Waste Stream
Analysis & Assessments
During our initial Waste stream Analyses, and our waste stream Assessments, we evaluate your current and historical waste and recycling data, additional data and metrics relative to your facility or portfolio, individual service specifications, expenses, and contacts using a predictive analytical approach.
Predictive Analytics
Predictive Analytics is a branch of advanced analytics which assists with predictions about future outcomes using CURRENT and HISTORICAL DATA combined with statistical modeling, data mining techniques, and industry experience unique to the Blue Planet team.
Employing predictive analytics, along with our industry experience, and out-of-the box thinking, allows Blue Planet to identify risks and opportunities within our client-partner’s waste streams, and implement a sustainable and successful program.
Predictive Analytic models are designed to assess CURRENT and HISTORICAL DATA, discover patterns, observe trends, and use that information to predict future trends, while avoiding risk.
Benefits of Predictive Analytics & Modeling Include:
• Better Overall Command and Control
• Risk Reduction
• Program Security and Reliability
• Operational Efficiency
Site Survey Data Confirmation
Although Blue Planet, in most cases, is capable to analyses and assess the historic and current data, and other service information provided by our Client-Partners, some times there is no substitute for actually hitting the street and diving into your dumpster.
Real-Time data is vital in uncovering missing, incomplete, or contradicting information from the service providers.
Cameras and Monitors (Technology)
Blue Planet dose not solely rely on technology. Camera’s and ‘fullness’ sensors and monitors can be helpful to a small degree; however, they CANNOT replace real-time human intelligence. In addition, they must be mounted on someone else’s property (containers), and all to often camera’s, fullness sensors, and monitors become blocked, loose single, are damaged, or report unreliable data.
