Informed Decisions
We help our customers make optimal decisions
Stay on Track With Data Collection
Organizations invest significant resources in data collection and analysis efforts, such as fielding new sensors, spending on expensive laboratory testing, and deploying large data science teams. Throughout these processes, it is easy to lose sight of the ultimate objective of all these investments: to make better, more informed decisions.
Making Decisions is Hard for Many Reasons
Decisions can be difficult due to uncertainties, unclear priorities, and conflicting values. Analytical approaches fall into two categories: heuristics and decision analysis. Heuristics are qualitative and prone to bias. Decision analysis, a normative framework, offers a data-driven, quantitative approach. Common tools within decision analysis include influence diagrams, decision trees, and optimization techniques, allowing for a clear comparison of potential options and their trade-offs.
Making Decisions is Hard for Many Reasons
Decisions can be difficult due to uncertainties, unclear priorities, and conflicting values. Analytical approaches fall into two categories: heuristics and decision analysis. Heuristics are qualitative and prone to bias. Decision analysis, a normative framework, offers a data-driven, quantitative approach. Common tools within decision analysis include influence diagrams, decision trees, and optimization techniques, allowing for a clear comparison of potential options and their trade-offs.
Questions
Our Informed Decisions Helps Our Customers Answer Tough Questions
How should underground transmission lines replacements be prioritized in a large urban area subject to seismic risks?
ATS performed an analysis of a large electric utility company’s network of underground transmission lines in an urban area, which led to board approval of $200M effort to replace three lines that pose the greatest risk, leading to projected failure risk cost savings of $400M over 50 years.
How can wildfire mitigation efforts be prioritized in a cost-effective manner by large electric utility companies?
ATS built machine learning and artificial intelligence models to determine the mitigation efficacy of wildfire mitigation measures for a large electric utility company’s $3B investment to cover 5,300 miles of conductors over a four-year period. This analysis was critical to justifying this investment to the regulators and the public. For another electric utility company, ATS was able to direct future wildfire mitigation investment at the asset level providing the most cost-effective solution for the utility and the public.
What are the most vulnerable assets in a black start network?
ATS performed asset and system risk analysis of a large electric utility company’s black start network consisting of over a dozen substations and connecting 400kV transmission lines, which identified the highest risk assets in the system: overhead line fittings on a single circuit. Replacement of these fittings will result in a projected risk cost savings of over $350M over 25 years.