Haulers must help their customers achieve waste diversion goals or risk losing business. It’s happening all across America: Federal, state and local governments are committed to waste diversion as an important component of their plans to cut greenhouse gas emissions, conserve resources, save money, inspire youth, attract industry and create jobs. Major cities, institutions, universities and military bases everywhere are scrambling to comply. And they’re turning to their haulers for help.
To effectively manage their waste streams, customers need to manage their data streams. They are requiring haulers to provide reports with ever-finer levels of detail. That is where automation comes in.
Fully automated truck scales and analytic software solutions are now available to make sense of the large volumes of data. How large? If a city is using five trucks, each with two routes per day, five days per week, and 500 customers per route, then the operations team receives 1.3 million data records per year.
That’s a lot of data, especially if you are still entering it manually. And, just like a load of recyclables, the data stream is no good if it is contaminated. Data contamination happens when route sheets are incomplete, illegible or inaccurately entered. A clean stream of data begins at the waste container and carries all the way through to management reports.
Obtaining highly accurate information you can trust can be straightforward, without driver involvement or administrative data entry, in one integrated system. And it starts with data from trucks.
The ideal system for acquiring data from trucks tracks the amount of waste and where it came from, without requiring drivers to do anything but drive.
Global positioning system (GPS) devices often are used for determining the latitude/longitude of a waste cart, bin or dumpster. This satellite technology is accurate to within a few feet and assists the software by matching the container location with the customer account, without the need for driver intervention.
However, radio frequency identification (RFID) tags can pinpoint each container to a unique address. This is especially important for residential pickups where carts can be lined up side by side and represent multiple customers or residences. Location data is essential if haulers are to deal with a common problem: improperly loaded bins.
On-board truck scales
To automatically collect, analyze and report waste and diversion data, you need the weight of each pickup, measured with on-board truck scales. For front-end-loading (FEL) waste trucks, these scales should be part of the fork assembly so each load can be weighed individually.
Weigh-in-motion scales allow drivers to simply pick up the cart and go—no stopping is required for the weight to settle. This load weight is time stamped, marked by location and stored with the customer account, without any driver intervention. Load records are available for wireless transmission on demand to the back office operations team.
Load weight data must be highly accurate. Slight inaccuracies here are magnified at the end of the data stream, where critical decisions are made. Some scales require frequent calibration—even daily—to achieve that. Others can operate accurately for months without having to pull a truck from service for calibration.
On-board truck scales are found on the full variety of waste trucks—FELs, side loaders, rear-loader cart tippers, underbody rear loaders, Curotto Cans, roll-offs with underbody scales and compactors—and can alert drivers when their trucks are full to achieve complete vehicle efficiency without over- or underloading.
With this system, data records contain weight, location, waste profile and customer information.
Waste stream reporting and analytics
Load management analytics software not only provides reports that meet all the different customer requirements (from landfill cost reduction to waste diversion), it also triggers alarms for conditions that require management attention.
Once the load data record is uploaded to the back office software, dispatchers and managers can track routes, identify loads and verify service from a map on their computer screens. This capability is crucial for accurate diversion programs. Excessive container weights can be pinpointed and managed at the customer level.
With load management software and on-board scales, diversion can be tracked at any point in time.
Waste diversion charts
The charts provided by analytic and reporting software are critical for visualizing waste diversion metrics. And the timeliness, accuracy and integrity of the charts are maintained using proven on-board scales and load data management software automation.
But, there is more to the software than producing these initial charts. The data can be mined for more detailed information, allowing improved diversion.
Deep data mining & easy-to-use analytics
Studying detailed data and identifying key issues and opportunities for improvement are important features of any software. It allows users to “drill down” through general summaries.
Haulers who effectively gather and analyze data can improve their business performance through cost savings and increased revenue. Those haulers are in a position to help their customers achieve waste diversion goals, whatever they may be.
A university in the Northwest discovered a secondary benefit from achieving its goal to reduce landfill fees by $5 million in five years. By capturing and analyzing the data needed to measure its progress, the hauler could inform the university exactly how much it is now recycling. The university grew its recycling rate to 58 percent, well above the national average of 35 percent.
A hauler in Windsor, Ontario, has been using on-board scales for more than 10 years. The data help the hauler track phantom loads, keep customers within their load contracts and improve profitability. Now the hauler is able to respond to a whole new level of requests from its customers (many are colleges) who need data to measure their own goals: reducing carbon footprints, increasing recycling rates and recovering costs through recycling.
Before data mining, operators were forced to export the load record database into spreadsheet software, such as Microsoft Excel. However, this was a highly manual process and required specially trained personnel to drill down into thousands of rows of data.
Effective load management software eliminates those headaches. It produces the necessary reports by filtering key statistics like over- and underloaded trucks, high-density accounts that are contributing too much waste to the landfill and profitable customers who are sorting correctly and diverting a major portion of their waste to recycling and composting.
Data analytics software analyzes the waste load database and provides standard charts, such as diversion rates and out-of-range density loads. These out-of-range conditions are set with simple administrative features. At a glance, those charged with improving sustainability metrics can determine what actions need to be taken.
Let’s look at an example. The sustainability manager for a city is tracking waste hauled to municipal landfills and recycling and organic loads hauled to material recovery facilities (MRFs). A quick look at his software dashboard report tells him 79 services or loads have exceeded some threshold that he had set in the software.
He exposes more detailed information in each layer of the report. He zooms into the “refuse” service type and sees 35 customers who have exceeded a threshold. As he continues to drill down into container types, he sees nine customers with 8-yard FEL refuse bins have exceeded their contracted weight density of 160 pounds per cubic yard. Already, we can see how precise and actionable this information is: These customers are most likely unprofitable for the hauler and contributing excessive greenhouse gas levels to the city.
He sees one customer is a restaurant—so we might guess it is dumping food scraps into the waste stream when this material should go to organics stream. Contacting the restaurant could remedy the problem and make the account profitable again. If the violation continues, he has the necessary data to take further action.
Achieve with automation
A complete data management system requires highly accurate truck scales, bin location technology, tightly integrated load management software and easy-to-use analytics for drilling into a deep data mine to produce meaningful customer reports.
Tracking weight data in a continuous stream from container to reports is essential for measuring progress toward all kinds of waste diversion goals. On-board truck scales and the software platform to capture and analyze the weight data take the headaches out of achieving end-to-end data integrity and reporting accuracy.
Alan Housley is vice president of marketing with Creative Microsystems (LoadMan On-board Truck Scales), Renton, Washington, and can be reached via email at email@example.com.