top of page

What do Managers need to know about Machine Learning?

Updated: Jan 15



We’ll keep this post tidy. A quick rundown of machine learning for managers on the go.


Definitions:
  • Artificial Intelligence (AI) is enabling computer systems to perform tasks usually requiring human intelligence.

  • Machine learning (ML) is a subset of AI.

  • ML is the scientific study of algorithms and statistics for large volumes of data.

  • ML enables computer systems to perform tasks without instruction.


What does that mean for businesses?

AI and ML can be used to:

  • Recognise patterns in large volumes of data.

  • Make inferences and predictions using data.

  • Automate low-level decisions or provide insights to take action on.

  • Solve actual problems.


How does that translate to business value?
  • Identify optimisation opportunities (e.g. improve operating conditions, automate manual or repetitive tasks).

  • Take a targeted approach. (ML highlights where to spend time and capital for maximum value).

  • Data-driven recommendations (e.g. operating conditions that results in highest NPV, how to market a new product).

  • Data-driven forecasts (e.g. customer loyalty or machinery performance).

  • Data-driven decisions (automate low-level decisions using AI or provide insights from gathered data to enable a human to make better decisions).


What do you need to get started?
  • Data. The more (good quality), the better.

  • People to build machine learning models and integrate them into business operations.

  • An integrated, multidisciplinary and collaborative approach.


AI and ML enable smarter, safer, more efficient ways of working.


For industry-specific examples or more information about how ML can transform your business, connect with us.


Comments


bottom of page