Using Machine Learning to Manage Data Gaps and Improve Decision-Making
Machine learning is often known for building prediction models using training data, i.e., identifying your susceptibility to an internal corrosion...
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In a recent dp-PRO webinar, Matthew Abbitt, Chief Product Officer at Irth, outlined how to measure risk in the damage prevention industry.
To appropriately measure risk, you need to be able to assign a Risk Score to various activities that take place around your assets. Risk Scoring is a calculated level of risk associated with an activity based on a pre-configured set of rules.
In this webinar, you’ll learn:
- Definitions of terms used in risk management, including automation, algorithm, machine learning, artificial intelligence (AI) and risk score
- The difference between automation and intelligence
- The importance of collecting the right data for your organization to calculate risk
- Where to start your risk model
- Common Risk Scoring use cases for the damage prevention industry
- Risk management best practices and benefits of risk scoring
As a trusted damage prevention partner, we’ve helped many customers use risk scoring to reap incredible benefits, including Crown Castle who reduced network asset damage by 19% in the first year of using UtiliSphere™ and SmartScore.
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