PRODUCT

CNet Training launches competency modelling tool

CNet Training has launched a Competency and Confidence Assessment Modelling (CCAM) Tool for the data centre sector. The software could transform the way data centre managers identify, manage and mitigate people risk, the company claims.

The CCAM Tool provides real-time analysis of both competence and confidence for individuals and teams through situational judgement assessments, and exposes root causes of employee behaviour (positive and negative) in data centre facilities.

Its complex software, which is supported by a team of psychologists and operates within International Test Commission guidelines, works through various criteria to identify people risk. It focuses on where individuals’ real skills, knowledge and ability gaps are and, through subsequent targeted intervention, behaviour can be positively changed and subsequently risks reduced.

The results of each assessment allow the right course of development action to be planned and taken to address individuals’ weaknesses. In addition, with the ability to take the CCAM Tool assessment again post-development, it ensures any costs incurred have been used effectively, thus maximising the opportunity to achieve ROI. It can also be used as a valuable pre-employment tool allowing managers to understand the development investment required for potential new staff.

Andrew Stevens, CEO of CNet Training, commented: ‘Ultimately risk is a human issue and businesses need people who are adept at tackling the threats they encounter, particularly within mission critical facilities. Understanding likely behaviours of individuals and teams in high risk environments is one of the biggest challenges a data centre facility faces today, but one that the CCAM Tool addresses.’

He added: ‘The CCAM Tool really does take the traditional Training Needs Analysis into a new and more justifiable dimension, and one that will help maximise competitive advantage, as productivity and quality of service will also improve.’

Company: 
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