What do managers need to know about machine learning?
We’ll keep this post tidy. A quick rundown of machine learning for managers on the go.
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: