About this course

Making decisions based on data is crucial in the asset management environment of today. This course gives you the tools to efficiently gather, process, and analyse data so that it may be used to inform strategic choices.

You will build a strong understanding of data principles, data quality, and analysis methods through self-paced learning, with a focus on using Microsoft Excel. A live session will help you see how these concepts apply in the real world by working through practical case studies. Finally, you’ll put your learning into action by visualising data and creating a compelling presentation to support informed decision-making.

You’ll begin with seven self-directed learning (SDL) modules, designed to build a solid understanding of the theoretical principles of data analysis in the context of Asset Management. Module 04 is longer than the others, as it focuses on using Microsoft Excel for data analysis. It includes hands-on practice with key functions in the software.

The SDL concludes with a quiz, which must be completed before the live engagement session. During the live session, you’ll apply the concepts covered in the SDL using case studies. The final course assessment brings everything together, requiring you to visualise data and create a compelling presentation to support informed decision-making.

Outcomes

At the end of this course learners will be able to:

Explain the role of data analysis in effective asset management decision-making

Differentiate between data, information, and knowledge in an asset management context

Describe the data management process

Identify relevant data sources for asset management decision-making

Explain key considerations for effective data collection

Use Excel to organise and analyse asset data

Assess and improve data quality to enhance decision-making

Select and apply appropriate analysis techniques to solve asset-related issues

Interpret and present data-driven insights visually for stakeholder engagement

Data Analysis for Asset Management Decision-making - Course Content
 

Who should attend?

  • Maintenance planners
  • Maintenance supervisors
  • Asset care engineers
  • Reliability engineers

Format and duration

  • Blended learning, with elearning and virtual classroom contact sessions.
  • 24 notional hours
  • Formative activities

Certification

  • Learners completing this training can obtain SAAMA CPD points.