Prescriptive analytics
[7] Prescriptive analytics uses algorithms and machine learning models to simulate various scenarios and predict the likely outcomes of different decisions.
It can continually take in new data to re-predict and re-prescribe, thus automatically improving prediction accuracy and prescribing better decision options.
The correct application of all these methods and the verification of their results implies the need for resources on a massive scale including human, computational and temporal for every Prescriptive Analytic project.
In order to scale, prescriptive analytics technologies need to be adaptive to take into account the growing volume, velocity, and variety of data that most mission critical processes and their environments may produce.
[10] While the term prescriptive analytics was first coined by IBM,[3] and was later trademarked by Texas-based company Ayata,[11][12] the underlying concepts have been around for hundreds of years.
The processes and decisions related to oil and natural gas exploration, development and production generate large amounts of data.
Many types of captured data are used to create models and images of the Earth’s structure and layers 5,000 - 35,000 feet below the surface and to describe activities around the wells themselves, such as depositional characteristics, machinery performance, oil flow rates, reservoir temperatures and pressures.
In unconventional resource plays, operational efficiency and effectiveness is diminished by reservoir inconsistencies, and decision-making impaired by high degrees of uncertainty.
[22] In the area of health, safety and environment, prescriptive analytics can predict and preempt incidents that can lead to reputational and financial loss for oil and gas companies.
[23] Common Structural Rules for Bulk Carriers and Oil Tankers ( managed by IACS organisation ) intensively utilizes the term "prescriptive requirements" as one of two main classes of checkable calculations by dedicated numerical tools and algorithms for verifying safety of ship hull construction.
Prescriptive analytics is playing a key role to help improve the performance in a number of areas involving various stakeholders: payers, providers and pharmaceutical companies.
Prescriptive analytics can help providers improve effectiveness of their clinical care delivery to the population they manage and in the process achieve better patient satisfaction and retention.
