LabVine Learning Courses - Laboratory Performance Solutions

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Laboratory Performance Solutions

Discover how to select the best scenario developed to improve the performance of your laboratory with certainty.

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About Laboratory Performance Solutions

An online program consisting of 30 minutes of e-learning that will teach you how to select the best-developed scenario to solve the performance problem of your laboratory with certainty, using simulation techniques in MS Excel.

Developed by:
Power of Process
Duration:
30 minutes
Learning Mode:
eLearning
Certificate:
Certificate of completion

Topics

  • Scenario Development
  • Evaluating Improvements

Pricing

Instructors

Andre Gouws


As the Head of Product and Methodology at OIM, André brings a wealth of expertise as an HR and Learning and Development (L&D) Executive. His extensive experience spans leading large L&D teams in listed companies to founding a skills development company focused on business and process improvements for medical laboratories. Through LEAN and Six Sigma methodologies, he successfully expanded this venture globally, reaching markets across the USA, South America, Canada, the UK, Europe, and Southern Africa. With a career spanning 30 years, André has been instrumental in designing, developing, and implementing a range of HR systems and accredited management and leadership development programs. These initiatives have had a significant financial impact on both internal and external clients and remain in active use today. André’s expertise encompasses business and process improvement methodologies, global skills development standards, coaching, and the management of multi-disciplinary teams across regions.


Chapter 1: Laboratory Performance Solutions

Scenario Development

22 minutes

This module explains how to develop different scenarios to improve a laboratory process and use a simulation model in MS Excel to test the best scenario for implementation.

Evaluating Improvements

8 minutes

This module explains how to evaluate improvement initiatives by considering system constraints, sensitivities, and alternative scenario development.