Prescriptive analytics: Difference between revisions

Revision as of 21:20, 6 August 2024

Revision as of 21:25, 6 August 2024

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Pricing is another area of focus. [[Natural gas prices]] fluctuate dramatically depending upon supply, demand, [[econometrics]], [[geopolitics]], and weather conditions. Gas producers, pipeline transmission companies and [[utility companies]] have a keen interest in more accurately predicting gas prices so that they can lock in favorable terms while hedging downside risk. Prescriptive analytics software can accurately predict prices by modeling internal and external variables simultaneously and also provide decision options and show the impact of each decision option.<ref>{{cite journal |last1=Watson |first1=Michael |title=Advanced Analytics in Supply Chain - What is it, and is it Better than Non-Advanced Analytics? |journal=SupplyChainDigest |date=November 13, 2012 |url=http://www.scdigest.com/experts/DrWatson_12-11-13.php?cid=6421 }}</ref>

==Applications in Maritimemaritime industry ==

Common Structural Rules for  Bulk Carriers and Oil Tankers ( [https://iacs.org.uk/publications/common-structural-rules/ 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.

==Applications in Healthcarehealthcare==

Multiple factors are driving [[healthcare]] providers to dramatically improve business processes and operations as the [[United States healthcare]] industry embarks on the necessary migration from a largely fee-for service, volume-based system to a fee-for-performance, value-based system. 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.

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In provider-payer negotiations, [[Health care provider|providers]] can improve their negotiating position with health insurers by developing a robust understanding of future service utilization. By accurately predicting utilization, providers can also better allocate personnel.

== Applications in Finance ==

Prescriptive analytics can significantly enhance financial planning and risk management by providing data-driven insights for making complex financial decisions. In investment management, it can aid in portfolio optimization by recommending asset allocations that balance returns and risk, considering factors such as market conditions, investor preferences, and regulations. This involves strategies for asset allocation, risk-return trade-offs, and portfolio rebalancing. In cases for fraud detection and prevention, prescriptive analytics can identify suspicious activities by analyzing transaction patterns and anomalies. It can also support real-time monitoring, anomaly detection in financial statements, and compliance with anti-money laundering regulations.<ref name=":2">{{Cite web |date=2021-09-23 |title=How Prescriptive Analytics Drives Optimal Outcomes - SFK Inc. {{!}} SKK Marine {{!}} SFK SecCon |url=https://sfkcorp.com/how-prescriptive-analytics-drives-optimal-outcomes/ |access-date=2024-08-06 |website=SFK Inc. {{!}} SKK Marine {{!}} SFK SecCon |at=Key Applications of Prescriptive Analytics>>>Supply Chain Optimization |language=en-US}}</ref>

== Applications in Supply Chain and Logistics Management ==

Prescriptive analytics is widely used in supply chain optimization, providing significant benefits in terms of efficiency and cost reduction. It is useful for inventory management, helping businesses determine optimal stock levels and reorder points by analyzing historical data, market trends, and demand forecasts. This ensures a balance between avoiding stockouts and minimizing excess inventory, potentially leading to reduced carrying costs, improved cash flow, and better customer satisfaction.<ref name=":2" />

In logistics and transportation, prescriptive analytics can enhance route planning, vehicle utilization, and delivery schedules. It accounts for factors such as traffic patterns and weather conditions, enabling real-time route optimization, load consolidation, and efficient fleet management.<ref name=":2" />

==See also==