Drive reliability with the right data science and engineering models.
Make well informed reliability decisions.
Today, our data systems are heavily reliant on subject matter expertise. While these resources add significant value, they can be better leveraged in situations where their expertise is uniquely required. Additionally, when reliant on human expertise, our models can become too conservative, resulting in wasted time and spending. We have the opportunity to better leverage our data to learn from previous patterns and quickly scale our programs. With data-driven reliability, you have the ability to dynamically adjust your plans, quickly make decisions based on live data, and holistically approach complex problems.
Create holistic reliability models that bridge the gap between data science and human expertise.
Data-driven intelligence improves your facility’s reliability performance through a combination of engineering, data science, and hybrid reliability models. Removing the data silos from your reliability models will give you the clarity and confidence needed to make reliability decisions today.
Let Data Drive Your Reliability
The Challenge with Our Current Risk Models
Capturing risk accurately is key for a facility management is to understand their true risks as well as how to deploy limited resources most effectively. As an industry, we must start thinking differently if we want to realize the massive economic gains and safety impacts that exist. We can’t continue to solve the problems of the 2020s using the solutions we had in the ‘80s and ‘90s.
Reliability as a Solution is Pinnacle’s fixed price service plus software solution focused on delivering to a quantified result.
Learn about the impacts of Data-Driven Reliability
Case Study
Supermajor Uses QRO to Predict 94.22% Availability and Associated HSE Risk, Using Model to Drive Benefit-to-Cost Design and Maintenance Optimization
