---
title: Home | Code18
description: Science ► Studies with business and sports teams ✓ Very high reliability (Cronbach’s α) ✓ Very high validity of team fit with performance
image: https://www.code18.team/hubfs/Website/Vorschaubilder/Code18_Science_EN.jpg
---

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 English

## SCIENCE ON THE

# Code18-Method

Today's modern management is more a **balancing of existing forces** and the **establishment of organic growth** rather than a linear or even exponential increase. With the aim of measuring the homeostasis (balance) and ontogenesis (growth) of basic forces in social systems, the Code18 method was developed. Code18 was born out of the need to counter old, heavy, and mostly descriptive, theoretical thinking with a holistic and intuitive method of reflection.

Code18 is **participative**, **safe**, **effective**, and **scientifically proven** and is also easy and quick to implement.

![Logo_Code18](https://www.code18.team/hubfs/logo-kreis-bunt_code18.svg "Logo_Code18")

### BASIC HUMAN FORCES

## The 18 Factor Code

The Code18 method consists of **6 basic motivational forces**, which are assigned to corresponding colors and sensations and each consist of **3 factors**. This results in a holistic method with **18 factors** that captures the basic forces of a social system (individual / team / organization). Contrary to common questionnaires whether best practice or academically used, Code18 works by subjective assessment, both in the actual state and the target state. This creates individual growth and success potentials. At the same time, the method avoids a laborious interpretation of many and long text items, an evaluative categorization and classification of behavioral patterns as well as social desirability.

### SOCIAL DESIRABILITY

## Why I Cannot Fake

Social desirability is the deliberate falsification of answers to present oneself in a more positive and conformist manner. This is used to indicate socially desired behaviors rather than existing behavioral patterns to prevent negative consequences. Social desirability is a major problem in scientific research in human behavior. Because Code18 does not ask for self-attributed behavioral patterns, there are true but no socially accepted answers. Therefore, answers can only be desirable to oneself.

![Logo_Code18](https://www.code18.team/hubfs/logo-kreis-bunt_code18.svg "Logo_Code18")

### INTERNAL CONSISTENCY

## The Interplay of the 18 Factors

The holistic and effective nature of the Code18 method was scientifically verified based on hundreds of individual profiles in which an individual self-assessment was performed. Internal consistency was calculated to verify the method: It determines how well the factors fit together and how well they capture a person holistically. The internal consistency is very good at *α* > .90 and thus captures a person extraordinarily adequately. Even the elimination of a factor never causes any decline or improvement of the method: **All factors are equally valid and important!**

There is also a very high level of internal consistency among athletes, which means that the method is valid not only in social systems of the **economy**, but also beyond, as in **sports**.

### STATISTICAL OPTIMIZATION

## The Significance of the 18 Factors

In addition, the allocation of the 18 factors to the 6 dimensions was statistically verified, since the before mentioned analysis does not yet show whether the 3 factors each actually belong to the respective dimension in terms of content. Thus, it was examined by a factor analysis, how many dimensions are statistically meaningful and which factors belong contentwise to which dimension.

The result shows the reasonable choice of 6 dimensions, as well as the content allocation of the 18 factors to the 6 dimensions. Where optimization was possible, the content allocation was strengthened by sharpening the factor synonyms that describe the factor in the online survey.

![Team-Tool_Code18](https://www.code18.team/hubfs/100-prozent-wissenschaftlichkeit_code18.svg "Team-Tool_Code18")

### SCIENCE ON

## Business Teams

Code18 for business teams was scientifically tested during **examination seminars of several days with** **working students** from higher technical schools for business (HFW Zug & HFW Aarau). In the seminar, the students complete the so-called *Business Plan Seminar* in their second school year. This lasts about four days and is conducted offsite in a seminar hotel. **Students manage a company as a management team of four** in the roles of CEO, COO, CMO, and CFO. The business game, a well-known and proven economic simulation, is played after a practice unit over six economic periods.

 

![Logo_Code18](https://www.code18.team/hubfs/logo-kreis-bunt_code18.svg "Logo_Code18")

## The Study Details

The management board, consisting of four students each, develops a strategy in advance and then makes various dynamic decisions for each business period, including production & logistics, marketing & sales, finance & investment as well as research & development, which are then transferred from the game makers to the simulation. At the end of the business period, various economic key performance indicators (KPI) result, whereby the average stock price of the company is considered to be relevant for performance. Hence, Code18 not only tested the reliability of the method based on individual personality profiles, but also the correlation between team fit and team performance based on the respective stock price.

The students could participate in the online survey until about two weeks before the seminar began. Subsequently, the individual profiles were created, and the team fit calculated based on the grouping. During the seminar, the groups were observed by team experts, but were not influenced at any time during the business game. The debriefing took place at the end of each seminar. The correlation between the calculated team fit and the corresponding success (average stock price over all economic periods) is statistically very high and significant (*r* = .90) and corresponds to an inverted U-shaped curve:

**+30% stock price with ideal team fit!**

![Team-Success_Code18](https://www.code18.team/hubfs/erfolg_code18.svg "Team-Success_Code18")

### THE SECRET TO SUCCESS

## The Interplay of the 18 Factors in Teams

All teams tested in the study correspond to an inverted U-shaped curve with an accuracy of 90% (*r* = .90). In the **performance range**, teams have up to **30% more success** (in the study a 30% higher stock price) than outside the area. Code 18 does not intervene in the technical area. The performance increase results from the ideal combination of human factors: The **fit within the team**. The additional performance is achieved by the optimal **balancing of dissimilarity** (heterogeneity) **and similarity** (homogeneity). In this way, team members benefit mutually from their different strengths (ideal heterogeneity) and at the same time from the similar focus of action and superordinate goal (ideal homogeneity) within the team.

### FURTHER READING ON

## Business Teams

![Team-Development-Method_Code18](https://www.code18.team/hubfs/teams-code18.svg "Team-Development-Method_Code18")

### Team Models for Code18

The results of the study on business teams led to an extension of the two most commonly used models on dynamics and performance in teams: The **Stages of Group Development** according to Tuckman and the **Team Roles** according to Belbin. Tuckman found out that teams go through different stages in their development. While team members find and get to know each other in the Forming Phase, they "storm off" in the Storming Phase where there are different goals, disagreements and conflicts, and tension and power struggles arise. By standardizing in the Norming Phase, where norms and rules are established within the team and each member has assumed a role and function, the team can focus on the common goal and perform in the Performance Phase.

Code18 recognizes the stages in which teams are underperforming based on a suboptimal fit of their team members. This shows how a team achieves **greater homogeneity** through better cooperation, where a team **has an ideal fit and is in flow**. At the same time, according to Belbin, teams are effective when there is a heterogeneity of characteristics: if all team members are equal in their nature, the result is a dangerously high level of harmony and unanimity. As a result, the team does not develop further and lacks the opportunity to recognize change and consider alternatives. Code18 makes it evident how a team can achieve **greater heterogeneity** by working together constructively and critically, thus **achieving an ideal fit and entering the flow**.

![Organizational-Development-Method_Code18](https://www.code18.team/hubfs/organisationen-code18.svg "Organizational-Development-Method_Code18")

### Organizational Model for Code18 

The deliberate lack of categorization and classification allows Code18 to offer a quality typology: Instead of just describing what a social system *is* like, Code18 also shows what a social system *can* do. When the **18 factors are restructured in filters, three qualities result**. These three qualities show **how a social system acts with internal and external stress and strain** - not reacts! ***Agility*** for a flexible, adaptable, proactive, and anticipatory social system is achieved through a combination of 6 factors as well as ***Innovation*** for a social system with change and renewal. The remaining 6 factors in their combination result in ***Resilience*** for a social system, which shows itself as the ability to hold itself harmless in crises and difficulties.

 

![Team-Performance_Code18](https://www.code18.team/hubfs/100-prozent-wissenschaftlichkeit_code18.svg "Team-Performance_Code18")

## SCIENCE ON

# Sports Teams

Code18 for sports teams was with **four professional ice hockey teams** of the Swiss League (EHC Olten, EVZ Academy, HC Thurgau, SC Langenthal). The study was written at the **University of St. Gallen (HSG)**. To determine the player constellation on the field and the team fit, game statistics of the participating teams were obtained from the **Swiss Ice Hockey Federation (SIHF)** and the respective player constellation was determined in case of goals scored or goals against. The study considered the first half of the season as long as the individual profiles were actual and valid.

![Logo_Code18](https://www.code18.team/hubfs/logo-kreis-bunt_code18.svg "Logo_Code18")

## The Study Details

Remarkably, by mid-season an average of over 80 different player combinations per team were already on the ice field, scoring goals or conceding goals against. However, only goals scored or goals against in numerical equality (i.e. 5:5 / 4:4 / 3:3) and for which all players on the ice participated in the online survey were considered. The calculated fits were then transferred to the flow model and checked whether these fits were within the performance range or outside, where top performance cannot be shown due to the suboptimal team fit.

The ice hockey players were able to participate in the online survey for about 4 weeks before the Christmas break. Afterwards, the individual profiles were created, and the team fit was calculated based on the respective constellation on the ice field. Individual and team profiles were sent to the teams before the end of the season. The correlation between the determined team fit and the corresponding success (number of goals scored & goals against) is statistically very high and significant (*p* < .001), and can be clearly proven:

**+46% goals scored and -62% goals against with ideal fit!**

![Logo_Code18](https://www.code18.team/hubfs/logo-kreis-beige_code18.svg "Logo_Code18")

### STATISTICAL VERIFICATION

## Swiss League Study

All goals considered in the study with numerical equality and possible calculation of the fit of the players on the ice field were coded in case of goals scored or goals against. The study examined whether goals scored are statistically random when the fit is ideal and in the performance range described above, and whether goals against are statistically random when the fit is not ideal and outside the performance range. In fact, the likelihood of both hypotheses could be excluded with a probability of less than one per mil (*p* < .001), which **clearly confirms the Code18 performance range model**.

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