Use Case

Predictive Maintenance


Machine downtime is expensive, so avoid it by performing predictive maintenance. Take advantage of advanced analytics to improve asset availability, keep your supply chain moving and increase customer satisfaction.

Efficiency Gains

Automate predictive models that drive proactive maintenance strategy

Risk Mitigation

Address issues before equipment failure

Bottom-Line Returns

Extend useful life of equipment to improve machine availability and boost customer satisfaction


Business Problem

Your most expensive assets are the ones that cost you money because they’re down. They cost you  additional operating expenses, lost sales, supply chain disruption, and, worst of all, customer satisfaction. You can maintain and regularly inspect your machine assets yet still be caught off guard by mechanical failure. The more frequently this happens, the more likely maintenance budgets will be exceeded, and the higher the risk of supply chain disruption. Predictive maintenance schedules reduce the risk of major failure by addressing small issues before they become big ones.

Alteryx Solution

Predictive maintenance helps you connect the dots among data, analytics, and service records. It automates the process of identifying events and conditions that will soon lead to downtime or repairs, then it alerts you to them. Acting on patterns in the data reported by your machines, you can schedule service calls and order parts when it’s convenient for you, instead of having to deal with unanticipated outages. Predictive maintenance is an important tool in improving relationships with customers and keeping the supply chain moving smoothly.

Alteryx provides an easy-to-use, drag-and-drop canvas for predictive maintenance and downtime analytics. By tying your maintenance and labor costs to historical outcomes, you can obtain the best results from technicians, keep machine-related costs of production low, and maximize your uptime and customer service levels.


1 – Data Connection
Connect part, maintenance, and failure data

2 – Prep and Blend

Automatically clean and format data for modeling

3 – Predictive Modeling

Create decision tree model to predict parts failure


Addition Resources

Starter Kit for Predictive Analytics
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Starter Kit for Supply Chain

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Starter Kit for Data Blending
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Prepare Your Supply Chain for Uncertainty
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Analytics Automation for Supply Chain Intelligence
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GC Optimizes Data with Alteryx Analytics Automation
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