Environmental Data Analytics & Visual Modeling

How does Exponent help clients leverage data to make informed environmental decisions?

When stakeholders are involved in regulatory disputes involving environmental issues, face critical decisions concerning growth and expansion, or plan to adopt a recycling or product stewardship initiative, a properly constructed data analysis and visual modeling service can provide important insights for informed decisions.

Astute organizations recognize the value of developing powerful but easy to use analytical tools for routine or emerging needs. Well-designed Interactive data analytics tools provide a means for organizations to process, explore, and analyze data in real time, often through intuitive and interactive visualizations. These tools can serve many purposes, including sharing data and analytical results within and between organizations (e.g., business intelligence), regulatory agencies, or the broader public to meet data transparency requirements. However, the applications of interactive data analytics tools extend well beyond project management. They can be used to address a diversity of needs, such as improving product development, forecasting trends, and aiding decision-making.

Our comprehensive data collection and data cleaning services leverage data from multiple sources including public disclosures, compliance reporting, routine monitoring, results from past investigations, and internal organizational data to create statistical models. Exponent's multidisciplinary teams use innovative approaches, classical statistics, and modern analytical tools to generate important understanding for our clients' most critical accident investigations or environmental sustainability programs.   

Exponent's environmental data services and analytics have been used to support clients with high-profile projects including oil spills, chemical releases, major contaminated sites, and toxic tort cases.

Custom interactive data analytics tools

Our environmental and data scientists have vast experience developing and deploying software tools, including interactive data analytics tools (e.g., "dashboards") for clients. Our greatest strength is developing custom and effective analytical tools for clients that leverage our working knowledge of the science that the applications are built around, and from an understanding of the data, models, or regulatory aspects that are required to build robust, custom, and scalable analytic tools.  

 From the relatively simple and familiar, to more flexible and highly customizable applications, Exponent's professionals develop production quality interactive data analytics tools on a diversity of platforms. These tools provide the broad range of capabilities necessary for our clients to effectively manage data and information. Common applications include performing routine tasks that involve estimating outcomes or potential risk based on user defined selections that feed into simple to complex models or algorithms. The possible applications are broad and nearly endless; therefore, each application is tailored to client goals, data needs, and user experience. Development is enhanced with iterative feedback from clients so that the tools we develop are ideally suited to our clients' needs.

Example applications of interactive data analytics tools we have developed include:

• Dashboard showing likelihood of failure for utilities assets both at present and in the future
• Dashboard for tracking progress on complex data collection efforts for machine learning products
• Dashboard enabling customers (buyer of manufactured good) to visualize defect rates of multiple suppliers and providing full spectrum surveillance, including high level overall rates that could be explored over specific time windows, comparing multiple suppliers, and quickly showing potential financial impact
• An application to compare the fate and transport of metals in groundwater plumes from coal combustion residual ponds under different closure scenarios
• An application to evaluate how sampling method (interval) affects the ability to detect the efficacy of best management practices (BMPs) in reducing annual pollutant loads and identify the most economical method
• A stochastic numerical modeling tool to evaluate and manage human inhalation exposure potential