The burden of waste generation

The United States generates and disposes of approximately 7.6 billion tons of industrial waste each year. Non-municipal solid waste, including industrial scraps, makes up almost 99% of all the waste in the country. Beyond their environmental consequences, these considerable figures put companies at the mercy of rising waste disposal costs that produce substantial budget cuts.

In the context of global environmental awareness, companies are looking for competitive solutions to optimize their production processes and limit waste generation. Businesses can significantly reduce their ecological footprint and waste disposal expenses by finding alternative waste uses. To do this, companies must identify and invest in promising leads that increase their chances of commercial success.

Turning waste into profits with data-based insights

Using your internal database as a foundation, predictive models can generate waste-repurposing recommendations for your production process and help you identify resource recovery opportunities. However, most companies leave a significant portion of their internal knowledge untapped. This often results in biased datasets and unreliable predictions.

Adopting data management and analytical strategies allows you to uncover and exploit this dark data to boost prediction accuracy and direct your research team's effort to evidence-based opportunities.

Key strategies for leveraging the potential of dark data

Converting dark data into evidence-based insights helps identify commercially viable waste-repurposing alternatives for your supply chain and target markets.

Structuring and exploiting dark data can enrich your internal database, decrease data bias, and unravel high-potential waste upcycling leads. However, handling unverified and scattered data is time-consuming and labor-intensive. Here are key data strategies to stack the odds in your favor.

Data management: structure and harmonize

• Collect and combine scattered data in a unique knowledge management platform.
• Digitize physical documents and harmonize formats, terminologies, and abbreviations.
• Identify knowledge gaps in your internal database.
• Confirm data quality, accuracy, and integrity to establish robust data foundations.

Data mining: analyze and predict

• Integrate custom search tools to retrieve information quickly.
• Run predictive artificial intelligence (AI) and machine learning (ML) models on curated datasets.
• Obtain precise data-based recommendations to upcycle your waste byproducts effectively.
• Focus your efforts on highly tuned results.

Data sharing: collaborate and innovate

• Accelerate interdisciplinary brainstorming through a shared cloud-based data management platform.
• Facilitate secure exchanges of sensitive information.
• Connect across seemingly unrelated scientific disciplines and unravel innovative resource recovery opportunities.

Download this success story to learn how CAS Custom Services^SM helped ICL identify application leads for 75% of target waste products.

Looking ahead

In an era of environmental awareness, companies must optimize resources and reduce their ecological footprint while outpacing competition.

By structuring their internal knowledge, companies can transform dark data into evidence-based assets and identify effective ways to reincorporate waste byproducts into their value chain, reaching new markets while reducing waste generation, facility overloading, and disposal costs.

Exploiting byproducts' hidden value can significantly lower environmental impact while broadening commercial opportunities, giving products a circular lifecycle and paving the way to sustainable growth and profit.