Advanced Industrial Analytics

The GrayMatter Pre-Qualification Briefing is a one-hour discussion that takes your key stakeholders through an inventory of the data you have or have not collected.

• Determine analytics strategy phase
• Discuss sample use cases and identify best fit
• Identify business potential & three business problems to solve

The Challenge: Many organizations need help to identify the problem they want to solve and define what it means to have a successful outcome.

GrayMatter’s advanced analytics platform begins analyzing data within minutes and making predictions within hours. We work with you to validate those predictions and fine-tune the variables being measured over a roughly two-week process.

• Historical data ingestion & data audit
• Select and apply appropriate data analysis models
• Test initial predictions against actual results within 2 weeks

The Challenge: Identifying what data to use and what to exclude is a key part of creating valid predictions. GrayMatter’s pre-built library of algorithms uses 25 data models to recommend the best prospects for improving efficiency and reducing costs.

You have the data, predictions are flowing and now it’s time to scale. Within 4-8 weeks, you lead the way on building a concept for a pilot project, and GrayMatter provides guidance to help apply your concept to other facilities and operationalize predictions. That means using predictions to alert operators to make changes before a problem occurs.

• Configure a digital twin for each asset
• Automate data preparation
• Enable multi-site, real-time data comparisons

The Challenge: Many large industrial companies have built analytics solutions for one or two use cases or for an individual facility. Template building for scale allows organizations to build on work that has already been done with the goal of using GrayMatter’s advanced analytics platform to speed up data analysis and operationalize predictions.

Deploying an advanced analytics strategy shouldn’t be a one-time event. The goal at this stage is to help companies use advanced analytics to automate the process of Kaizen, Lean Six Sigma or similar methodologies. The ability to use data to make predictions with data accelerates and integrates with a company’s existing continuous improvement and enterprise analytics strategies. Some companies at this level may even want to monetize their data analytics platform for companies that purchase their services.

• Connect operational data with enterprise analytics platform & accelerate continuous improvement
• Build a customer-facing analytics service
• Develop additional use cases to scale 3 months and beyond

The Challenge: Advanced analytics help companies improve their operations, but they can also help a client provide additional services to their customers as a means of real-time asset monitoring to reduce equipment downtime and improve maintenance.