Evaluating impact

Alongside evaluating model accuracy, it is essential to gauge the business impact of a data product. This involves selecting relevant metrics or key performance indicators (KPIs) that align with the organization’s goals and objectives.

These metrics or KPIs should provide a clear picture of how the solution is affecting the business’s bottom line.

Let’s look at some concrete business examples of data science, machine learning, and artificial intelligence solutions across different industries, and how business impact could be measured.

Predictive maintenance in manufacturing

• Use Case: Implementing machine learning models to predict equipment failures and optimize maintenance schedules within a manufacturing company
• Metrics/KPIs: To measure the impact of manufacturing, the following metrics could be tracked:
  • Reduction in unplanned downtime
  • Increase in equipment availability and uptime
  • Reduction in maintenance costs
  • Improvement in...