Anybody who has tried to process waste data knows exactly why we wrote the title of this blog. Waste data is beyond hard, it is really complicated. By the time you get all of your systems up and running and the data validated, you’ve earned that Ph.D. in waste! Over the past year and a half, GLYNT has extended our automated, AI-powered, audit-ready data system to waste data. It took several attempts to get the data model and workflow automation right. But we did it! This blog post is all about our lessons learned and insights on how to prepare your own waste data. But before we dig in, let’s go back to the Why and the Who. Why is waste data important? Who is the user of this data?


The circular economy. In the circular economy nothing is ever used and discarded. It is thoughtfully designed for re-use in some manner. The success of the circular economy is measured by decreasing tonnage added to landfills. Landfills are the source of about 20% of global carbon emissions, and waste is a top 3 source of emissions. The data on waste – how much was generated, where it went – is key to tracking progress on reducing waste and its emissions.


Anyone who reads corporate sustainability reports. Avoidance of waste is so key to a successful sustainability strategy that tons of waste generated are included in many regulatory mandates, financial reporting requirements and customer sustainability data requests. The producers of waste data are the sustainability and finance team, the users are consumers of corporate sustainability reports. In addition, tracking waste data can support audits of waste bills, key to driving operational savings in waste management.

Here’s a sample graphic of waste data from New York City. The pie chart in the middle shows the composition of waste generated. This is the summation of waste pickups by waste type by month. The outer ring shows where the waste might go. The gray bit shows that 23% has no possible option for re-use, this waste is going into the landfill. But all the other slices of the pie chart are candidates for “diversion,” e.g. non-landfill outcomes.

Here are 5 Key Components of Our Waste Ph.D.

1. Key Waste Data is Not Printed

GLYNT has an expert system for energy and water utility data, and we were surprised to find that it did not work for waste utilities and private waste vendors. The first friction we encountered was data that was not printed.

Residential services can be printed as: “Pickup for the Happy Community, January 2024, $4500.” What is not printed is: Was the service once per week? How many homes were served? What is the size of the waste container? Is there a recycling service? Any or all of these questions are often not answered in the waste bill, additional information is required.

2. Waste Acronyms Are a New Language

Waste volumes can be Cu Yd, CY, G, Gal and so on. These one and two letter acronyms for volume, frequency, container type, service type and waste type are meaningful, but easily missed by a new waste data system. Don’t skip the odd character, track it down!

3. Standard Documents-to-Data Tools will Fail

GLYNT has expert systems for energy and water invoices, and general business invoices. Well… waste invoices are a mix of the two. And waste invoices are produced by thousands of vendors, without a standard format or schema. All of these factors stack up and break typical OCR, AI or invoice extraction technology. You’ll need a solution that is easy to configure, so each vendor variant can be captured and automated.

4. Drive to the Goal: Tons of Waste, by Waste Type, By Site, By Month

It is super easy to get lost in preparing the data. There is so much going on in every waste bill! But the point of the exercise must be kept in mind. This is the only way to reduce data preparation risk. Focus on your big tonnage vendors and your dense waste types (e.g. high emissions). Get accurate data flowing from this starting point, then expand to all vendors. And remember, with On Call services the monthly pickups will have considerable variation. This is not the time and place for data sampling and estimation. Get the actual data from all the invoices.

5. Bill Data Alone Is Not Useful

Once you are sitting in front of your waste data, you’ll find that it does not work with reporting! You’ll need to fill in location identifiers, standardized waste types, standardized waste units of measure, conversion factors, emissions factors and more. Think of waste as Printed Data + Additional Data = Useful Data. Plan on spending a considerable amount of time preparing the Additional Data.

If you don’t want to get a Ph.D. in waste data, talk to GLYNT! We produce accurate, audit-ready waste data for sites around the world. We’ve set up an automated system so you don’t have to.