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ISSN : 1598-7248 (Print)
ISSN : 2234-6473 (Online)

Industrial Engineering & Management Systems Vol.19 No.3 pp.657-668
DOI : https://doi.org/10.7232/iems.2020.19.3.657

Finding the Causal Relations among Key Competencies in Microbreweries: A Multi-Criteria Decision-Making Approach

João Sidou Dias, Milad Yousefi*

Department of Industrial Engineering and Transportation, Universidade Federal do Rio Grande do Sul – UFRGS, 90035-190, Porto Alegre, RS, Brazil

^*Corresponding Author, E-mail: Yousefi.milad@gmail.com

Received: November 29, 2019 Review: May 4, 2020 Accepted: May 25, 2020

ABSTRACT

The brewing market in Brazil goes through an important transformation where the craft beer, which is carried out in the so-called “microbreweries” has gained more space and consumers. Driven by the entry of increasingly new microbreweries, competition in an unstable economic environment makes the survival of these small and medium-sized enterprises (SMEs) difficult. SMEs need to constantly improving their human resource in order to survive in the business arena. This paper tries to extract the competencies using a competency model for head brewer job position. Then a decision-making trial and evaluation laboratory (DEMATEL) method is used to find the causal relations among key competencies in Brazilian microbrewery industry. The competencies are in four groups including: managerial, interpersonal, technical and personal. The results show that the managerial group of competencies is the most important group in head brewer job position. The results show that the “active listening”, “mental agility”, “emotional resilience” and “proactivity” have the highest level of influence on the other competencies. To the best our knowledge, this is the first application of competency model and DEMATEL in microbrewery industry.

Keywords : Competency Model , Multi Criteria Decision Making , DEMATEL , Microbrewery

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1. INTRODUCTION

The brewing market in Brazil has perceived what has been known as craft brewing revolution. According to the Brazilian Association of beer industry (CervBrasil, 2017), this market has reached to nearly 14 billion liters per year, which is the third biggest in the world and about 0.7% of that corresponds to craft beer. The Unit-ed States - the pioneer in the industry – had this per-centage in 1994 and tripled it in 1998 where currently this ratio reaches to almost 15%. Consequently, the analysts conclude that Brazil still should expect a meaningful increase in craft beer market. Despite the economic crisis, the number of craft breweries increases yearly. Brazil reached to the number of 889 microbrew-eries at the end of 2018.

Despite the observed growth in the market, the mi-crobreweries must be constantly looking for ways to improve their internal processes and enable them to remain in the market. In this highly competitive envi-ronment, most companies are new with only a few years of experience in the market. Therefore; in most cases their processes are not fully structured. The hu-man resource selection process in SMEs is usually in-formal and without technical structures. Consequently, they have difficulty in finding the right person for their vacant positions.

According to Kashi (2015) and Kashi and Franek (2014), a competency model represents a set of compe-tencies that are necessary for performing a specific job or a set of jobs; including personal characteristics, skills and knowledge. All key positions of enterprises need to have models of skill competencies developed as a sup-port for hiring new staff or improving the existing staff.

The head brewer is one of the key job positions in a microbrewery that is responsible for everything that is related to the beer production process and the related operations. This position involves many tasks such as: managing other brewers and assistants, decision-making related to purchasing and suppliers, participating in meetings with customers, suppliers etc., managing re-sources, developing new recipes and products, and set-ting production goals (Partnership 2019).

Regardless the size of a microbrewery the head brewer position is essential. For this reason, the head brewer position is chosen to do this study. In this job position, a set of activities can be done by the same employee or in some cases, they can be outsourced. Therefore, the head brewer is the most important job position in this market. In this way, the objective of this study is to outline the competency model of the head brewer position in microbreweries.

Multi-criteria decision-making methods can be found in different fields of study from healthcare to economic problems (Yousefi 2017;Yousefi et al., 2020). The Decision-Making Trial and Evaluation Laboratory (DEMATEL) is a multi-criteria decision-making ap-proach that breaks down the problems into factors or components to find the interrelation between them then divide them into cause and effect groups (Lada et al., 2020). This method provides cause-effect diagrams where can clearly show the relations of cause and effect factors. Theses diagrams deliver a more in-depth analy-sis to identify the best solution of a given problem. It is possible to use DEMATEL method to understand both the casual relations between groups of competencies and each individual competency (Bouzon 2015).

The need for improvement in staffing process and professional development in head brewer position are two of main motivations for this research. In order to obtain he objective of this paper a DEMATEL method is used to analyze the competency model for the head brewer job position. The achieved results identify the most important competencies as well as the most influ-ential competencies over others for this job position.

The remainder of this paper is as follows: the background of study is covered in the second section. The third section concentrates on the research method-ology using in this paper. The achieved results are shown in fourth section. Finally, the conclusions and future studies are discussed in the last part.

2. RESEARCH BACKGROUND

There is a distinct and particular production pro-cess for each beer type. However, they all follow the same steps and they need four main ingredients includ-ing water, malt, hops and yeast (Baldo et al., 2014;Olajire, 2020). At this time most breweries in Brazil are “American Light Lager” type, and do not follow the so-called German beer purity law (Reinheitsgebot) that determined in 1516 that beers produced in Bavaria con-tained only water, malt and hops (Bonato 2016). Thus, despite using cereals without malt in their formulation, the beers follow the same basic process. Figure 1 demonstrates the stages of brewing process.

The head brewer is responsible for everything that relates to the process of beer production in the routine of a microbrewery. A qualified head brewer needs to have some competencies to be able to do this job. Ac-cording to Seema Sanghi (2007), competencies are a set of attributes that make someone qualified enough to work in a position. These attributes go beyond the theo-retical knowledge and skill. Competencies refer to the ability to master knowledge and having total conditions of practicing it in day-to-day tasks.

A model of competency is an organized structure with the necessary competencies for performing in a given process or activity. Individual competencies are appropriately allocated in models of competency there-fore; they can be studied to assign the right person to the right position within an organization’s workforce (Marrelli et al., 2005).

The applications of DEMATEL in competency models in the literature are studies to understand the relation between them. Figure 2 to 4 show the map of keywords based on a co-occurrence network of studies in Web of Science using keywords of DEMATEL and competency. Map of co-occurrence network depicts the relation between DEMATEL and competency models using VOSviewer software (Jan and Ludo, 2010).

The competency models might have different for-mats and they can be adapted according to the needs of organizations. A common way is to determine com-mon competencies of all areas firstly and then add spe-cific competencies to each function. Grouping compe-tencies into subgroups facilitates understanding of the model.

2.1 Decision-Making Trial and Evaluation Laboratory

The DEMATEL method was developed by Fontela and Gabus (1974) in the Science and Human Affairs Program of the Battelle Memorial Institute of Geneva for the research and problem solving of complex and interrelated groups. Although hierarchical decision-making methods are widely common, they lead to a linear activism that neglects the interrelations between factors and feedbacks. This drawback becomes more significant when the possible solutions are connected and one can influence others (Tzeng et al., 2007). To avoid this problem, the DEMATEL method decom-posed the complex problems into factors or compo-nents. The analysis from DEMATEL determines all the exerted and received influences for all components in a problem. For doing that, DEMATEL provides a diagram that can clearly show the importance of each compo-nent as well as its relation with other components (cause or effect). Based on this information we can choose the best solution for a given problem (Wu and Lee, 2007).

To implement a DEMATEL model, experts are in-terviewed and asked to classify the relations between factors of a complex system. Evaluating the degree of influence generates a hierarchy between the criteria and the direction and intensity of their relations (Fontela and Gabus, 1976). The process of DEMATEL method as a final product provides a visual representation that shows how the interviewees see the whole system (Tzeng, Chiang, and Li 2007).

3. RESEARCH METHODOLOGY

The research methodology of this study contains three main steps:

(i) Determining the model of competency for head brewer in microbreweries,
(ii) Constructing the questioner and interviewing experts and
(iii) Application of the DEMATEL method.

First, a competency model based on the activities of head brewer in microbreweries is built. This model is adapted from study of Kashi (2015) that is originally for the position of process engineer in automotive indus-try. After extracting the factors from literature, the ex-perts were asked to modified them based on at hand case study. The competency model in this study consists 4 main factors and 18 components that are demon-strated in Figure 5.

Based on the competency model, a questioner is created to be used during the face-to-face interviews with experts. The comparison matrix should be filled on a scale of 0 to 4, according to the degree of influence that one competency has on the others according to the interviewees. Table 1 shows the correspondence be-tween the numerical responses and their degree of influ-ence.

To conduct the interviews, eight experts with experience in the beer market were selected from four different microbreweries located in the capital city of Rio Grande do Sul state of Brazil (Porto Alegre). The profile of experts can be found in Table 2.

The definition of each competency is extracted from the study of Seema Sanghi (2007) and they can be seen in Table 3. These definitions are used during the interviews to explain the competencies to the respond-ents. In case of any doubt, additional explanations are added by giving real case examples.

3.1 Application of DEMATEL

Figure 6 demonstrates the even phases for applica-tion of DEMATEL method. The following studies used the same steps to introduce DEMATEL: Tzeng et al. (2007), Wu and Lee (2007), Wu (2008), Yang et al. (2008), Sumrit and Anuntavoranich (2013) and Rodrigues (2017). In our case, the first two phases that are “defining the objectives” and “data collection through interviews of experts” are same as step (i) and step (ii) that are mentioned in the last section.

3.1.1 Phase 1

This phase defines which criteria and factors will be considered in the analysis. This step should be done with the help of decision makers of the model.

3.1.2 Phase 2

In phase 2, the experts are interviewed in order to evaluate the degree of influence for each of n factors (criteria) on the others. This process is performed by constructing a square matrix n by n that will be fill by the interviewer. The number of experts can vary to achieve the most accurate result possible. The sample size for DEMATEL is discussed in different studies and the sample size of 8 to 45 is considered as acceptable (Karaşan and Kahraman, 2019;Nakano et al., 2009;Prakash and Srivastava, 2019;Rajeev, 2016;Sumrit and Anuntavoranich, 2013;Tzeng et al., 2007).

3.1.3 Phase 3

The expert’s opinion on the degree of influence between the factors is measured from a numerical scale 0 to 4 (Table 1). Matrix Z will be created using the data from matrix that is created in each interview. In this matrix each element Z_ij is obtained from the average of the corresponding elements of all respondents.

z_{i j} = \frac{z_{i j}^{1} + z_{i j}^{2} + z_{i j}^{3} + ... + z_{i j}^{p}}{p}

(1)

3.1.4 Phase 4

In this phase, the initial direct influence matrix D is calculated. The matrix D is obtained from the normali-zation of the mean matrix Z calculated in phase 3. Based on matrix D, the initial influence that each of the elements exerts or receives from the others is calculated using Eq (2), (3) and (4). Then a square matrix with el-ements from 0 to 1 is obtained.

s = \frac{1}{\max (m a x_{1 \leq i \leq n} \sum_{j = 1}^{n} z_{i j}, m a x_{1 \leq j \leq n} \sum_{i = 1}^{n} z_{i j}}

(2)

\begin{array}{l} D = [d_{i j}] = [s \times z_{i j}], \\ p a r a (s > 0 e i, j = 1, 2, 3, ..., n) \end{array}

(3)

\underset{m \to \infty}{l i m} d^{m} = {[0]}_{n \times n}, w h e r e D = [d_{i j}]

(4)

3.1.5 Phase 5

Equation (5) shows how the total relation matrix T (Eq (5)), which uses the identity matrix of the same or-der as T, is calculated.

T = D \times {(I - D)}^{- 1}

(5)

T = [t_{i j}], i, j = 1, 2, 3, ..., n

(6)

3.1.6 Phase 6

The sums of the rows (i) and the columns (j) gener-ate two vectors W (Eq (7)) and V (Eq(8)). These vectors represent the total value that one factor exerts on others.

R_{i} = {[R_{i}]}_{n \times 1} = {(\sum_{j = 1}^{n} t_{i j})}_{n \times 1}

(7)

C_{i} = {[c_{i}]}^{'}_{1 \times n} = {(\sum_{i = 1}^{n} t_{i j})}_{1 \times n}^{'}

(8)

3.1.7 Phase 7

In this phase, the cause-and-effect diagram is constructed. This diagram provides a visual analysis of the relations between vectors R_i and C_i. The horizontal axis (X) represents the “Importance” and the vertical axis (Y) represents the “Influence” of each factor on others. The relations between factors are shown with arrows.

To eliminate the weak relations, a threshold is used and only the relations higher than the threshold are considered. The threshold can be calculated using Eq (9). The threshold can be calculated with one or 1.5 standard deviations obtained from the elements of total relation matrix T in Eq (5). More details on choosing the threshold will be given in results section.

a = \frac{\sum_{i = 1}^{n} \sum_{j = 1}^{n} [t_{i j}]}{N}

(9)

4. RESULTS

The data collection is done through face-to-face in-terviews. Afterwards, the DEMATEL method is applied for five times to obtain the results. Four out of five ap-plications of DEMATEL method are for each group of competencies without considering other groups. After that, another time the model runs to find the interrela-tion between four groups.

For the analysis of cause-and-effect relations dia-grams, it is necessary to correctly interpret what is being demonstrated: The higher the value corresponding to the X-axis, the greater its importance and the higher the value of the Y-axis the greater its influence on other competencies. It should be noted that, this value of Y-axis can be negative or positive. A positive number means that the factor is influencing other factors while a negative value means that it receives influences from other factors. In other words, the factors with positive values are causes and the ones with negative values are effects. The arrows point to the most significant cause-effect relations between the competencies based on the determined threshold. This multicriteria decision-making approach is programmed in the Scilab that is a free and open source software.

Figure 7 shows result of the first execution of the model that is the cause-effect diagram among all com-petencies from all groups. The managerial competencies appear as the most important ones. Moreover, in term of influencing other competencies they show strong relation. The threshold in this step is equal to 0.4453, that comes from the average of the elements of the total matrix plus 1.5 standard deviation. That means only the relations stronger than this number are shown in Figure 7. It is worth mentioning that in this diagram a threshold with one standard deviation is too small to eliminate weak relations therefore; 1.5 standard devia-tion is used to calculate the threshold.

The cause and effect diagram of managerial com-petencies (without considering the competencies from other groups) is shown in Figure 8. The diagram demon-strates that the leadership and change management are the most important competencies in this group. Howev-er, administrating the information is the most influential competency. For this analysis, a threshold of 3.339 was used, referring to the mean of the total relation matrix elements plus a standard deviation.

The cause-and-effect diagram of interpersonal skills can be found in the Figure 9. In this diagram, the negotiating competency shows the least importance and at the same time, receives the highest influence from active listening and effective communication. Although the importance of active listening and cooperation are almost the same, the active listening influence negotiat-ing, cooperation and motivating others. While the coop-eration is an effect factor. The threshold to make this diagram is equal to 1.958, which is equivalent to the mean of the total matrix plus a standard deviation.

As it can be seen in Figure 10, the strategic thinking is the most importance one and it has the highest influ-ence among technical competencies considering a threshold of 1.937. The threshold is calculated same as before. The least important factor in this group is the technical knowledge but it influences the strategic think-ing that is the most important competency of this sec-tion.

Figure 11 shows the case and effect diagram for group of personal competencies. The most important competency is mental agility and the least important one is emotional resilience. In terms of influence, the creativity and proactivity are influenced by the mental agility. The threshold in this diagram is equal to 2.974. After applying this threshold, we found out that the emotional resilience competency has no significant in-fluence on any other competency of this group. The influence that emotional resilience receives from other competencies also is negligible.

After analyzing the interrelations between compe-tencies, in this section we are going to rank the compe-tencies in terms of their importance. In order to do that, the weight of R_i + C_i vector of each competency is cal-culated. The weight for each competency is shown in Table 4. The most important competencies are leader-ship, problem solving and administrating the infor-mation with 6.1%, 5.98% and 5.95% respectively.

Based on the ranking of all competencies, we can calculate the importance of each group that is equal to the sum of weights of its members. Table 5 shows that the two groups of managerial and interpersonal compe-tencies with 29.43% and 26.89% are more important than the other two groups. The difference between weights of technical group and personal group is negligi-ble.

5. DISCUSSION

Brazilian beer market is going through a period of great expansion, therefore the microbreweries opened in recent decades are challenged to reinvent themselves continuously to survive and grow. Microbreweries face constant challenges in the transition to becoming com-panies with a level of organization that allows them to survive, grow and increase market share.

The objective of this paper was to study the interre-lations between the competencies assigned to the posi-tion of head brewer in the microbrewery market. Ana-lyzing the interrelations between competencies make managers able to give priority to the right aspects of this position, whether in hiring staff or in training them. To this end, the DEMATEL method effectively trans-formed the interviews of experts into relevant infor-mation for analyzing the competencies involved in the head brewer position.

The head brewer position can be categorized as a managerial position; hence, it is not surprising that the results show that the group of managerial and interper-sonal competencies overcome the other competency groups. Although the technical knowledge is very im-portant, experts believe that the head brewers are able to learn technics during their work, while the set of managerial and interpersonal skills are more difficult to be improved in a short time.

One of the most important advantages of DE-MATEL is the ability to demonstrate the interrelations between factors (Karaşan and Kahraman, 2019). In this sense, the results show that the competencies “active listening”, “mental agility”, “emotional resilience” and “proactivity” have the highest level of influence on oth-er competencies. When competencies are categorized as a “cause”, they can influence those that are categorized as “effect”. In other words, an improvement in a cause competency will improve the cause competencies that are connected with them.

This study focuses on a head brewer job position in microbreweries. The same approach, after some modi-fications can be applied to other positions in mi-crobreweries as well as macro breweries. Similarly, the use of the DEMATEL method with a competency mod-el relevant to the position can be used in other functions. As a future work, it is also possible to verify effective selection tools based on the intended competencies aimed at this sector.

ACKNOWLEDGEMENTS

Authors would like to thank all those who partici-pate in the interview and make this research possible. The authors also thank the research coordination of the Brazilian ministry of education (Coordenação de Aper-feiçoamento de Pessoal de Nível Superior – CAPES, Process n. 88882. 316153/2013-01), for the financial support received to conduct this research.

Figure

Figure 1.

Stages of beer production (Olajire 2020).

Figure 2.

Map of keywords based on a co-occurrence network (Competency).

Figure 3.

Map of keywords based on a co-occurrence network (Model).

Figure 4.

Map of keywords based on a co-occurrence network (DEMATEL).

Figure 5.

Competency model for head brewer position extracted from (Kashi, 2015;Seema Sanghi, 2007).

Figure 6.

Decision making trial and evaluation laboratory steps.

Figure 7.

The cause and effect diagram considering all competencies.

Figure 8.

The cause and effect diagram of managerial competencies.

Figure 9.

The cause and effect diagram of interpersonal skills.

Figure 10.

The cause and effect diagram for technical competencies.

Figure 11.

The cause and effect diagram for personal competencies.

Table

Table 1.

Measurement scales used in DEMATEL

Level of influence	Numerical value
No influence	0
Very low influence	1
Low influence	2
High influence	3
Very high influence	4

Table 2.

The profile of the respondents

No expert	Sex	Age	degree level	Current job position	Experience in brewery	Experience in the current position
1	Male	29	Bachelor’s degree	Production/Maintenance supervisor	17 months	15 months
2	Female	26	Bachelor’s degree	Quality control manager	5 years	12 months
3	Male	30	Post-graduate	Head brewer	5 years	3 years
4	Female	45	Post-graduate	Sommelier	6 years	18 months
5	Female	38	PhD	Head brewer	5 years	3 years
6	Male	42	Bachelor’s degree	Head brewer	8 years	5 years
7	Male	29	Bachelor’s degree	Head brewer	8 years	5 months
8	Male	30	Bachelor’s degree	Commercial director	8 years	5 years

Table 3.

Definition of competences

Competency	Definition
Information management	The ability to react to different kinds of information.
Problem solving	The ability to solve problems.
Leadership	The ability to lead and influence people.
Delegating	The ability to delegate tasks.
Change management	The ability to manage and react to imposed changes.
Effective communication	The ability to convey information to another effectively.
Negotiating	The ability to negotiate.
Active listening	The ability to listen and consider other opinions.
Cooperation	The ability to work with others.
Motivating others	The ability to motivate others.
Technical knowledge	The relevant knowledge of the activities.
Business knowledge	The relevant knowledge of the general business functions.
Strategic thinking	The strategic thinking to execute the activities.
Analytical thinking	The analytical thinking to execute the activities.
Proactivity	The ability to react to problems in advance to prevent them.
Creativity	The ability to be inventive in problem solving.
Mental agility	The ability to react quickly.
Emotional resilience	The ability to deal with adverse situations.

Table 4.

Ranking the importance of competencies

Ri+Ci: Importance vector.

Ri-Ci : Influence vector.

Group	Competency	Ri	Ci	Ri+Ci	Ri-Ci	Weight	Ranking
Managerial	Information management	7.61	7.39	14.99	0.22	5.95%	3
Problem solving	7.13	7.93	15.06	-0.79	5.98%	2
Leadership	7.57	7.79	15.36	-0.22	6.10%	1
Delegating	6.96	7.18	14.14	-0.22	5.61%	7
Change management	6.96	7.62	14.58	-0.65	5.79%	5
Interpersonal	Effective communication	6.99	6.68	13.67	0.30	5.43%	11
Negotiation	5.88	7.10	12.97	-1.22	5.15%	17
Active listening	7.20	6.22	13.41	0.98	5.33%	15
Cooperation	6.90	7.25	14.15	-0.35	5.62%	6
Motivating others	6.47	7.06	13.53	-0.59	5.37%	12
Technical	Technical knowledge	6.66	6.27	12.93	0.39	5.13%	18
Business knowledge	6.92	6.96	13.87	-0.04	5.51%	9
Strategic thinking	7.40	7.47	14.87	-0.07	5.90%	4
Analytical thinking	6.74	6.72	13.46	0.01	5.34%	14
Personal	Proactivity	6.98	6.52	13.50	0.46	5.36%	13
Creativity	6.89	6.52	13.41	0.36	5.32%	16
Mental agility	7.51	6.62	14.13	0.89	5.61%	8
Emotional resilience	7.20	6.64	13.84	0.55	5.49%	10

Table 5.

Ranking the importance of group competencies

Ranking	Group of competencies	Weight
1	Managerial	29.43%
2	Interpersonal	26.89%
3	Technical	21.89%
4	Personal	21.79%

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