Prior to the development of SkillGrader, the industry best practice for skill assessment was to have an expert use paper-based forms to assess individuals. There are several issues with this approach.
First, paper assessments led by an expert tend to be subjective: two assessors may have different viewpoints or disagree on the level, or grading, of skill displayed. The result is that assessments cannot be reliably compared to one another to analyse trends. SkillGrader eliminates almost all subjectivity by asking the observer to simply record who performed specific actions listed on the electronic form. SkillGrader then uses an algorithm compute the assessment results. This means that assessors don’t require a high degree of expertise to evaluate personnel – which is why we now call them observers.
Second, in addition to making assessments more objective, reducing the expertise required of the observer also creates far more opportunities for assessment. With SkillGrader, any training event, drill, on-the-job activity or certification process becomes an opportunity to assess skills and gather data. This provides the organization with a clearer and more complete picture of abilities, gaps, skill fade and procedural drift.
Finally, the paper-based approach means that any data collected was “locked” on paper. Time-consuming data entry was needed to convert the “paper data” into digital data for deeper analysis. Instead, SkillGrader records all data in a database making it possible to report on trends, identify workforce leaders, reveal organizational risks, and perform cross-skill evaluations of individual employees.
