Quality data is the foundation of a strong reliability program.
Today, data collection is often human dependent, inefficient, and vulnerable to quality issues. Data is collected in siloes, making it inaccessible and difficult to use for future analyses. As a result, your ability to scale data-driven initiatives can be significantly impacted. The key to improving data collection is knowing where to automate your processes with technology while leveraging the appropriate amount of human oversight.
Collect and store the right data with quality and efficiency.
We leverage a combination of data science, focused human oversight, and data collection technology to quantify the impact of your data prior to collection, minimizing waste and redundancy.
Implementing with Continuous Improvement in Mind
Whether you are a maintenance manager or a business leader, a data-driven approach to reliability can help you overcome the critical challenges of sustaining your mechanical integrity (MI) program. Identify and prioritize improvement opportunities based on data-driven insights. Better monitor and communicate the effectiveness of program improvements KPIs, metrics, and feedback loops.