S, B, G, RC and L, despite this statement we could also say that this group of consultants / auditors have a competence that coincides with the interval (according to the first criterion) and that can lead us to various evaluation analyzes. This assessment is important when you want to enter new people.
In the same way, we could say that from the more academic point of view (second criterion) the consultant "S" is the most competent that the group is furthest from this stage because its interval is in the interval, which represents a logical result.
Competencies were determined related to the results that caused divergent opinions but we tried to strictly follow the concept of defined competence.
According to what is intended with each tool used, we can draw the particular conclusions, being able to know which is the most complete or optimal for a given activity. Of course, the determination of the competency gaps is a result that will allow making a successful training plan to reduce that gap over time.
Despite the usefulness of these approaches in groups, it is very popular for companies to use more of the first method outlined related to determining optimal competencies.
Conclusions.
The determination of competences using fuzzy mathematics is a way to measure individual and group competence with less uncertainty and can be used at the managerial level for a deeper knowledge of the intellectual capacities of staff or working families.
The determination of the competences under these methods allows us to analyze from many points the groups of people who interact in a company. The most important thing is not to know which is the most competitive or the order of competition, but to be certain of group competitiveness.
Bibliography.
- Artola Pimentel, L. (2004), Mathematical Procedure to Evaluate the Transit towards World Class Companies., Projections Vol. 21, N o 2, pp. 127-139, August 2002. Universidad Católica del Norte, Antofagasta - Chile, generalidadesCoezo, Y (2000), Lógica Difusa, http://www.dei.uc.edu.py/tai2000/logicaCuesta Santos A. (2001), Management by Competences 2001 Editorial Academia.CUJAE (2000) Seminar: Business Management in Uncertainty Lozano Gutiérrez, M, Fuentes Martín, F. (2001), Fuzzy treatment of the intangible in business valuation, http://www.eumed.net /cursecon/libreria/index.htm, 2001
Cuesta, Santos (2001) Management by Competition, Editorial Academia
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