Integrating systems thinking skills with multi-criteria decision-making technology to recruit employee candidates

Highlights

• Hire candidates using systems-thinking skills based supplemental recruiting tool.

• Fuzzy multi-criteria decision-making approaches are developed to rank candidates.

• Job-Fit Recruiting strategy developed to find candidates for a specific position.

• Flexible Recruiting strategy developed to seek candidates with the highest skills.

• Rank candidates based on fuzzy multi-criteria decision-making approaches.

Abstract

The emergence of modern complex systems is often exacerbated by a proliferation of information and complication of technologies. Because current complex systems challenges can limit an organization's ability to efficiently handle socio-technical systems, it is essential to provide methods and techniques that count on individuals' systems skills. When selecting future employees, companies must constantly refresh their recruitment methods in order to find capable candidates with the required level of systemic skills who are better fit for their organization's requirements and objectives. The purpose of this study is to use systems thinking skills as a supplemental selection tool when recruiting prospective employees. To the best of our knowledge, there is no prior research that studied the use of systems thinking skills for recruiting purposes. The proposed framework offers an established tool to HRM professionals for assessing and screening of prospective employees of an organization based on their level of systems thinking skills while controlling uncertainties of complex decision-making environment with the fuzzy linguistic approach. This framework works as an expert system to find the most appropriate candidate for the organization to enhance the human capital for the organization. Several large industries, among others, Boeing, the government such as the Army, Military Academy, and National Science Foundation, highlighted the significance of having qualified (systemic) individuals who can successfully deal with complex systems problems. The correct recruiting decision will reduce the rate of job turnover and also help organizations to eliminate unnecessary budget allocated for costly recruitment processes. The proposed framework is intended to first evaluate the pool of applicants according to their level of systems thinking skills and then rank them based on the recruitment strategy and workforce needs of the organization. To achieve the purpose of the study, two recruiting strategies are adopted from the human resource management literature 1) Job-Fit Recruiting strategy—finding candidates who are most aligned with a specific position requirement and 2) Flexible Recruiting strategy—finding candidates with the highest potentials. The proposed framework is validated using a real case study in a US large-scale organization.

Introduction

A successful organization must have in place an effective system of recruitment in order to hire the best candidates for particular positions (Leisink & Steijn, 2009). The organization’s recruitment system is essential, and as Ahmad and Schroeder (2002) stated, “paying close attention to recruitment and selection is consistent with one of the basic principles of quality management, which is the notion that prevention is better than a cure. It is hard to modify (cure) negative behavioral traits of employees. Therefore, it is best to check for requisite behavioral traits during the recruitment and selection process to prevent a mismatch between the technical and social systems”. An organization with “staff [employees] who consistently fulfill their roles and are capable of taking on increased responsibilities,” has a competitive advantage over their rivals when dealing with complex system problem domains (Cole, 2002, p. 172). Employees’ attributes, including ability and motivation, shape the organization’s performance and should be considered in the recruitment process (Delery & Shaw, 2001). Among the skills a high-quality employee should have is the ability to engage in turbulent and complex environments; this ability is referred to as systems thinking (Checkland, 1999, Schiuma et al., 2012). Systems thinking is the thought process that promotes thinking and speaking in a new holistic language (Checkland, 1999).

A report “Future of Jobs” published by World Economic Forum in 2016, surveyed strategic leaders and upper management of top 100 companies of nine major industries, including basic and infrastructure, consumer, energy, financial services and investors, healthcare, information and communication technology, media, entertainment and information, mobility, and professional services in 15 major developed and emerging economic countries to find employment, skills, and workforce strategies needed for the fourth industrial revolution. The report discussed complex problem solving and systems skills as important skills for the next five years, outpacing the need for other skills such as people management, emotional intelligence, content skills, etc. Similarly, several large industries, among others, Boeing, the government such as the Army, Military Academy, and National Science Foundation, highlighted the significance of having qualified individuals who can successfully deal with complex systems problems. In the literature, systems thinking plays a significant role by providing tools and techniques to solve complex systems problems (Boardman and Sauser, 2006, Gorod et al., 2008, Hossain, Jaradat, Hamilton, Keating, & Georger, 2020, Jaradat et al., 2018, DeLaurentis, 2005). However, the performance of existing tools and techniques are limited by their design and integrity to facilitate comprehensive solutions for social-technical problems. For instance, many of the existing tools focus on specific domains such as education to assess students' systems thinking skills (Frank, 2010, Camelia and Ferris, 2016, Frank, 2002). Also, some other tools have limited capabilities as they evaluate one or few aspects of systems thinking (Dolansky and Moore, 2013, Hossain, Dayarathna, Nagahi, & Jaradat, 2020, Plate, 2008, Hopper and Stave, 2008). In this study, researchers used a comprehensive tool (Jaradat, 2015), which consists of seven dimensions of systems thinking skills as selection criteria to find systems thinkers based on the organizational job requirements. The proposed selection criteria will reshape the traditional recruiting process by assisting organizations in determining individuals who can work in the complex systems problem domain.

Over the past decade, the person-job fit has been a trending topic in the industry because of the high turnover and the cost of employing new staff (Hoffman and Woehr, 2006, Liu et al., 2010). Many studies have emphasized the advantages of matching Individuals’ skills with job requirements as it decreases the likelihood of job resignations (Dahling and Librizzi, 2015, Hesketh, 1993, Schneider et al., 1995). Thus, it is important to compare an individual’s skillset with the degree of work complexity in an organization while examining the other qualifications in the recruitment process. The proposed recruitment framework investigates the individuals' capability of dealing with complex system problems using seven dimensions (level of Complexity, Independence, Interaction, Uncertainty, Change, Systems Worldview, and Flexibility). Through the broad spectrum of determining individuals' systems thinking skills, this study assists recruiters in finding the right candidate to fit the posted job position based on the candidate's skill set.

Employees are challenged to maintain and elevate their performance during periods of increasing complexities and pressures due to factors such as a reduction in workforce, resources, and costs. These challenges include high levels of 1) complexity – large scale systems with a high flow of information, technical and contextual issues; 2) integration – systems combined operationally, managerially, or geographically to produce new goals; 3) interdependence – mutual influence among systems and their related elements, making analysis difficult; 4) evolutionary development – issues related to technological changes, the evolution of requirements, and evolution of the social infrastructure because of the interaction with the surrounding environment; 5) uncertainty – incomplete knowledge of systems and the unintended consequences they experience; 6) systems worldview – compatibility among multiple perspectives and consideration of technical and nontechnical issues related to large complex systems; and 7) flexibility – the challenges associated with the ability to add, adjust or remove both physical components and functions (Jaradat, 2015, Keating, 2008). These challenges, which are commonly found in complex systems, blur the lines between technical, social, organizational, managerial, and policy considerations (Boardman and Sauser, 2006, Gorod et al., 2008, Jaradat et al., 2018, Nagahi et al., 2020, DeLaurentis, 2005). To address these challenges, it is necessary to build a cadre of qualified employees who can take a more holistic approach to effectively engage in complex systems. With the approach proposed in this study, organizations can select and hire candidates based on their systems thinking skills, including complexity, integration, interdependence, evolutionary development, ambiguity, uncertainty, systems worldview, and flexibility (Jaradat et al., 2020, Jaradat, 2015, Jaradat et al., 2018, Nagahi, Jaradat, El Amrani, Hamilton, & Georger, 2020). This new approach can supplement the current methods used to hire candidates and can be useful to identify candidates for positions. For example, if a specific job position requires an individual with high-level systemic thinking skills, then it is appropriate to hire a more “holistic” systems thinker. On the other hand, if the position requires individuals with a focus on a reductionism-based approach, then it is appropriate to select a reductionist-oriented thinker.

There is a literary gap regarding the utilization of systems thinking when making hiring decisions in order to increase an organization’s ability to respond effectively to organizational complex systems problems. The primary goal of this research is to use systems thinking skills as a supplemental selection tool for hiring prospective employees. The aim is to rank all applicants based on their systems thinking skills and then to hire the candidates most in line with the organization’s strategy. The intent is not to criticize the current hiring method but to provide a method to supplement the current screening and selection process. According to personnel selection literature, we have identified two important strategies for ranking new applicants. One is to find applicants who are most aligned with the level of systems thinking skills needed for a specific position requirement, and the second is to find applicants who possess the highest systems thinking skills among a pool of candidates. An established optimization tool will be applied to locate prospective employees. The $L_p$ metric will be implemented to deal with Job Fit recruiting strategy, whereas ELECTRE III will be used as a Flexible Recruiting strategy. Fuzzy logic will be applied to derive the necessary weights implemented in the selected Multi-Criteria Decision-Making (MCDM) tools with the consideration of a vague preference of managers under the uncertain decision-making environment.

The goal behind the proposed recruiting framework can be classified as two folds. First, to develop a comprehensive employee selection criterion by utilizing seven dimensions of systems thinking. The proposed recruiting framework will serve as a supporting tool for the top management to make appropriate hiring decisions, along with other traditional recruiting procedures. Second, to develop a new recruitment framework that will assist the recruiters in finding the right candidate to fit the posted job position based on the candidate’s skillset.

The existing recruiting tools and methods are incomplete in the sense that they do not consider individuals’ systems thinking skills in identifying the most suitable employee for a specific position depending on the skills requirements of that position. These skills are important to identify, especially with the increasing complexity and uncertainty surrounding work environments. The identifications of these skills will allow the right positioning and recruitment of individuals that will fit the skills levels requirements of the job. Thus, enhance work performance. In an attempt to close this gap, this research introduces a new expert system tool to expert HRM professionals to help recruiters classify employees based on their systems thinking skills. Since recruitment is a decision-making process, this tool implements MDCM methods to help classify employees based on their systems thinking skills. The contributions of the study with respect to theoretical, practical, and methodological dimensions of the proposed framework are discussed below.

Although systems thinking has been around for decades, there are insufficient tools and techniques purposefully designed to deal with complex socio-technical problems. At best, some tools measure only one or two systems thinking skills (Dolansky and Moore, 2013, Hopper and Stave, 2008, Plate, 2008). Many of the current tools are designed for specific domains such as education to test student systems thinking skills (Frank, 2010, Camelia and Ferris, 2016, Frank, 2002). These techniques, while they might satisfy a specific need, have not been designed or specifically structured to facilitate solutions to socio-technical problems. The review of relevant literature also shows that there are few systems thinking tools and techniques specifically designed to deal with complex system problem domains. Because current complex systems challenges can limit an organization's ability to engineer and manage socio-technical systems, it is essential to have a cadre of qualified individuals who can take a more holistic 'systemic' approach to deal with complex system problems.

The proposed framework offers an established instrument to expert HRM professionals for assessing and screening of prospective employees based on their systems thinking skills level with the consideration of uncertainties in the complex decision-making environment using the fuzzy linguistic approach. This framework works as an expert system to identify the most appropriate candidates for an organization to enhance the organization's human capital by matching individuals’ skills with job requirements. The proposed framework is implemented in a real case study of a large organization in the US. The novelty of the work is that it provides the first framework in the literature that evaluate a pool of applicants according to their level of systems thinking skills, and then sort them consistent with the recruitment strategy and workforce needs of the organization through Job Fit Recruiting and Flexible Recruiting strategies.

• Job Fit Recruiting: The novelty of the proposed expert framework is to evaluate and rank the systems thinking capability of prospective employees based on the degree of the work complexity in the organization (based on HRM professional feedback) for the specific job.

• Flexible Recruiting: The intent is to screen the pool of prospective employees based on their systems thinking skills scores to find the candidate with the highest level of systems thinking based on seven systemic skills dimensions while controlling vagueness and uncertainties of complex decision making using the fuzzy linguistic approach.

Feeling motivated and well-fit for a job enhances employees' levels of comfort and performance, allows them to better serve the entity they work for, and successfully grow within that entity. In addition to the traditional recruiting tools, researchers should invest in looking into employees' mindsets and their impact on companies and industries. There is a lack of research that combines individuals’ systems thinking skills with current decision-making tools.

The current study is intended to assess the systems thinking skills of existing employees in order to better fit them in the organization. This research sets the basis for new recruiting tools that can mimic the decision-making aptitude of expert recruiters to match employers' needs and thus, reducing turnover and cutting the training cost. Besides individuals' systems skills, the proposed framework can be expanded to include personality traits, level of problem-solving ability, resource management capacity, content, and social skills. The framework can also be enhanced, making use of more advanced, new recruiting methods that work better with these traits.

Because of the increasing complexity, decision making is becoming a vital process in organizations. The recruitment process is an important phase where organizations utilize decision making to select the right candidates for the job requirements. When selecting a candidate, an organization must have a precise selection criterion to match them to the job (Gamage, 2014). In the proposed recruiting framework, the researchers used systems thinking skills as a criterion to screen prospective candidates and sort them using fuzzy MCDM methods. Unlike classical MCDM approaches, fuzzy MCDM can obtain more sensitive results in vague decision-making environments. The newly developed recruitment framework can be used to evaluate candidates based on their systems thinking skills and help recruiters to perform Job Fit Recruiting or Flexible Recruiting to find the best candidate.

The following paper is divided into five sections. Section 2 provides an overview of systems thinking approaches, recruiting strategies, and various MCDM techniques. Section 3 discusses the integration of systems thinking skills and $L_p$ metric/ELECTRE III approaches to satisfy the organization’s recruitment strategy. Section 4 presents a case study to demonstrate the proposed approach. Section 5 shows the results comparison and sensitivity analysis. The paper ends with concluding thoughts, limitations, and future research in Section 6.