Practical Solution to Cost Effective Liability Management
We live in a world that aspires to be data-driven, and numerous industries have placed high expectations on artificial intelligence, machine learning (AI/ML) and data science to automatically power their digital transformation.
Most companies are working to expand their offerings into this area of data digitization, and every day there are new tech start-ups, claiming to revolutionize the way we do business.
Unfortunately, data-driven decision-making still remains elusive and broadly ineffective at yielding the promised benefits due to:
- inefficient communication along the supply chain of data-holders,
- inadequate data interpretation using traditional methods,
- inaccurate mathematical/statistical modelling, and
- poor communication of modelling result to decisions makers.
Analythium has partnered with Clear-Site Site Access Solutions and 360 Energy Liability Management Ltd. to present on a Practical solution to cost effective liability management at this years Virtual RemTech Symposium (October 14th, 2020).
In this presentation, we demonstrated solutions that seamlessly pull together collective efforts of cross-disciplinary teams with widely different skill sets (statisticians/mathematicians, software engineers, industrial engineers, environmental scientists and regulatory specialists) to build customizable data science applications.
The proposed solution is more than data digitization, as it involves developing robust models and interactive visualization tools that work to intuitively communicate data insights and provide actionable intelligence.
We presented several environmental case studies to illustrate how automated data-analytics and iterative modelling algorithms can be integrated to build simple, cost-effective liability management solutions.
Our analytics application successfully redirected the site from a trajectory of implementation and operation of a million dollar in-situ groundwater remediation system to regulatory closure based on leaving contaminants, which were not a cause of current or future predicted risk in place.
If you want to learn more about our approach, schedule a free consultation and turn our expertise into your advantage.
