Government employees charged with monitoring environmental compliance face a downpour of information, wading through countless reports and stacks of paperwork to accomplish their mission. To help these dedicated public servants increase productivity, agencies should consider a broader set of tools to control pollution, enforce regulations and improve compliance. Although foundational to compliance work, regulations, data self-reporting, manual audits and inspections do not go far enough to hold environmental operators accountable for their environmental footprint. In today’s modern world of computing, addressing these limitations requires new approaches and effective methods for enforcement, tracking violators, and detecting unreported discrepancies.

With data and AI tools such as SAS Viya, state agencies can now take a more proactive role in environmental monitoring, compliance and enforcement activities without the need to greatly expand the workforce. Embedding automation into non-compliance detection works not only to improve the productivity of agency teams but also allows them to uncover hidden and nuanced noncompliance otherwise not detectable through traditional means.

The status quo of environmental compliance efforts

For decades, state environmental agencies have largely relied on manual processes to monitor and enforce compliance. This approach involves sorting through piles of paperwork, conducting randomized audits and selective field verifications. In addition to being a time- and resource-intensive process, the manual methods for compliance and enforcement are fundamentally reactive. That means agencies find themselves in a perpetual state of catch-up, living with long back logs and chasing down individual leads without a clear strategy to guide their next investigation. With data and AI, agencies can break free from the status quo, depending on anonymous tips and instead proactively and strategically monitor compliance with advanced technology.

The power of data and AI in environmental compliance

Data and AI hold the promise to greatly improve agency productivity through automation. Environmental agencies can sort through and analyze thousands of permit documents to detect non-compliance, with powerful capabilities such as the ability to create business peer groups to draw comparisons with a sensible baseline and detect aberrations from the normal. Using versions of these tools tailored to specific needs gives state agencies new capabilities, including:

Data-driven detection: Leveraging mature and well-defined data models, agencies can employ advanced techniques like time series analysis, forecasting, and clustering to pinpoint instances of non-compliance. This is a departure from the hit-or-miss nature of traditional audits, offering a more targeted approach.

Simple insights from complex reports: The thought of integrating analytics into environmental compliance may seem daunting. For agencies with less mature databases, natural language processing, a branch of AI that helps computers understand, interpret and manipulate human language, can be used to sift through permit documents, extracting vital compliance data to construct a comprehensive data warehouse. These new data can then be fed into the solution’s models to detect hidden noncompliance.

Powerful data analysis for non-experts: Decision-makers at state agencies often assume in-house technical expertise is required to benefit from advanced analytics tools. A fully managed analytics solution can alleviate that need, supporting agencies in implementation and operations so they are not left to navigate the complexities of analytics alone. With this approach, domain knowledge is more valuable for extracting insights than pure technical skills, enabling workers to focus on what they do best —enforcing environmental compliance.

Tools scaled to agency needs: Not all agencies need a massive analytics platform. A right-sized solution can be tactically deployed at a scale that fits a given state or department’s needs, and its budget. Because the solution is designed to be accessible and manageable, it requires relatively small computing environments given the size of state environmental agency data.

A modern approach for modern challenges

To keep pace with the speed of development and consumption across the globe, environmental authorities must turn to innovative solutions for environmental compliance and enforcement. Data and AI platforms can help secure a greener future for our planet — and identify counterproductive instances of deception and noncompliance by leveraging data to supercharge productivity, and anticipate and address potential non-compliance, agencies can more effectively allocate investigative resources to where they are most needed.

When agencies have tools that empower them to do more with their resources and data at hand, our communal effort to protect the Earth becomes more proactive and well-informed. This not only enhances the efficiency of compliance efforts but also contributes to a healthier environment for all. For the full picture, check out SAS’ Environmental Compliance in Government solution brief, and see how Public Sector Analytics from SAS can expedite permit processing and improve facility compliance.


About Author

Dan Childers

SAS Solutions Architect

As a Solutions Architect at SAS, Dan creates practical analytics and AI solutions to some of the public sector's most vexing problems in areas including law enforcement, finance, commerce and emergency management. More recently, he architected and designed SAS for Environmental Compliance.

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