Given that a top performer gets results, applying jobEQ formula for explaining results leads to 3 questions: What kind of attitude does a top performer have? What values does the top performer hold? What competencies does a top performer have (which a low performer doesn’t have)? In other words, a complete Model of Excellence will have to define the attitude, the values and the competencies of top performers, and explain how these differ from attitude, values and competencies observed with lower performers holding the same kind of function. jobEQ’s technology for making maps of excellence in any of these 3 domains can be combined with other technology for the other 2 domains.
Using a Model of Excellence
A Model of Excellence answers the following question: “What is the difference between a top performer and a low performer?” Such a model can be used to recruit the right person for the job, to train or coach them to be more like the model, and to manage them in such a way that one maximizes the chance on retention. Here are some in-depth looks at how a jobEQ Model of Excellence can help an organization.
The application of a model for recruiting consists in first writing the job advertisement so that it is congruent with attitude, values and competencies as found for the model and secondly testing whether the candidate corresponds to the model. A good advertisement will decrease the number of “low potential” candidates and increase the number of “high potential” candidates. A good selection will allow ranking the candidates based on their fit with the model (from “best fit” to “worst fit”). As a result, the company ends up with a better funnel though which it can approach the job market.
Indeed, one of the common challenges when applying testing for recruiting in Anglo-Saxon countries is that one has to prove the relevance of the testing towards the job and prove that these tests do not discriminate against minorities. jobEQ's tools solve these issues by objectively testing Emotional Intelligence only within the workplace context.
Training & Coaching
By comparing a person with a model, we know which are the areas of development in order to obtain a high performer. To some degree training may help to close the gaps. Using training, we can pass on knowledge needed to develop competencies, but also knowledge to help a person cope with all sides of one’s personality, thus tackling the attitude gap. Finally, training can be used to help the person appreciate the company values or the values important for the job. Once we know that the person has the necessary knowledge, coaching will help to ensure that the person uses the right attitude, values and competencies when actually doing the job.
Last but not least, for optimal performance and maximal retention, the management style used for a category of workers should be compatible with the attitude, values and competencies indicated by the Model of Excellence. For instance, if the model indicates that one needs to have independent workers who value difference, its only demotivating to install a management system that obliges the workers to collaborate closely and to rigorously follow the same procedure over and over again. Management that is incompatible will not only undermine job performance, but will also lead to high staff turnover rates, since persons will be leaving sooner than their “natural clock” indicates.
Organizational CultureStrongly related to this, jobEQ's tools can help to model the organizational culture. Read more about this topic.
Building the Model
A Model of Excellence answers the following question: “What is the difference between a top performer and a low performer?” This page focuses on several approaches one can follow to come up with a model, independent of the technology being used, and independent whether one considers the attitude, the values or the competencies (or all of them).
1. Standard Group
In this purely statistical method one takes a group of best performing persons for a certain function and gathers the same information for each of them. For instance, one asks each of the respondents to fill out the iWAM, the VSQ or COMET questionnaire. Based on the scores of this whole test group, one computes the average score for each of the questionnaire’s parameters as well as the standard deviation for each of the parameters.
Below, Figure 1 gives an example of such a standard group for the 16 operating factors measured by the iWAM questionnaire:
2. Contrastive Analysis
This method is achieved by comparing example of excellence with "counter-examples,” given by persons who do not display excellence. For iWAM and VSQ, jobEQ has developed a statistical approach based on this principle. You take 3 or more proven high performers for a certain job function, have them fill out the questionnaire and compare their scores with scores of at least 3 low performers holding the same function.
The principle of contrastive analysis can be combined with a statistical approach. It is easy to draw a chart indicating the “standard group” for high performers and comparing that area with the standard group of low performers. One can also use the data to see which parameters showed a significant difference between the groups.
Figure 2 shows again the same 8 persons consisting the model of Figure 1. In this figure, the group has been split up according to their performance. Parameters for which the data showed a significant difference between the means will be visually recognizable (e.g. OF1+ indicates “starting”: the top performers value “taking initiative” to a much higher extend than the persons considered “low performers”. OF1- indicates that top performers have less patience, etc.) For significant parameters there will be little or no overlap between the scores for both groups.
When one compares Figure 1 to Figure 2, one will also notice that the zone that will be considered “the Model of Excellence” will be much more narrow for figure 2. A contrastive analysis results in a model with a higher degree of precision. For instance, using the model of figure 1, we might consider a person with a score of 25% for OF4- as being “within range”, while figure 2 indicates that the only persons with a score of more than 19% are those belong to the least performing respondents.
3. Engineering the Model
Sometimes a large group of persons holding the function is not available, due to a lack of people to test. Also, sometimes the company cannot or will not have low performers go through the modeling phase, thus making approach 2 impossible. Finally, a job may be new, so that there are no successful examples of persons holding the function. In those cases, we cannot build a statistical reliable model. This leaves us 2 options.
First, one can build a model based on general knowledge about the function and the context the person will have to operate in (the management style, company culture, etc). Secondly, one can select some persons who have held the function or who one deems able of holding the function and build a model inspired on their scores. And of course both options can be combined.
This approach is more limited than others, because we only have information to situate the top performers, but no information on the significance of the zone we consider the model of excellence. This lack of information can be lessened with general knowledge of what are considered good patterns for the function and of what is the standard group for the given culture (either the country the selected persons are working in or their company culture).
4. Modeling Competencies using COMET
The description of the 3 previous approaches always starts from jobEQ’s iWAM & VSQ questionnaires. This makes sense for determining attitude and values. Similarly, you can apply these approaches on the COMET/EQ questionnaire, showing which emotional intelligence competencies make a difference when it comes to successful leadership, for instance.
However, given the wide array of competences one can distinguish, a questionnaire such as
COMET/EQ may indicate necessary competencies, but cannot guarantee to help to generate the full list of needed competencies. Modeling can learn whether COMET/EQ competencies would be necessary for the job, but it doesn’t help us build a sufficient list of competencies.
That’s why jobEQ defined COMET as a methodology for which we also make a 360° test tool available. The COMET/EQ questionnaire on the jobEQ website is actually just an application, showing the use of an assessment tool based on this COMET methodology, and the demo-version only allows to use it in the context of self-assessment. However,the core of the COMET method is building a competence grid and a competence dictionary for a specific job function, based on an analysis of the competencies present in top performers holding that function. By preference this analysis also includes a contrastive element, where we compare these competencies with competencies found in lower performers.
A custom questionnaire is then developed based on the competence dictionary. This questionnaires tests to what degree the person tested applies the behaviors described in the competence dictionary as defining elements of the competencies. Ideally this questionnaire is tested statistically on top performers and low performers to see whether it helps to predict job performance, before it is administered to third persons.
While we recommend a custom approach for modeling competencies, the 3 standard approaches described in this paper will generally result in very good models. Even if one designs a custom questionnaire, it is recommended to apply the standard approaches where possible.
The approach you use will be tailored to your specific organization. The main questions will be “What kind of information can the company offer about its top performers?" “How precise can we distinguish top performers from other groups?” and “How many persons can be tested?”