Dream Team ● HRMS ● Human Capital ● Human resources ● Livrea ● Smartpeg ● Soft Skills
The right person in the right place
Teams created with a software tool are more successful and people are more cooperative.
Abtract
Human Resources Management (HRMS) are constantly evolving, speeding up, and simplifying the management, the evaluation, and the development processes of people in te company.
However, can they also improve people-to-people matching, role assignments, and team building? What kind of additional assets can they provide, if any? Is there a discernible improvement in general effectiveness that stems from their implementation?
In this work, we tested whether teams created using HRMS algorithms were better than random teams. The results show that the people selected by the software algorithms worked better toghether, were more suitable to cover the assigned roles, and, generally, the software generated teams performed better.
1. Introduction
In the post-industrial era, the central role of Human Capital is extremely clear. The new knowledge economy is based on people’s skills and talents. The experience and research reported here stem from the belief that nowadays, to improve businesses, it is necessary to start with people. Doing this
means focusing on motivation, well-being, human capital, and training.
After all, when employees are engaged, profitability has a 21% increase, while the disengaged cost companies between $450 and $550 billion a year. Gallup also tells us that only 15% of the workers are motivated.
Well-being and productivity go hand in hand, bolstered by motivation and satisfaction. Engaged employees make it a point to show up to work and do more work. Highly engaged business units realize a 41% reduction in absenteeism and a 17% increase in productivity. Engaged workers are also more likely to stay with their employers.
Human Resources Management Software (HRMS) is constantly evolving, speeding up, and simplifying the management, the evaluation, and the development processes of people in the company.
However, can they also improve people-to-people matching, role assignments, and team building?
In this work, we tested whether teams created using HRMS algorithms were better than random teams in terms of performance, role match, and affinity between members for a project or activity. We organized an experiment that involved students at the University of Bologna. The results show that the people selected by the software algorithms worked better together, were more suitable to cover the assigned roles, and, generally, the software-generated teams performed better.
1.1 Soft Skills
In the Industry 4.0 society, Soft Skills represent a fundamental asset to achieving professional success. The World Economic Forum supports the statement that Soft Skills are an essential ingredient for professional success. Soft skills such as critical thinking, problem solving, self-management, active learning, resilience, stress tolerance, and flexibility have been identified as the most important skills in The Future of Jobs Report 2020.
Analytical thinking and creative thinking are highlighted as the most important skills for workers in the 2023 edition of the report. Job roles and requested skill profiles are changing following the changes in our society and way of live. According to the 2023 edition of the report Employers estimate that 44% of workers’ skills will be disrupted in the next five years. Six in 10 workers will require training before 2027 and the highest priority for skills training from 2023-2027 is analytical thinking. The second priority for workforce development is to promote creative thinking.
Recent reports have suggested that many employees in the labor market today lack essential Soft Skills. A study involving managers at firms in different industries in Italy and Finland highlights that specific Soft Skills, particularly work in team and flexibility to develop, are becoming increasingly
important.
A recent analysis of online job postings from 2010 to 2019 in the U.S. energy sector showed an increasing trend of high levels of “soft” skills (such as social, cognitive, people management, project management, and customer service skills) request, while the requirement for “hard” skills (such as products and marketing, engineering, and general computer skills) remains relatively flat.
In a survey , 348 IT managers were asked to rate the importance of various skills. Soft Skills were rated high, while Hard Skills related to knowledge of operating systems, hardware, databases, security, web development languages, telecommunications, and networking were rated much lower.
Higher levels of employees’ skills are related to a higher average level of labor productivity. High levels of soft and Hard Skills are significantly and positively associated with individual level informativeness.
Today, Soft Skills (transversal competencies) are increasingly appreciated by employers as essential skills for professional success. Likewise, these competencies are necessary to operate as individuals in today’s society Given this situation, in the future post COVID-19 educational model, it is essential to design training programs that promote both Hard Skills (specific competencies) and Soft Skills.
To meet the challenges of this “hybrid” working mode, as the survey finds, further changes from management are needed, such as the coordination of schedules to encourage a sufficient degree of in person interaction, and additional investment in ICT tools and skills as well as more Soft Skills to master online communication Soft Skills are becoming a decisive factor toward graduate employability in the 21st Century economy.
James Heckman, a Nobel Prize-winning economist, determined that having Soft Skills literacy statistically leads to success in life more so than technical skills literacy. He cites evidence that demonstrates that Soft Skills and competencies are essential for achieving professional and personal lifesuccess. Heckman’s timeless recommendation to educators, published more than two decades ago, is to consider investing in sustainable Soft Skills educational system that trains students in the art of interpersonal, professional, and leadership/management skills to help develop a successful pathway for future students.
Higher Education students need to be prepared to address sustainable solutions to the complex problems faced in this century. They should become proficient problem solvers, able to work in multidisciplinary teams, ready to adapt to new technologies, and able to acquire new knowledge and skills when needed.
Given the current skill gap situation, companies should adopt a strategy to tackle the problem, at least until the global educational system catch up. Successful companies are the ones that invest in their staff: continuous learning, stimulating work environments, rewarding career paths, full exploitation of personal talents, correct use of benefits and incentives, are all tools to increase the company’s competitiveness and productivity.
This poses a series of very complex challenges for entrepreneurs and human resources managers: how to identify the right person to fill a role? How to help that person to fully express his potential? And then, how to avoid losing the talented person?
Human Resources Managers, who are asked to make important decisions, can almost rely on tools from psychology and human resource management best practices such as interviews, aptitude tests, personality assessments, questionnaires. The correct usage of these tools in real world requires specialized professionals, relevant investments, and a lot of time. Traditional profile evaluation requires complex tests, deep interview and long questionnaires
but a good estimation of the result can be achieved also through observation of the candidate’s behaviour in a much shorter timeframe. The information technology play a crucial role in skill assessment skill development processes. From recruitment to talent retention, software tools allow HR manager to get the job done at sustainable cost for the organization.
1.2. Soft Skills for Success
Soft Skills for Success (S²4S, read it “es two-four es”) is a project aiming at supporting young professionals and University students to identify their strengths and weaknesses in terms of Soft Skills. The S²4S initiative was launched in 2010 by Prof. Roberto Verdone of the University of Bologna. Electronic Engineer, Professor of Telecommunications, he has been giving courses on Soft Skills and collaborates with psychologists and experts of Human Resources, for more than one decade.
S²4S relies on the experiments performed on students attending the Project Management and Soft Skills (PMSS) graduate course at the University of Bologna taught in english by Prof. Verdone.
Since 2024, S²4S has become part of RESTART, a large programme funded by the “Piano Nazionale di Ripresa e Resilienza“, dedicated to the future of telecommunications, including activities geared towards the development of soft skill.
1.2. Group management – intuition v.s. software
As information technology has evolved, progressively more effective tools for monitoring and managing human resources have emerged that offer the added value of being able to serve as an easily accessible database of individual development.
The principle behind Human Resource Management
System (HRMS) is that, through a series of integrated functions and modules, the platform enables employees to become aware of their talents, as well as their personal and corporate responsibilities and goals.
In parallel, it provides managers, HR managers, and advisors with an effective tool for obtaining useful information, with the intention of enhancing each person’s talents and optimizing management, increasing productivity, and improving the business climate with a view to overall well-being and sustainable growth.
No one works alone, so it is critical to be able to build an effective work team that is more than the sum of its parts. Balancing the experience gained by the individual with the method and parametricity inherent in the HRMS’ algorithms to ensure objective and stable results without ignoring the human factor and individuality of individuals.
For high-performing teams to be created, it is not enough that the appropriate technical skills are achieved, but rather that there is connection and harmony among the parties. It is increasingly clear that technical skills possessed by people alone are not enough. A survey of newly hired managers showed that only 11% of failure of them corresponds to lack of techincal competencies, while 89% are due to poor Soft Skills, in order of importance:
- Coachability
- Emotional intelligence
- Motivation
- Temperament
Knowing these facts, we started a research project to measure how well the combination of human capital (Soft Skills, affinity, personality) and technology (algorithms, software, machine learning) could generate better performing teams where people felt more satisfied and engaged. We believed that by
combining information about people, skills, and project requirements, a software tool might generate valuable recommendations and insights to create the best possible team. We hypothesized that the project teams created according to the software’s recommendation would perform better than teams
whose member was chosen randomly among candidates that meet the basic qualification requirements.
ID Questions
- The people in my group have the right skills?
- The roles were assigned to the most suitable people to fulfill them?
- I get along well with most of the people on the team that I have been assigned to?
- It was easy for us to find converging opinions and solutions?
- If I recap with this same group we would be successful in the activities that would be proposed to us?
2. Materials and methods
To test our hypothesis that the project teams created according to an HRMS recommendation would perform better than the teams whose member was chosen randomly.
We selected the Dream Team tools included in LIVREA HRMS developed by Smartpeg. Smartpeg is a company focused on the innovation of Human Resources & Talent Management that has been collaborating with the S²4S intiative since 2020 to promote the value of individual talents and Soft Skills.
2.1. Dataset
For these experiments, we involved students attending the 2021 editions of the Project Management and Soft Skills (PMSS) and Introduction to Project
Management and Soft Skills (IPMSS) courses at the University of Bologna.
The students were assigned to project teams, and some teams were formed using the ”Dream Team” algorithm by Livrea HRMS, while others were randomly assembled. At the end of the semester, all students were asked to respond to the questions. The responses were recorded using a Likert scale with values ranging from 1 to 5. The raw research data collected are available in the Mendelay Data repository at: https://data.mendeley.com/.
2.2. LIVREA Dream Team
The Dream Team functionality is one of the modules available in HRMS software Livrea. The software platform combines the analysis of soft skills,
hard skills, and personal attitude with the goal of supporting them in gaining awareness of individual characteristics and in personal end professional
development.
Given a pool of people and a set of requirements, the DT algorithm generates six different team proposals that maximize the team performance index (TPI) with a specific choice of relative weights. TPI is a
weighted average of five indexes.
T P I(W) = I×W = RMI ·wRMI+CI ·wCI+SI ·wSI+AI ·wAI+EI ·wEI (1)
where: W = (wRMI, wCI, wSI, wAI, wEI) is the relative weights vector and I = (RMI, CI, SI, AI, EI) is the performance indexes vector. The five components of the performance index vector are:
- Role Match Index (RMI): this index is calculated as the average of the Hard Skills Index and the Soft Skill Index. The former is the average of the distance between expected and acted Hard Skills. In case you do not possess a certain Hard skill, is assigned maximum distance i.e. 1. If you possess the expected level or more, is assigned distance 0 (no over-skilling penalty is applied). The second is the average distance between expected and acted Soft Skills. If one does not possess a certain soft skill, it is assigned the maximum distance i.e. 1. If you possess the expected level or more, is assigned distance 0. Any deviation from the expected value either positively or negatively increases this distance (over-skilling and under-skilling penalties are
applied). The expected skill profile for each specific role can be tailored to fit the specific organization, and custom roles can be defined from scratch - Competence Index (CI): sum of all Hard Skills acted upon, required for that role. The index’s maximum represents intensity of ten on all Hard Skills required by the role
- Synergy Index (SI): average of predicted synergy between every possible pair of people among team members, based on collected feedback
- Alchemy Index (AI): the average of the distances between every possible pair of people among team members, based on personality
assessment results - Experience Index (EI): is the sum of all seniority of all team members on the skill required by their role in the project
The Dream Team Index (DTI) is a particular case of team performance index where all weights are set to 0.2 that summarizes the overall team performances. The Dream Team algorithm generates the six-team proposal described below. The weight values can be tailored to match the user’s specific needs. For the experiment described in this work, default values have been used.
- Dream Team: the team with the maximum DTI
- Role Match Index: aim to the maximize the RMI. The other index are non considered
- Competence Team: aim to maximize the CI
- Synergy Team: aim to maximize the SI
- Alchemy Team: aim to maximize the AI
- Experience Team: aim to maximize the EI
We define the project team as a set of project roles. Each role has a specific profile of requested Hard Skills and requested Soft Skills. Skill requirements are expressed as minimum skill intensity desiderata formeach skill. Also two others parameters are considered: the role orientation coefficient α and the skill coreness c factor. Role orientation tune the relative weight balance of soft and Hard Skills. The skill coreness model the relative importance of every single skill for the role in the specific organizational context.
3. Results
In the questions about the team and team working experience, the test group (the teams made by Dream Team) score better results then the control group. Wilcoxon Rank-Sum non-parametric test detects the statistically significant difference between the answers associated with the teams made by Dream Team and the control group for all six questions.
The experiment with the students of PMSS had the objective of verifying whether and to what extent a technological tool such as Livrea can make a real contribution to company performance and the organizational climate.
4. Conclusion
The experiment demostrated the LIVREA tool’s remarkable ability to capture the participants’ personality elements and Soft Skills, generating teams that could manifest considerably more synergy and chemistry than those achieved by randomly choosing students at the time of group formation.
With regard to performance, the questions relating to role coverage, the probability of success of the work group and the right skills to achieve the objectives were analyzed. Regarding the organizational climate, the Dream Team algorithms generated work groups where people were bettere at collaborating together. One of the points that emerged from the results concerns the greater success achieved in affinity factors (alchemy).
Responses on matching people in TDs were higher than those on role coverage and skills. A starting point to deepen the use of self-report tools to measure preople’s Soft Skills. A starting point to deepen the use of self-report tools to measure preople’s soft skills. The investigation also raised additional questions in the research team, wich opened up new perspectives for investigation, related to the impact of HRMS tools and the combination of artificial intelligence with human intelligence and expertise in human resource management.