After the arrival of AI waste management organisations now fall into three groups:
- The businesses that adapted : organisations adopting AI today to get more from their material, staff and infrastructure.
- The businesses that waited: those struggling to keep pace as competitors maintain profit margins with the help of detailed composition data.
- The businesses getting left behind: the organisations left behind as AI transforms the industry around them, and cost pressures continue to grow.
NG Nordic (a Nordic total waste company) is firmly in the first camp. Rather than waiting for change to reach them, they’re experimenting with AI waste analytics now. Their team are building in-house AI expertise, testing applications, and laying the foundations for a more industrialised, automated future.
Industrialising manual facility processes
Product Quality Manager Camilla Stridsklev has been at the forefront of the learning process.
Together with her small team, Camilla has been experimenting with the Analyzer system at NG Nordic’s largest mixed waste recovery facility:
Identifying objects in a huge waste stream requires a lot of experience, and a lot of operators.
We were looking for technology that could support and supplement their everyday tasks, and replace part of the manual labour required to pick through waste.’’
Camilla Stridsklev
Product Quality manager at NG Nordic
Manually identifying waste is currently time-consuming and expensive, but it’s also essential: strict quality requirements from both regulators and customers mean that accurate sampling data impacts both compliance and profitability.
For Camilla, detailed composition data represents a competitive advantage:
As waste treatment becomes more advanced, we see more stringent requirements from downstream customers and regulators. We believe that it will be an advantage to say more than we can today about the material we deliver.”
Camilla Stridsklev
Product Quality manager at NG Nordic
The search for a technology that could gather more data, in less time, led NG Nordic’s team to Greyparrot Analyzer.
Laying the foundations for industrialised waste management
By installing Analyzer at a major facility with highly variable infeed material, Camilla’s team is investigating a data-led facility management model that they can roll out across the organisation:
This is part of the large initiative to increase the industrialisation of the way we treat waste. We started at our largest plant because that’s where we’ll make the biggest gains going forward. Then we can spread those learnings to other plants.”
Camilla Stridsklev
Product Quality manager at NG Nordic
Rather than narrowing their focus to a single process or plant, NG Nordic’s team view AI waste analytics as a critical enabler of their broader vision: bringing more industrialisation, standardisation, and efficiency to waste treatment. AI adoption has been about building understanding and solutions that will scale:
Up until now, the most important thing for us has been to learn. We believe that AI will be part of the future in waste treatment, and we want to be part of it.
We’ve already learned that there’s huge potential to understand our production much better. Until now, we couldn’t measure processes in this level of detail. That data will help us make the right decisions about adjustments and investments, and document the entire process.”
Camilla Stridsklev
Product Quality manager at NG Nordic
NG Nordic’s vision extends beyond internal process improvements, too. Camilla believes that AI waste analytics has the potential to foster more trust in the waste system as a whole:
For many people, it’s mysterious what happens with waste once it leaves their hands. With this technology, we can bring documentation and transparency to the process.”
Camilla Stridsklev
Product Quality manager at NG Nordic
Building a more transparent, efficient recycling system
NG Nordic now relies on systems like Analyzer to prepare for the future of waste management. By embracing AI waste analytics today, its team is already moving closer to a fully industrialised, transparent, and data-driven approach to waste management.
For Camilla, that progress has been down to experimentation and openness:
Go into it open-minded. Some things that we thought were difficult were easy, and vice versa. You need to have an idea of what you want to achieve, but be open-minded and try to learn the potential of the technology.”
Camilla Stridsklev
Product Quality manager at NG Nordic
Learn how more waste management leaders are using AI to boost efficiency (and profits) here.
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