CASE STUDY

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A N A N A LY S I S O F S A L E S P E O P L E W I T H I NT H E T E C H N O L O G Y I N D U S T R Y

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A B S T R A C T

JobFit assessments measure behavioural traits thatmost heavily affect a candidate’s performance on ajob. The following case study, conducted by JobFit,measures assessment data in order to analyse thecorrelation between JobFit Executive Job Matchscores and General Performance of candidates in twodistinct sales roles. The primary objective of thisstudy is to improve and standardise the performanceof the selected sales organisation. Performanceindicators that are pivotal to the sales roles wereprovided. Six performance traits are measured andcompared to Success Patterns in order to obtain theJob Match scores. The data collected shows a positivesignificant correlation between the two variables. Theresults are analysed using linear regression andANOVA. JobFit Executive Job Match explains 32% ofgeneral sales performance in Sales Position A and27% in Sales Position B.

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I N T R O D U C T I O N

Employee assessments are often utilised for assessing anindividual for hire. Some assessments focus on identifyingskills while others identify behaviours and/or emotionalintelligence. Krumboltz & Vidalakis found that a deeperpurpose can be served by these tools. Use in careercounseling, performance problem identification,suggestion of alternative pathways for candidates, andstimulation of action are some of the dynamics that putvalue into the employee assessment process. (Krumboltz etal , 2000). Their additional finding, which shares the mostrelevance with the JobFit assessment, is that assessmentscan also facilitate cognitive, emotional, and behaviourallearning, with emphasis on the behavioural aspect.

The employee assessment utilised in this study is theJobFit Executive. This behavioural assessment measurespersonality traits and a measurement of cognitive abilitythat, when added together, create a job match score.Variables and terms of the assessment and its results willbe defined in the Method section. The intended purpose of this study is to identify whatcorrelation, if any, exists between Job Match percentageand General Performance ratings. JobFit has hypothesised,based on previous assessments and data, that a higher jobmatch percentage will have a positive correlation withGeneral Performance ratings.

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PA R T I C I PA N T S

Overall a total of 124 candidates in Sales Role A and 29candidates in Sales Role B participated in the study. Theparticipant pool utilised in the data analysis consisted ofcandidates with a minimum of 2 years’ experience in theirrespective roles.

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M E T H O D

The JobFit Executive is comprised of three components:personality, reasoning ability, and interest. The providedanswers to these questions are compared to the SuccessPattern corresponding to each role, where a Job Match scoreis calculated, acting as our independent variable. SuccessPatterns are a culmination of personality traits andreasoning ability measurements that reflect an individualthat would be categorised as a top performer in their role.Interest measurements are not used to calculate Job MatchPercentage, and thus are not included in the analysis. JobMatch scores are displayed as a percentage match to theSuccess Pattern.

The dependent variable, or General Performance rating, isdetermined by the client’s choice of various aspects of thejob—referred to as KPIs—that, when measured andsubsequently averaged together, create an overall GeneralPerformance score. For exemplary purposes, some of theseKPIs may include areas like Product Knowledge,Communication, Productivity, or Customer Relations. JobFitprovides the client with a means of measuring the KPIschosen by the client, typically on a number-pointed scale.

The assessment measures reasoning ability as well as 6personality traits; these psychometric factors are combinedto create a JobFit Executive Assessment Job Match score:manageability, people contact, attitude, competitiveness,sense of urgency, and take charge. The table on thefollowing page provides the definition of reasoning abilityand each personality trait:

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M E T H O D

REASONING ABILITY

A measure of expected learning, reasoning,and problem solving potential

PEOPLE CONTACT

The tendency to be outgoing, people-orientedand to part ic ipate with others

MANAGEABILITY

The tendency to fo l low pol ic ies , acceptsupervision, and work within the rules

ATTITUDE

The tendency to have a posit ive or optimist icoutlook regarding people and outcomes

COMPETITIVENESS

The tendency to work toward goals and to tryto exceed others ' performance

SENSE OF URGENCY

Tendency to display intolerance and aneagerness for immediate results

TAKE CHARGE

The tendency to str ive for control pf peopleand situations and to lead more than fo l low

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M E T H O D

REASONING ABILITY

7 - 9

PEOPLE CONTACT

MANAGEABILITY

ATTITUDE

COMPETITIVENESS

SENSE OF URGENCY

TAKE CHARGE

The Success Patterns for both Sales Role A and Sales RoleB define the observed range of scores within the patternfor each of these traits. They are as follows:

SALES ROLES A

SALES ROLES B

6 - 9

4 - 6

7 - 9

3 - 6

7 - 9

4 - 7

1 - 3

3 - 9

3 - 9

3 - 5

3 - 5

6 - 8

7 - 9

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M E T H O D

You may notice the differences between score ranges formanageability, people contact, and attitude. Optimalmanageability for Sales Role A is 4 to 6 while Sales Role Bis in the 7 to 9. From a statistical standpoint, highermanageability for Role B may be justified due to thepositive ‘ l ikely to be useful’ correlation [p-value <0.25] withKPIs 3, 4, 6, and the Weighted score while Role A requires alower level due to ‘ l ikely to be useful’ negative correlations[p-value <0.25] with KPIs 4 and 6.

Optimal people contact for Sales Role A is in the 3 to 6range while 7 to 9 is the optimal range for Sales Role B.From a statistical standpoint, higher people contact forRole B may be justified due to the ‘very beneficial’ positivecorrelation [p-value <0.05] with KPI 3 while Role A has‘likely to be useful’ negative correlations [p-value <0.25]with KPIs 1 , 2, 4, 6, and the Weighted Score.

Optimal attitude for Sales Role A is in the 4 to 7 rangewhile 1 to 3 is the optimal range for Sales Role B. From astatistical standpoint, lower attitude for Role B may bejustified due to the negative correlations with four of thesix KPIs while Role A has a ‘very beneficial’ positivecorrelation [p-value <0.05] with KPI 3.

After completion of assessments, the scores were thenanalysed in order to derive comparisons between Job Matchpercentage and General Performance. In this case, GeneralPerformance rating was defined by performers that fell intoquartile categories.

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A N A LY S I S

A graph is provided in Figure 1A to show the positive l inearcorrelation

Figure 1A: Linear graph displaying positive correlation ofSales Role A candidate scores and performance

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A N A LY S I S

A graph is provided in Figure 1B to show the positive l inearcorrelation

Figure 1B: Linear graph displaying positive correlation ofSales Role B candidate scores and performance

These results support JobFit 's hypothesis that there is asignificant correlation between Job Match score andGeneral Performance.

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A N A LY S I S

Figure 2: KPI scores used to calculate general performancerating.

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C O N C L U S I O N

This correlational study found that a higher Job Matchscore calculated from the JobFit Executive relates tohigher General Performance. Although possible outcomesmay vary if the sample size changes, it can be reasonablydeduced that similar correlations may be presented if thestudy were repeated with different job positions within thesame organisation, or within a different organisation.

R E F E R E N C E S

Krumboltz, J . D . , Vidalakis, N. K . (2000). Expanding learningopportunities using career assessments. Journal of CareerAssessment , 8(4), 315 – 327. doi :10.1177/106907270000800401

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