Jombay’s experiential InBasket simulation platform provides organizations with an opportunity to assess key managerial capabilities by putting the assessment taker in the role of a manager and presenting him/her with a series of emails that represent situations managers face on a daily basis. The assessment taker is required to make decisions and take key actions such as assigning and prioritizing tasks, planning projects, allocating resources, and helping develop individual employees. Jombay’s InBasket simulation is available in two versions, ManageFirst for first level managers, and ManageNxT for manager of managers or middle managers.
Jombay’s experiential inBasket simulation is based on the commonly used and highly effective in-tray exercise. The platform is powered by content that is engaging, relevant, and industry-specific. It posits a set of relevant and comprehensive scenarios that all managers face, responses to which help assess the assessment taker’s managerial capability on predefined behaviors.
Key Information
Virtual AC
20 mins
English (US)
Free trial : Yes No training required to use
Adaptability, Customer Service, Drive for Results, Goal-focused, Leadership, People Development, People Management, Planning and Organisation, Resourcefulness, Strategic Perspective
Jombay is ISO 27001:2013, SCO2 certified(Current under renewal), and is compliant with various security standards. Jombay performs yearly external VAPT(Vulnerability Assessment and Penetration Testing) audits to monitor the product and data security. Jombay’s physical infrastructure is hosted and managed by Amazon Web Services (AWS). AWS’ data center operations have achieved a wide variety of security certifications. Jombay utilizes AWS and relies to a great extent on the technical security measures adopted by AWS.
Jombay’s system has a default data retention period of 2 year. The data retention period can be configured as per the client requirements.
Jombay’s system runs a daily cron job to de-identify data for clients for whom the retention period has expired. This process is fully automated. We conduct yearly audits of the database and other storage systems to verify that all data retention/deletion mechanisms are working and are in accordance with Jombay’s policies.
In scenarios where a client asks for complete deletion of the data, it’s managed by executing scripts which delete the records instead of updating them on the system.
Reliability, Validity and Norm Group Info
Reliablity
Stability was assessed with test-retest administration. 200 people took the simulation twice, with the mean interval of 40 days. Coefficient was 0.53.
Validity
By collecting test scores and criterion scores (e.g. job performance ratings, grades in a training course, supervisor or manager ratings), one can determine how much confidence may be placed in using test scores to predict job success. In such cases, criterion validity is referred to as predictive validity. In the business domain, using a validation sample of 110 candidates, it was reported that the overall composite scores on InBasket Simulation correlated .24 with panel interview ratings and .31 with perception ratings on potential by the internal stakeholders.
<p>&bull; 6500+ Job Specific Formulas &bull; 175 Job Performance Impact Traits &bull; 25+ Years Research &amp; Validation &bull; Advanced Assessment Technology &bull; High ROI &bull; Easily Customized &bull; Reports Specific to Person and Job &bull; 29+ Languages &bull; No Adverse Impact</p>
<p>The Harrison Assessments System provides a comprehensive assessment of the behavioural competencies required for a position and accurately predicts success and potential obstacles. Integrated selection tools include performance based interviewing questions, how to attract the candidate, and the ability to calculate eligibility, suitability, and interview ratings for a composite ranking of candidates.</p>
<p>The assessment is web-based and scored online with comprehensive results available within 15 seconds.</p>
<p><strong>Enjoyment Performance Theory:&nbsp;</strong> Enjoyment Performance Theory states that an individual will perform more effectively in a job if they enjoy the tasks required by that job, have interests that relate to the position, and have work environment preferences that correspond with the environment of the workplace. Harrison Assessment&rsquo;s global research indicates that the enjoyment of these various aspects of a job is highly correlated with good performance. &quot;If you enjoy an activity, you tend to do it more. By doing it more, you tend to learn and improve the related skills. As a result, you tend to gain recognition (including self recognition) which helps you enjoy the activity more.&quot;</p>
<p>Candidates rank answers in order of what you they&nbsp; know enjoy. Enjoyment performance theory states that if someone enjoys 75% of the tasks required in a job role they are 3x more likely to be successful.</p>
<p><strong>Paradox Theory:&nbsp;</strong>Harrison Assessment&rsquo;s Paradox Theory provides a greater depth of psychological understanding because it reveals an entire system of behaviour rather than merely offering insights about specific traits. It also predicts stress behaviour and provides a framework that facilitates objective understanding of self and a clear direction for self-development.</p>
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<p><strong>Eligibility/Suitability</strong></p>
<p>The ability to predict job performance is dependent upon identifying all of the critical factors. If one assesses eligibility or technical competencies, it only represents a portion of the critical factors to predict performance. When behavioural competencies are also measured, such as emotional intelligence, personality, and work preferences, a high degree of accuracy is attained to predict performance.</p>
<p>Note:&nbsp;No training required use the assessment as we will support you in administering and delivering the reports to you. should you wish to manage this process yourself, we would be able to offer the training.</p>
Bias results when test performance is affected by unintended factors and those factors are not evenly distributed between groups. This results in group differences in test performance that are not related to the constructs the test is intended to measure. For example, a test of numerical reasoning that uses a lot of text may be biased against people who have English as an additional language. Group differences do not result from different levels of numerical reasoning ability, but from questions being more difficult for some due to their use of language.
Test developers may address bias through some or all of the following:
. Providing a clear rationale for what the test is, and is not, intended to measure
· Reviewing content to ensure it is accessible and free from complex language
· Ensuring scoring is automated and objective (i.e. free from user bias)
· Providing evidence of any group difference in test scores
· Examining the effect of group membership on individual questions – sometimes referred to as ‘differential item functioning’ or ‘dif’
· Ensuring norm groups used for comparisons are representative of the populations they reflect
· Providing guidance on using the reports and interpreting constructs measured
Reliability is an indicator of the consistency of a psychometric measure (Field, 2013). It is usually indicated by a reliability coefficient(r) as a number ranging between 0 and 1, with r = 0 indicating no reliability, and r = 1 indicating perfect reliability. A quick heads up, don’t expect to see a test with perfect reliability.
Reliability may refer to a test’s internal consistency, the equivalence of different versions of the test (parallel form reliability) or stability over time (test-retest reliability). Each measures a different aspect of consistency, so figures can be expected to vary across the different types of reliability.
The EFPA Test Review Criteria states that reliability estimates should be based on a minimum sample size of 100 and ideally 200 or more. Internal consistency and parallel form values should be 0.7 or greater to indicate adequate reliability, and test-retest values should be 0.6 or greater.
Most test scores are interpreted by comparing them to a relevant reference or norm group. This puts the score into context, showing how the test taker performed or reported relative to others. Norm groups should be sufficiently large (the EFPA Test Review Criteria states a minimum of 200) and collected within the last 20 years. Norm groups may be quite general (e.g. ‘UK graduates’) or more occupationally specific (e.g. ‘applicants to ABC law firm’).
A key consideration is the representativeness of the norm group and how it matches a user’s target group of test takers. It is therefore important to consider the distribution of factors such as age, gender and race in norm groups to ensure they are representative of the populations they claim to reflect. This is particularly important with norms claiming to represent the ‘general population’ or other wide-ranging groups. Occupationally specific norms are unlikely to be fully representative of the wider population, but evidence of their composition should still be available.
Validity shows the extent to which a test measures what it claims to, and so the meaning that users can attach to test scores. There are many different types of validity, though in organisational settings the main ones are content, construct and criterion validity. Reference may also be made to other types of validity such as face validity, which concerns the extent to which a test looks job-relevant to respondents.
Content validity relates to the actual questions in the test or the task that test takers need to perform. The more closely the content matches the type of information or problems that a test taker will face in the workplace, the higher its content validity. For tests such as personality or motivation, content validity relates more to the relevance of the behaviours assessed by the test rather than the actual questions asked.
Construct validity shows how the constructs measured by the test relate to other measures. This is often done by comparing one test against another. Where tests measure multiple scales, as is the case with assessments of personality and motivation, it is also common to look at how the measure's scales relate to each other.
Criterion validity looks at the extent to which scores on the test are statistically related to external criteria, such as job performance. Criterion validity may be described as 'concurrent' when test scores and criterion measures are taken at the same time, or 'predictive' when test scores are taken at one point in time and criterion measures are taken some time later.
Construct and criterion validity are often indicated by correlation coefficients which range from 0, indicating no association between the test and criterion measures, and 1, indicating a perfect association between the test and criterion measures. It is difficult to specify precisely what an acceptable level of validity is, as this will depend on many factors including what other measures the test is compared against or what criteria are used to evaluate its effectiveness. However, for criterion validity, tests showing associations with outcome measures of less than 0.2 are unlikely to provide useful information and ideally criterion validity coefficients should be 0.35 or higher. The samples used for criterion validity studies should also be at least 100.
Overall, whilst a publisher should provide validity evidence for their test, validity comes form using the right test for the right purpose. Therefore, users need to use available validity evidence to evaluate the relevance of the test for their specific purpose.
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