Job Evaluation Decision Tree Training| South Africa (English session)

Want to learn other ways to evaluate jobs that use a different point of view?

Korn Ferry Decision Tree is another approach that is tried and true.

Job Evaluation can be a complex task – but in today’s business day and age, it no longer has to be.

Our Korn Ferry Decision Tree Methodology is an automated Job Evaluation system that is powerful, reliable and user-friendly. It is a web-based tool that simplifies the overall Job Evaluation process. The Decision Tree system helps organizations build a database of job evaluations (including checks and balances). It also has added functionalities that allow one (or several) users to maintain, share, export, archive information, and produce a wide-range of value-add reports.

Together with practical training users of the Decision Tree web-based system learn the rationale behind the methodology and how to competently work their way through the system. The training will ensure they are comfortable with auditing and validating grades, and will be able to practically evaluate positions on the system with comfort and confidence.

Programme Highlights:

  • Introduction to Job Evaluation
  • Navigation of the ins and outs of the Decision Tree system and the six associated sub-factors
  • Sensitization to Decision Tree System rationales and functionalities
  • Demonstration of first-level system auditing and validation of grades
  • Evaluation of positions on the system from a practical point of view.

Who should attend?

HR employees of organizations that currently make use of, or intend to make use of the Decision Tree Method. Please note: previous Job Evaluation experience is not required.

Duration2 days

Cost: $ 1400 (excl. VAT)

Format: Face to Face

And now for the fine print…

In order for Training to go ahead, we need a minimum of six confirmed participants.

Should there be enrolments of fewer than 6 participants for any given public training course, Korn Ferry reserves the right to cancel and/or postpone the training, until optimal enrolments are reached.

Korn Ferry will, however, provide sufficient notification to participants, and their affiliated companies, should such an occurrence arise. Participants may then choose an alternate programme date, option or obtain a refund for the training programme costs only.

Furthermore, in order for there to be an optimal virtual online learning experience, we apply a maximum number of 10 participants limit to ensure an intimate learning environment and an opportunity to provide individualized attention.

In-House Training

Should your company wish to enrol more than 6 participants onto one of the Public Training courses, we may then discuss the provision of In-House training as an alternative, in which case suitable dates can be arranged outside of the existing public training calendar.

Ready to join us on your learning growth journey in 2023?

Contact our TrainingAfrica Hub to obtain your Training Enrolment Form:

Email: TrainingAfrica@kornferry.com

Telephone: +27 11 783 2632

Payment and Cancellation Policy

Training fees must be paid in advance. Confirmation of payment and acknowledgement thereof must be received before delegates may attend training. Cancellations will only be accepted in writing.

Please take note or our cancellation policy:

  • 100% will be refunded for cancellations one month before the training date.
  • 50% will be refunded for cancellations two - four weeks before training date.
  • No refunds will be given for cancellations less than two weeks before the training date, however the candidate may select an alternate training date option.
  • No refunds, or alternate trainings will be given for no-shows, unless in exceptional circumstances (and at the discretion of Korn Ferry – i.e. Accidents, Personal / Family Tragedies and other unanticipated incidents).
  • Date: 21-22 August 2023
  • Location: Johannesburg
  • Fee: $ 1400 (excl. VAT)
Register
  • Date: 20-21 November 2023
  • Location: Johannesburg
  • Fee: $ 1400 (excl. VAT)
Register
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