Facilities Recommendation Decision SoftwareDecision Engine

Machine Learning Data-Driven Decision Making

How Our Facilities Recommendation Decision Software Works

By leveraging all your historical data and past decisions, Decision Engine brings machine learning techniques to facilities management for the first time. Integrated seamlessly with Service Automation, Decision Engine uses prescriptive analytics to improve the proposal evaluation process.

Its innovative approach brings data-based decision making to routine FM decisions. And using advanced machine learning methods, Decision Engine evolves to make even better recommendations over time.

How It Helps

Make Data-driven Decisions

No longer rely on guesstimates

Improve Decision Speed

Spend less time verifying, contesting, discussing proposals

Reduce Costs

Make better proposal accept / reject decisions

Boost Decision Quality and Consistency

Use historical patterns as well as supporting intelligence to augment FM experience and expertise

Drive Efficiency

Enable providers to more easily respond to rejected proposals


Actionable Intelligence

Displays data-informed proposal accept / reject recommendation

Single Click Action

Enables action on recommendation via easy and seamless user experience

Supporting Intelligence

Key supporting data available with recommendation

Rejected Proposal Detail

Rejection explanation and faster experience for Service Providers to respond to rejected proposals